CData Python Connector for Avalara

Build 26.0.9655

CData Python Connector for Avalara

Overview

The CData Python Connector for Avalara allows developers to write Python scripts with connectivity to Avalara. The connector wraps the complexity of accessing Avalara data in an interface commonly used by Python connectors to common database systems.

Key Features

  • WHL installation packages that enable installation with "pip install".
  • Supported for Python 3.10 or newer on Windows, Linux, and macOS.
  • Write and execute SQL queries to fetch and update data in Avalara.
  • Custom dialect class that enables SQLAlchemy 1.3 and 1.4 to use this connector.

Getting Started

See Getting Started to install the connector to your Python distribution and to create a basic connection to Avalara.

Using the Python Connector/Using from Tools

See Using the Connector for examples of executing basic SELECT, INSERT, UPDATE, DELETE, and EXECUTE queries with the module's provided classes.

See Using from Tools to connect Avalara data to tools such as Pandas or Petl.

SQLAlchemy ORM

SQLAlchemy can be leveraged to model the tables in Avalara with mapped classes. See From SQLAlchemy for instructions for configuring the Python connector with SQLAlchemy.

Pandas

Pandas' DataFrames can be used alongside the connector to generate analytical graphics. See From Pandas for a guide.

Schema Discovery

See Schema Discovery to query the provided system tables, which allows users to discover the available tables, views, and stored procedure, alongside additional information about their columns or parameters.

Advanced Features

Advanced Features details additional features supported by the connector, such as defining user defined views, ssl configuration, remoting, caching, firewall/proxy settings, and advanced logging.

SQL Compliance

See SQL Compliance for a syntax reference and code examples outlining the supported SQL.

Data Model

See Data Model for the available database objects. This section also provides more detailed information on querying specific Avalara entities.

Connection String Options

The Connection properties describe the various options that can be used to establish a connection.

CData Python Connector for Avalara

Getting Started

Connecting to Avalara

For information on the available WHL files for supported environments, and how to install the appropriate file for your Python distribution, see Package Installation.

For information on the module to import, and how to configure the necessary connection properties in a connection string, see Establishing a Connection.

Other available connection properties can be used to configure other aspects of the connector capabilities.

Python Version Support

The CData Python Connector for Avalara can be installed and used in Python 3.10 or newer.

Avalara Version Support

The connector leverages the Avalara Avatax API to enable bidirectional access to Avalara.

See Also

  • Using the Connector: Establish connections and query Avalara through Python code.
  • From SQLAlchemy: Use SQLAlchemy to establish a connection with dialect URL, and interact with Avalara data using mapped classes and Sessions.

CData Python Connector for Avalara

Package Installation

Dependencies

The Python connectors require that Python 3.10 or newer be installed.

Installation

The CData Python Connector for Avalara is available as a WHL file for Windows, Linux, and Mac. Each connector is built using the Python 3.10 Stable ABI (indicated by the abi3 tag in the filename), so a single wheel supports any Python 3.10 or newer installation — there is no need to match your exact Python minor version. Use the "pip install" command with the appropriate WHL file for your platform.

Windows:

pip install cdata_avalara_connector-26.0.9655-cp310-abi3-win_amd64.whl

Linux:

pip install cdata_avalara_connector-26.0.9655-cp310-abi3-linux_x86_64.whl

macOS:

pip install cdata_avalara_connector-26.0.9655-cp310-abi3-macosx_12_0_arm64.whl

The macOS wheel supports arm64 (Apple Silicon) architectures only on macOS 12 and newer.

Regardless of the environment, certain distributions might require that the "pip3 install" command be used instead, to differentiate from a Python 2 distribution that might exist already. After installation, confirm whether the connector is successfully installed by running the "pip list" command. If "cdata_avalara_connector" is present in the list output by the command, then the installation was successful.

Upgrading

When upgrading, "pip install" does not automatically clean up old JRE files. To avoid leftover files that could cause JVM errors, uninstall the previous version before installing the new one.

Licensing

After the installation is complete, a separate step is needed to activate a license for the connector. Among the CData assets in the distribution's site packages, there is an install-license tool that activates this license. From within the distribution's site-packages folder, after navigating to the "cdata/installlic_avalara" folder, simply use a command like the below to activate the license. Omitting the <key> argument activates a trial license:

  • Windows:
    ./install-license.exe <key>
  • Linux / Mac:
    ./install-license.sh <key>

Sometimes, file access issues may cause pip to install the connector in a fallback file path that is not the python distribution's main or primary site-packages location. This can make it difficult to find where the connector was installed, and from there, the license activator. In that event, this python script below will print out the full file path of the connector's native file. This file will be stored in the mentioned cdata folder, from which the installlic_avalara folder is trivial to find:

import os
import cdata.avalara
path = os.path.abspath(cdata.avalara.__file__)
print(path)

Uninstallation

If the connector needs to be uninstalled for any reason, do so by running the pip uninstall command, as in the example below:

pip uninstall cdata-avalara-connector

CData Python Connector for Avalara

Establishing a Connection

The objects available within our connector are accessible from the "cdata.avalara" module. To use the module's objects directly:

  1. Import the module as follows:
    import cdata.avalara as mod
  2. To establish a connection string, call the connect() method from the connector object using an appropriate connection string, such as:
    mod.connect("User=MyUser;Password=MyPassword;")

Connecting to Avalara

By default, the connector connects to a production environment. Set UseSandbox to true to configure the connector to connect to a Avalara sandbox environment.

Authenticating to Avalara

There are two authentication methods available for connecting to the Avalara data source: Basic and LicenseKey.

Login Credentials

To use login credentials for authentication, set the following:

  • AuthScheme: Set this to Basic.
  • User: Set this to your Avalara username.
  • Password: Set this to your Avalara password.

Account Number and License Key

Alternatively, you can authenticate using your account number and license key. Connect to the data source using the following:

  • AuthScheme: Set this to LicenseKey.
  • AccountId: Set this to your Avalara Account Id. The Account Id is listed in the upper right-hand corner of the Avalara admin console.
  • LicenseKey: Set this to your Avalara license key. You can generate a license key by logging into Avalara as an account adminstrator and navigating to Settings > Reset License Key.

CData Python Connector for Avalara

Configuring JNI

Java Native Interface (JNI) is a standard programming interface for writing Java native methods and embedding the Java virtual machine into native applications.

The connector leverages the JNI for improved performance on Mac and Linux.

Configure the Config INI File

The Linux and Mac editions of the Avalara python connector are configured with an ini file. This file is used to set several parameters, including JNI behavior. This file is to be located in:

{path_to_distribution_site-packages}/cdata/config.ini

Ensure that any configuration properties you set in the ini file fall under the following section name (adjust the 311 number if you are using an different python version from 3.11):

  • For Linux:
    [avalara.cpython-311-x86_64-linux-gnu.so]
  • For Mac:
    [avalara.cpython-311-darwin.so]

Configure the JNI connector's behavior by editing the properties in the connector's config.ini file. The connector can be configured as follows:

  • LOGFILE: Set this the same way as the CDATA_LOGFILE envrionment variable below.
  • JAVA_HOME: Configure the path to the JVM library location used to launch the JVM.
  • CLASS_PATH: Use a colon-separated list to configure the paths to the third-party jar libraries.

Configure Environment Variables

Additionally, set the following environment variables:

  • CDATA_JAVA_HOME: Configure the path to the JVM library location used to launch the JVM.
  • CDATA_JVM_OPTIONS: Place JVM options here.
  • CDATA_LOGFILE: Set this in the following scheme: <SCHEME>://<TAG>[|<LEVEL>]

    • SCHEME: The options are STDOUT, FILE.
      • STDOUT: Both the native wrapper and odbc core log into stdout. The Logfile and Verbosity properties can override the behavior of ODBC core.
      • FILE: The native wrapper logs into <FILENAME> while the odbc core logs into <FILENAME>.driver.log. The Logfile and Verbosity properties can override the behavior of ODBC core.
    • TAG
      • For STDOUT, set this to 1. For FILE, set this to the filename.
    • LEVEL
      • Set to one of: FATAL | ERROR | WARNING | INFO | DEBUG

The following are some examples of this syntax:

  • STDOUT://1|DEBUG
  • FILE:///tmp/my_py.log|DEBUG

Custom Logger

The Python connector supports a custom logging mechanism for redirecting log output to any destination, such as a cloud storage service or logging framework. Use setCustomLoggerFactory() to register a factory function that creates a logger instance for each connection.

The factory function receives the context string from the Logfile connection property (the portion after CUSTOM://) and must return an object with a writeLog(verbosity, message) method.

To enable custom logging:

  1. Call setCustomLoggerFactory() with your factory function before opening connections.
  2. Set Logfile to CUSTOM:// followed by a context string to identify the connection.
  3. Set Verbosity to the desired log level.

The following example demonstrates a custom logger factory that creates a separate logger instance per connection:

import cdata.avalara as mod
import time

class MyLogger:
    def __init__(self, loggerId):
        self.loggerId = loggerId
    def writeLog(self, verbosity, message):
        print("[MyLogger " + self.loggerId + "] " + message)

def createLogger(context):
    return MyLogger(context[len("MyLoggerId="):])

mod.setCustomLoggerFactory(createLogger)

conn1 = mod.connect("...;Logfile=CUSTOM://MyLoggerId=1;Verbosity=2;")
# do something with conn1
time.sleep(1)  # Wait for logs to flush from conn1

conn2 = mod.connect("...;Logfile=CUSTOM://MyLoggerId=2;Verbosity=2;")
# do something with conn2
time.sleep(1)  # Wait for logs to flush from conn2

CData Python Connector for Avalara

Fine-Tuning Data Access

Fine Tuning Data Access

You can use the following properties to gain more control over the data returned from Avalara:

  • CompanyCode: Only transaction information tied to this company code will be returned.
  • IncludeAdjustedTransactions: Set this to true to include adjusted transactions in the transaction listing.

CData Python Connector for Avalara

Changelog

General Changes

DateVersionSourceCategoryTypeDescription
2026-05-2826.0.9644AvalaraMetadataChanged
  • Changed the data type of the PageSize connection property from string to integer.
2026-05-2726.0.9643GeneralConnectionRemoved
  • Removed the deprecated ReplaceInvalidTypesWithNull connection property. Use the ReplaceInvalidValuesWithNull property instead.
2026-05-2226.0.9638PythonRemoved
  • Remove support for Intel x64 architecture on macOS
2026-05-0726.0.9623GeneralData ModelAdded
  • Added the ColumnCapabilities column to the sys_tablecolumns system table. This column is a bit mask denoting the column's write capabilities.
2026-05-0726.0.9623PythonChanged
  • Updated embedded JRE to jre-17.0.19+10 (Linux x64 / MacOs x64).
2026-04-1526.0.9601GeneralQuery ExecChanged
  • String comparisons using GREATER, LESS, and CONTAINS operators are now case-insensitive by default.
2026-04-0826.0.9594AvalaraSecurityChanged
  • TLS 1.3 is now supported by default for HTTP connections.
2026-01-1325.0.9509GeneralAdded
  • Added support for the REGEXP_REPLACE() string function.
2025-12-2125.0.9486PythonAdded
  • Added support for custom loggers in Python connectors on Linux and macOS.
2025-12-0525.0.9470GeneralAdded
  • Added support for the INSERT INTO SELECT statement, with driver-side execution for providers that do not support the operation natively.
2025-11-0425.0.9439AvalaraAdded
  • Added the Country and ClassificationEvent columns to the ItemClassification view.
  • Added the VarianceAmount and VendorName columns to the Transactions table.
2025-10-3025.0.9434PythonChanged
  • Updated embedded JRE to jre-17.0.17+10 (Linux x64 / MacOs x64).
2025-10-0625.0.9410GeneralAdded
  • Support for parsing datetime formats using ".S" and ",S" for milliseconds and nanoseconds.
2025-09-1225.0.9386GeneralAdded
  • Added the IsInsertable, IsUpdateable, and IsDeleteable columns to the sys_tables table.
2025-09-1025.0.9384GeneralChanged
  • All columns in statically defined Views are now reported as read-only.
2025-09-0325.0.9377GeneralChanged
  • Corrected the behavior when IN criteria with NULL values are used in the projection part. It now returns NULL instead of 0. For example, "NULL IN (1,2)" returns "NULL".
2025-09-0125.0.9375GeneralAdded
  • Added support for using the CAST function with infinity values. This function can cast "inf" and "-inf" to DOUBLE, FLOAT, or REAL.
2025-08-2125.0.9364GeneralChanged
  • Report behavior change:
    • Fixed inconsistent string value comparisons in non-table queries.
    • For example, "SELECT 'A' = 'a'" previously returned false, but it now returns true.
2025-08-1325.0.9356GeneralChanged
  • Changed the maximum number of pages held in memory from 15 to 5 for the page providers to decrease heap usage.
2025-07-0725.0.9319PythonRemoved
  • Removed the 32-bit version of Windows Python.
2025-07-0225.0.9314PythonRemoved
  • Removed support for Python 3.9.
2025-06-2525.0.9307GeneralRemoved
  • Removed the "ADLS Gen 1" value from the ConnectionType property.
2025-06-2525.0.9307PythonAdded
  • Added support for Python 3.13 in Windows, Linux, and Mac editions.
2025-06-2525.0.9307PythonRemoved
  • Removed support for Python 3.8 as it is no longer supported.
2025-06-2025.0.9302GeneralAdded
  • Created the following functions:
    • TEXT_ENCODE: encodes a string into a different charset (UTF8 → UTF7 and returns a binary array as the result).
    • TEXT_DECODE: takes a binary array and decodes it back into a string when provided the charset.
    • BASE64_ENCODE: takes a binary array and encodes it as a base64 string (varchar).
    • BASE64_DECODE: takes a base 64-encoded string and decodes it into a binary array.
2025-06-1825.0.9300GeneralChanged
  • The internal code for exception handling has been refactored. Exception messages returned during certain error conditions may now have different wording or formatting.
2025-05-2725.0.9278GeneralRemoved
  • Removed the "Proprietary" enum option from ProxyAuthscheme.
2025-05-1225.0.9263PythonChanged
  • Updated embedded JRE to jre-17.0.15+6 (Linux x64 / MacOS x64) and jre-17.0.15+6 (MacOS aarch64).
2025-02-2025.0.9182AvalaraAdded
  • Added the CompanyCode column to the following tables and views: Transactions, TransactionAddresses, TransactionInvoiceMessages, TransactionLines, TransactionLocationTypes, TransactionMessages, TransactionParameters, TransactionSummary, and TransactionTaxDetailsByTaxType.
2025-02-1524.0.9177GeneralAdded
  • Added support for converting unsigned integer types to the nearest signed data type that has enough precision to hold the unsigned value.This is done for JDBC only because it does not have support for unsigned data types.
2024-12-1624.0.9116AvalaraAdded
  • Added the following views: PostalCodes, Regions, TaxRatesByAddress, and TaxRatesByZipCode.
2024-11-2724.0.9097GeneralAdded
  • Added ThreadId to LogModule output. Logfile lines now include the Thread ID associated with the action being performed.
2024-06-0524.0.8922PythonAdded
  • Added support for Python 3.12.
2024-06-0524.0.8922AvalaraRemoved
  • Removed the Auto AuthScheme option. The default value for the AuthScheme connection property is now Basic.
2024-05-0924.0.8895GeneralChanged
  • The ROUND function previously did not accept negative precision values. That feature has now been restored.
2024-03-1523.0.8840GeneralAdded
  • Created a new SQL function called STRING_COMPARE that provides java's String.compare() ability to SQL queries. Returns a number representative of the compared value of two strings
2023-11-2923.0.8733GeneralChanged
  • The ROUND function doesn't accept the negative precision values anymore.
2023-11-2923.0.8733GeneralChanged
  • The returning types of the FDMonth, FDQuarter, FDWeek, LDMonth, LDQuarter, LDWeek functions are changed from Timestamp to Date.
  • The return type of the ABS function will be consistent with the parameter value type.
2023-11-2823.0.8732GeneralAdded
  • Added the HMACSHA256 formatter to allow for secrets to be decoded if it is in base64 format
2023-08-2923.0.8641PythonAdded
  • Added support for SQLAlchemy 2.0.
2023-06-2023.0.8571GeneralAdded
  • Added the new sys_lastresultinfo system table.
2023-05-1923.0.8539PythonAdded
  • Added support for Python 3.11 on Windows, Linux and Mac.
2023-05-1623.0.8536PythonRemoved
  • Removed support for Python 3.7 on Windows and Linux
2023-04-2523.0.8515GeneralRemoved
  • Removed support for the SELECT INTO CSV statement. The core code doesn't support it anymore.
2022-12-1422.0.8383GeneralChanged
  • Added the Default column to the sys_procedureparameters table.
2022-11-1522.0.8354PythonChanged
  • Updated embedded JRE to jre8u345-b01(Linux x64 / MacOS x64) and jre-17.0.5+8(MacOS aarch64).
2022-09-3022.0.8308GeneralChanged
  • Added the IsPath column to the sys_procedureparameters table.
2022-08-3122.0.8278AvalaraAdded
  • Added support for Output streams in the DownloadBatch stored procedure via the FileStream parameter.
2022-05-1822.0.8173PythonAdded
  • Added support for Python 3.10 on Windows, Linux, and Mac
  • Added support for Python 3.9 on Mac
  • Added support for Mac M1
2022-05-1822.0.8173PythonRemoved
  • Removed support for Python 3.6 on Windows and Linux
2021-09-0221.0.7915GeneralAdded
  • Added support for the STRING_SPLIT table-valued function in the CROSS APPLY clause.
2021-08-0721.0.7889GeneralChanged
  • Added the KeySeq column to the sys_foreignkeys table.
2021-08-0621.0.7888GeneralChanged
  • Added the new sys_primarykeys system table.
2021-07-2321.0.7874GeneralChanged
  • Updated the Literal Function Names for relative date/datetime functions. Previously, relative date/datetime functions resolved to a different value when used in the projection as opposed to the predicate. For example: SELECT LAST_MONTH() AS lm, Col FROM Table WHERE Col > LAST_MONTH(). Formerly, the two LAST_MONTH() methods would resolve to different datetimes. Now, they will match.
  • As a replacement for the previous behavior, the relative date/datetime functions in the criteria may have an 'L' appended to them. For example: WHERE col > L_LAST_MONTH(). This will continue to resolve to the same values that were previously calculated in the criteria. Note that the "L_" prefix will only work in the predicate - it not available for the projection.
2021-04-2521.0.7785GeneralAdded
  • Added support for handling client side formulas during insert / update. For example: UPDATE Table SET Col1 = CONCAT(Col1, " - ", Col2) WHERE Col2 LIKE 'A%'
2021-04-2321.0.7783GeneralChanged
  • Updated how display sizes are determined for varchar primary key and foreign key columns so they will match the reported length of the column.
2021-04-1621.0.7776GeneralAdded
  • Non-conditional updates between two columns is now available to all drivers. For example: UPDATE Table SET Col1=Col2
2021-04-1621.0.7776GeneralChanged
  • Reduced the length to 255 for varchar primary key and foreign key columns.
2021-04-1621.0.7776GeneralChanged
  • Updated implicit and metadata caching to improve performance and support for multiple connections. Old metadata caches are not compatible - you need to generate new metadata caches if you are currently using CacheMetadata.
2021-04-1621.0.7776GeneralChanged
  • Updated index naming convention to avoid duplicates.

CData Python Connector for Avalara

Using the Connector

This section provides a walk-through for writing Avalara data access code in Python script.

For more information on the available data source entities and how to query them with SQL, see Data Model. For the SQL syntax, see SQL Compliance.

Connecting from Code

For information on how to deploy the connector and configure the connection to Avalara, see Package Installation and Establishing a Connection.

For information on how to connect with the avalara.connector module and its related classes, see Connecting.

Executing SQL

The connection's cursor object is used to directly execute SQL queries. For information on how to execute SELECT statements and process the returned result sets, see Querying Data. For information on to modify the data in Avalara with INSERT, UPDATE, and DELETE statements, see Modifying Data .

Executing Stored Procedures

You can call stored procedures by using the EXECUTE statement. For further information, see Calling Stored Procedures.

CData Python Connector for Avalara

Connecting

Connecting with the cdata.avalara Module:

The connector's module is used directly to establish a connection with the data source. It does this by using a connection string as its argument. For example:
import cdata.avalara as mod
conn = mod.connect("User=MyUser;Password=MyPassword;")

Once the connection is created, you can use it to execute subsequent SQL queries.

CData Python Connector for Avalara

Querying Data

After connecting as described in Connecting, you can use the open connection to execute SQL statements.

Executing Queries

To execute SQL statements that return data, use the execute() method. Once a query is executed, the result set is fetched from the cursor. This result set can then be iterated over to process the records individually.

For example:

cur = conn.execute("SELECT Id, TotalTax FROM Transactions")
rs = cur.fetchall()
for row in rs:
	print(row)

Parameterized Queries

Various Python collections, such as arrays and tuples, can act as additional arguments for the execute() method. This enables you to parameterize the queries executed and help to prevent SQL Injection.

For example:

cmd = "SELECT Id, TotalTax FROM Transactions WHERE Code = ?"
params = ["051349"]
cur = conn.execute(cmd, params)
rs = cur.fetchall()
for row in rs:
	print(row)

CData Python Connector for Avalara

Modifying Data

The connection is also used to issue INSERT, UPDATE, and DELETE commands to the data source. Parameters can be used with these statements if desired.

Note that the connector does not support transactions. As with normal write operations, all SQL statements executed by this connector affect the data source immediately. Call the connection's commit() method following the execution.

Insert

The following example adds a new record to the table:
cmd = "INSERT INTO Transactions (Id, TotalTax) VALUES (?, ?)"
params = ["Jon Doe", "John"]
cur = conn.execute(cmd, params)
print("Records affected: ", cur.rowcount)

Update

The following example modifies an existing record in the table:
cmd = "UPDATE Transactions SET TotalTax = ? WHERE Id = ?"
params = ["John", "4000121038642"]
cur = conn.execute(cmd, params)
print("Records affected: ", cur.rowcount)

Delete

The following example removes an existing record from the table:

cmd = "DELETE FROM Transactions WHERE Id = ?"
params = ["4000121038642"]
cur = conn.execute(cmd, params)
print("Records affected: ", cur.rowcount)

CData Python Connector for Avalara

Calling Stored Procedures

You can execute stored procedures using either the execute() or callproc() method of the connection.

Calling Stored Procedures Using Execute()

When you call stored procedures by issuing EXECUTE commands, the stored procedure arguments are parameterized. For example:
cmd = "EXECUTE SelectEntries ObjectName = ?"
params = ["Account"]
conn.execute(cmd, params)

Calling Stored Procedures Using Callproc()

When you call stored procedured by issuing the callproc() method, the stored procedure arguments are a procedure name and a list of parameters. For example:
cur = conn.cursor()
params = ["Account"]
cur.callproc("SelectEntries", params)

CData Python Connector for Avalara

Using from Tools

The connector is integrated with other tools and packages within Python.

Python Integration Guides

The following sections show how to create and use connections with the connector in common packages in Python:

Complete List of Avalara Integration Quickstarts

For information on connecting from other applications, see Avalara integration guides.

CData Python Connector for Avalara

From SQLAlchemy

The CData Python Connector for Avalara includes a Dialect class that enables integration with SQLAlchemy. Bear in mind that several aspects of connector functionality are not currently supported in SQLAlchemy 2.0 or above. If necessary, downgrade SQLAlchemy to version 1.4 or 1.3 before using this connector.

The following sections detail various aspects of this integration:

Connecting From SQLAlchemy

To construct a URL with which SQLAlchemy loads and uses the appropriate connector automatically, see Connecting

Reflecting Metadata With SQLAlchemy

To learn how to model Avalara tables with mapped classes, see Reflecting Metadata.

Querying Data From SQLAlchemy

To learn how to use mapped classes to query the associated tables, see Querying Data.

Modifying Data From SQLAlchemy

The connector provides INSERT/UPDATE/DELETE functionality in SQLAlchemy. To learn how to call the session's execute() method to affect the data in the data source, see Modifying Data.

CData Python Connector for Avalara

Connecting

Connecting With a Dialect URL

Establishing a connection using SQLAlchemy requires a specific URL format. For this connector, you can create the engine using either of the following URL formats:

Format 1


from sqlalchemy import create_engine
engine = create_engine("avalara:///?User=MyUser;Password=MyPassword;")

Format 2


from sqlalchemy import create_engine
engine = create_engine("avalara://User:Password@/?CompanyCode=DEFAULT;")

For SQLAlchemy 2.0, the dialect name is avalara_2. To establish a connection, use the following URL format:

from sqlalchemy import create_engine
engine = create_engine("avalara_2:///?User=MyUser;Password=MyPassword;")

CData Python Connector for Avalara

Reflecting Metadata

SQLAlchemy can act as an Object-relational Map (ORM). This enables you to treat records of a database table as instantiable records. To leverage this functionality, you must reflect the underlying metadata in one of the following ways.

Note: The following examples employ SQLAlchemy 1.4.

Modeling Data Using a Mapping Class

Use "sqlalchemy.ext.declarative.declarative_base" to declare a mapping class for the table you wish to model in the ORM. A known table in the data model is modeled either partially or completely, as shown in the following example:
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class Transactions(Base):
	__tablename__ = "Transactions"
	Id = Column(String, primary_key=True)
	Id = Column(String)
	TotalTax = Column(String)

Automatically Reflecting Metadata

Rather than mapping tables manually, SQLAlchemy can discover the metadata for one or more tables automatically. To accomplish this across the entire data model, use automap_base:
from sqlalchemy import MetaData
from sqlalchemy.ext.automap import automap_base
meta = MetaData()
abase = automap_base(metadata=meta)
abase.prepare(autoload_with=engine)
Transactions = abase.classes.Transactions

You can also reflect a single table with an inspector. When reflecting this way, providing a list of specific columns to map is optional:

from sqlalchemy import MetaData, Table
from sqlalchemy import inspect
meta = MetaData()
insp = inspect(engine)
Transactions_table = Table("Transactions", meta)
insp.reflect_table(Transactions_table, ["Id","TotalTax"])

CData Python Connector for Avalara

Querying Data

After you use the steps in Connecting to connect, and use one of the methods in Reflecting Metadata to reflect some of the metadata, you can use a session object to query data.

Querying Data Using the Query Method

If the mapping class has been prepared, use it with a session object to query the data source. After binding the engine to the session, provide the mapping class to the session's query method.

For example:

engine = create_engine("avalara:///?User=MyUser;Password=MyPassword;")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Transactions).filter_by(Code="051349"):
	print("Id: ", instance.Id)
	print("Id: ", instance.Id)
	print("TotalTax: ", instance.TotalTax)
	print("---------")

Querying Data Using the Execute Method

The session object can also run the query with the execute() method alongside the appropriate Table object. Assuming you have an active session, the following is just as viable:
Transactions_table = Transactions.metadata.tables["Transactions"]
for instance in session.execute(Transactions_table.select().where(Transactions_table.c.Code == "051349")):
	print("Id: ", instance.Id)
	print("FullName: ", instance.Name)
	print("City: ", instance.BillingCity)
	print("---------")

CData Python Connector for Avalara

Executing JOINs

Implicit Joining

If mapped classes of related Avalara objects have a singular foreign key relationship, the classes are implicitly joined. After importing the necessary objects, a relationship is established between your two mapped classes, as in the example below:
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, String, Integer, DateTime, ForeignKey
from sqlalchemy.orm import sessionmaker, relationship

Base = declarative_base()
class Contact(Base):
	__tablename__ = "Contact"
	Id = Column(Integer, primary_key=True)
	Name = Column(String)
	Email = Column(String)
	BirthDate = Column(DateTime)
	AccountId = Column(String, ForeignKey("Account.Id"))
	Account_Link = relationship("Account", back_populates="Contact_Link")

class Account(Base):
	__tablename__ = "Account"
	Id = Column(String, primary_key=True)
	Name = Column(String)
	BillingCity = Column(String)
	NumberOfEmployees = Column(Integer)
	Contact_Link = relationship("Contact", order_by=Contact.Id, back_populates="Account_Link")

Once the relationship is established, the tables are queried simultaneously using the session's query() method. For example:

rs = session.query(Account, Contact).filter(Account.Id == Contact.AccountId)
for Ac, Ct in rs:
  print("AccountId: ", Ac.Id)
  print("AccountName: ", Ac.Name)
  print("ContactId: ", Ct.Id)
  print("ContactName: ", Ct.Name)

Other Join Forms

In situations where mapped classes have either no foreign keys or multiple foreign keys, you may need different forms of the JOIN query to accommodate them. Using the earlier classes as examples, the following JOIN queries are possible as well:
  • Explicit condition (necessary if there are no foreign keys in your mapped classes):
    rs = session.query(Account, Contact).join(Contact, Account.Id == Contact.AccountId)
    for Ac, Ct in rs:
  • Left-to-right relationship:
    rs = session.query(Account, Contact).join(Account.Contact_Link)
    for Ac, Ct in rs:
  • Left-to-right relationship with explicit target:
    rs = session.query(Account, Contact).join(Contact, Account.Contact_Link)
    for Ac, Ct in rs:
  • String form of a left-to-right relationship:
    rs = session.query(Account, Contact).join("Contact_Link")
    for Ac, Ct in rs:

CData Python Connector for Avalara

Other SQL Clauses

SQLAlchemy ORM also exposes support for other clauses in SQL, such as ORDER BY, GROUP BY, LIMIT, and OFFSET. All of these are supported by this connector:

ORDER BY

The following example sorts by a specified column using the session object's query() method:
rs = session.query(Transactions).order_by(Transactions.AnnualRevenue)
for instance in rs:
	print("Id: ", instance.Id)
	print("Id: ", instance.Id)
	print("TotalTax: ", instance.TotalTax)
	print("---------")

You can also use the session object's execute() method perform an ORDER BY. For example:

rs = session.execute(Transactions_table.select().order_by(Transactions_table.c.AnnualRevenue))
for instance in rs:

GROUP BY

The following example uses the session object's query() method to group records with a specified column:
rs = session.query(func.count(Transactions.Id).label("CustomCount"), Transactions.Id).group_by(Transactions.Id)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("Id: ", instance.Id)
	print("---------")

You can also use the session object's execute() method to perform a GROUP BY:

rs = session.execute(Transactions_table.select().with_only_columns([func.count(Transactions_table.c.Id).label("CustomCount"), Transactions_table.c.Id]).group_by(Transactions_table.c.Id))
for instance in rs:

LIMIT and OFFSET

The following example uses the session object's query() method to skip the first 100 records and fetch the following 25:
rs = session.query(Transactions).limit(25).offset(100)
for instance in rs:
	print("Id: ", instance.Id)
	print("Id: ", instance.Id)
	print("TotalTax: ", instance.TotalTax)
	print("---------")

You can also use the session object's execute() method to set a LIMIT or OFFSET:

rs = session.execute(Transactions_table.select().limit(25).offset(100))
for instance in rs:

CData Python Connector for Avalara

Aggregate Functions

Certain aggregate functions can also be used within SQLAlchemy by using the func module.

To import this module, execute:

from sqlalchemy.sql import func

Once func is imported, the following aggregate functions are available:

COUNT

The following example counts the number of records in a set of groups using the session object's query() method.
rs = session.query(func.count(Transactions.Id).label("CustomCount"), Transactions.Id).group_by(Transactions.Id)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("Id: ", instance.Id)
	print("---------")

You can also execute COUNT using the session object's execute() method:

rs = session.execute(Transactions_table.select().with_only_columns([func.count(Transactions_table.c.Id).label("CustomCount"), Transactions_table.c.Id])group_by(Transactions_table.c.Id))
for instance in rs:

SUM

This example calculates the cumulative amount of a numeric column in a set of groups.

rs = session.query(func.sum(Transactions.AnnualRevenue).label("CustomSum"), Transactions.Id).group_by(Transactions.Id)
for instance in rs:
	print("Sum: ", instance.CustomSum)
	print("Id: ", instance.Id)
	print("---------")

You can also invoke SUM using the session object's execute() method.

rs = session.execute(Transactions_table.select().with_only_columns([func.sum(Transactions_table.c.AnnualRevenue).label("CustomSum"), Transactions_table.c.Id]).group_by(Transactions_table.c.Id))
for instance in rs:

AVG

This example uses the session object's query() method to calculate the average amount of a numeric column in a set of groups:
rs = session.query(func.avg(Transactions.AnnualRevenue).label("CustomAvg"), Transactions.Id).group_by(Transactions.Id)
for instance in rs:
	print("Avg: ", instance.CustomAvg)
	print("Id: ", instance.Id)
	print("---------")

You can also use the session object's execute() method to invoke AVG:

rs = session.execute(Transactions_table.select().with_only_columns([func.avg(Transactions_table.c.AnnualRevenue).label("CustomAvg"), Transactions_table.c.Id]).group_by(Transactions_table.c.Id))
for instance in rs:

MAX and MIN

This example finds the maximum value and minimum value of a numeric column in a set of groups.
rs = session.query(func.max(Transactions.AnnualRevenue).label("CustomMax"), func.min(Transactions.AnnualRevenue).label("CustomMin"), Transactions.Id).group_by(Transactions.Id)
for instance in rs:
	print("Max: ", instance.CustomMax)
	print("Min: ", instance.CustomMin)
	print("Id: ", instance.Id)
	print("---------")

You can also use the session object's execute() method to invoke MAX and MIN:

rs = session.execute(Transactions_table.select().with_only_columns([func.max(Transactions_table.c.AnnualRevenue).label("CustomMax"), func.min(Transactions_table.c.AnnualRevenue).label("CustomMin"), Transactions_table.c.Id]).group_by(Transactions_table.c.Id))
for instance in rs:

CData Python Connector for Avalara

Modifying Data

Commands can be executed individually by the session with a call to "execute()".

Obtaining the Table Object

The query supplied to this method is constructed using the associated Table object of a mapped class. This Table object is obtained from the mapped class's metadata field, as below:

Transactions_table = Transactions.metadata.tables["Transactions"]

Once the table object is obtained, the write operations are executed in the following ways. The queries are executed immediately without the need for a call to "commit()":

Insert

The following example adds a new record to the table:

session.execute(Transactions_table.insert(), {"Id": "Jon Doe", "TotalTax": "John"})

Update

The following example modifies an existing record in the table:

session.execute(Transactions_table.update().where(Transactions_table.c.Id == "4000121038642").values(Id="Jon Doe", TotalTax="John"))

Delete

The following example removes an existing record from the table:

session.execute(Transactions_table.delete().where(Transactions_table.c.Id == "4000121038642"))

CData Python Connector for Avalara

From Pandas

When combined with the connector, Pandas can be used to generate data frames that contain your Avalara data. Once created, a data frame can be passed to various other Python packages.

Connecting

Pandas relies on an SQLAlchemy engine to execute queries. Before you can use Pandas you must import it:
import pandas as pd
from sqlalchemy import create_engine
engine = create_engine("avalara:///?User=MyUser;Password=MyPassword;")

Querying Data

In Pandas, SELECT queries are provided in a call to the read_sql() method, alongside a relevant connection object. Pandas executes the query on that connection, and returns the results in the form of a data frame, which can be used for a variety of purposes.
df = pd.read_sql("""
	SELECT
	   Id,
	   TotalTax,
     $exNumericCol;
	FROM Transactions;""", engine)
print(df)

Modifying Data

To insert new records into a table, create a new data frame, and define its fields accordingly. When that is done, call to_sql() on the data frame to perform the INSERT operation with the connector, as shown in the example below. You must set the "if _exists" argument to "append" to prevent Pandas from attempting building the table from scratch. To prevent Pandas from writing the data frame index as a column, set index=False.
df = pd.DataFrame({"Id": ["Jon Doe"], "TotalTax": ["John"]})
df.to_sql("Transactions", con=engine, if_exists="append", index=False)

CData Python Connector for Avalara

From Matplotlib

Matplotlib contains a number of tools that can graphically model Avalara data after being fed a data frame From Pandas.

Using PyPlot

Before any Matplotlib tool, such as pyplot, can be used, it must be imported:
from matplotlib import pyplot as plt

Once a Pandas data frame is obtained, it can be used to create a plot visualizing Avalara data. For example, the following plot generates and displays a bar graph relating Id and AnnualRevenue values:

df.plot(kind="bar", x="Id", y=["AnnualRevenue"])
plt.show()

CData Python Connector for Avalara

From Petl

The connector can be used to create ETL applications and pipelines for CSV data in Python using Petl.

Install Required Modules

Install the Petl modules using the pip utility.
pip install petl

Connecting

After you import the modules, including the CData Python Connector for Avalara, you can use the connector's connect function to create a connection using a valid Avalara connection string. If you prefer not to use a direct connection, you can use a SQLAlchemy engine.
import petl as etl
import cdata.avalara as mod
cnxn = mod.connect("User=MyUser;Password=MyPassword;")

Extract, Transform, and Load the Avalara Data

Create a SQL query string and store the query results in a DataFrame.
sql = "SELECT	Id, TotalTax FROM Transactions "
table1 = etl.fromdb(cnxn,sql)

Loading Data

With the query results stored in a DataFrame, you can load your data into any supported Petl destination. The following example loads the data into a CSV file.
etl.tocsv(table1,'output.csv')

Modifying Data

Insert new rows into Avalara tables using Petl's appenddb function.
table1 = [['Id','TotalTax'],['Jon Doe','John']]
etl.appenddb(table1,cnxn,'Transactions')

CData Python Connector for Avalara

Schema Discovery

The extension supports schema discovery by using SQL queries to available System Tables.

Using SQL

The following sections describe the discovery of metadata through several System Tables:

CData Python Connector for Avalara

Tables and Views

The connector possesses system tables that are used to discover the tables and views available in the data model. Of these system tables, "sys_tables" and "sys_views" are used to fetch information about the available tables and views respectively:

Tables


import cdata.avalara as mod
conn = mod.connect("User=MyUser;Password=MyPassword;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_tables"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

Views


import cdata.avalara as mod
conn = mod.connect("User=MyUser;Password=MyPassword;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_views"
cur.execute(cmd, params)
rs = cur.fetchall()
for row in rs:
	print(row)

CData Python Connector for Avalara

Columns

The available columns for any given table are fetched from a system table called "sys_tablecolumns". A specific table name is provided in the WHERE criteria to restrict the table from which the column information is fetched:

import cdata.avalara as mod
conn = mod.connect("User=MyUser;Password=MyPassword;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_tablecolumns WHERE TableName = 'Transactions'"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

CData Python Connector for Avalara

Procedures

Procedures

A system table called "sys_procedures" is queried to obtain the available stored procedures that are executed:
import cdata.avalara as mod
conn = mod.connect("User=MyUser;Password=MyPassword;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_procedures"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

Parameters

The input parameters of any stored procedure are similarly obtained from the "sys_procedureparameters" system table:
import cdata.avalara as mod
conn = mod.connect("User=MyUser;Password=MyPassword;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'SelectEntries'"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

CData Python Connector for Avalara

Advanced Features

This section details a selection of advanced features of the Avalara connector.

User Defined Views

The connector supports the use of user defined views, virtual tables whose contents are decided by a pre-configured user defined query. These views are useful when you cannot directly control queries being issued to the drivers. For an overview of creating and configuring custom views, see User Defined Views .

SSL Configuration

Use SSL Configuration to adjust how connector handles TLS/SSL certificate negotiations. You can choose from various certificate formats;. For further information, see the SSLServerCert property under "Connection String Options" .

Firewall and Proxy

Configure the connector for compliance with Firewall and Proxy, including Windows proxies and HTTP proxies. You can also set up tunnel connections.

Caching Data

Caching Data enables faster access to data and reduces the number of API calls, improving performance. The connector supports a simple caching model where multiple connections can also share the cache over time. When configuring the cache connection, you can specify automatic or explicit data caching.

Query Processing

The connector offloads as much of the SELECT statement processing as possible to Avalara and then processes the rest of the query in memory (client-side).

For further information, see Query Processing.

Logging

For an overview of configuration settings that can be used to refine CData logging, see Logging. Only two connection properties are required for basic logging, but there are numerous features that support more refined logging, which enables you to use the LogModules connection property to specify subsets of information to be logged.

Exception Handling

For an overview of how exceptions are reported and the components of an exception, see Exception Handling.

CData Python Connector for Avalara

User Defined Views

The CData Python Connector for Avalara supports the use of user defined views: user-defined virtual tables whose contents are decided by a preconfigured query. User defined views are useful in situations where you cannot directly control the query being issued to the driver; for example, when using the driver from a tool.

Use a user defined view to define predicates that are always applied. If you specify additional predicates in the query to the view, they are combined with the query already defined as part of the view.

There are two ways to create user defined views:

  • Create a JSON-formatted configuration file defining the views you want.
  • DDL statements.

Defining Views Using a Configuration File

User defined views are defined in a JSON-formatted configuration file called UserDefinedViews.json. The connector automatically detects the views specified in this file.

You can also have multiple view definitions and control them using the UserDefinedViews connection property. When you use this property, only the specified views are seen by the connector.

This user defined view configuration file is formatted so that each root element defines the name of a view, and includes a child element, called query, which contains the custom SQL query for the view.

For example:

{
	"MyView": {
		"query": "SELECT * FROM Transactions WHERE MyColumn = 'value'"
	},
	"MyView2": {
		"query": "SELECT * FROM MyTable WHERE Id IN (1,2,3)"
	}
}
Use the UserDefinedViews connection property to specify the location of your JSON configuration file. For example:
"UserDefinedViews", "C:\\Users\\yourusername\\Desktop\\tmp\\UserDefinedViews.json"

Defining Views Using DDL Statements

The connector is also capable of creating and altering the schema via DDL Statements such as CREATE LOCAL VIEW, ALTER LOCAL VIEW, and DROP LOCAL VIEW.

Create a View

To create a new view using DDL statements, provide the view name and query as follows:

CREATE LOCAL VIEW [MyViewName] AS SELECT * FROM Customers LIMIT 20;

If no JSON file exists, the above code creates one. The view is then created in the JSON configuration file and is now discoverable. The JSON file location is specified by the UserDefinedViews connection property.

Alter a View

To alter an existing view, provide the name of an existing view alongside the new query you would like to use instead:

ALTER LOCAL VIEW [MyViewName] AS SELECT * FROM Customers WHERE TimeModified > '3/1/2020';

The view is then updated in the JSON configuration file.

Drop a View

To drop an existing view, provide the name of an existing schema alongside the new query you would like to use instead.

DROP LOCAL VIEW [MyViewName]

This removes the view from the JSON configuration file. It can no longer be queried.

Schema for User Defined Views

In order to avoid a view's name clashing with an actual entity in the data model, user defined views are exposed in the UserViews schema by default. To change the name of the schema used for UserViews, reset the UserViewsSchemaName property.

Working with User Defined Views

For example, a SQL statement with a user defined view called UserViews.RCustomers only lists customers in Raleigh:
SELECT * FROM Customers WHERE City = 'Raleigh';
An example of a query to the driver:
SELECT * FROM UserViews.RCustomers WHERE Status = 'Active';
Resulting in the effective query to the source:
SELECT * FROM Customers WHERE City = 'Raleigh' AND Status = 'Active';
That is a very simple example of a query to a user defined view that is effectively a combination of the view query and the view definition. It is possible to compose these queries in much more complex patterns. All SQL operations are allowed in both queries and are combined when appropriate.

CData Python Connector for Avalara

SSL Configuration

Customizing the SSL Configuration

By default, the connector attempts to negotiate TLS with the server. The server certificate is validated against the default system trusted certificate store. You can override how the certificate gets validated using the SSLServerCert connection property.

To specify another certificate, see the SSLServerCert connection property.

CData Python Connector for Avalara

Firewall and Proxy

Connecting Through a Firewall or Proxy

HTTP Proxies

Note: The connector uses the system proxy settings by default, without further configuration needed. If you want to connect to other proxies, set ProxyAutoDetect to False and read further.

To authenticate to an HTTP proxy, set the following:

  • ProxyServer: the hostname or IP address of the proxy server that you want to route HTTP traffic through.
  • ProxyPort: the TCP port that the proxy server is running on.
  • ProxyAuthScheme: the authentication method the connector uses when authenticating to the proxy server.
  • ProxyUser: the username of a user account registered with the proxy server.
  • ProxyPassword: the password associated with the ProxyUser.

Other Proxies

Set the following properties:

CData Python Connector for Avalara

Caching Data

Caching Data

Caching data provides several benefits, including faster access to data and reducing the number of API calls, which improve performance. The connector supports a simple caching model where multiple connections can also share the cache over time. You can enable and configure caching features by setting the necessary connection properties.

Contents

The sections in this chapter detail the connector's caching functionality and link to the corresponding connection properties, as well as SQL statements.

Configuring the Cache Connection

Configuring the Cache Connection describes the properties that you can set when configuring the cache database.

Caching Metadata

Caching Metadata describes the CacheMetadata property. This property determines whether or not to cache the table metadata to a file store.

Automatically Caching Data

Automatically Caching Data describes how the connector automatically refreshes the cache when the AutoCache property is set.

Explicitly Caching Data

Explicitly Caching Data describes how you can decide what data is stored in the cache and when it is updated.

Data Type Mapping

Data Type Mapping shows the mappings between the data types configured in the schema and the data types in the database.

CData Python Connector for Avalara

Configuring the Cache Connection

Configuring the Caching Database

This section describes the properties for caching data to the persistent store of your choice.

CacheLocation

The CacheLocation property species the path to a file-system-based database. When caching is enabled, a file-system-based database is used by default. If CacheLocation is not specified, this database is stored at the path in Location. If neither of these connection properties are specified, the connector uses a platform-dependent default location.

CacheConnection

The CacheConnection property specifies a database driver and the connection string to the caching database.

CacheDriver and CacheProvider

Both the CacheDriver and CacheProvider properties are supported. Each specifies a database driver and the connection string to the caching database. CacheDriver is designed for Linux and MacOS; CacheProvider is Windows-based.

CData Python Connector for Avalara

Caching Metadata

This section describes how to enable caching metadata and how to update the metadata cache.

Before being able to query data, the connector requires relevant metadata to be retrieved. By default, metadata is cached in memory and shared across connections. But if you want to persist across processes, or if metadata requests are expensive, the solution is to cache the metadata to disk.

Enable Caching Metadata

To enable caching of metadata, set CacheMetadata = true and see Configuring the Cache Connection for instructions on how to configure your connection string. The connector caches the metadata the first time it is needed and uses the metadata cache for subsequent requests.

Update the Metadata Cache

Because metadata is cached, changes to metadata on the live source, for example, adding or removing a column or attribute, are not automatically reflected in the metadata cache. To get updates to the live metadata, you need to delete or drop the cached data.

CData Python Connector for Avalara

Automatically Caching Data

Automatically caching data is useful when you do not want to rebuild the cache for each query. When you query data for the first time, the connector automatically initializes and builds a cache in the background. When AutoCache = true, the connector uses the cache for subsequent query executions, resulting in faster response times.

Configuring Automatic Caching

Caching the Transactions Table

The following example caches the Transactions table in the file specified by the CacheLocation property of the connection string.

SELECT Id, TotalTax FROM Transactions WHERE Code = '051349'

Common Use Case

A common use for automatically caching data is to improve driver performance when making repeated requests to a live data source, such as building a report or creating a visualization. With auto caching enabled, repeated requests to the same data may be executed in a short period of time, but within an allowable tolerance (CacheTolerance) of what is considered "live" data.

CData Python Connector for Avalara

Explicitly Caching Data

With explicit caching (AutoCache = false), you decide exactly what data is cached and when to query the cache instead of the live data. Explicit caching gives you full control over the cache contents by using CACHE Statements. This section describes some strategies to use the caching features offered by the connector.

Creating the Cache

To load data in the cache, issue the following statement.

CACHE SELECT * FROM tableName WHERE ...

Once the statement is issued, any matching data in tableName is loaded into the corresponding table.

Updating the Cache

This section describes two ways to update the cache.

Updating with the SELECT Statement

The following example shows a statement that can update modified rows and add missing rows in the cached table. However, this statement does not delete extra rows that are already in the cache. This statement only merges the new rows or updates the existing rows.

CACHE SELECT * FROM Transactions WHERE Code = '051349'

Updating with the TRUNCATE Statement

The following example shows a statement that can update modified rows and add missing rows in the cached table. This statement can also delete rows in the cache table that are not present in the live data source.

  CACHE WITH TRUNCATE SELECT * FROM Transactions WHERE Code = '051349'
  

Query the Data in Online or Offline Mode

This section describes how to query the data in online or offline mode.

Online: Select Cached Tables

You can use the tableName#CACHE syntax to explicitly execute queries to the cache while still online, as shown in the following example.

SELECT * FROM Transactions#CACHE

Offline: Select Cached Tables

With Offline = true, SELECT statements always execute against the local cache database, regardless of whether you explicitly specify the cached table or not. Modification of the cache is disabled in Offline mode to prevent accidentally updating only the cached data. Executing a DELETE/UPDATE/INSERT statement while in Offline mode results in an exception.

The following example selects from the local cache but not the live data source because Offline = true.

SELECT * FROM Transactions WHERE Code='051349' ORDER BY TotalTax ASC

Delete Data from the Cache

You can delete data from the cache by building a direct connection to the database. Note that the connector does not support manually deleting data from the cache.

Common Use Case

A common use for caching is to have an application always query the cached data and only update the cache at set intervals, such as once every day or every two hours. There are two ways in which this can be implemented:

  • AutoCache = false and Offline = false. All queries issued by the application explicitly reference the tableName#CACHE table. When the cache needs to be updated, the application executes a tableName#CACHE ... statement to bring the cached data up to date.
  • Offline = true. Caching is transparent to the application. All queries are executed against the table as normal, so most application code does not need to be aware that caching is done. To update the cached data, simply create a separate connection with Offline = false and execute a tableName#CACHE ... statement.

CData Python Connector for Avalara

Data Type Mapping

The connector maps types from the data source to the corresponding data type available in the chosen cache database. The following table shows the mappings between the data types configured in the schema and the data types in the database. Some schema types have synonyms which are all listed in the Schema column.

Data Type Mapping

Note: String columns can map to different data types depending on their length.

Schema .NET JDBC SQL Server Derby MySQL Oracle SQLite Access
int, integer, int32 Int32 int int INTEGER INT NUMBER integer LONG
smallint, short, int16 Int16 short smallint SMALLINT SMALLINT NUMBER integer SHORT
double, float, real Double double float DOUBLE DOUBLE NUMBER double DOUBLE
date DateTime java.sql.Date date DATE DATE DATE date DATETIME
datetime, timestamp DateTime java.sql.Date datetime TIMESTAMP DATETIME TIMESTAMP datetime DATETIME
time, timespan TimeSpan java.sql.Time time TIME TIME TIMESTAMP datetime DATETIME
string, varchar String java.lang.String If length > 4000: nvarchar(max), Otherwise: nvarchar(length)If length > 32672: LONG VARCHAR, Otherwise VARCHAR(length)If length > 255: LONGTEXT, Otherwise: VARCHAR(length)If length > 4000: CLOB, Otherwise: VARCHAR2(length)nvarchar(length)If length > 255: LONGTEXT, Otherwise: VARCHAR(length)
long, int64, bigint Int64 long bigint BIGINT BIGINT NUMBER bigint LONG
boolean, bool Boolean boolean tinyint SMALLINT BIT NUMBER tinyint BIT
decimal, numeric Decimal java.math.BigDecimal decimal DECIMAL DECIMAL DECIMAL decimal CURRENCY
uuid Guid java.util.UUID nvarchar(length) VARCHAR(length)VARCHAR(length) VARCHAR2(length)nvarchar(length) VARCHAR(length)
binary, varbinary, longvarbinary byte[] byte[] binary(1000) or varbinary(max) after SQL Server 2000, image otherwise BLOB LONGBLOB BLOB BLOB LONGBINARY

CData Python Connector for Avalara

Query Processing

Query Processing

CData has a client-side SQL engine built into the connector library. This enables support for the full capabilities that SQL-92 offers, including filters, aggregations, functions, etc.

For sources that do not support SQL-92, the connector offloads as much of SQL statement processing as possible to Avalara and then processes the rest of the query in memory (client-side). This results in optimal performance.

For data sources with limited query capabilities, the connector handles transformations of the SQL query to make it simpler for the connector. The goal is to make smart decisions based on the query capabilities of the data source to push down as much of the computation as possible. The Avalara Query Evaluation component examines SQL queries and returns information indicating what parts of the query the connector is not capable of executing natively.

The Avalara Query Slicer component is used in more specific cases to separate a single query into multiple independent queries. The client-side Query Engine makes decisions about simplifying queries, breaking queries into multiple queries, and pushing down or computing aggregations on the client-side while minimizing the size of the result set.

There's a significant trade-off in evaluating queries, even partially, client-side. There are always queries that are impossible to execute efficiently in this model, and some can be particularly expensive to compute in this manner. CData always pushes down as much of the query as is feasible for the data source to generate the most efficient query possible and provide the most flexible query capabilities.

More Information

For a full discussion of how CData handles query processing, see CData Architecture: Query Execution.

CData Python Connector for Avalara

Logging

Logging

Capturing connector logging can be very helpful when diagnosing error messages or other unexpected behavior.

Basic Logging

To begin capturing connector logging, set these properties:

  • Logfile: A filepath that designates the name and location of the log file.
  • Verbosity: A numerical value (1-5) that determines the amount of detail in the log. See the page in the Connection Properties section for an explanation of the five levels.
  • MaxLogFileSize: When the limit is hit, a new log is created in the same folder with the date and time appended to the end. The default limit is 100 MB. Values lower than 100 kB will use 100 kB as the value instead.
  • MaxLogFileCount: A string specifying the maximum file count of log files. When the limit is hit, a new log is created in the same folder with the date and time appended to the end and the oldest log file will be deleted. Minimum supported value is 2. A value of 0 or a negative value indicates no limit on the count.

Once these properties are set, the connector populates the log file as it carries out various tasks, such as when authentication is performed or queries are executed. If the specified file doesn't already exist, it is created.

Log Verbosity

The verbosity level determines the amount of detail that the connector reports to the Logfile. Supported Verbosity levels range from 1 to 5.

The following list describes each level:

1Setting Verbosity to 1 logs the query, the number of rows returned by it, the start of execution and the time taken, and any errors.
2Setting Verbosity to 2 logs everything included in Verbosity 1, cache queries, and additional information about the request.
3Setting Verbosity to 3 also logs HTTP headers, as well as the body of the request and the response.
4Setting Verbosity to 4 also logs transport-level communication with the data source. This includes SSL negotiation.
5Setting Verbosity to 5 also logs communication with the data source and additional details that may be helpful in troubleshooting problems. This includes interface commands.

For normal operations, Verbosity should not be set to greater than 1. At higher verbosities you can log substantial amounts of data, which can delay execution times.

To refine the logged content further by showing/hiding specific categories of information, see LogModules.

Sensitive Data

Verbosity levels of 3 and higher may capture information that you do not want shared outside of your organization. The following lists information of concern for each level:

  • Verbosity 3: The full body of the request and the response, which includes all the data returned by the connector
  • Verbosity 4: SSL certificates
  • Verbosity 5: Any extra transfer data not included at Verbosity 3, such as non human-readable binary transfer data

Note: Although we mask sensitive values, such as passwords, in the connection string and any request in the log, it is always best practice to review the logs for any sensitive information before sharing outside your organization.

Advanced Logging

You may want to refine the exact information that is recorded to the log file. This can be accomplished using the LogModules property. This property allows you to filter the logging using a semicolon-separated list of logging modules.

Example property value:

LogModules=INFO;EXEC;SSL;SQL;META;

Note that the logfile filtering triggered by the Verbosity connection property takes precedence over the filtering imposed by this connection property. This means that operations of a higher verbosity level than the level specified in the Verbosity connection property are not printed in the logfile, even if they belong to one of the modules specified in this connection property.

The available modules and submodules are:

Module Name Module Description Submodules
INFO General Information. Includes the connection string, product version (build number), and initial connection messages.
  • Connec – Information related to creating or destroying connections.
  • Messag – Generic label for messages pertaining to connections, the connection string, and product version. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
EXEC Query Execution. Includes execution messages for user-written SQL queries, parsed SQL queries, and normalized SQL queries. Success/failure messages for queries and query pages appear here as well.
  • Messag – Messages pertaining to query execution. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
  • Normlz – Query normalization steps. Query normalization is when the product takes the user-submitted query and rewrites the query to get the same results with optimal performance.
  • Origin – This label applies to any messages recording a user's original query (the exact, unaltered, non-normalized query executed by the user).
  • Page – Messages related to query paging.
  • Parsed – Query parsing steps. Parsing is the process of converting the user-submitted query into a standardized format for easier processing.
HTTP HTTP protocol messages. Includes HTTP requests/responses (including POST messages), as well as Kerberos related messages.
  • KERB – HTTP requests related to Kerberos.
  • Messag – Messages pertaining to HTTP protocols. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
  • Unpack – This label applies to messages about zipped data being returned from the service API and unpacked by the product.
  • Res – Messages containing HTTP responses.
  • Req – Messages containing HTTP requests.
WSDL Messages pertaining to the generation of WSDL/XSD files.
SSL SSL certificate messages.
  • Certif – Messages pertaining to SSL certificates.
AUTH Authentication related failure/success messages.
  • Messag – Messages pertaining to authentication. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
  • OAuth – Messages related to OAuth authentication.
  • Krbros – Kerberos-related authentication messages.
SQL Includes SQL transactions, SQL bulk transfer messages, and SQL result set messages.
  • Bulk – Messages pertaining to bulk query execution.
  • Cache – Messages related to reading row data from and writing row data to the product's cache for better performance.
  • Messag – Messages pertaining to SQL transactions. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
  • ResSet – Query resultsets.
  • Transc – Messages related to handling transactions, including information about the number of jobs executed and backup table handling.
META Metadata cache and schema messages.
  • Cache – Messages related to reading from and modifying column and table definitions in the product's cache for better performance.
  • Schema – Messages related to retrieving metadata from or modifying the service schema.
  • MemSto – Messages related to writing to or reading from in-memory metadata cache.
  • Storag – Messages relating to storing metadata on disk or in an external data store, rather than in memory.
FUNC Information related to executing SQL functions.
  • Errmsg – Error messages related to executing SQL functions.
TCP Incoming and outgoing raw bytes on TCP transport layer messages.
  • Send – Raw data sent via the TCP protocol.
  • Receiv – Raw data received via the TCP protocol.
FTP Messages pertaining to the File Transfer Protocol.
  • Info – Status messages related to communication in the FTP protocol.
  • Client – Messages related to actions taken by the FTP client (the product) during FTP communication.
  • Server – Messages related to actions taken by the FTP server during FTP communication.
SFTP Messages pertaining to the Secure File Transfer Protocol.
  • Info – Status messages related to communication in the SFTP protocol.
  • To_Server – Messages related to actions taken by the SFTP client (the product) during SFTP communication.
  • From_Server – Messages related to actions taken by the SFTP server during SFTP communication.
POP Messages pertaining to data transferred via the Post Office Protocol.
  • Client – Messages related to actions taken by the POP client (the product) during POP communication.
  • Server – Messages related to actions taken by the POP server during POP communication.
  • Status – Status messages related to communication in the POP protocol.
SMTP Messages pertaining to data transferred via the Simple Mail Transfer Protocol.
  • Client – Messages related to actions taken by the SMTP client (the product) during SMTP communication.
  • Server – Messages related to actions taken by the SMTP server during SMTP communication.
  • Status – Status messages related to communication in the SMTP protocol.
CORE Messages relating to various internal product operations not covered by other modules.
DEMN Messages related to SQL remoting.
CLJB Messages about bulk data uploads (cloud job).
  • Commit – Submissions for bulk data uploads.
SRCE Miscellaneous messages produced by the product that don't belong in any other module.
TRANCE Advanced messages concerning low-level product operations.

CData Python Connector for Avalara

Exception Handling

Exception Handling

Exceptions can be surfaced from either the API or the CData Python Connector for Avalara. Each exception will have an error code, an error message, and a SQL state.

Error Codes

The error code classifies the type of error.

0 NONE Used for unclassified errors and internally handled errors. This code also covers data source-specific errors that do not fit in any specific category.
65537 TCP_UNKNOWN_HOST Unable to resolve a hostname (DNS failure).
65538 TCP_CONNECTION_REFUSED Could not connect to the remote port.
65539 TCP_AUTH_FAILED Login failed when using a binary authentication protocol. Use this for auth errors when the protocol is not HTTP (LDAP, SASL, Kerberos, ...).
65540 TCP_TIMEOUT Did not receive a response after sending a request to the server.
65541 TCP_PROTOCOL For wire protocol drivers. Either the server sent a bad packet that we are unable to process, or we cannot construct a packet to send.
131073 TLS_SERVER_UNTRUSTED Could not verify SSL server certificate.
131074 TLS_CLIENT_UNTRUSTED Server did not accept the client certificate we sent.
196609 OAUTH_DECRYPT_FAILED OAuthEncryptKey did not decrypt the OAuthSettings file.
196610 OAUTH_MISSING_CLIENT_INFO OAuthClientId / OAuthClientSecret / OAuthJWTCert is missing.
196611 OAUTH_MISSING_PROP General OAuth property missing. OAUTH_MISSING_CLIENT_INFO is used for missing client ID/secret and JWT cert.
196612 OAUTH_NO_ACCESS_TOKEN Unable to retrieve access token. Only use this when getting a token in GetOAuthAccessToken / RefreshOAuthAccessToken.
196613 OAUTH_TOKEN_EXPIRED The access token expired. Normally used with a RefreshOAuth/OAuthException behavior.
196614 OAUTH_INVALID_PROP OAuth property has an invalid value. OAUTH_MISSING_CLIENT_INFO / OAUTH_MISSING_PROP is used if the value is not set.
262145 HTTP_REQUEST_TIMEOUT Did not receive a response from the HTTP server.
262146 HTTP_CLIENT_ERROR Generic HTTP 4xx error. Only use for 4xx errors not covered by other codes.
262147 HTTP_AUTH_FAILED HTTP 401 error.
262148 HTTP_LIMIT_EXCEEDED HTTP 429 error.
262149 HTTP_SERVER_ERROR HTTP 5xx error.
262150 HTTP_NOT_FOUND_ERROR HTTP 404 error.
327681 CORE_TIMEOUT General timeout. Not related to a specific network request.
327682 CORE_OP_NOT_ALLOWED Operation blocked by provider permissions.
327683 CORE_CONNECTION_CONFIG Connection configuration is not valid.
327684 CORE_SERIALIZE Failed to encode data into a specific format (XML, JSON, CSV, ...).
327685 CORE_DESERIALIZE Failed to decode data from a specific format (XML, JSON, CSV, ...).
393217 SQL_SYNTAX_ERROR Unable to parse a SQL query.
393218 SQL_MISSING_COLUMNS Query did not include required columns.
393219 SQL_MISSING_PARAMS Stored procedure call did not include required parameters.
393220 SQL_QUERY_NOT_SUPPORTED A part of the query is not allowed in the current context.
458753 SSH_SERVER_UNTRUSTED Could not verify SSH server.
524289 STORAGE_LIST_EXCEPTION Issue listing storage resources.
524290 STORAGE_RESOURCE_NOT_FOUND Issue finding storage resources.
524291 STORAGE_ROOT_RESOURCE_NOT_FOUND The root resource (bucket/share/drive) was not found; cannot create it in flat file drivers.
524292 STORAGE_RESOURCE_NOT_A_DIRECTORY Storage resource is not a directory.
524293 STORAGE_RESOURCE_NOT_A_FILE Storage resource is not a file.
524294 STORAGE_PERMISSIONS_DENIED Storage permissions denied.

SQL State

The SQL state is used when throwing generic provider errors to the wrapper and indicates the success or failure of a call.

Some of the common SQL states are listed below:

07007 REQUIRED_CLAUSE Class Code 07: Dynamic SQL Error.
08001 OPEN_CONNECTION Class Code 08: Connection Exception. The connection was unable to be established to the application server or other server.
08004 REJECT_CONNECTION The application server rejected establishment of the connection.
42501 PRIVILEGE_IDENTIFIED_OBJECT Class Code 42: Syntax Error or Access Rule Violation. The authorization ID does not have the privilege to perform the specified operation on the identified object.
42506 AUTH_FAILED Owner authorization failure occurred.
42601 SQL_SYNTAX A character, token, or clause is invalid or missing.

Error Message

The error message provides more detailed reasoning about why the error occurred. It provides an explanation of the issue, and may include steps on how to resolve it.

CData Python Connector for Avalara

SQL Compliance

The CData Python Connector for Avalara supports several operations on data, including querying, deleting, modifying, and inserting.

SELECT Statements

See SELECT Statements for a syntax reference and examples.

See Data Model for information on the capabilities of the Avalara API.

INSERT Statements

See INSERT Statements for a syntax reference and examples.

UPDATE Statements

The primary key Id is required to update a record. See UPDATE Statements for a syntax reference and examples.

DELETE Statements

The primary key Id is required to delete a record. See DELETE Statements for a syntax reference and examples.

CACHE Statements

CACHE statements allow granular control over the connector's caching functionality. For a syntax reference and examples, see CACHE Statements.

For more information on the caching feature, see Caching Data.

EXECUTE Statements

Use EXECUTE or EXEC statements to execute stored procedures. See EXECUTE Statements for a syntax reference and examples.

Names and Quoting

  • Table and column names are considered identifier names; as such, they are restricted to the following characters: [A-Z, a-z, 0-9, _:@].
  • To use a table or column name with characters not listed above, the name must be quoted using square brackets ([name]) in any SQL statement.
  • Parameter names can optionally start with the @ symbol (e.g., @p1 or @CustomerName) and cannot be quoted.
  • Strings must be quoted using single quotes (e.g., 'John Doe').

CData Python Connector for Avalara

SQL Functions

The connector provides functions that are similar to those that are available with most standard databases. These functions are implemented in the CData provider engine and thus are available across all data sources with the same consistent API. Three categories of functions are available: string, date, and math.

The connector interprets all SQL function inputs as either strings or column identifiers, so you need to escape all literals as strings, with single quotes. For example, contrast the SQL Server syntax and connector syntax for the DATENAME function:

  • SQL Server:
    SELECT DATENAME(yy,GETDATE())
  • connector:
    SELECT DATENAME('yy',GETDATE())

String Functions

These functions perform string manipulations and return a string value. See STRING Functions for more details.

Date Functions

These functions perform date and date time manipulations. See DATE Functions for more details.

Math Functions

These functions provide mathematical operations. See MATH Functions for more details.

CData Python Connector for Avalara

STRING Functions

ASCII(character_expression)

Returns the ASCII code value of the left-most character of the character expression.

  • character_expression: The character expression.

                      SELECT ASCII('0');
                      --  Result: 48
                    

BASE64_ENCODE(input_binary)

Returns the Base64-encoded string form of a binary input.

  • input_binary: The binary value to encode.

                        SELECT BASE64_ENCODE(BinaryData);
                    -- Result: 'QmFzZTY0RW5jb2RlZA=='
                    

BASE64_DECODE(input_string)

Returns the binary result of decoding a Base64-encoded string.

  • input_string: The Base64-encoded string.

                        SELECT BASE64_DECODE('QmFzZTY0RW5jb2RlZA==');
                    -- Result: (binary output)
                    

CHAR(integer_expression)

Converts the integer ASCII code to the corresponding character.

  • integer_expression: The integer from 0 through 255.

                      SELECT CHAR(48);
                      -- Result: '0'
                    

CHARINDEX(expressionToFind ,expressionToSearch [,start_location ])

Returns the starting position of the specified expression in the character string.

  • expressionToFind: The character expression to find.
  • expressionToSearch: The character expression, typically a column, to search.
  • start_location: An optional character position to start searching for expressionToFind in expressionToSearch.

                      SELECT CHARINDEX('456', '0123456');
                      -- Result: 4

                      SELECT CHARINDEX('456', '0123456', 5);
                      -- Result: -1
                    

CHAR_LENGTH(character_expression),

Returns the number of UTF-8 characters present in the expression.

  • character_expression: The set of characters to be evaluated for length.

				 SELECT CHAR_LENGTH('sample text') FROM Account LIMIT 1
				 -- Result: 11			
				

CONCAT(string_value1, string_value2, ..., string_valueN)

Returns the string that is the concatenation of two or more string values.

  • string_value1: The first string to be concatenated.
  • string_value2: The second string to be concatenated.
  • string_valueN: (optional) Any additional strings to be concatenated.

                      SELECT CONCAT('Hello, ', 'world!');
                      -- Result: 'Hello, world!'
                    

CONTAINS(expressionToSearch, expressionToFind)

Returns 1 if expressionToFind is found within expressionToSearch; otherwise, 0.

  • expressionToSearch: The character expression, typically a column, to search.
  • expressionToFind: The character expression to find.

                      SELECT CONTAINS('0123456', '456');
                      -- Result: 1

                      SELECT CONTAINS('0123456', 'Not a number');
                      -- Result: 0
                    

ENDSWITH(character_expression, character_suffix)

Returns 1 if character_expression ends with character_suffix; otherwise, 0.

  • character_expression: The character expression.
  • character_suffix: The character suffix to search for.

                      SELECT ENDSWITH('0123456', '456');
                      -- Result: 1

                      SELECT ENDSWITH('0123456', '012');
                      -- Result: 0
                    

FILESIZE(uri)

Returns the number of bytes present in the file at the specified file path.

  • uri: The path of the file from which to read the size.

				SELECT FILESIZE('C:/Users/User1/Desktop/myfile.txt');
				-- Result: 23684
				

FORMAT(value [, parseFormat], format )

Returns the value formatted with the specified format.

  • value: The string to format.
  • format: The string specifying the output syntax of the date or numeric format.
  • parseFormat: The string specifying the input syntax of the date value. Not applicable to numeric types.

                      SELECT FORMAT(12.34, '#');
                      -- Result: 12

                      SELECT FORMAT(12.34, '#.###');
                      -- Result: 12.34

                      SELECT FORMAT(1234, '0.000E0');
                      -- Result: 1.234E3
                      
                      SELECT FORMAT('2019/01/01', 'yyyy-MM-dd');
                      -- Result: 2019-01-01
                      
                      SELECT FORMAT('20190101', 'yyyyMMdd', 'yyyy-MM-dd');
                      -- Result: '2019-01-01'
                    

HASHBYTES(algorithm, value)

Returns the hash of the input value as a byte array using the given algorithm. The supported algorithms are MD5, SHA1, SHA2_256, SHA2_512, SHA3_224, SHA3_256, SHA3_384, and SHA3_512.

  • algorithm: The algorithm to use for hashing. Must be one of MD5, SHA1, SHA2_256, SHA2_512, SHA3_224, SHA3_256, SHA3_384, or SHA3_512.
  • value: The value to hash. Must be either a string or byte array.

                      SELECT HASHBYTES('MD5', 'Test');
                      -- Result (byte array): 0x0CBC6611F5540BD0809A388DC95A615B
                    

INDEXOF(expressionToSearch, expressionToFind [,start_location ])

Returns the starting position of the specified expression in the character string.

  • expressionToSearch: The character expression, typically a column, to search.
  • expressionToFind: The character expression to find.
  • start_location: An optional character position to start searching for expressionToFind in expressionToSearch.

                      SELECT INDEXOF('0123456', '456');
                      -- Result: 4

                      SELECT INDEXOF('0123456', '456', 5);
                      -- Result: -1
                    

ISALPHABETIC(character_expression)

Returns 1 if the character expression consists only of alphabetic characters; otherwise, 0.

  • character_expression: The string expression to evaluate.

                      SELECT ISALPHABETIC('Hello');
                      -- Result: 1

                      SELECT ISALPHABETIC('Hello123');
                      -- Result: 0

                      SELECT ISALPHABETIC('Hello!');
                      -- Result: 0
                    

ISALPHANUMERIC(character_expression)

Returns 1 if the character expression consists only of alphabetic and numeric characters; otherwise, 0.

  • character_expression: The string expression to evaluate.

                      SELECT ISALPHANUMERIC('Hello123');
                      -- Result: 1

                      SELECT ISALPHANUMERIC('123');
                      -- Result: 1

                      SELECT ISALPHANUMERIC('Hello.123');
                      -- Result: 0
                    

ISNUMERIC(character_expression)

Returns 1 if the character expression consists only of numeric digits and up to one decimal point; otherwise, 0.

  • character_expression: The string expression to evaluate.

                      SELECT ISNUMERIC('123');
                      -- Result: 1

                      SELECT ISNUMERIC('123.45');
                      -- Result: 1

                      SELECT ISNUMERIC('123.45.67');
                      -- Result: 0

                      SELECT ISNUMERIC('12a3');
                      -- Result: 0
                    

JSON_EXTRACT(json, jsonpath)

Selects any value in a JSON array or object. The path to the array is specified in the jsonpath argument. Return value is numeric or null.

  • json: The JSON document to extract.
  • jsonpath: The XPath used to select the nodes. The JSONPath must be a string constant. The values of the nodes selected will be returned in a token-separated list.

                      SELECT JSON_EXTRACT('{"test": {"data": 1}}', '$.test');
                      -- Result: '{"data":1}'

                      SELECT JSON_EXTRACT('{"test": {"data": 1}}', '$.test.data');
                      -- Result: 1

                      SELECT JSON_EXTRACT('{"test": {"data": [1, 2, 3]}}', '$.test.data[1]');
                      -- Result: 2
                    

LEFT ( character_expression , integer_expression )

Returns the specified number of characters counting from the left of the specified string.

  • character_expression: The character expression.
  • integer_expression: The positive integer that specifies how many characters will be returned counting from the left of character_expression.

                      SELECT LEFT('1234567890', 3);
                      -- Result: '123'
                    

LEN(string_expression)

Returns the number of characters of the specified string expression.

  • string_expression: The string expression.

                      SELECT LEN('12345');
                      -- Result: 5
                    

LOCATE(substring,string)

Returns an integer representing how many characters into the string the substring appears.

  • substring: The substring to find inside larger string.
  • string: The larger string that is searched for the substring.
  • start locations: An optional integer that sets the character position (offset) from which to start searching.

				SELECT LOCATE('sample','XXXXXsampleXXXXX');
				-- Result: 6

                SELECT LOCATE('sample', 'XXXXXsampleXXXXX', 7)
                -- Result: 0
				

LOWER ( character_expression )

Returns the character expression with the uppercase character data converted to lowercase.

  • character_expression: The character expression.

                      SELECT LOWER('MIXED case');
                      -- Result: 'mixed case'
                    

LTRIM(character_expression)

Returns the character expression with leading blanks removed.

  • character_expression: The character expression.

                      SELECT LTRIM('     trimmed');
                      -- Result: 'trimmed'
                    

MASK(string_expression, mask_character [, start_index [, end_index ]])

Replaces the characters between start_index and end_index with the mask_character within the string.

  • string_expression: The string expression to be searched.
  • mask_character: The character to mask with.
  • start_index: The optional number of characters to leave unmasked at beginning of string. Defaults to 0.
  • end_index: The optional number of characters to leave unmasked at end of string. Defaults to 0.

                        SELECT MASK('1234567890','*',);
                        -- Result: '**********'
                        SELECT MASK('1234567890','*', 4);
                        -- Result: '1234******'
                        SELECT MASK('1234567890','*', 4, 2);
                        -- Result: '1234****90'  
                    

NCHAR(integer_expression)

Returns the Unicode character with the specified integer code as defined by the Unicode standard.

  • integer_expression: The integer from 0 through 65535 (0 through xFFFF).

OCTET_LENGTH(character_expression),

Returns the number of bytes present in the expression.

  • character_expression: The set of characters to be be evaluated.

				 SELECT OCTET_LENGTH('text') FROM Account LIMIT 1
				 -- Result: 4
				

PATINDEX(pattern, expression)

Returns the starting position of the first occurrence of the pattern in the expression. Returns 0 if the pattern is not found.

  • pattern: The character expression that contains the sequence to be found. The wild-card character % can be used only at the start or end of the expression.
  • expression: The expression, typically a column, to search for the pattern.

                      SELECT PATINDEX('123%', '1234567890');
                      -- Result: 1

                      SELECT PATINDEX('%890', '1234567890');
                      -- Result: 8

                      SELECT PATINDEX('%456%', '1234567890');
                      -- Result: 4
                    

POSITION(expressionToFind IN expressionToSearch)

Returns the starting position of the specified expression in the character string.

  • expressionToFind: The character expression to find.
  • expressionToSearch: The character expression, typically a column, to search.

                      SELECT POSITION('456' IN '123456');
                      -- Result: 4

                      SELECT POSITION('x' IN '123456');
                      -- Result: 0
                    

QUOTENAME(character_string [, quote_character])

Returns a valid SQL Server-delimited identifier by adding the necessary delimiters to the specified Unicode string.

  • character_string: The string of Unicode character data. The string is limited to 128 characters. Inputs greater than 128 characters return null.
  • quote_character: An optional single character to be used as the delimiter. These include:
    • a single quotation mark (')
    • a left or right bracket ([])
    • a double quotation mark (")
    • a left or right parenthesis ( () )
    • a greater or less than sign (><)
    • a left or right brace ({})
    • a backtick (`)

    If quote_character is not specified brackets are used. If an unacceptable character is supplied, it returns NULL.


                      SELECT QUOTENAME('table_name');
                      -- Result: '[table_name]'

                      SELECT QUOTENAME('table_name', '"');
                      -- Result: '"table_name"'

                      SELECT QUOTENAME('table_name', '[');
                      -- Result: '[table_name]'
                    

REGEXP_REPLACE(expr, pattern [, replacement [, position [, occurrence [, match_type]]]])

Replaces occurrences of a regular expression pattern in the input string with a specified value and returns the resulting string.

  • expr: The string expression to be searched.
  • pattern: The regular expression pattern to match.
  • replacement: (optional) The string to replace each matched occurrence of pattern with. Supports backreferences \1 through \9 and escape sequences \n, \r, \t, and \\. By default, this argument is an empty string, meaning matched portions are removed from the output string.
  • position: (optional) The 1-based starting position used when searching for regular expression matches in expr. The default is 1. All characters prior to the starting position are included in the output string unaltered. Skipped characters are ignored when calculating regular expression matches, even if they match pattern.
  • occurrence: (optional) Specifies whether all occurrences of pattern,, or only a specific occurrence of pattern are replaced. The default is 0, which means all occurrences of pattern are replaced with replacement. Set to 1 to only replace the first instance of the pattern; 2 to replace the second; etc.
  • match_type: (optional) Modifiers used to customize matching behavior. Supported values are: 'c' (case-sensitive, default), 'i' (case-insensitive), 'm' (multiline), 'n' (dot matches newline), 'x' (extended mode). These can be freely combined by including the letters back to back. For example, 'im' applies the functionality of both 'i' and 'm'. The regular expression syntax used is that of the Extended mode ('x') ignores whitespace and allows inline comments. If the pattern needs to match a literal space, it must be explicitly escaped.

                      SELECT REGEXP_REPLACE('abc123def456', '\d+', 'NUM');
                      -- Result: 'abcNUMdefNUM'

                      SELECT REGEXP_REPLACE('Hello\nHELLO\nhello', '^hello', 'X', 1, 0, 'im');
                      -- Result: 'X\nX\nX'
                    

REPLACE(string_expression, string_pattern, string_replacement)

Replaces all occurrences of a string with another string.

  • string_expression: The string expression to be searched. This can be a character or binary data type.
  • string_pattern: The substring to be found. Cannot be an empty string.
  • string_replacement: The replacement string.

                      SELECT REPLACE('1234567890', '456', '|');
                      -- Result: '123|7890'

                      SELECT REPLACE('123123123', '123', '.');
                      -- Result: '...'

                      SELECT REPLACE('1234567890', 'a', 'b');
                      -- Result: '1234567890'
                    

REPLICATE ( string_expression ,integer_expression )

Repeats the string value the specified number of times.

  • string_expression: The string to replicate.
  • integer_expression: The repeat count.

                      SELECT REPLACE('x', 5);
                      -- Result: 'xxxxx'
                    

REVERSE ( string_expression )

Returns the reverse order of the string expression.

  • string_expression: The string.

                      SELECT REVERSE('1234567890');
                      -- Result: '0987654321'
                    

RIGHT ( character_expression , integer_expression )

Returns the right part of the string with the specified number of characters.

  • character_expression: The character expression.
  • integer_expression: The positive integer that specifies how many characters of the character expression will be returned.

                      SELECT RIGHT('1234567890', 3);
                      -- Result: '890'
                    

RTRIM(character_expression)

Returns the character expression after it removes trailing blanks.

  • character_expression: The character expression.

                      SELECT RTRIM('trimmed     ');
                      -- Result: 'trimmed'
                    

SOUNDEX(character_expression)

Returns the four-character Soundex code, based on how the string sounds when spoken.

  • character_expression: The alphanumeric expression of character data.

                      SELECT SOUNDEX('smith');
                      -- Result: 'S530'
                    

SPACE(repeatcount)

Returns the string that consists of repeated spaces.

  • repeatcount: The number of spaces.

                      SELECT SPACE(5);
                      -- Result: '     '
                    

SPLIT(string, delimiter, offset)

Returns a section of the string between to delimiters.

  • string: The string to split.
  • delimiter: The character to split the string with.
  • offset: The number of the split to return. Positive numbers are treated as offsets from the left, and negative numbers are treated as offsets from the right.

                      SELECT SPLIT('a/b/c/d', '/', 1);
                      -- Result: 'a'
                      SELECT SPLIT('a/b/c/d', '/', -2);
                      -- Result: 'c'
                    

STARTSWITH(character_expression, character_prefix)

Returns 1 if character_expression starts with character_prefix; otherwise, 0.

  • character_expression: The character expression.
  • character_prefix: The character prefix to search for.

                      SELECT STARTSWITH('0123456', '012');
                      -- Result: 1

                      SELECT STARTSWITH('0123456', '456');
                      -- Result: 0
                    

STR ( float_expression [ , integer_length [ , integer_decimal ] ] )

Returns the character data converted from the numeric data. For example, STR(123.45, 6, 1) returns 123.5.

  • float_expression: The float expression.
  • length: The optional total length to return. This includes decimal point, sign, digits, and spaces. The default is 10.
  • decimal: The optional number of places to the right of the decimal point. The decimal must be less than or equal to 16.

                      SELECT STR('123.456');
                      -- Result: '123'

                      SELECT STR('123.456', 2);
                      -- Result: '**'

                      SELECT STR('123.456', 10, 2);
                      -- Result: '123.46'
                    

STUFF(character_expression , integer_start , integer_length , replaceWith_expression)

Inserts a string into another string. It deletes the specified length of characters in the first string at the start position and then inserts the second string into the first string at the start position.

  • character_expression: The string expression.
  • start: The integer value that specifies the location to start deletion and insertion. If start or length is negative, null is returned. If start is longer than the string to be modified, character_expression, null is returned.
  • length: The integer that specifies the number of characters to delete. If length is longer than character_expression, deletion occurs up to the last character in replaceWith_expression.
  • replaceWith_expression: The expression of character data that will replace length characters of character_expression beginning at the start value.

                      SELECT STUFF('1234567890', 3, 2, 'xx');
                      -- Result: '12xx567890'
                    

SUBSTRING(string_value FROM start FOR length)

Returns the part of the string with the specified length; starts at the specified index.

  • string_value: The character string.
  • start: The positive integer that specifies the start index of characters to return.
  • length: Optional. The positive integer that specifies how many characters will be returned.

                      SELECT SUBSTRING('1234567890' FROM 3 FOR 2);
                      -- Result: '34'

                      SELECT SUBSTRING('1234567890' FROM 3);
                      -- Result: '34567890'
                    
You can also drop the FROM and FOR clauses:
                    SELECT SUBSTRING('1234567890', 3, 2)
                    --Result: '34'
                    SELECT SUBSTRING('1234567890', 3)
                    --Result: '34567890'
                    

TEXT_ENCODE(input_string, charset)

Returns binary output by encoding a string using the specified character set.

  • input_string: The plain text string.
  • charset: The character set to use, such as 'UTF-8', 'ISO-8859-1'.

                    SELECT TEXT_ENCODE('Café', 'UTF-8');
                    -- Result: (binary output)
                    

TEXT_DECODE(input_binary, charset)

Returns a string decoded from binary data using the specified character set.

  • input_binary: The binary value to decode.
  • charset: The character set used for decoding.

                    SELECT TEXT_DECODE(BinaryData, 'UTF-8');
                    -- Result: 'Café'
                    

TOSTRING(string_value1)

Converts the value of this instance to its equivalent string representation.

  • string_value1: The string to be converted.

                      SELECT TOSTRING(123);
                      -- Result: '123'

                      SELECT TOSTRING(123.456);
                      -- Result: '123.456'

                      SELECT TOSTRING(null);
                      -- Result: ''
                    

TRIM(trimspec trimchar FROM string_value)

Returns the character expression with leading and/or trailing blanks removed.

  • trimspec: Optional. If included must be one of the keywords BOTH, LEADING or TRAILING.
  • trimchar: Optional. If included should be a one-character string value.
  • string_value: The string value to trim.

                      SELECT TRIM('     trimmed     ');
                      -- Result: 'trimmed'

                      SELECT TRIM(LEADING FROM '     trimmed     ');
                      -- Result: 'trimmed     '

                      SELECT TRIM('-' FROM '-----trimmed-----');
                      -- Result: 'trimmed'

                      SELECT TRIM(BOTH '-' FROM '-----trimmed-----');
                      -- Result: 'trimmed'

                      SELECT TRIM(TRAILING '-' FROM '-----trimmed-----');
                      -- Result: '-----trimmed'
                    

UNICODE(ncharacter_expression)

Returns the integer value defined by the Unicode standard of the first character of the input expression.

  • ncharacter_expression: The Unicode character expression.

UPPER ( character_expression )

Returns the character expression with lowercase character data converted to uppercase.

  • character_expression: The character expression.

                      SELECT UPPER('MIXED case');
                      -- Result: 'MIXED CASE'
                    

XML_EXTRACT(xml, xpath [, separator])

Extracts an XML document using the specified XPath to flatten the XML. A comma is used to separate the outputs by default, but this can be changed by specifying the third parameter.

  • xml: The XML document to extract.
  • xpath: The XPath used to select the nodes. The nodes selected will be returned in a token-separated list.
  • separator: The optional token used to separate the items in the flattened response. If this is not specified, the separator will be a comma.

                      SELECT XML_EXTRACT('<vowels><ch>a</ch><ch>e</ch><ch>i</ch><ch>o</ch><ch>u</ch></vowels>', '/vowels/ch');
                      -- Result: 'a,e,i,o,u'

                      SELECT XML_EXTRACT('<vowels><ch>a</ch><ch>e</ch><ch>i</ch><ch>o</ch><ch>u</ch></vowels>', '/vowels/ch', ';');
                      -- Result: 'a;e;i;o;u'
                    

CData Python Connector for Avalara

MATH Functions

ABS ( numeric_expression )

Returns the absolute (positive) value of the specified numeric expression.

  • numeric_expression: The expression of an indeterminate numeric data type except for the bit data type.

                      SELECT ABS(15);
                      -- Result: 15

                      SELECT ABS(-15);
                      -- Result: 15
                    

ACOS ( float_expression )

Returns the arc cosine, the angle in radians whose cosine is the specified float expression.

  • float_expression: The float expression that specifies the cosine of the angle to be returned. Values outside the range from -1 to 1 return null.

                      SELECT ACOS(0.5);
                      -- Result: 1.0471975511966
                    

ASIN ( float_expression )

Returns the arc sine, the angle in radians whose sine is the specified float expression.

  • float_expression: The float expression that specifies the sine of the angle to be returned. Values outside the range from -1 to 1 return null.

                      SELECT ASIN(0.5);
                      -- Result: 0.523598775598299
                    

ATAN ( float_expression )

Returns the arc tangent, the angle in radians whose tangent is the specified float expression.

  • float_expression: The float expression that specifies the tangent of the angle to be returned.

                      SELECT ATAN(10);
                      -- Result: 1.47112767430373
                    

ATN2 ( float_expression1 , float_expression2 )

Returns the angle in radians between the positive x-axis and the ray from the origin to the point (y, x) where x and y are the values of the two specified float expressions.

  • float_expression1: The float expression that is the y-coordinate.
  • float_expression2: The float expression that is the x-coordinate.

                      SELECT ATN2(1, 1);
                      -- Result: 0.785398163397448
                    

CEILING ( numeric_expression ) or CEIL( numeric_expression )

Returns the smallest integer greater than or equal to the specified numeric expression.

  • numeric_expression: The expression of an indeterminate numeric data type except for the bit data type.

                      SELECT CEILING(1.3);
                      -- Result: 2

                      SELECT CEILING(1.5);
                      -- Result: 2

                      SELECT CEILING(1.7);
                      -- Result: 2
                    

COS ( float_expression )

Returns the trigonometric cosine of the specified angle in radians in the specified expression.

  • float_expression: The float expression of the specified angle in radians.

                      SELECT COS(1);
                      -- Result: 0.54030230586814
                    

COT ( float_expression )

Returns the trigonometric cotangent of the angle in radians specified by float_expression.

  • float_expression: The float expression of the angle in radians.

                      SELECT COT(1);
                      -- Result: 0.642092615934331
                    

DEGREES ( numeric_expression )

Returns the angle in degrees for the angle specified in radians.

  • numeric_expression: The angle in radians, an expression of an indeterminate numeric data type except for the bit data type.

                      SELECT DEGREES(3.1415926);
                      -- Result: 179.999996929531
                    

EXP ( float_expression )

Returns the exponential value of the specified float expression. For example, EXP(LOG(20)) is 20.

  • float_expression: The float expression.

                      SELECT EXP(2);
                      -- Result: 7.38905609893065
                    

EXPR ( expression )

Evaluates the expression.

  • expression: The expression. Operators allowed are +, -, *, /, ==, !=, >, <, >=, and <=.

                      SELECT EXPR('1 + 2 * 3');
                      -- Result: 7

                      SELECT EXPR('1 + 2 * 3 == 7');
                      -- Result: true
                    

FLOOR ( numeric_expression )

Returns the largest integer less than or equal to the numeric expression.

  • numeric_expression: The expression of an indeterminate numeric data type except for the bit data type.

                      SELECT FLOOR(1.3);
                      -- Result: 1

                      SELECT FLOOR(1.5);
                      -- Result: 1

                      SELECT FLOOR(1.7);
                      -- Result: 1
                    

GREATEST(int1,int2,....)

Returns the greatest of the supplied integers.

				SELECT GREATEST(3,5,8,10,1)
				-- Result: 10			
				

HEX(value)

Returns a the equivalent hex for the input value.

  • value: A string or numerical value to be converted into hex.

				SELECT HEX(866849198);
				-- Result: 33AB11AE
				
				SELECT HEX('Sample Text');
				-- Result: 53616D706C652054657874
				

JSON_AVG(json, jsonpath)

Computes the average value of a JSON array within a JSON object. The path to the array is specified in the jsonpath argument. Return value is numeric or null.

  • json: The JSON document to compute.
  • jsonpath: The JSONPath used to select the nodes. [x], [2..], [..8], or [1..12] are accepted. [x] selects all nodes.

                      SELECT JSON_AVG('[1,2,3,4,5]', '$[x]');
                      -- Result: 3

                      SELECT JSON_AVG('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[x]');
                      -- Result: 3

                      SELECT JSON_AVG('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[3..]');
                      -- Result: 4.5
                    

JSON_COUNT(json, jsonpath)

Returns the number of elements in a JSON array within a JSON object. The path to the array is specified in the jsonpath argument. Return value is numeric or null.

  • json: The JSON document to compute.
  • jsonpath: The JSONPath used to select the nodes. [x], [2..], [..8], or [1..12] are accepted. [x] selects all nodes.

                      SELECT JSON_COUNT('[1,2,3,4,5]', '$[x]');
                      -- Result: 5

                      SELECT JSON_COUNT('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[x]');
                      -- Result: 5

                      SELECT JSON_COUNT('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[3..]');
                      -- Result: 2
                    

JSON_MAX(json, jsonpath)

Gets the maximum value in a JSON array within a JSON object. The path to the array is specified in the jsonpath argument. Return value is numeric or null.

  • json: The JSON document to compute.
  • jsonpath: The JSONPath used to select the nodes. [x], [2..], [..8], or [1..12] are accepted. [x] selects all nodes.

                      SELECT JSON_MAX('[1,2,3,4,5]', '$[x]');
                      -- Result: 5

                      SELECT JSON_MAX('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[x]');
                      -- Result: 5

                      SELECT JSON_MAX('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[..3]');
                      -- Result: 4
                    

JSON_MIN(json, jsonpath)

Gets the minimum value in a JSON array within a JSON object. The path to the array is specified in the jsonpath argument. Return value is numeric or null.

  • json: The JSON document to compute.
  • jsonpath: The JSONPath used to select the nodes. [x], [2..], [..8], or [1..12] are accepted. [x] selects all nodes.

                      SELECT JSON_MIN('[1,2,3,4,5]', '$[x]');
                      -- Result: 1

                      SELECT JSON_MIN('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[x]');
                      -- Result: 1

                      SELECT JSON_MIN('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[3..]');
                      -- Result: 4
                    

JSON_SUM(json, jsonpath)

Computes the summary value in JSON according to the JSONPath expression. Return value is numeric or null.

  • json: The JSON document to compute.
  • jsonpath: The JSONPath used to select the nodes. [x], [2..], [..8], or [1..12] are accepted. [x] selects all nodes.

                      SELECT JSON_SUM('[1,2,3,4,5]', '$[x]');
                      -- Result: 15

                      SELECT JSON_SUM('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[x]');
                      -- Result: 15

                      SELECT JSON_SUM('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[3..]');
                      -- Result: 9
                    

LEAST(int1,int2,....)

Returns the least of the supplied integers.

				SELECT LEAST(3,5,8,10,1)
				-- Result: 1			
				

LOG ( float_expression [, base ] )

Returns the natural logarithm of the specified float expression.

  • float_expression: The float expression.
  • base: The optional integer argument that sets the base for the logarithm.

                      SELECT LOG(7.3890560);
                      -- Result: 1.99999998661119
                    

LOG10 ( float_expression )

Returns the base-10 logarithm of the specified float expression.

  • float_expression: The expression of type float.

                      SELECT LOG10(10000);
                      -- Result: 4
                    

MOD(dividend,divisor)

Returns the integer value associated with the remainder when dividing the dividend by the divisor.

  • dividend: The number to take the modulus of.
  • divisor: The number to divide the dividend by when determining the modulus.

				SELECT MOD(10,3);
				-- Result: 1
				

NEGATE(real_number)

Returns the opposite to the real number input.

  • real_number: The real number to find the opposite of.

				SELECT NEGATE(10);
				-- Result: -10
				
				SELECT NEGATE(-12.4)
				--Result: 12.4
				

PI ( )

Returns the constant value of pi.

                  SELECT PI()
                  -- Result: 3.14159265358979 
                

POWER ( float_expression , y )

Returns the value of the specified expression raised to the specified power.

  • float_expression: The float expression.
  • y: The power to raise float_expression to.

                      SELECT POWER(2, 10);
                      -- Result: 1024

                      SELECT POWER(2, -2);
                      -- Result: 0.25
                    

RADIANS ( float_expression )

Returns the angle in radians of the angle in degrees.

  • float_expression: The degrees of the angle as a float expression.

                      SELECT RADIANS(180);
                      -- Result: 3.14159265358979
                    

RAND ( [ integer_seed ] )

Returns a pseudorandom float value from 0 through 1, exclusive.

  • seed: The optional integer expression that specifies the seed value. If seed is not specified, a seed value at random will be assigned.

                      SELECT RAND();
                      -- This result may be different, since the seed is randomized
                      -- Result: 0.873159630165044

                      SELECT RAND(1);
                      -- This result will always be the same, since the seed is constant
                      -- Result: 0.248668584157093
                    

ROUND ( numeric_expression [ ,integer_length] [ ,function ] )

Returns the numeric value rounded to the specified length or precision.

  • numeric_expression: The expression of a numeric data type.
  • length: The optional precision to round the numeric expression to. When this is omitted, the default behavior will be to round to the nearest whole number.
  • function: The optional type of operation to perform. When the function parameter is omitted or has a value of 0 (default), numeric_expression is rounded. When a value other than 0 is specified, numeric_expression is truncated.

                      SELECT ROUND(1.3, 0);
                      -- Result: 1

                      SELECT ROUND(1.55, 1);
                      -- Result: 1.6

                      SELECT ROUND(1.7, 0, 0);
                      -- Result: 2

                      SELECT ROUND(1.7, 0, 1);
                      -- Result: 1
                      
                      SELECT ROUND (1.24);
                      -- Result: 1.0
                    

SIGN ( numeric_expression )

Returns the positive sign (1), 0, or negative sign (-1) of the specified expression.

  • numeric_expression: The expression of an indeterminate data type except for the bit data type.

                      SELECT SIGN(0);
                      -- Result: 0

                      SELECT SIGN(10);
                      -- Result: 1

                      SELECT SIGN(-10);
                      -- Result: -1
                    

SIN ( float_expression )

Returns the trigonometric sine of the angle in radians.

  • float_expression: The float expression specifying the angle in radians.

                     SELECT SIN(1);
                     -- Result: 0.841470984807897
                    

SQRT ( float_expression )

Returns the square root of the specified float value.

  • float_expression: The expression of type float.

                      SELECT SQRT(100);
                      -- Result: 10
                    

SQUARE ( float_expression )

Returns the square of the specified float value.

  • float_expression: The expression of type float.

                      SELECT SQUARE(10);
                      -- Result: 100

                      SELECT SQUARE(-10);
                      -- Result: 100
                    

TAN ( float_expression )

Returns the tangent of the input expression.

  • float_expression: The expression of type float.

                      SELECT TAN(1);
                      -- Result: 1.5574077246549
                    

TRUNC(decimal_number,precision)

Returns the supplied decimal number truncated to have the supplied decimal precision.

  • decimal_number: The decimal value to truncate.
  • precision: The number of decimal places to truncate the decimal number to.

				SELECT TRUNC(10.3423,2);
				-- Result: 10.34
				

_ROW_NUMBER_()

Returns a row index as an additional column.

				SELECT ColumnName, _ROW_NUMBER_() FROM TableName
				-- Result: ColumnData, 0
				ColumnData2, 1
				ColumnData3, 2
				

CData Python Connector for Avalara

DATE Functions

CURRENT_DATE()

Returns the current date value.

                  SELECT CURRENT_DATE();
                  -- Result: 2018-02-01
                

CURRENT_TIMESTAMP()

Returns the current time stamp of the database system as a datetime value. This value is equal to GETDATE and SYSDATETIME, and is always in the local timezone.

                  SELECT CURRENT_TIMESTAMP();
                  -- Result: 2018-02-01 03:04:05
                

DATEADD (datepart , integer_number , date [, dateformat])

Returns the datetime value that results from adding the specified number (a signed integer) to the specified date part of the date.

  • datepart: The part of the date to add the specified number to. The valid values and abbreviations are
    • year (yy, yyyy)
    • quarter (qq, q)
    • month (mm, m)
    • week (wk, ww)
    • weekday (dw)
    • dayofyear (dy, y)
    • day (dd, d)
    • hour (hh)
    • minute (mi, n)
    • second (ss, s)
    • millisecond (ms)
  • number: The number to be added.
  • date: The expression of the datetime data type.
  • dateformat: The optional output date format.

                  SELECT DATEADD('d', 5, '2018-02-01');
                  -- Result: 2018-02-06

                  SELECT DATEADD('hh', 5, '2018-02-01 00:00:00');
                  -- Result: 2018-02-01 05:00:00
                

DATEDIFF ( datepart , startdate , enddate )

Returns the difference (a signed integer) of the specified time interval between the specified start date and end date.

  • datepart: The part of the date that is the time interval of the difference between the start date and end date. The valid values and abbreviations are:
    • Year (year, yyyy, yy)
    • Quarter (quarter, qq, q)
    • Month (month, mm, m)
    • Week (week, wk, ww)
    • Weekday (weekday, dw)
    • Dayofyear (dayofyear, dy, y)
    • Day (day, dd, d)
    • Hour (hour, hh)
    • Minute (minute, mi, n)
    • Second (second, ss, s)
    • Millisecond (millisecond, ms)
  • startdate: The datetime expression of the start date.
  • enddate: The datetime expression of the end date.

                  SELECT DATEDIFF('d', '2018-02-01', '2018-02-10');
                  -- Result: 9

                  SELECT DATEDIFF('hh', '2018-02-01 00:00:00', '2018-02-01 12:00:00');
                  -- Result: 12
                

DATE_FORMAT(date,format)

Returns the date or timestamp in the format specified. This function mirrors the MySQL DATE_FORMAT function.

  • date: A date or timestamp string.
  • format: The specifier string of the desired output format. The list of supported format specifiers comes from the MySQL DATE_FORMAT function (see link to MySQL documentation above).

					SELECT DATE_FORMAT('9/4/2021 3:11:53 AM','%h')
					-- Result: 03
				  

DATEFROMPARTS(integer_year, integer_month, integer_day)

Returns the datetime value for the specified year, month, and day.

  • year: The integer expression specifying the year.
  • month: The integer expression specifying the month.
  • day: The integer expression specifying the day.

                    SELECT DATEFROMPARTS(2018, 2, 1);
                    -- Result: 2018-02-01
                  

DATENAME(datepart , date)

Returns the character string that represents the specified date part of the specified date.

  • datepart: The part of the date to return. The valid values and abbreviations are year (yy, yyyy), quarter (qq, q), month (mm, m), dayofyear (dy, y), day (dd, d), week (wk, ww), weekday (dw), hour (hh), minute (mi, n), second (ss, s), millisecond (ms), microsecond (mcs), and nanosecond (ns).
  • date: The datetime expression.

                     SELECT DATENAME('yy', '2018-02-01');
                     -- Result: '2018'

                     SELECT DATENAME('dw', '2018-02-01');
                     -- Result: 'Thursday'
                   

DATEPART(datepart, date [,integer_datefirst])

Returns a character string that represents the specified date part of the specified date.

  • datepart: The part of the date to return. The valid values and abbreviations are year (yy, yyyy), quarter (qq, q), month (mm, m), dayofyear (dy, y), day (dd, d), week (wk, ww), weekday (dw), hour (hh), minute (mi, n), second (ss, s), millisecond (ms), microsecond (mcs), nanosecond (ns), ISODOW, ISO_WEEK (isoweek, isowk,isoww), and ISOYEAR.
  • date: The datetime string.
  • datefirst: The optional integer representing the first day of the week. The default is 7, Sunday.

                    SELECT DATEPART('yy', '2018-02-01');
                    -- Result: 2018

                    SELECT DATEPART('dw', '2018-02-01');
                    -- Result: 5
                  

DATETIMEFROMPARTS(integer_year, integer_month, integer_day, integer_hour, integer_minute, integer_seconds, integer_milliseconds)

Returns the datetime value for the specified date parts.

  • year: The integer expression specifying the year.
  • month: The integer expression specifying the month.
  • day: The integer expression specifying the day.
  • hour: The integer expression specifying the hour.
  • minute: The integer expression specifying the minute.
  • seconds: The integer expression specifying the seconds.
  • milliseconds: The integer expression specifying the milliseconds.

                    SELECT DATETIMEFROMPARTS(2018, 2, 1, 1, 2, 3, 456);
                    -- Result: 2018-02-01 01:02:03.456
                  

DATETIME2FROMPARTS(integer_year, integer_month, integer_day, integer_hour, integer_minute, integer_seconds, integer_fractions, integer_precision)

Returns the datetime value for the specified date parts.

  • year: The integer expression specifying the year.
  • month: The integer expression specifying the month.
  • day: The integer expression specifying the day.
  • hour: The integer expression specifying the hour.
  • minute: The integer expression specifying the minute.
  • seconds: The integer expression specifying the seconds.
  • fractions: The integer expression specifying the fractions of the second.
  • precision: The integer expression specifying the precision of the fraction.

				    SELECT DATETIME2FROMPARTS(2018, 2, 1, 1, 2, 3, 456, 3);
                    -- Result: 2018-02-01 01:02:03.456
                  

DATE_TRUNC(date, datepart)

Truncates the date to the precision of the given date part. Modeled after the Oracle TRUNC function.

  • date: The datetime string that specifies the date.
  • datepart: Refer to the Oracle documentation for valid datepart syntax.

				    SELECT DATE_TRUNC('05-04-2005', 'YY');
                    -- Result: '1/1/2005'
					
                    SELECT DATE_TRUNC('05-04-2005', 'MM');
                    -- Result: '5/1/2005'                    
                  

DATE_TRUNC2(datepart, date, [weekday])

Truncates the date to the precision of the given date part. Modeled after the PostgreSQL date_trunc function.

  • datepart: One of 'millennium', 'century', 'decade', 'year', 'quarter', 'month', 'week', 'day', 'hour', 'minute' or 'second'.
  • date: The datetime string that specifies the date.
  • weekday: The optional day of the week to use as the first day for 'week'. One of 'sunday', 'monday', etc.

                    SELECT DATE_TRUNC2('year', '2020-02-04');
                    -- Result: '2020-01-01'

                    SELECT DATE_TRUNC2('week', '2020-02-04', 'monday');
                    -- Result: '2020-02-02', which is the previous Monday
                  

DAY(date)

Returns the integer that specifies the day component of the specified date.

  • date: The datetime string that specifies the date.

                    SELECT DAY('2018-02-01');
                    -- Result: 1
                  

DAYNAME(date)

Returns the name of the day of the week of the specified date.

  • date: The datetime string that specifies the date.

                    SELECT DAYNAME('8/18/2021');
                    -- Result: Wednesday
                  

DAYOFMONTH(date)

Returns the day of the month of the given date part.
  • date: The datetime string that specifies the date.

				  SELECT DAYOFMONTH('04/15/2000');
				  -- Result: 15
				  

DAYOFWEEK(date)

Returns the day of the week of the given date part.
  • date: The datetime string that specifies the date.

				  SELECT DAYOFWEEK('04/15/2000');
				  -- Result: 7
				  

DAYOFYEAR(date)

Returns the day of the year of the given date part.
  • date: The datetime string that specifies the date.

				  SELECT DAYOFYEAR('04/15/2000');
				  -- Result: 106
				  

EOMONTH(date [, integer_month_to_add ]) or LAST_DAY(date)

Returns the last day of the month that contains the specified date with an optional offset.

  • date: The datetime expression specifying the date for which to return the last day of the month.
  • integer_month_to_add: The optional integer expression specifying the number of months to add to the date before calculating the end of the month.

                  SELECT EOMONTH('2018-02-01');
                  -- Result: 2018-02-28
                  
                  SELECT LAST_DAY('2018-02-01');
                  -- Result: 2018-02-28

                  SELECT EOMONTH('2018-02-01', 2);
                  -- Result: 2018-04-30
                

EXTRACT(date_part FROM date_column_name)

Returns the last day of the month that contains the specified date with an optional offset.

  • date_part: One of the following date components: YEAR, MONTH, DAY, HOUR, MINUTE, SECOND.
  • date_column_name: The name of a date column in a table.

                  SELECT EXTRACT(YEAR FROM DateColumn)
                  -- Result: 2021
                

FDWEEK(date)

Returns the first day of the week of the given date part.
  • date: The datetime string that specifies the date.
  • weeks to add: An optional integer expression specifying the number of months to add to the date before calculating the first day of the week.

				  SELECT FDWEEK('02-08-2018');
				  -- Result: 2/4/2018

          SELECT FDWEEK('02-08-2018', 1)
          --Result: 02/11/2018
				  

FDMONTH(date)

Returns the first day of the month of the given date part.
  • date: The datetime string that specifies the date.
  • month to add: An optional integer expression specifying the number of months to add to the date before calculating the first day of the month.

				  SELECT FDMONTH('02-08-2018');
				  -- Result: 2/1/2018

          SELECT FDMONTH('02-08-2018', 1) 
          --Result: 03/01/2018
				  

FDQUARTER(date)

Returns the first day of the quarter of the given date part.
  • date: The datetime string that specifies the date.
  • quarters to add: An optional integer expression specifying the number of months to add to the date before calculating the first day of the quarter.

				  SELECT FDQUARTER('05-08-2018');
				  -- Result: 4/1/2018

          SELECT FDQUARTER('05-08-2018',1)
          --Result: 07/01/2018
				  

FILEMODIFIEDTIME(uri)

Returns the time stamp associated with the Date Modified of the relevant file.

  • uri: An absolute path pointing to a file on the local file system.

				 SELECT FILEMODIFIEDTIME('C:/Documents/myfile.txt');
				 -- Result: 6/25/2019 10:06:58 AM
				 

FROM_DAYS(datevalue)

Returns a date derived from the number of days after 1582-10-15 (based upon the Gregorian calendar). This will be equivalent to the MYSQL FROM_DAYS function.

  • datevalue: A integer value representing the number of days since 1582-10-15.

				SELECT FROM_DAYS(736000);
				-- Result: 2/6/2015
				

FROM_UNIXTIME(time, issecond)

Returns a representation of the unix_timestamp argument as a value in YYYY-MM-DD HH:MM:SS expressed in the current time zone.

  • time: The time stamp value from epoch time. Milliseconds are accepted.
  • issecond: Indicates the time stamp value is milliseconds to epoch time.

                      SELECT FROM_UNIXTIME(1540495231, 1);
                      -- Result: 2018-10-25 19:20:31

                      SELECT FROM_UNIXTIME(1540495357385, 0);
                      -- Result: 2018-10-25 19:22:37
                    

GETDATE()

Returns the current time stamp of the database system as a datetime value. This value is equal to CURRENT_TIMESTAMP and SYSDATETIME, and is always in the local timezone.

                  SELECT GETDATE();
                  -- Result: 2018-02-01 03:04:05
                

GETUTCDATE()

Returns the current time stamp of the database system formatted as a UTC datetime value. This value is equal to SYSUTCDATETIME.

In addition, GETUTCDATE can take an optional second parameter, a date and time that are converted to UTC.

                  SELECT GETUTCDATE();
                  -- For example, if the local timezone is Eastern European Time (GMT+2)
                  -- Result: 2018-02-01 05:04:05

                  SELECT GETUTCDATE('2020/08/31 13:56:00')
                  --Result: '2020-08-31 17:56:00'
                

HOUR(date)

Returns the hour component from the provided datetime.

  • date: The datetime string that specifies the date.

				SELECT HOUR('02-02-2020 11:30:00');
				-- Result: 11
				

ISDATE(date, [date_format])

Returns 1 if the value is a valid date, time, or datetime value; otherwise, 0.

  • date: The datetime string.
  • date_format: The optional datetime format.

                      SELECT ISDATE('2018-02-01', 'yyyy-MM-dd');
                      -- Result: 1

                      SELECT ISDATE('Not a date');
                      -- Result: 0
                    

LAST_WEEK()

Returns a time stamp equivalent to exactly one week before the current date.

				SELECT LAST_WEEK();	//Assume the date is 3/17/2020	
			 -- Result: 3/10/2020 00:00:00
				

LAST_MONTH()

Returns a time stamp equivalent to exactly one month before the current date.

	
				SELECT LAST_MONTH(); //Assume the date is 3/17/2020
				-- Result: 2/17/2020 00:00:00
				

LAST_YEAR()

Returns a time stamp equivalent to exactly one year before the current date.

				SELECT LAST_YEAR();	//Assume the date is 3/17/2020	
				-- Result: 3/10/2019 00:00:00
				

LDWEEK(date)

Returns the last day of the provided week.

  • date: The datetime string.
  • weeks to add: An optional integer expression specifying the number of months to add to the date before calculating the last day of the week.

				SELECT LDWEEK('02-02-2020');
				-- Result: 2/8/2020
				

LDMONTH(date)

Returns the last day of the provided month.

  • date: The datetime string.
  • months to add: An optional integer expression specifying the number of months to add to the date before calculating the last day of the month.

				SELECT LDMONTH('02-02-2020');
				-- Result: 2/29/2020

        SELECT LDMONTH('02-08-2020', 1)
        --Result: 03/31/2020
				

LDQUARTER(date)

Returns the last day of the provided quarter.

  • date: The datetime string.
  • quarters to add: An optional integer expression specifying the number of months to add to the date before calculating the last day of the quarter.

				SELECT LDQUARTER('02-02-2020');
				-- Result: 3/31/2020

        SELECT LDQUARTER('02-02-2020',1)
        --Result: 06/30/2020
				

MAKEDATE(year, days)

Returns a date value from a year and a number of days.

  • year: The year
  • days: The number of days into the year. Value must be greater than 0.

          SELECT MAKEDATE(2020, 1);
          -- Result: 2020-01-01
        

MINUTE(date)

Returns the minute component from the provided datetime.

  • date: The datetime string that specifies the date.

				SELECT MINUTE('02-02-2020 11:15:00');
				-- Result: 15
				

MONTH(date)

Returns the month component from the provided datetime.

  • date: The datetime string that specifies the date.

				SELECT MONTH('02-02-2020');
				-- Result: 2
				

QUARTER(date)

Returns the quarter associated with the provided datetime.

  • date: The datetime string that specifies the date.

				SELECT QUARTER('02-02-2020');
				-- Result: 1
				

SECOND(date)

Returns the second component from the provided datetime.

  • date: The datetime string that specifies the date.

				SELECT SECOND('02-02-2020 11:15:23');
				-- Result: 23
				

SMALLDATETIMEFROMPARTS(integer_year, integer_month, integer_day, integer_hour, integer_minute)

Returns the datetime value for the specified date and time.

  • year: The integer expression specifying the year.
  • month: The integer expression specifying the month.
  • day: The integer expression specifying the day.
  • hour: The integer expression specifying the hour.
  • minute: The integer expression specifying the minute.

                      SELECT SMALLDATETIMEFROMPARTS(2018, 2, 1, 1, 2);
                      -- Result: 2018-02-01 01:02:00
                    

STRTODATE(string,format)

Parses the provided string value and returns the corresponding datetime.

  • string: The string value to be converted to datetime format.
  • format: A format string which describes how to interpret the first string input. A few special formats are available as well, including UNIX, UNIXMILIS, TICKS, and FILETICKS.

				SELECT STRTODATE('03*04*2020','dd*MM*yyyy');
				-- Result: 4/3/2020
				

SYSDATETIME()

Returns the current time stamp as a datetime value of the database system. It is equal to GETDATE and CURRENT_TIMESTAMP, and is always in the local timezone.

                  SELECT SYSDATETIME();
                  -- Result: 2018-02-01 03:04:05
                

SYSUTCDATETIME()

Returns the current system date and time as a UTC datetime value. It is equal to GETUTCDATE.

                  SELECT SYSUTCDATETIME();
                  -- For example, if the local timezone is Eastern European Time (GMT+2)
                  -- Result: 2018-02-01 05:04:05
                

TIMEFROMPARTS(integer_hour, integer_minute, integer_seconds, integer_fractions, integer_precision)

Returns the time value for the specified time and with the specified precision.

  • hour: The integer expression specifying the hour.
  • minute: The integer expression specifying the minute.
  • seconds: The integer expression specifying the seconds.
  • fractions: The integer expression specifying the fractions of the second.
  • precision : The integer expression specifying the precision of the fraction.

                      SELECT TIMEFROMPARTS(1, 2, 3, 456, 3);
                      -- Result: 01:02:03.456
                    

TO_DAYS(date)

Returns the number of days since 0000-00-01. This will only return a value for dates on or after 1582-10-15 (based upon the Gregorian calendar). This will be equivalent to the MYSQL TO_DAYS function.

  • date: The datetime string that specifies the date.

				SELECT TO_DAYS('02-06-2015');
				-- Result: 736000
				

WEEK(date)

Returns the week (of the year) associated with the provided datetime.

  • date: The datetime string that specifies the date.

				SELECT WEEK('02-17-2020 11:15:23');
				-- Result: 8
				

YEAR(date)

Returns the integer that specifies the year of the specified date.

  • date: The datetime string.

                      SELECT YEAR('2018-02-01');
                      -- Result: 2018
                    

CData Python Connector for Avalara

Date Literal Functions

The following date literal functions can be used to filter date fields using relative intervals. Note that while the <, >, and = operators are supported for these functions, <= and >= are not.

L_TODAY()

The current day.

  SELECT * FROM MyTable WHERE MyDateField = L_TODAY()

L_YESTERDAY()

The previous day.

  SELECT * FROM MyTable WHERE MyDateField = L_YESTERDAY()

L_TOMORROW()

The following day.

  SELECT * FROM MyTable WHERE MyDateField = L_TOMORROW()

L_LAST_WEEK()

Every day in the preceding week.

  SELECT * FROM MyTable WHERE MyDateField = L_LAST_WEEK()

L_THIS_WEEK()

Every day in the current week.

  SELECT * FROM MyTable WHERE MyDateField = L_THIS_WEEK()

L_NEXT_WEEK()

Every day in the following week.

  SELECT * FROM MyTable WHERE MyDateField = L_NEXT_WEEK()
Also available:
  • L_LAST/L_THIS/L_NEXT MONTH
  • L_LAST/L_THIS/L_NEXT QUARTER
  • L_LAST/L_THIS/L_NEXT YEAR

L_LAST_N_DAYS(n)

The previous n days, excluding the current day.

  SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_DAYS(3)

L_NEXT_N_DAYS(n)

The following n days, including the current day.

  SELECT * FROM MyTable WHERE MyDateField = L_NEXT_N_DAYS(3)
Also available:
  • L_LAST/L_NEXT_90_DAYS

L_LAST_N_WEEKS(n)

Every day in every week, starting n weeks before current week, and ending in the previous week.

  SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_WEEKS(3)

L_NEXT_N_WEEKS(n)

Every day in every week, starting the following week, and ending n weeks in the future.

  SELECT * FROM MyTable WHERE MyDateField = L_NEXT_N_WEEKS(3)
Also available:
  • L_LAST/L_NEXT_N_MONTHS(n)
  • L_LAST/L_NEXT_N_QUARTERS(n)
  • L_LAST/L_NEXT_N_YEARS(n)

CData Python Connector for Avalara

SELECT Statements

A SELECT statement can consist of the following basic clauses.

  • SELECT
  • INTO
  • FROM
  • JOIN
  • WHERE
  • GROUP BY
  • HAVING
  • UNION
  • ORDER BY
  • LIMIT

SELECT Syntax

The following syntax diagram outlines the syntax supported by the SQL engine of the connector:

SELECT {
  [ TOP <numeric_literal> | DISTINCT ]
  { 
    * 
    | { 
        <expression> [ [ AS ] <column_reference> ] 
        | { <table_name> | <correlation_name> } .* 
      } [ , ... ] 
  }
  { 
    FROM <table_reference> [ [ AS ] <identifier> ] 
  } [ , ... ]
  [ [  
      INNER | { { LEFT | RIGHT | FULL } [ OUTER ] } 
    ] JOIN <table_reference> [ ON <search_condition> ] [ [ AS ] <identifier> ] 
  ] [ ... ] 
  [ WHERE <search_condition> ]
  [ GROUP BY <column_reference> [ , ... ]
  [ HAVING <search_condition> ]
  [ UNION [ ALL ] <select_statement> ]
  [ 
    ORDER BY 
    <column_reference> [ ASC | DESC ] [ NULLS FIRST | NULLS LAST ]
  ]
  [ 
    LIMIT <expression>
    [ 
      { OFFSET | , }
      <expression> 
    ]
  ] 
} | SCOPE_IDENTITY() 

<expression> ::=
  | <column_reference>
  | @ <parameter> 
  | ?
  | COUNT( * | { [ DISTINCT ] <expression> } )
  | { AVG | MAX | MIN | SUM | COUNT } ( <expression> ) 
  | NULLIF ( <expression> , <expression> ) 
  | COALESCE ( <expression> , ... ) 
  | CASE <expression>
      WHEN { <expression> | <search_condition> } THEN { <expression> | NULL } [ ... ]
    [ ELSE { <expression> | NULL } ]
    END 
  | {RANK() | DENSE_RANK()} OVER ([PARTITION BY <column_reference>] {ORDER BY <column_reference>})
  | <literal>
  | <sql_function> 

<search_condition> ::= 
  {
    <expression> { = | > | < | >= | <= | <> | != | LIKE | NOT LIKE | IN | NOT IN | IS NULL | IS NOT NULL | AND | OR | CONTAINS | BETWEEN | IS DISTINCT FROM | IS NOT DISTINCT FROM } [ <expression> ]
  } [ { AND | OR } ... ] 

Examples

  1. Return all columns:
    SELECT * FROM Transactions
  2. Rename a column:
    SELECT [TotalTax] AS MY_TotalTax FROM Transactions
  3. Cast a column's data as a different data type:
    SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Transactions
  4. Search data:
    SELECT * FROM Transactions WHERE Code = '051349'
  5. Return the number of items matching the query criteria:
    SELECT COUNT(*) AS MyCount FROM Transactions 
  6. Return the number of unique items matching the query criteria:
    SELECT COUNT(DISTINCT TotalTax) FROM Transactions 
  7. Return the unique items matching the query criteria:
    SELECT DISTINCT TotalTax FROM Transactions 
  8. Sort a result set in ascending order:
    SELECT Id, TotalTax FROM Transactions  ORDER BY TotalTax ASC
  9. Restrict a result set to the specified number of rows:
    SELECT Id, TotalTax FROM Transactions LIMIT 10 
  10. Parameterize a query to pass in inputs at execution time. This enables you to create prepared statements and mitigate SQL injection attacks.
    SELECT * FROM Transactions WHERE Code = @param
See Explicitly Caching Data for information on using the SELECT statement in offline mode.

Pseudo Columns

Some input-only fields are available in SELECT statements. These fields, called pseudo columns, do not appear as regular columns in the results, yet may be specified as part of the WHERE clause. You can use pseudo columns to access additional features from Avalara.

    SELECT * FROM Transactions WHERE Pseudo = '@Pseudo'
    

Aggregate Functions

For SELECT examples using aggregate functions, see Aggregate Functions.

JOIN Queries

See JOIN Queries for SELECT query examples using JOINs.

Date Literal Functions

Date Literal Functions contains SELECT examples with date literal functions.

Window Functions

See Window Functions for SELECT examples containing window functions.

Table-Valued Functions

See Table-Valued Functions for SELECT examples with table-valued functions.

CData Python Connector for Avalara

Aggregate Functions

COUNT

Returns the number of rows matching the query criteria.

SELECT COUNT(*) FROM Transactions WHERE Code = '051349'

COUNT(DISTINCT)

Returns the number of distinct, non-null field values matching the query criteria.

SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Transactions WHERE Code = '051349'

AVG

Returns the average of the column values.

SELECT TotalTax, AVG(AnnualRevenue) FROM Transactions WHERE Code = '051349'  GROUP BY TotalTax

MIN

Returns the minimum column value.

SELECT MIN(AnnualRevenue), TotalTax FROM Transactions WHERE Code = '051349' GROUP BY TotalTax

MAX

Returns the maximum column value.

SELECT TotalTax, MAX(AnnualRevenue) FROM Transactions WHERE Code = '051349' GROUP BY TotalTax

SUM

Returns the total sum of the column values.

SELECT SUM(AnnualRevenue) FROM Transactions WHERE Code = '051349'

CData Python Connector for Avalara

JOIN Queries

The CData Python Connector for Avalara supports standard SQL joins like the following examples.

Inner Join

An inner join selects only rows from both tables that match the join condition:

SELECT c.Date, o.ItemCode, o.IsItemTaxable, o.Description FROM Transactions c INNER JOIN TransactionLines o ON c.Id = o.TransactionId

Left Join

A left join selects all rows in the FROM table and only matching rows in the JOIN table:

SELECT c.ContactName, o.CustomerCode, o.Name, o.Value FROM Customers c LEFT JOIN CustomerCustomFields o ON c.CustomerCode = o.CustomerCode Where c.CompanyId = '247015' And o.CompanyId = '247015'

CData Python Connector for Avalara

Window Functions

Window functions allow you to create computed fields from a group of rows (a window) that return a result for each row, as opposed to one computed result for a set of rows, as is the case with aggregate functions. The connector supports the following window function syntax.

Note: Window function support is an experimental feature of the connector. This functionality extends beyond the connector's core scope of being SQL-92 compliant. As such, performance with window functions may not be optimal.

Window Function Clauses

OVER

The OVER clause defines the window over which window functions are performed.

SELECT A, B, <window function> OVER (<window frame>) FROM TableName

The <window function> refers to any supported window function clause, and the <window frame> refers to one or more clauses that specify the logic by which the window is defined.

PARTITION BY

The PARTITION BY clause subdivides a window into sub-windows called partitions. For each unique value in the column specified in the PARTITION BY clause, every record with that value collectively forms an individual partition.

SELECT A, B, <window function> OVER (PARTITION BY A ORDER BY B) From Transactions

The <window function> refers to any supported window function clause.

Window Functions

The connector supports math, ranking, and analytic window functions.

Math

These window functions perform mathematical operations on the records within the window.

COUNT()

Calculates the number of records in each partition. The calculated column is of the data type "int".

In each partition, every record will display the total number of records in that partition.

SELECT Name, Role, Earnings, COUNT() OVER (PARTITION BY Role) FROM Employees

COUNT_BIG()

Calculates the number of records in each partition. The calculated column is of the data type "bigint".

In each partition, every record will display the total number of records in that partition.

SELECT Name, Role, Earnings, COUNT_BIG() OVER (PARTITION BY Role) FROM Employees

MIN(numeric_column)

Calculates the minimum value of a numerical column per partition.

In each partition, every record will display the minimum value of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, MIN(Earnings) OVER (PARTITION BY Role) FROM Employees

MAX(numeric_column)

Calculates the maximum value of a numerical column per partition.

In each partition, every record will display the maximum value of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, MAX(Earnings) OVER (PARTITION BY Role) FROM Employees

SUM(numeric_column)

Calculates the sum of a numerical column per partition.

In each partition, every record will display the sum of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, SUM(Earnings) OVER (PARTITION BY Role) FROM Employees

AVG(numeric_column)

Calculates the average value of a numerical column per partition.

In each partition, every record will display the average value of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, AVG(Earnings) OVER (PARTITION BY Role) FROM Employees

MEDIAN(numeric_column)

Calculates the median value of a numerical column per partition.

In each partition, every record will display the median value of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, MEDIAN(Earnings) OVER (PARTITION BY Role) FROM Employees

STDEV(numeric_column)

Calculates the standard deviation of a numerical column per partition.

In each partition, every record will display the standard deviation of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, STDEV(Earnings) OVER (PARTITION BY Role) FROM Employees

STDEVP(numeric_column)

Calculates the population standard deviation of a numerical column per partition.

In each partition, every record will display the population standard deviation of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, STDEVP(Earnings) OVER (PARTITION BY Role) FROM Employees

VAR(numeric_column)

Calculates the statistical standard variance of a numerical column per partition.

In each partition, every record will display the statistical standard variance of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, VAR(Earnings) OVER (PARTITION BY Role) FROM Employees

VARP(numeric_column)

Calculates the variance population of a numerical column per partition.

In each partition, every record will display the variance population of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, VARP(Earnings) OVER (PARTITION BY Role) FROM Employees

Ranking

These window functions rank records that fall within the window and its partitions.

RANK()

Assigns a rank number to each record in a window based on the value of the column specified in the required ORDER BY clause.

If two or more records have an equal value in the in ranked column, they all receive the same rank number and the rank count increments internally, skipping ahead one rank number for each record with a duplicate value in the ORDER BY column.

SELECT Id, TotalTax, RANK() OVER (ORDER BY TotalTax) AS Rank FROM Transactions

If you add a PARTITION BY clause, a separate set of ranks is calculated for each partition.

SELECT Id, TotalTax, RANK() OVER (PARTITION BY Id ORDER BY TotalTax) AS Rank FROM Transactions

DENSE_RANK()

Operates like the RANK() function, but it doesn't increment the internal rank counter for each record with a duplicate value in the ranked column.

This means that, while records with identical values in the ORDER BY column still share a rank number, the function never skips a rank number.

SELECT Id, TotalTax, DENSE_RANK() OVER (PARTITION BY Id ORDER BY TotalTax) AS Rank FROM Transactions

If you add a PARTITION BY clause, a separate set of ranks is calculated for each partition.

SELECT Id, TotalTax, DENSE_RANK() OVER (PARTITION BY Id ORDER BY TotalTax) AS Rank FROM Transactions

ROW_NUMBER()

Calculates a row number for each record. An ORDER BY clause in the OVER clause is required.

SELECT Name, Role, Earnings, ROW_NUMBER() OVER (ORDER BY Role) FROM Employees
If you define multiple partitions with PARTITION BY, a new set of row numbers are calculated for each partition.
SELECT Name, Role, Earnings, ROW_NUMBER() OVER (PARTITION BY Role ORDER BY Earnings) FROM Employees

NTILE()

Distributes rows of an ordered partition into a specified number of approximately equal groups, or buckets. It assigns each group a bucket number starting from one. For each row in a group, the NTILE() function assigns a bucket number representing the group to which the row belongs.

The syntax of NTILE() is:

NTILE(buckets) OVER (
    [PARTITION BY partition_expression, ... ]
    ORDER BY sort_expression [ASC | DESC], ...
)
The following are paramaters that NTILE() supports:

  • buckets: The number of buckets into which the rows are divided. The buckets can be an expression or subquery that evaluates to a positive integer. It cannot be a window function.
  • PARTITION BY: distributes rows of a result set into partitions to which the NTILE() function is applied.
  • ORDER BY is clause that specifies the logical order of rows in each partition to which the NTILE() is applied.

If the number of rows is not divisible by the buckets, the NTILE() function returns groups of two sizes with the difference by one. The larger groups always precede the smaller group in the order set by ORDER BY in the OVER() clause.

If the total of rows is divisible by the number of buckets, the function divides the rows evenly among buckets. The following statement creates a new table named ntile_demo that stores 10 integers:

CREATE TABLE sales.ntile_demo (
	v INT NOT NULL
);
	
INSERT INTO sales.ntile_demo(v) 
VALUES(1),(2),(3),(4),(5),(6),(7),(8),(9),(10);	
	
SELECT * FROM sales.ntile_demo;
This statement uses the NTILE() function to divide ten rows into three groups:
SELECT 
	v, 
	NTILE (3) OVER (
		ORDER BY v
	) buckets
FROM 
	sales.ntile_demo;

Analytical

These window functions perform analytical operations on the records within the window.

PERCENT_RANK()

Calculates the relative rank SQL Percentile of each row. It returns values greater than zero, but the maximum value is one. It does not count any NULL values. This function is nondeterministic.

The syntax of PERCENT_RANK() is:

PERCENT_RANK() OVER (
      [PARTITION BY partition_expression, ... ]
      ORDER BY sort_expression [ASC | DESC], ...
  )
  
This syntax uses the following parameters.

  • PARTITION BY: By default, SQL Server treats the whole data set as a single set. You can specify the PARTITION BY clause to divide data into multiple sets. The Percent_Rank function performs the analytical calculations on each set. This parameter is optional.
  • ORDER BY: Sorts the data in either ascending or descending order. This parameter is required.

CData Python Connector for Avalara

Table-Valued Functions

Table-valued functions are functions that return a table (rowset).

Note: Table-valued function support is an experimental feature of the connector. This functionality extends beyond the connector's core scope of being SQL-92 compliant. As such, performance with these functions may not be optimal.

Table-Valued Function Clauses

CROSS APPLY

The CROSS APPLY operator is used to perform a subquery on each row of a table or resultset produced by a preceding table expression.

<table_expression_1> CROSS APPLY <table_expression_2>

The second table expression can reference results from the first table expression to create derived columns or an altered recordset via a table-valued function.

Each resulting record is an instance of the record it's splitting, with all the same column values, except for the column(s) containing the value split by the function.

WITH

The WITH clause is used alongside certain table-valued functions to match against constructs within the structure being split (keys, element names, attribute names, etc.) and/or to specify metadata for the columns generated from the function.
SELECT A.ColumnName, X.DerivedColumnName FROM TableName A CROSS APPLY <table-valued function> WITH (DerivedColumnName varchar(255)) AS X

Table-Valued Functions

STRING_SPLIT(input_text,delimiter)

Takes each record in the recordset of the preceding table expression, splits the column containing delimiters (input_text) into substrings separated by the delimiter, and returns one record per substring.

  • input_text: A column whose value you want to parse.
  • delimiter: The character used to split the value of the column specified in input_text.

Suppose there is a column called "SplitColumn" with the following content:

One-Two-Three
To unpack this value across multiple records:
SELECT A.ID, X.Value FROM [TableWithDelimitedStringField] A CROSS APPLY STRING_SPLIT(A.SplitColumn,'-') WITH (Value VARCHAR(255)) AS X

-- Results:
-----------
|ID|Value|
|1|One|
|1|Two|
|1|Three|

JSONTABLE(json_content,[jsonpath])

For each record in the recordset of the preceding table expression, returns one record for each instance of a key in a JSON array (json_content) that matches the key(s) specified in the WITH clause, at the scope specified by the "jsonpath" input.

  • json_content: A JSON "table" (array of objects). The contents can nest, but this must be a single JSON array, not any other JSON structure, at the root level.
    • The values of every instance of the key(s) provided in the WITH clause are retrievable only for substructures which are immediate children of the root-level JSON array.
  • jsonpath: An optional JSONPath query defining the scope, within the json_content array, that you want to pull content from. The JSON key(s) identified in the WITH clause must exist at the scope defined in this parameter. This defaults to the JSON root ($).

Consider a sample table with a single record, including an ID column and column with JSON content called "JSONColumn" with the following content:

[
	{
		"name": "Samuel",
		"email": "sam@gmail.com",
		"extrainfo": {
			"city": "Seattle"
		}
	},
	{
		"name": "Katherine",
		"email": "kat@gmail.com",
	},
	{
		"name": "George",
		"email": "george23@gmail.com",
	},
	{
		"name": "Carlos",
		"email": "carlos32@gmail.com",
	}
]

To extract all values for a certain key, specify the scope in the JSONTABLE function and provide the desired key(s) in the WITH clause.

SELECT A.ID, X.name FROM [TableWithJSONField] A CROSS APPLY JSONTABLE(A.JSONColumn) WITH (name VARCHAR(255)) AS X

-- Results: 
|ID|name|
---------
|1 |Samuel|
|1 |Katherine|
|1 |George|
|1 |Carlos|

XMLTABLE(xml_content,[xpath,child_type])

For each record in the resultset of the preceding table expression, returns one record for each of the elements and/or attributes in an XML structure (xml_content) that match the tag name(s) and/or attribute name(s) specified in the WITH clause, at the scope specified in the "xpath" input.

  • xml_content: A column containing an XML structure.
  • xpath: An optional XPath that specifies the scope within the XML structure at which the connector extracts content matching the tag/attribute name(s) specified in the WITH clause.
    • When extracting the content of sub-elements, the connector can retrieve all content from tags at the root level, (depth 0) immediate children of the root (depth 1), and children of those children (depth 2).
    • When extracting element attribute content, the connector can retrieve all content from tags containing the specified attribute at the root level (depth 0) and from immediate children of root-level elements (depth 1).
  • child_type: An optional parameter that specifies the part(s) of the parent element (specified in the xpath input) that the column(s) provided in the WITH clause are checked against to identify content.
    • You can supply the following values:
      • 0: The column(s) in the WITH clause are checked for matches against the parent element's attribute names and sub-element tag names.
      • 1: The column(s) in the WITH clause are checked for matches against the parent element's attribute names.
      • 2: The column(s) in the WITH clause are checked for matches against the parent element's sub-element tag names.
    • When not supplied, this defaults to 0.

Extracting Sub-Element Values

Consider a sample table with a single record, including an ID column and a column with XML content called "XMLContent" with the following content:
<shoppingList>
    <item>
        <name>Apples</name>
        <quantity>3</quantity>
        <unit>Kg</unit>
    </item>
    <item>
        <name>Bread</name>
        <quantity>2</quantity>
        <unit>Loaf</unit>
		<extrainfo>
			<Type>Whole-Grain</Type>
		</extrainfo>
    </item>
    <item>
        <name>Milk</name>
        <quantity>1</quantity>
        <unit>Carton</unit>
    </item>
    <item>
        <name>Eggs</name>
        <quantity>12</quantity>
        <unit></unit>
    </item>
</shoppingList>

To extract sub-element content, specify the scope in the XMLTABLE function and provide the desired element name(s) in the WITH clause. Note that this will not work if the XMLTABLE function's child_type input is set to 1.

SELECT A.ID, X.name FROM [TableWithXMLField] A CROSS APPLY XMLTABLE(A.XMLContent,'//*/item') WITH (name VARCHAR(255)) AS X

-- Results: 
|ID|name|
---------
|1|Apples|
|1|Bread|
|1|Milk|
|1|Eggs|

Extracting Values Using Element Tag Attributes

Suppose you have this sample table with a single record, including an ID column and a column with XML content called "XMLContent" with the following content:

<restaurant>
  <dish type="appetizer">
    <name lang="en">Caprese Salad</name>
    <chef>Chef Giovanni</chef>
    <price currency="USD">9.99</price>
  </dish>
  <dish type="main-course">
    <name lang="fr">Boeuf Bourguignon</name>
    <chef>Chef Marie</chef>
    <price currency="EUR">19.99</price>
  </dish>
  <dish type="dessert">
    <name lang="es">Tres Leches Cake</name>
    <chef>Chef Alejandro</chef>
    <price currency="MXN">89.99</price>
  </dish>
</restaurant>

To extract attribute content, specify the scope in the XMLTABLE function and provide the desired attribute name(s) in the WITH clause. Note that this will not work if the XMLTABLE function's child_type input is set to 2.

SELECT A.ID, X.type FROM [TableWithXMLField] A CROSS APPLY XMLTABLE(A.XMLContent,'//*/dish') WITH (type VARCHAR(255)) AS X

-- Results: 
|ID|type|
---------
|1|appetizer|
|1|main-course|
|1|dessert|

CSVTABLE(csv_content,[delimiter])

For each record in the resultset of the preceding table expression, reads from a column that contains a CSV table (csv_content) and for each record in that CSV table, returns one record containing the value of the CSV column(s) specified in the WITH clause.

  • csv_content: A column containing a CSV table.
  • delimiter: An optional custom delimiter (instead of a comma) which splits the CSV content contained in the csv_content input.

Consider a sample table with a single record, including an ID column and a column containing CSV table called "CSVContent" with the following content:

Name;Category;Price
Apple;Fruit;0.99
Spaghetti;Pasta;5.49
Chicken Breast;Meat;8.99
Broccoli;Vegetable;2.49

To select every value in the "Name" column and account for the custom delimiter (;):

SELECT A.ID, X.Name FROM [TableWithCSVField] A CROSS APPLY CSVTABLE(A.CSVContent,';') WITH (Name VARCHAR(255)) AS X

-- Results:
|ID|Name|
-----------
|1|Apple|
|1|Spaghetti|
|1|Chicken Breast|
|1|Broccoli|

CData Python Connector for Avalara

INSERT Statements

To create new records, use INSERT statements.

INSERT Syntax

The INSERT statement specifies the columns to be inserted and the new column values. You can specify the column values in a comma-separated list in the VALUES clause, as shown in the following example:

INSERT INTO <table_name> 
( <column_reference> [ , ... ] )
VALUES 
( { <expression> | NULL } [ , ... ] ) 
  

<expression> ::=
  | @ <parameter> 
  | ?
  | <literal>
The following is an example query:
INSERT INTO Transactions (TotalTax) VALUES ('John')

CData Python Connector for Avalara

UPDATE Statements

To modify existing records, use UPDATE statements.

Update Syntax

The UPDATE statement takes as input a comma-separated list of columns and new column values as name-value pairs in the SET clause, as shown in the following example:

UPDATE <table_name> SET <select_statement> | {<column_reference> = <expression> [ , ... ]} WHERE { Id = <expression>  } [ { AND | OR } ... ] 

<expression> ::=
  | @ <parameter> 
  | ?
  | <literal>

The following is an example query:

UPDATE Transactions SET TotalTax='John' WHERE Id = @myId

CData Python Connector for Avalara

DELETE Statements

To delete information from a table, use DELETE statements.

DELETE Syntax

The DELETE statement requires the table name in the FROM clause and the row's primary key in the WHERE clause, as shown in the following example:

<delete_statement> ::= DELETE FROM <table_name> WHERE { Id = <expression> } [ { AND | OR } ... ]

<expression> ::=
  | @ <parameter> 
  | ?
  | <literal>

The following is an example query:

DELETE FROM Transactions WHERE Id = @myId

CData Python Connector for Avalara

CACHE Statements

When caching is enabled, CACHE statements provide complete control over the data that is cached and the table to which it is cached. The CACHE statement executes the SELECT statement specified and caches its results to a table with the same name in the cache database or to table specified in <cached_table_name>. The connector updates or inserts rows to the cache depending on whether or not they already exist in the cache, so the primary key, which is used to identify existing rows, must be included in the selected columns.

See Caching Data for more information on different caching strategies.

CACHE Statement Syntax

The cache statement may include the following options that alter its behavior:

CACHE [ <cached_table_name> ] [ WITH TRUNCATE | AUTOCOMMIT | SCHEMA ONLY | DROP EXISTING | ALTER SCHEMA ] <select_statement> 

WITH TRUNCATE

If this option is set, the connector removes existing rows in the cache table before adding the selected rows. Use this option if you want to refresh the entire cache table but keep its existing schema.

AUTOCOMMIT

If this option is set, the connector commits each row individually. Use this option if you want to ignore the rows that could not be cached due to some reason. By default, the entire result set is cached as a single transaction.

DROP EXISTING

If this option is set, the connector drops the existing cache table before caching the new results. Use this option if you want to refresh the entire cache table, including its schema.

SCHEMA ONLY

If this option is set, the connector creates the cache table based on the SELECT statement without executing the query.

ALTER SCHEMA

If this option is set, the connector alters the schema of the existing table in the cache if it does not match the schema of the SELECT statement. This option results in new columns or dropped columns, if the schema of the SELECT statement does not match the cached table.

Common Queries

Use the following cache statement to cache all rows of a table:

CACHE SELECT * FROM Transactions

Use the following cache statement to cache all rows of a table into the cache table CachedTransactions:

CACHE CachedTransactions SELECT * FROM Transactions

Use the following cache statement for incremental caching. The DateModified column may not exist in all tables. The cache statement shows how incremental caching would work if there were such a column. Also, notice that, in this case, the WITH TRUNCATE and DROP EXISTING options are specifically omitted, which would have deleted all existing rows.

CACHE CachedTransactions SELECT * FROM Transactions WHERE DateModified > '2013-04-04'

Use the following cache statements to create a table with all available columns that will then cache only a few of them. The sequence of statements cache only Id and TotalTax even though the cache table CachedTransactions has all the columns in Transactions.

CACHE CachedTransactions SCHEMA ONLY SELECT * FROM Transactions
CACHE CachedTransactions SELECT Id, TotalTax FROM Transactions

CData Python Connector for Avalara

EXECUTE Statements

To execute stored procedures, you can use EXECUTE or EXEC statements.

EXEC and EXECUTE assign stored procedure inputs, referenced by name, to values or parameter names.

Stored Procedure Syntax

To execute a stored procedure as an SQL statement, use the following syntax:

 
{ EXECUTE | EXEC } <stored_proc_name> 
{
  [ @ ] <input_name> = <expression>
} [ , ... ]

<expression> ::=
  | @ <parameter> 
  | ?
  | <literal>

Example Statements

Reference stored procedure inputs by name:

EXECUTE my_proc @second = 2, @first = 1, @third = 3;

Execute a parameterized stored procedure statement:

EXECUTE my_proc second = @p1, first = @p2, third = @p3; 

CData Python Connector for Avalara

PIVOT and UNPIVOT

PIVOT and UNPIVOT can be used to change a table-valued expression into another table.

PIVOT

PIVOT rotates a table-value expression by turning unique values from one column into multiple columns in the output. PIVOT can run aggregations where required on any column value.
PIVOT Synax

 
"SELECT 'AverageCost' AS Cost_Sorted_By_Production_Days, [0], [1], [2], [3], [4]
FROM
(
SELECT DaysToManufacture, StandardCost
FROM Production.Product
) AS SourceTable
PIVOT
(
AVG(StandardCost)
FOR DaysToManufacture IN ([0], [1], [2], [3], [4])
) AS PivotTable;"

UNPIVOT

UNPIVOT carries out nearly the opposite to PIVOT by rotating columns of a table-valued expressions into column values.
UNPIVOT Sytax

 
"SELECT VendorID, Employee, Orders
FROM
(SELECT VendorID, Emp1, Emp2, Emp3, Emp4, Emp5
FROM pvt) p
UNPIVOT
(Orders FOR Employee IN
(Emp1, Emp2, Emp3, Emp4, Emp5)
)AS unpvt;"

For further information on PIVOT and UNPIVOT, see FROM clause plus JOIN, APPLY, PIVOT (Transact-SQL)

CData Python Connector for Avalara

Data Model

Overview

This section shows the available API objects and provides more information on executing SQL to Avalara APIs.

Key Features

  • The connector models Avalara entities as relational views, allowing you to write SQL to query Avalara data.
  • Stored procedures allow you to execute operations to Avalara.
  • Live connectivity to these objects means any changes to your Avalara account are immediately reflected when using the connector.

Tables

Tables describes the available tables. Tables are statically defined to model Accounts, Transactions, Users, and more.

Views

Views describes the available views. Views are statically defined to model Reports, Subscriptions, and more.

Stored Procedures

Stored Procedures are function-like interfaces to Avalara. Stored procedures allow you to execute operations to Avalara, including downloading documents and moving envelopes.

CData Python Connector for Avalara

Tables

The connector models the data in Avalara as a list of tables in a relational database that can be queried using standard SQL statements.

CData Python Connector for Avalara Tables

Name Description
Accounts Accounts table for AvalaraAvatax data provider.
Batches Batches table for AvalaraAvatax data provider.
Companies Companies table for AvalaraAvatax data provider.
Contacts Contacts table for AvalaraAvatax data provider.
Customers Customers table for AvalaraAvatax data provider.
DataSources DataSources table for AvalaraAvatax data provider.
DistanceThresholds DistanceThresholds table for AvalaraAvatax data provider.
FilingCalendars FilingCalendars table for AvalaraAvatax data provider.
Items Items table for AvalaraAvatax data provider.
Locations Locations table for AvalaraAvatax data provider.
MultiDocument MultiDocument table for AvalaraAvatax data provider.
Nexus Nexus table for AvalaraAvatax data provider.
Notices Notices table for AvalaraAvatax data provider.
Notifications Notifications table for AvalaraAvatax data provider.
Settings Settings table for AvalaraAvatax data provider.
TaxCodes TaxCodes table for AvalaraAvatax data provider.
TaxRules TaxRules table for AvalaraAvatax data provider.
TransactionLines TransactionLines view for AvalaraAvatax data provider.
Transactions Transactions table for AvalaraAvatax data provider.
Upcs Upcs table for AvalaraAvatax data provider.
Users Users table for AvalaraAvatax data provider.

CData Python Connector for Avalara

Accounts

Accounts table for AvalaraAvatax data provider.

Select

The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. Most of the columns support server side filtering with the following operators: =,>,<,<=,>=,IN,NOT,IN,AND,OR,LIKE. The rest of the filter is executed client side within the connector. For example, the following query is processed server side:

SELECT * FROM Accounts WHERE accountStatusId = 'Active' AND accountTypeId = 'Regular1'

Insert

To add an Account.

INSERT INTO Accounts (id, name, effectiveDate, accountStatusId, accountTypeId) VALUES ('12345', 'Test Account', '2019-06-24T00:00:00+00:00', 'Test', 'Regular')

Update

Avalara allows updates Accounts columns.

UPDATE Accounts SET crmid = '0010b000Ardit' WHERE Id = 2000137504 

In order to update AccountsSubscriptions #TEMP table should be used.

INSERT INTO AccountsSubscriptions#TEMP (subscriptionDescription, id) VALUES ('Avacert2', '567961')
UPDATE Accounts SET linkedSubscriptions = 'AccountsSubscriptions#TEMP', crmid = '0010b000Ardit' WHERE Id = 2000137504

Delete

Accounts can be deleted by providing the Id of the address and issuing a DELETE statement.

DELETE FROM Accounts WHERE Id = 100

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number assigned to this account.

ModifiedUserId Int False

The user ID of the user who last modified this record.

CreatedUserId Int False

The User ID of the user who created this record.

AccountTypeId String False

The type of this account.

AccountStatusId String False

The current status of this account.

CrmId String False

For system registrar use only.

LinkedSubscriptions String False

A list of subscriptions granted to this account.

Name String False

The name of this account.

LinkedUsers String False

A list of all the users belonging to this account.

ModifiedDate Datetime False

The date/time when this record was last modified.

EndDate Datetime False

If this account has been closed, this is the last date the account was open.

EffectiveDate Datetime False

The earliest date on which this account may be used.

CreatedDate Datetime False

The date when this record was created.

PageKey String False

CData Python Connector for Avalara

Batches

Batches table for AvalaraAvatax data provider.

Insert

Create batch objects attached to a company. Each batch object must have one file object. When a batch is created, it is added to the AvaTax Batch Queue and will be processed as quickly as possible in the order it was received. As a result of this operation you will get the status of a batch. First insert the file, referencing the local path of the file on your machine, using #TEMP table:

INSERT INTO File#TEMP (Name, FileLocalPath, ContentType) VALUES ('samplebatch.csv', 'C:\\Users\\User\\Desktop\\BatchFile.csv', 'text/csv')
Then insert in the main Batches table. The following fielda are required:
INSERT INTO Batches (CompanyId, Name, LinkedFiles, Type) VALUES ('247015', 'TestBatch2', 'File#TEMP', 'TransactionImport')

Update

UPDATE operation is not supported for Batches table.

Delete

If you attempt to delete a batch that is being processed, you will receive an error message. Deleting a batch does not delete any transactions that were created by importing the batch. Deleting a batch requires one of the following user roles: CSPAdmin, CSPTester, SSTAdmin, SystemAdmin, SystemOperator, TechnicalSupportAdmin; Companyid and Id should be specified in the WHERE clause.

DELETE FROM Batches WHERE Id = 9030440 AND CompanyId = 247015

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this batch.

CompanyId [KEY] Int False

The Company ID number of the company that owns this batch.

BatchAgent String False

The agent used to create this batch.

CurrentRecord Int False

The current record being processed

CompletedDate Datetime False

The date/time when this batch was completely processed.

LinkedFiles String False

The list of files contained in this batch.

Name String False

The user-friendly readable name for this batch.

ModifiedUserId Int False

The user ID of the user who last modified this record.

CreatedUserId Int False

The User ID of the user who created this record.

Status String False

This batch's current processing status.

RecordCount Int False

The number of records in this batch; determined by the server.

ModifiedDate Datetime False

The date/time when this record was last modified.

AccountId Int False

The Account ID number of the account that owns this batch.

Type String False

The type of this batch.Possible values are:ItemImport, CompanyLocationImport, ExemptCertImport, TaxRuleImport, TransactionImport, UPCBulkImport.

StartedDate Datetime False

The date/time when this batch started processing.

CreatedDate Datetime False

The date when this record was created.

Options String False

Any optional flags provided for this batch.

PageKey String False

CData Python Connector for Avalara

Companies

Companies table for AvalaraAvatax data provider.

Insert

To insert a new company to an existing account you need to specify AccountId, CompanyCode, Name and DefaultCountry fields.

INSERT INTO Companies (AccountId, CompanyCode, Name, defaultCountry) VALUES ('2000137504', 'SAB', 'SAB&Co', 'US')

Update

Avalara allows UPDATEs on Companies columns, expect for aggregate columns. Aggregate columns can not be updated.

UPDATE Companies SET Name = 'UpdatedName' WHERE Id = 283040

Delete

A company can be deleted by providing the Id of the company and issuing a DELETE statement.

DELETE FROM Companies WHERE Id = 283040

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this company.

DefaultLocationId Int False

If set, this is the unique ID number of the default location for this company.

LinkedNexus String False

Optional: A list of nexus defined for this company. To fetch this list, add the query string `?$include=Nexus` to your URL.

NonReportingChildCompanies String False

TaxDependencyLevelId String False

Used to apply tax detail dependency at a jurisdiction level.

DefaultCountry String False

The two character ISO-3166 country code of the default country for this company.

LinkedTaxRules String False

Optional: A list of tax rules defined for this company.

Name String False

The name of this company, as shown to customers.

CreatedDate Datetime False

The date when this record was created.

MossCountry String False

The country code of the mini-one-stop-shop used for Value Added Tax (VAT) processing.

LinkedContacts String False

Optional: A list of contacts defined for this company.

CompanyCode String False

A unique code that references this company within your account.

WarningsEnabled Bool False

Set this value to true to receive warnings in API calls via SOAP.

LinkedLocations String False

Optional: A list of locations defined for this company.

LinkedItems String False

Optional: A list of items defined for this company.

CreatedUserId Int False

The User ID of the user who created this record.

AccountId Int False

The unique ID number of the account this company belongs to.

ModifiedDate Datetime False

The date/time when this record was last modified.

RoundingLevelId String False

Indicates whether this company prefers to round amounts at the document level or line level.

BusinessIdentificationNo String False

Business Identification No.

LinkedUpcs String False

Optional: A list of UPCs defined for this company.

InProgress Bool False

Set this value to true to indicate that you are still working to finish configuring this company. While this value is true, no tax reporting will occur and the company will not be usable for transactions.

IsReportingEntity Bool False

Set this flag to true if this company must file its own tax returns. For users who have Returns enabled, this flag turns on monthly Worksheet generation for the company.

LinkedTaxCodes String False

Optional: A list of tax codes defined for this company.

ParentCompanyId Int False

If this company is fully owned by another company, this is the unique identity of the parent company.

BaseCurrencyCode String False

This is the three character ISO-4217 currency code of the default currency used by this company.

IsTest Bool False

Set this flag to true to indicate that this company is a test company. If you have Returns enabled, Test companies will not file tax returns and can be used for validation purposes.

IsActive Bool False

This flag indicates whether tax activity can occur for this company. Set this flag to true to permit the company to process transactions.

SstEffectiveDate Date False

If this company participates in Streamlined Sales Tax, this is the date when the company joined the SST program.

MossId String False

The unique identifier of the mini-one-stop-shop used for Value Added Tax (VAT) processing.

ModifiedUserId Int False

The user ID of the user who last modified this record.

LinkedSettings String False

Optional: A list of settings defined for this company.

SstPid String False

If this company files Streamlined Sales Tax, this is the PID of this company as defined by the Streamlined Sales Tax governing board.

TaxpayerIdNumber String False

For United States companies, this field contains your Taxpayer Identification Number. This is a nine digit number that is usually called an EIN for an Employer Identification Number if this company is a corporation, or SSN for a Social Security Number if this company is a person. This value is required if the address provided is inside the US and if you subscribed to the Avalara Managed Returns or SST Certified Service Provider service. Otherwise it is optional.

IsDefault Bool False

This flag is true if this company is the default company for this account. Only one company may be set as the default.

HasProfile Bool False

Set this flag to true to give this company its own unique tax profile. If this flag is true, this company will have its own Nexus, TaxRule, TaxCode, and Item definitions. If this flag is false, this company will inherit all profile values from its parent.

CData Python Connector for Avalara

Contacts

Contacts table for AvalaraAvatax data provider.

Select

The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. Most of the columns support server side filtering with the following operators: =,>,<,<=,>=,IN,NOT,IN,AND,OR,LIKE. The rest of the filter is executed client side within the connector. For example, the following query is processed server side:

SELECT * FROM Contacts WHERE companyid = 247015
SELECT * FROM Contacts WHERE companyid = 247015 AND region = 'NY'

Insert

To add a Contact, ContactCode is a required field.

INSERT INTO Contacts (companyId, contactCode, firstName, lastName, title, line1, city, region, postalCode, country, email, phone) VALUES ('247015', 'TestContactc7356131ca2442', " +
          "'Bob', 'McExample', 'Owner', '2000 Main Street', 'Irvine', 'CA', '92614', 'US', 'bob@example.org', '714 555-1212')

Update

Avalara allows updates Contacts columns. To update a Contact, Id and CompanyId should be specified in the WHERE clause of the Update statement.

UPDATE Contacts SET firstName = 'tidra' WHERE CompanyId = 247015 AND Id = 175596

Delete

Contacts can be deleted by providing the Companyid and Id of the Contact and issuing a DELETE statement.

DELETE FROM Contacts WHERE Id = 100

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this contact.

FirstName String False

The first or given name of this contact.

CreatedUserId Int False

The User ID of the user who created this record.

Mobile String False

The mobile phone number for this contact.

Region String False

Name or ISO 3166 code identifying the region within the country.

ModifiedDate Datetime False

The date/time when this record was last modified.

Phone String False

The main phone number for this contact.

Line3 String False

The third line of the postal mailing address of this contact.

PostalCode String False

The postal code or zip code of the postal mailing address of this contact.

Line2 String False

The second line of the postal mailing address of this contact.

Line1 String False

The first line of the postal mailing address of this contact.

LastName String False

The last or family name of this contact.

ModifiedUserId Int False

The user ID of the user who last modified this record.

CompanyId [KEY] Int False

The unique ID number of the company to which this contact belongs.

Email String False

The email address of this contact.

Country String False

Name or ISO 3166 code identifying the country.

City String False

The city of the postal mailing address of this contact.

MiddleName String False

The middle name of this contact.

Fax String False

The facsimile phone number for this contact.

CreatedDate Datetime False

The date when this record was created.

Title String False

Professional title of this contact.

ContactCode String False

A unique code for this contact.

PageKey String False

CData Python Connector for Avalara

Customers

Customers table for AvalaraAvatax data provider.

Select

To retrieve Customer records from Customers table, at least CompanyId or CompanyId and CustomerCode should be specified in the WHERE clause. The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. CompanyId and CustomerCode fields support server side filtering with the = operator. The rest of the filter is executed client side within the connector. For example, the following query is processed server side:

SELECT * FROM Customers WHERE CompanyId = '247015'
SELECT * FROM Contacts WHERE CompanyId = 247015 AND CustomerCode = 'CC001'

Columns

Name Type ReadOnly Description
Id Int False

Unique ID number of this customer.

CompanyId [KEY] Int False

The unique ID number of the AvaTax company that recorded this customer.

CustomerCode [KEY] String False

The unique code identifying this customer. Must be unique within your company.

AlternateId String False

A customer-configurable alternate ID number for this customer. You may set this value to match any other system that would like to reference this customer record.

IsShip Bool False

True if this customer record is specifically used for ship-to purposes.

LinkedShipTos String False

A list of ship-to customer records that are connected to this bill-to customer.

Region String False

ISO 3166 code identifying the region within the country.

IsBill Bool False

True if this customer record is specifically used for bill-to purposes.

EmailAddress String False

The main email address for this customer.

LinkedCustomFields String False

A list of custom fields defined on this customer.

TaxpayerIdNumber String False

For customers in the United States, this field is the federal taxpayer ID number. For businesses, this is a Federal Employer Identification Number. For individuals, this will be a Social Security Number.

ModifiedDate Datetime False

The date/time when this record was last modified.

LinkedCertificates String False

A list of exemption certficates that apply to this customer.

FaxNumber String False

The fax phone number for this customer, if any.

AttnName String False

Indicates the 'Attn' component of the address for this customer, if this customer requires mailings to be shipped to the attention of a specific person or department name.

PhoneNumber String False

The main phone number for this customer.

PostalCode String False

Postal Code / Zip Code component of the address of this customer.

Line2 String False

Second line of the street address of this customer.

Line1 String False

First line of the street address of this customer.

LastTransaction Datetime False

Date when this customer last executed a transaction.

Country String False

Name or ISO 3166 code identifying the country.

City String False

City component of the street address of this customer.

LinkedExposureZones String False

A list of exposure zones where you do business with this customer.

ContactName String False

The name of the main contact person for this customer.

CreatedDate Datetime False

The date when this record was created.

Name String False

A friendly name identifying this customer.

CData Python Connector for Avalara

DataSources

DataSources table for AvalaraAvatax data provider.

Insert

To create a data source at least CompanyId and Source should be specified.

INSERT INTO DataSources (CompanyId, Source) VALUES (247015, 'Amazon v2 Extractor')

Update

To update a data source, you need to specify Id and CompanyId in WHERE clause.

UPDATE DataSources SET isEnabled = true WHERE Id = 297 AND CompanyId = 247015

Delete

To delete a user, you need to specify Id and AccountId in WHERE clause.

DELETE FROM DataSources WHERE Id = 297 AND CompanyId = 247015

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The id of the datasource.

CompanyId [KEY] Int False

The id of the company to which the datasource belongs to.

Source String False

The extractor/connector id.

ModifiedUserId Int False

The user ID of the user who last modified this record.

CreatedUserId Int False

The User ID of the user who created this record.

ModifiedDate Datetime False

The date/time when this record was last modified.

IsAuthorized Bool False

True if this data source is authorized.

LastSyncedDate Datetime False

The date when the information was last synched.

IsSynced Bool False

If all the information has been transferred from the extractor to the database.

DeletedDate Datetime False

The date when this record was deleted.

IsEnabled Bool False

The connection using the connection_id is enabled. The customer is responsible to enable or disable.

Instance String False

The unique ID number of this connection.

CreatedDate Datetime False

The date when this record was created.

Recalculate Bool False

Specifies whether transactions created by this data source needs to re-calculate tax or not

PageKey String False

CData Python Connector for Avalara

DistanceThresholds

DistanceThresholds table for AvalaraAvatax data provider.

A company-distance-threshold model indicates the distance between a company and the taxing borders of various countries. Distance thresholds are necessary to correctly calculate some value-added taxes.

Insert

To create a distance-threshold object you need one of the following user roles: AccountAdmin, CompanyAdmin, CSPAdmin, CSPTester, SiteAdmin, SSTAdmin, SystemAdmin, TechnicalSupportAdmin. At least the following fields should be specified:

INSERT INTO DistanceThresholds (companyId, originCountry, destinationCountry, type) VALUES (283040, 'FR', 'BR', 'Purchase')

Update

To update a distance-threshold, you need to specify Id and CompanyId in WHERE clause.

UPDATE DistanceThresholds SET EffDate = '2019/11/08' WHERE Id = 11785 AND CompanyId = 283040

Delete

To delete a distance-threshold, you need to specify Id and AccountId in WHERE clause.

DELETE FROM DistanceThresholds WHERE Id = 11785 AND CompanyId = 283040

Columns

Name Type ReadOnly Description
Id [KEY] Int False

A unique ID number representing this distance threshold object.

CompanyId [KEY] Int False

The ID number of the company that defined this distance threshold.

OriginCountry String False

The origin country for this threshold.

DestinationCountry String False

The destination country for this threshold.

Type String False

Indicates the distance threshold type. This value can be either `Sale` or `Purchase`.

EffDate Datetime False

For distance threshold values that change over time, this is the earliest date for which this distance threshold is valid. If null, this distance threshold is valid for all dates earlier than the `endDate` field.

EndDate Datetime False

For distance threshold values that change over time, this is the latest date for which this distance threshold is valid. If null, this distance threshold is valid for all dates later than the `effDate` field.

ThresholdExceeded Bool False

True if your tax professional has determined that the value-added tax distance threshold is exceeded for this pair of countries. If you set this value to `false`, your value added taxes will be calculated using the origin country. Otherwise, value added taxes will be calculated on the destination country.

PageKey String False

CData Python Connector for Avalara

FilingCalendars

FilingCalendars table for AvalaraAvatax data provider.

Select

To retrieve records from FilingCalendar table, at least CompanyId should be specified in the WHERE clause. The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. Most of the columns support server side filtering with the following operators: =,>,<,<=,>=,IN,NOT,IN,AND,OR,LIKE. The rest of the filter is executed client side within the connector. For example, the following query is processed server side:

SELECT * FROM FilingCalendars WHERE CompanyId = '247015' AND Success = False

Columns

Name Type ReadOnly Description
CompanyId [KEY] Int False

CompanyId of the request

ActivePoa Bool False

Notes if there is an actice POA

ExpirationDate Datetime False

End Date of POA

LinkedAvailablePOA String False

POA download

Bytes String False

Bytes of the file

Filename String False

Original filename

Success Bool False

True if this download succeeded

ContentType String False

Mime content type

Region String False

Region POA is for

EffectiveDate Datetime False

Effective Date of the POA

Country String False

Country POA is for

CData Python Connector for Avalara

Items

Items table for AvalaraAvatax data provider.

Select

The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. Most of the columns support server side filtering with the following operators: =,>,<,<=,>=,IN,NOT,IN,AND,OR,LIKE. The rest of the filter is executed client side within the connector. For example, the following query is processed server side:

SELECT * FROM Items WHERE CompanyId = 247015 AND Description LIKE '%MUG'
SELECT * FROM Items WHERE CompanyId = 247015 AND ModifiedUserId IN (289767, 1354)

Insert

To add an Item.

INSERT INTO Items (companyId, itemCode, taxCode, description, itemGroup) VALUES ('247015', 'CERMUG1', 'P0000000', 'Ceramic Mug', 'Mugs')")

In order to add an item with ItemsClassifications #TEMP table should be used

INSERT INTO Itemsclassifications#TEMP (productCode, systemCode) VALUES ('P0000000', 'TARIC')")
INSERT INTO Items (companyId, itemCode, taxCode, description, itemGroup, Linkedclassifications) VALUES ('247015', 'CERMUG', 'P0000000', 'Ceramic Mug', 'Mugs', 'Itemsclassifications#TEMP')")
INSERT INTO Items (companyId, itemCode, taxCode, description, itemGroup) VALUES ('247015', 'CERMUG1', 'P0000000', 'Ceramic Mug', 'Mugs')")

Update

Avalara allows updates to Items columns.

UPDATE Items SET Description = 'description', itemcode = 'CERMUG' WHERE Id = '189117938' AND CompanyId = '247015'

In order to update ItemsClassifications, a #TEMP table should be used.

INSERT INTO Itemsclassifications#TEMP (systemcode, productcode) VALUES ('P0000001', 'AVATAXCEDE')")
UPDATE items SET description = 'description', itemcode = 'CERMUG', linkedclassifications = 'Itemsclassifications#TEMP' WHERE id = '189117938' AND companyId = '247015'")

Delete

Items can be deleted by providing the Id of the address and issuing a DELETE statement.

DELETE FROM Items WHERE Id = 100

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this item.

CompanyId [KEY] Int False

The unique ID number of the company that owns this item.

ItemCode String False

A unique code representing this item.

ModifiedUserId Int False

The user ID of the user who last modified this record.

LinkedClassifications String False

List of classifications that belong to this item. A single classification consists of a productCode and a systemCode for a particular item.

CreatedUserId Int False

The User ID of the user who created this record.

ItemGroup String False

A way to group similar items.

ModifiedDate Datetime False

The date/time when this record was last modified.

Description String False

A friendly description of this item in your product catalog.

LinkedParameters String False

List of item parameters.

CreatedDate Datetime False

The date when this record was created.

TaxCode String False

CData Python Connector for Avalara

Locations

Locations table for AvalaraAvatax data provider.

Insert

To create a location at least the following fields should be specified.

INSERT INTO Locations (CompanyId, Line1, LocationCode, AddressTypeId, AddressCategoryId, PostalCode, Country) VALUES (247015, '2000 Main Street', 'L001', 'Location', 'MainOffice', 92614, 'US')

Update

To update a location, you need to specify Id and CompanyId in WHERE clause.

UPDATE Locations SET City = 'Irvine' WHERE Id = 56789 AND CompanyId = 247015

Delete

To delete a location, you need to specify Id and AccountId in WHERE clause.

DELETE FROM Locations WHERE Id = 56789 AND CompanyId = 247015

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this location.

CompanyId [KEY] Int False

The unique ID number of the company that operates at this location.

RegisteredDate Datetime False

The date when this location was registered with a tax authority. Not required.

DbaName String False

If this location has a different business name from its legal entity name, specify the 'Doing Business As' name for this location.

EffectiveDate Date False

The date when this location was opened for business, or null if not known.

CreatedUserId Int False

The User ID of the user who created this record.

AddressCategoryId String False

Indicates the type of place of business represented by this location.

Region String False

Name or ISO 3166 code identifying the region within the country of the physical address of this location.

LastTransactionDate Datetime False

The most recent date when a transaction was processed for this location. Set by AvaTax.

ModifiedDate Datetime False

The date/time when this record was last modified.

OutletName String False

A friendly name for this location.

IsRegistered Bool False

Set this flag to true to indicate that this location has been registered with a tax authority.

Line3 String False

The third line of the physical address of this location.

LocationCode String False

A code that identifies this location. Must be unique within your company.

PostalCode String False

The postal code or zip code of the physical address of this location.

Line2 String False

The second line of the physical address of this location.

Line1 String False

The first line of the physical address of this location.

AddressTypeId String False

Indicates whether this location is a physical place of business or a temporary salesperson location.

ModifiedUserId Int False

The user ID of the user who last modified this record.

Country String False

Name or ISO 3166 code identifying the country of the physical address of this location.

City String False

The city of the physical address of this location.

Description String False

A friendly name for this location.

County String False

The county name of the physical address of this location. Not required.

IsDefault Bool False

Set this flag to true to indicate that this is the default location for this company.

EndDate Date False

If this place of business has closed, the date when this location closed business.

LinkedSettings String False

Extra information required by certain jurisdictions for filing.

CreatedDate Datetime False

The date when this record was created.

PageKey String False

CData Python Connector for Avalara

MultiDocument

MultiDocument table for AvalaraAvatax data provider.

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this MultiDocument object.

Code [KEY] String False

The transaction code of the MultiDocument transaction. All individual transactions within this MultiDocument object will have this code as a prefix.

Type [KEY] String False

Indicates the type of MultiDocument transaction.

ModifiedUserId Int False

The user ID of the user who last modified this record.

CreatedUserId Int False

The user ID of the user who created this record.

ModifiedDate Datetime False

The date/time when this record was last modified.

AccountId Int False

The unique ID number of the AvaTax customer account that created this MultiDocument object.

LinkedDocuments String False

A separate document will exist for each unique combination of buyer and seller in this MultiDocument transaction.

CreatedDate Datetime False

The date/time when this record was created.

CData Python Connector for Avalara

Nexus

Nexus table for AvalaraAvatax data provider.

Insert

To create a nexus declaration for your company, you must first obtain a list of Avalara-defined nexus querying NexusDefinitions table. Once you have determined which nexus you wish to declare, you should customize only the user-selectable fields in this object. The user selectable fields for the nexus object are CompanyId, EffectiveDate, EndDate, LocalNexusTypeId, TaxId, NexusTypeId, HasPermanentEstablishment, and IsSellerImporterOfRecord. When calling CreateNexus or UpdateNexus, all values in your nexus object except for the user-selectable fields must match an Avalara-defined system nexus object. If any data does not match, AvaTax may not recognize your nexus declaration. To create a Nexus you must specify Country, Region, JurisdictionTypeId, JurisCode, JurisName, ShortName, NexusTaxTypeGroup of an existing Avalara-defined system nexus object and optionally any other selectable field.

INSERT INTO Nexus (CompanyId, Country, Region, JurisdictionTypeId, JurisCode, JurisName, ShortName, NexusTaxTypeGroup, EffectiveDate) VALUES (283040, 'US', 'US', 'Country', 'US', 'UNITED STATES', 'UNITED STATES', 'Hospitality', '2019-11-08')

Update

Only user selectable fields can be updated. To update a nexus object, you need to specify Id and CompanyId in WHERE clause.

UPDATE Nexus SET HasPermanentEstablishment = true WHERE Id = 20684351 AND CompanyId = 283040

Delete

To delete a nexus object, you need to specify Id and CompanyId in WHERE clause.

DELETE FROM Nexus WHERE Id = 20684351 AND CompanyId = 283040

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this declaration of nexus.

CompanyId [KEY] Int False

The unique ID number of the company that declared nexus.

TaxAuthorityId Int False

A unique ID number of the tax authority that is associated with this nexus.

IsSellerImporterOfRecord Bool False

For nexus declarations at the country level, specifies whether this company is considered the importer of record in this nexus region. Set this value to `true` to consider your company as the importer of record and collect these taxes. Leave this value as false or null and taxes will be calculated as if your company is not the importer of record.

StateAssignedNo String False

The state assigned number of this jurisdiction.

Sourcing String False

Indicates whether this nexus is defined as origin or destination nexus.

JurisName String False

The common name of the jurisdiction in which this company declared nexus.

TaxId String False

Optional - the tax identification number under which you declared nexus.

JurisCode String False

The code identifying the jurisdiction in which this company declared nexus.

EffectiveDate Date False

The date when this nexus began. If not known, set to null.

CreatedUserId Int False

The User ID of the user who created this record.

Region String False

Name or ISO 3166 code identifying the region within the country.

ModifiedDate Datetime False

The date/time when this record was last modified.

NexusTaxTypeGroup String False

The type of nexus that this company is declaring. Replaces NexusTypeId.

ShortName String False

The short name of the jurisdiction.

IsSSTActive Bool False

For the United States, this flag indicates whether this particular nexus falls within a U.S.

JurisdictionTypeId String False

The type of the jurisdiction in which this company declared nexus.

HasLocalNexus Bool False

True if you are also declaring local nexus within this jurisdiction. Many U.S. states have options for declaring nexus in local jurisdictions as well as within the state.

ModifiedUserId Int False

The user ID of the user who last modified this record.

Country String False

Name or ISO 3166 code identifying the country in which this company declared nexus.

HasPermanentEstablishment Bool False

Set this value to true if your company has a permanent establishment within this jurisdiction.

NexusTypeId String False

The type of nexus that this company is declaring.

EndDate Date False

If this nexus will end or has ended on a specific date, set this to the date when this nexus ends.

LocalNexusTypeId String False

If you are declaring local nexus within this jurisdiction, this indicates whether you are declaring only a specified list of local jurisdictions, all state-administered local jurisdictions, or all local jurisdictions.

SignatureCode String False

The signature code of the boundary region as defined by Avalara.

CreatedDate Datetime False

The date when this record was created.

PageKey String False

Nexus table for AvalaraAvatax data provider.

Insert

To create a nexus declaration for your company, you must first obtain a list of Avalara-defined nexus querying NexusDefinitions table. Once you have determined which nexus you wish to declare, you should customize only the user-selectable fields in this object. The user selectable fields for the nexus object are CompanyId, EffectiveDate, EndDate, LocalNexusTypeId, TaxId, NexusTypeId, HasPermanentEstablishment, and IsSellerImporterOfRecord. When calling CreateNexus or UpdateNexus, all values in your nexus object except for the user-selectable fields must match an Avalara-defined system nexus object. If any data does not match, AvaTax may not recognize your nexus declaration. To create a Nexus you must specify Country, Region, JurisdictionTypeId, JurisCode, JurisName, ShortName, NexusTaxTypeGroup of an existing Avalara-defined system nexus object and optionally any other selectable field.

INSERT INTO Nexus (CompanyId, Country, Region, JurisdictionTypeId, JurisCode, JurisName, ShortName, NexusTaxTypeGroup, EffectiveDate) VALUES (283040, 'US', 'US', 'Country', 'US', 'UNITED STATES', 'UNITED STATES', 'Hospitality', '2019-11-08')

Update

Only user selectable fields can be updated. To update a nexus object, you need to specify Id and CompanyId in WHERE clause.

UPDATE Nexus SET HasPermanentEstablishment = true WHERE Id = 20684351 AND CompanyId = 283040

Delete

To delete a nexus object, you need to specify Id and CompanyId in WHERE clause.

DELETE FROM Nexus WHERE Id = 20684351 AND CompanyId = 283040

Columns

Name Type Description
Id [KEY] Int The unique ID number of this declaration of nexus.
TaxAuthorityId Int A unique ID number of the tax authority that is associated with this nexus.
IsSellerImporterOfRecord Bool For nexus declarations at the country level, specifies whether this company is considered the importer of record in this nexus region. Set this value to `true` to consider your company as the importer of record and collect these taxes. Leave this value as false or null and taxes will be calculated as if your company is not the importer of record.
StateAssignedNo String The state assigned number of this jurisdiction.
Sourcing String Indicates whether this nexus is defined as origin or destination nexus.
JurisName String The common name of the jurisdiction in which this company declared nexus.
TaxId String Optional - the tax identification number under which you declared nexus.
JurisCode String The code identifying the jurisdiction in which this company declared nexus.
EffectiveDate Date The date when this nexus began. If not known, set to null.
CreatedUserId Int The User ID of the user who created this record.
Region String Name or ISO 3166 code identifying the region within the country.
ModifiedDate Datetime The date/time when this record was last modified.
NexusTaxTypeGroup String The type of nexus that this company is declaring. Replaces NexusTypeId.
ShortName String The short name of the jurisdiction.
IsSSTActive Bool For the United States, this flag indicates whether this particular nexus falls within a U.S.
JurisdictionTypeId String The type of the jurisdiction in which this company declared nexus.
HasLocalNexus Bool True if you are also declaring local nexus within this jurisdiction. Many U.S. states have options for declaring nexus in local jurisdictions as well as within the state.
ModifiedUserId Int The user ID of the user who last modified this record.
Country String Name or ISO 3166 code identifying the country in which this company declared nexus.
HasPermanentEstablishment Bool Set this value to true if your company has a permanent establishment within this jurisdiction.
NexusTypeId String The type of nexus that this company is declaring.
EndDate Date If this nexus will end or has ended on a specific date, set this to the date when this nexus ends.
LocalNexusTypeId String If you are declaring local nexus within this jurisdiction, this indicates whether you are declaring only a specified list of local jurisdictions, all state-administered local jurisdictions, or all local jurisdictions.
SignatureCode String The signature code of the boundary region as defined by Avalara.
CreatedDate Datetime The date when this record was created.
PageKey String

Pseudo-Columns

Pseudo column fields are used in the WHERE clause of SELECT statements and offer more granular control over the data returned from the data source.

Name Type Description
Rows@Next String Identifier for the next page of results. Do not set this value manually.

CData Python Connector for Avalara

Notices

Notices table for AvalaraAvatax data provider.

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this notice.

CompanyId [KEY] Int False

The unique ID number of the company to which this notice belongs.

TicketReferenceNo String False

The ticket reference number of the notice.

ExpectedResolutionDate Datetime False

Expected resolution date of the notice.

ShowResolutionDateToCustomer Bool False

Indicator to show customer this resolution date.

ClosedDate Datetime False

The closed date of the notice.

FilingFrequency String False

The filing frequency of the notice.

LinkedComments String False

Additional comments on the notice.

CustomerTypeId String False

NoticeCustomerTypeID can be retrieved from the definitions API.

ReceivedDate Datetime False

The received date of the notice.

PriorityId String False

The priority of the notice.

TypeId Int False

The tax notice type id.

JurisdictionType String False

The jurisdiction type of the notice.

SalesForceCaseUrl String False

The URL to the sales force case.

Description String False

The description of the notice.

Reason String False

The notice reason.

TaxPeriod String False

The tax period of the notice.

CreatedDate Datetime False

The date when this record was created.

TotalRemit String False

The total remmitance amount for the notice.

CreatedUserId Int False

The User ID of the user who created this record.

StatusId Int False

The status id of the notice.

ModifiedDate Datetime False

The date/time when this record was last modified.

JurisdictionName String False

The jurisdiction name of the notice.

FilingTypeId String False

The filing type of the notice.

ComplianceContactId Int False

The id of the compliance contact.

Status String False

The status of the notice.

TaxAuthorityId Int False

The tax authority id of the notice.

CustomerComment String False

Comments from the customer on this notice.

TaxFormCode String False

The tax form code of the notice.

RevenueContactId Int False

The id of the revenue contact.

DocumentReference String False

The document reference of the notice.

ReasonId Int False

The notice reason id.

LinkedRootCause String False

Notice Root Cause Details.

ClosedByUserId Int False

The unique ID number of the user that closed the notice.

Country String False

Name or ISO 3166 code identifying the country that sent this notice.

TicketReferenceUrl String False

The ticket reference url of the notice.

CreatedByUserName String False

The user who created the notice.

OwnedByUserId Int False

The unique ID number of the user that owns the notice.

HideFromCustomer Bool False

Indicator to hide from customer.

LinkedResponsibility String False

Notice Responsibility Details.

ModifiedUserId Int False

The user ID of the user who last modified this record.

Region String False

Name or ISO 3166 code identifying the region within the country that sent this notice.

CustomerFundingOptionId String False

The notice customer funding options.

AvaFileFormId Int False

The ava file form id of the notice.

SalesForceCase String False

The sales force case of the notice.

LinkedFinances String False

Finance details of the notice.

Type String False

The tax notice type description.

PageKey String False

CData Python Connector for Avalara

Notifications

Notifications table for AvalaraAvatax data provider.

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique id of the notification.

CompanyId Int False

If this notification was tied to a specific company, this will be the unique ID number of the company that received the notification.

CreatedUserId Int False

The unique ID number of the user who created the notification.

ActionDueDate Datetime False

If there is a specific action suggested by this notification, and if this action is requested by a specific due date, this value will be the due date for the action.

ActionName String False

If there is a specific action suggested by this notification, this is the name of the action.

ReferenceObject String False

The type name of object referred to by this notification, if any.

Dismissed Bool False

Wether the notification is dismissed.

ModifiedDate Datetime False

The UTC timestamp of the time when this notification was last modified.

ReferenceId Int False

The unique reference Id number of the object referred to by this notification, if any.

Message String False

The message for this notification. This is a friendly description of the notification and any relevant information that can help you decide what kind of action, if any, to take in response.

ActionLink String False

If there is a specific action suggested by this notification, this is the URL of the action.

DismissedDate Datetime False

If this notification has been dismissed, this indicates the timestamp (in UTC time) when the user dismissed the notification.

ModifiedUserId Int False

The unique ID number of the user who most recently modified this notification.

ExpireDate Datetime False

If this notification is time sensitive, this is the latest date when the notification should be displayed to the user.

NeedsAction Bool False

If this notification object requires user action to resolve, this value will be set to true.

DismissedByUserId Int False

If this notification has been dismissed, this indicates the unique ID number of the user that dismissed the notification.

Category String False

The category of this notification.

Topic String False

The topic of this notification.

AccountId Int False

The unique ID number of the account that received this notification.

CreatedDate Datetime False

The UTC timestamp of the time when this notification was created.

SeverityLevelId String False

The severity level of the notification.

PageKey String False

CData Python Connector for Avalara

Settings

Settings table for AvalaraAvatax data provider.

The company settings system is a metadata system that you can use to store extra information about a company. Your integration or connector could use this data storage to keep track of preference information, reminders, or any other storage that would need to persist even if the customer uninstalls your application.

Insert

A setting can refer to any type of data you need to remember about this company object. When creating this object, you may define your own set, name, and value parameters. To define your own values, please choose a set name that begins with X- to indicate an extension. CompanyId, Set and Name are required fields.

INSERT INTO Settings (CompanyId, Set, Name) VALUES (283040, 'ItemsToRemember', 'Texas')

Update

To update a setting, you need to specify Id and CompanyId in WHERE clause.

UPDATE Settings SET Value = 'Alamo' WHERE Id = 297847 AND CompanyId = 283040

Delete

To delete a setting, you need to specify Id and CompanyId in WHERE clause.

DELETE FROM Settings WHERE Id = 297847 AND CompanyId = 283040

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this setting.

CompanyId [KEY] Int False

The unique ID number of the company this setting refers to.

Name String False

A user-defined name for this name-value pair.

Value String False

The value of this name-value pair.

Set String False

A user-defined set containing this setting.

PageKey String False

CData Python Connector for Avalara

TaxCodes

TaxCodes table for AvalaraAvatax data provider.

Insert

Create one or more new taxcode objects attached to a company specifying at least CompanyId, TaxCode, TaxCodeTypeId:

INSERT INTO TaxCodes (TaxCode, taxCodeTypeId, CompanyId) VALUES ('PS081283', 'P', '283040')

Update

Avalara allows one of the following user roles: AccountAdmin, CompanyAdmin, CSPTester, SSTAdmin, TechnicalSupportAdmin to update TaxCode objects. CompanyId and Id should be specified in the WHERE clause.

UPDATE TaxCodes SET Description = 'Yarn' WHERE Id = 85083 AND CompanyId = 283040

Delete

To delete a TaxCode object CompanyId and Id should be specified in the WHERE clause:

DELETE FROM TaxCodes WHERE Id = 85083 AND CompanyId = 283040

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this tax code.

CompanyId [KEY] Int False

The unique ID number of the company that owns this tax code.

ModifiedUserId Int False

The user ID of the user who last modified this record.

CreatedUserId Int False

The User ID of the user who created this record.

EntityUseCode String False

The Avalara Entity Use Code represented by this tax code.

ModifiedDate Datetime False

The date/time when this record was last modified.

TaxCodeTypeId String False

The type of this tax code.

GoodsServiceCode Int False

The Avalara Goods and Service Code represented by this tax code.

IsSSTCertified Bool False

True if this tax code has been certified by the Streamlined Sales Tax governing board.

TaxCode String False

A code string that identifies this tax code.

Description String False

A friendly description of this tax code.

IsPhysical Bool False

True if this tax code type refers to a physical object. Read only field.

IsActive Bool False

True if this tax code is active and can be used in transactions.

CreatedDate Datetime False

The date when this record was created.

PageKey String False

CData Python Connector for Avalara

TaxRules

TaxRules table for AvalaraAvatax data provider.

Insert

You can create custom tax rules to customize the behavior of AvaTax to match specific rules that are custom to your business. If you have obtained a ruling from a tax auditor that requires custom tax calculations, you can use custom tax rules to redefine the behavior for your company or item.

INSERT INTO TaxRules (CompanyId, JurisCode, JurisName, JurisdictionTypeId, TaxRuleTypeId, Country, TaxTypeId, TaxCode, TaxCodeId, TaxTypeGroup, TaxSubType) VALUES ('283040', '013', 'MARICOPA', 'County', 'ProductTaxabilityRule', 'US', 'BothSalesAndUseTax', 'PS081283', '85083', 'SalesAndUse', 'ALL')

Update

To update a tax rule, you need to specify Id and CompanyId in WHERE clause.

UPDATE TaxRules SET Description = 'Freight' WHERE Id = 56789 AND CompanyId = 247015

Delete

To delete a tax rule, you need to specify Id and AccountId in WHERE clause.

DELETE FROM TaxRules WHERE Id = 56789 AND CompanyId = 247015

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this tax rule.

CompanyId [KEY] Int False

The unique ID number of the company that owns this tax rule.

UomId Int False

For tax rules that are calculated using units of measurement, this indicates the unit of measurement type used to calculate the amounts for this rule.

Threshold String False

The per-unit threshold that must be met before this rule applies.

TaxRuleTypeId String False

This type value determines the behavior of the tax rule.

JurisCode String False

The code of the jurisdiction to which this tax rule applies.

EntityUseCode String False

The entity use code to which this rule applies.

NonPassthroughExpression String False

Reserved for Avalara internal usage. Leave this field null.

Description String False

A friendly name for this tax rule.

CreatedDate Datetime False

The date when this record was created.

CountyFIPS String False

For U.S. tax rules, this is the county's Federal Information Processing Standard (FIPS) code.

CreatedUserId Int False

The User ID of the user who created this record.

EndDate Date False

The last date for which this rule applies. If `null`, this rule will apply to all dates after the effective date.

TaxSubType String False

This field has different behavior based on the type of rule. For a product taxability rule, if the rule applies to an item, this value will override the tax sub type of the original product. For other rules, this value determines what tax sub types will be affected by the rule.

ModifiedDate Datetime False

The date/time when this record was last modified.

TaxCode String False

For rules that apply to a specific tax code only, this specifies which tax code is affected by this rule.

Options String False

Supports custom options for your tax rule.

JurisName String False

The name of the jurisdiction to which this tax rule applies.

TaxTypeGroup String False

This field has different behavior based on the type of rule. For a product taxability rule, if the rule applies to an item, this value will override the tax type group of the original product. For other rules, this value determines what tax type groups will be affected by the rule.

JurisdictionTypeId String False

The type of the jurisdiction to which this tax rule applies.

Cap String False

The maximum cap for the price of this item according to this rule. Any amount above this cap will not be subject to this rule.

Country String False

Name or ISO 3166 code identifying the country where this rule will apply.

Value String False

This field has different behavior based on the type of the tax rule. For a product taxability rule, this value is either 1 or 0, indicating taxable or non-taxable. For a rate override rule, this value is the corrected rate stored as a decimal, for example, a rate of 5% would be stored as 0.05 decimal. If you use the special value of 1.0, only the cap and threshold values will be applied and the rate will be left alone.

PreferredProgramId Int False

Reserved for Avalara internal usage. Leave this field null.

CurrencyCode String False

The currency code to use for this rule.

EffectiveDate Date False

The first date at which this rule applies. If `null`, this rule will apply to all dates prior to the end date.

StateFIPS String False

For U.S. tax rules, this is the state's Federal Information Processing Standard (FIPS) code.

RateTypeCode String False

Indicates the code of the rate type that applies to this rule.

ModifiedUserId Int False

The user ID of the user who last modified this record.

Region String False

Name or ISO 3166 code identifying the region where this rule will apply.

TaxTypeId String False

Some tax type groups contain multiple different types of tax. To create a rule that affects only one type of tax within a tax type group, set this value to the code matching the specific tax type within that group.

Sourcing String False

The sourcing types to which this rule applies.

TaxCodeId Int False

For rules that apply to a specific tax code only, this specifies which tax code is affected by this rule.

IsAllJuris Bool False

Allows you to make tax rules apply to lower jurisdictions. This feature is only available in the United States and Canada.

PageKey String False

CData Python Connector for Avalara

TransactionLines

TransactionLines view for AvalaraAvatax data provider.

Select

The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. The rest of the filter is executed client side within the connector. By default the lines of Adjusted transactions will not be listed. If you want to include them, you need to set IncludeAdjustedTransactions to true.

  • TrsnactionId, TransactionCode support the '=', IN operator.

For example, the following query is processed server side:

SELECT * FROM TransactionLines WHERE TransactionCode IN ('Code1', 'Code2')

Delete

To delete a TransactionLine item, you need to specify the TransactionCode and LineNumber in the WHERE clause.

DELETE FROM TransactionLines WHERE TransactionCode = 'TC001' AND LineNumber = 1

Columns

Name Type ReadOnly Description
Id Long False

The unique ID number of this transaction line item.

TransactionId Long False

The unique ID number of the transaction to which this line item belongs.

TransactionStatus String False

The status of the transaction to which this line item belongs.

TransactionCode [KEY] String False

A unique customer-provided code identifying this transaction.

DestinationAddressId Long False

The unique ID number of the destination address where this line was delivered or sold. In the case of a point-of-sale transaction, the destination address and origin address will be the same. In the case of a shipped transaction, they will be different.

TaxCalculated String False

The amount of tax that AvaTax calculated for the transaction.

DiscountAmount String False

The amount of discount that was applied to this line item.

HsCode String False

The cross-border harmonized system code (HSCode) used to calculate tariffs and duties for this line item.

DiscountTypeId Int False

The type of discount, if any, that was applied to this line item.

TaxableAmount String False

The taxable amount of this line item.

CostInsuranceFreight String False

Indicates the cost of insurance and freight for this line.

CertificateId String False

The CertCapture Certificate ID

TaxDate Date False

The date that was used for calculating tax amounts for this line item.

Ref2 String False

A user-defined reference identifier for this transaction line item.

EntityUseCode String False

The entity use code for this line item. Usage type often affects taxability rules.

Description String False

A description of the item or service represented by this line.

Ref1 String False

A user-defined reference identifier for this transaction line item.

ExemptNo String False

The customer Tax Id Number (tax_number) associated with a certificate.

Quantity String False

The quantity of products sold on this line item.

TaxCode String False

The code string for the tax code that was used to calculate this line item.

TaxOverrideType String False

If a tax override was specified, this indicates the type of tax override.

LineNumber [KEY] String False

The line number or code indicating the line on this invoice or receipt or document.

BusinessIdentificationNo String False

VAT business identification number used for this transaction.

ReportingDate Date False

The date when this transaction should be reported. By default, all transactions are reported on the date when the actual transaction took place. In some cases, line items may be reported later due to delayed shipments or other business reasons.

VatNumberTypeId Int False

Indicates the VAT number type for this line item.

VatCode String False

Indicates the VAT code for this line item.

LineAmount String False

The total amount of the transaction, including both taxable and exempt.

Tax String False

The tax for this line in this transaction.

LinkedLineLocationTypes String False

Optional: A list of location types for this line item.

IsItemTaxable Bool False

True if this item is taxable.

TaxOverrideAmount String False

If a tax override was specified, this indicates the amount of tax that was requested.

ExemptCertId Int False

The unique ID number of the exemption certificate that applied to this line item. It is the calc_id associated with a certificate in CertCapture.

ItemCode String False

The code string of the item represented by this line item.

BoundaryOverrideId Int False

The unique ID number of the boundary override applied to this line item.

OriginAddressId Long False

The unique ID number of the origin address where this line was delivered or sold.

TaxOverrideReason String False

If a tax override was specified, represents the reason for the tax override.

ExemptAmount String False

The amount of this line item that was exempt.

TaxIncluded Bool False

Indicates whether the amount for this line already includes tax.

IsSSTP Bool False

True if this item is a Streamlined Sales Tax line item.

Sourcing String False

Indicates whether this line item was taxed according to the origin or destination.

TaxEngine String False

The tax engine identifier that was used to calculate this line item.

TaxCodeId Int False

The unique ID number for the tax code that was used to calculate this line item.

RevAccount String False

The revenue account number for this line item.

CompanyCode String False

The code of the company that recorded this transaction.

CData Python Connector for Avalara

Transactions

Transactions table for AvalaraAvatax data provider.

Select

The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. Most of the columns support server side filtering with the following operators: =,>,<,<=,>=,IN,NOT,IN,AND,OR,LIKE. The rest of the filter is executed client side within the connector. By default the Adjusted transactions will not be listed. If you want to include them, you need to set IncludeAdjustedTransactions to true. For example, the following query is processed server side:

SELECT * FROM Transactions WHERE AdjustmentReason = 'PriceAdjusted'
SELECT * FROM Items WHERE Status = 'Cancelled'

Insert

To add a new Transaction item, the following columns need to be specified: CustomerCode, Date, Type, LinkedLines, Code, LinkedAddresses. If you want to commit the transaction, set the Commit flag in the request to true. The linked columns can be inserted using a #TEMP table or by passing the aggregate value.

The LinkedAddresses aggregate must include information about the origin and destination address. If this transaction occurred at a retail point-of-sale location, provide that single address here and leave all other address types null. If origin differs from destination, insert both ShipFrom and ShipTo address types. If you wish to use the address of an existing location for the actual company, specify the address in the addressType_locationCode field.

The examples below illustrate the aforementioned scenarios.

Inserting LinkedAddresses aggregate through #TEMP table with SingleLocation:

INSERT INTO Addresses#TEMP (SingleLocation_line1, SingleLocation_City, SingleLocation_County, SingleLocation_PostalCode) VALUES ('2000 Main Street', 'Irvine', 'US', '92614')")
INSERT INTO Addresses#TEMP (SingleLocation_locationCode) VALUES ('LC001')")

Inserting LinkedAddresses aggregate through #TEMP table with ShipFrom and ShipTo locations:

INSERT INTO Addresses#TEMP (shipTo_line1, shipTo_City, shipTo_County, shipTo_PostalCode, shipFrom_line1, shipFrom_City, shipFrom_Country, shipFrom_PostalCode) VALUES ('2000 Main Street', 'Irvine', 'US', '92614', '', '', 'US', '')")
INSERT INTO Addresses#TEMP (shipTo_locationCode, shipFrom_locationCode) VALUES ('LC001', 'LC002')")

Insert line items aggregate using #TEMP table. For a list of the columns you can insert into the temporary table, refer to TransactionLines table.

INSERT INTO TransactionLines#TEMP (ItemCode, Quantity, LineAmount) VALUES ('IC005', 3, 300)")

Insert into the main Transactions table :

INSERT INTO Transactions (LinkedLines, LinkedAddresses, Code, CompanyId, CustomerCode, Date, Type, Commit, TotalTax) VALUES (TransactionLines#TEMP, Addresses#TEMP, DC008, 247015, 'CC002', '09/30/2019', 'SalesInvoice', true, 12.0)")

Update

Avalara allows updates on Transactions. To update a transaction, AdjustmentReason and Adjustment description are required fields. Additionally, you need to specify the Code of the transaction you are updating in the WHERE clause.

Similarly, to Insert, you can update line items using temporary tables. To update an existing line, include the LineNumber of the line you wish to update. To insert a new line in the transaction, set the LineNumber to a new, non-existing value.

When a transaction is updated, the actual transaction's status changes to Adjusted and a new transaction with the updated information is created. The new transaction will have the same document code, but a different id and status: Saved or Commited. If you wish to commit the new updated transaction, set the Commit flag in the request to true.

INSERT INTO TransactionLines#TEMP (ItemCode, Quantity, LineAmount, LineNumber) VALUES (IC007, 3, 300, 3)
UPDATE Transactions SET LinkedLines = 'TransactionLines#TEMP', AdjustmentDescription = 'MyDescription', AdjustmentReason = 'PriceAdjusted' WHERE Code = '051349'

Columns

Name Type ReadOnly Description
Id Long False

The unique ID number of this transaction.

Code [KEY] String False

A unique customer-provided code identifying this transaction.

CompanyId Int False

The unique ID number of the company that recorded this transaction.

ExchangeRateEffectiveDate Date False

If this transaction included foreign currency exchange, this is the date as of which the exchange rate was calculated.

SalespersonCode String False

The salesperson who provided this transaction. Not required.

AdjustmentDescription String False

If this transaction was adjusted, indicates a description of the reason why the transaction was adjusted.

DestinationAddressId Long False

The unique ID number of the destination address for this transaction.

LinkedLocationTypes String False

A list of location types in this transaction.

IsSellerImporterOfRecord Bool False

By default, the value is null, when the value is null, the value can be set at nexus level and used. If the value is not null, it will override the value at nexus level. If true, this seller was considered the importer of record of a product shipped internationally.

BatchCode String False

If this transaction was created as part of a batch, this code indicates which batch.

LinkedTaxDetailsByTaxType String False

Contains the tax details per tax type

TaxDate Datetime False

Tax date for this transaction

EntityUseCode String False

The entity use code for this transaction. Entity use codes often affect exemption or taxability rules.

LinkedInvoiceMessages String False

Invoice messages associated with this transaction. Currently, this stores legally-required VAT messages.

Description String False

Description of this transaction. Field permits unicode values.

LinkedAddresses String False

A list of addreses used in this transaction.

TotalTax String False

The total tax for all lines in this transaction.

LinkedMessages String False

List of informational and warning messages regarding this API call. These messages are only relevant to the current API call.

ExemptNo String False

The customer Tax Id Number (tax_number) associated with a certificate.

TotalTaxable String False

The portion of the total amount of this transaction that was taxable.

ModifiedDate Datetime False

The date/time when this record was last modified.

Email String False

Email address associated with this transaction.

TaxOverrideType String False

If a tax override was applied to this transaction, indicates what type of tax override was applied.

BusinessIdentificationNo String False

VAT business identification number used for this transaction.

ReportingLocationCode String False

For customers who use location-based tax reporting, this field controls how this transaction will be filed for multi-location tax filings.

TotalTaxCalculated String False

The amount of tax that AvaTax calculated for the transaction.

ExchangeRate String False

If this transaction included foreign currency exchange, this is the exchange rate that was used.

CustomerCode String False

Unique code identifying the customer that requested this transaction.

Locked Bool False

If this transaction has been reported to a tax authority, this transaction is considered locked and may not be adjusted after reporting.

Status String False

The status of the transaction.

TotalAmount String False

The total amount of this transaction.

LinkedLines String False

A list of line items in this transaction.

TotalDiscount String False

The total amount of discounts applied to all lines within this transaction.

AdjustmentReason String False

If this transaction was adjusted, indicates the unique ID number of the reason why the transaction was adjusted.

TaxOverrideAmount String False

If a tax override was applied to this transaction, indicates the amount of tax that was requested by the customer.

SoftwareVersion String False

The software version used to calculate this transaction.

Country String False

The two-character ISO 3166 code of the country for this transaction.

CurrencyCode String False

The three-character ISO 4217 currency code that was used for payment for this transaction.

OriginAddressId Long False

The unique ID number of the origin address for this transaction.

TotalExempt String False

The amount of this transaction that was exempt.

PurchaseOrderNo String False

The customer-supplied purchase order number of this transaction.

TaxOverrideReason String False

If a tax override was applied to this transaction, indicates the reason for the tax override.

TaxOverrideDate Date False

The override tax date to use

LinkedParameters String False

Contains a list of extra parameters that were set when the transaction was created.

LinkedSummary String False

Contains a summary of tax on this transaction.

Version Int False

If this transaction was adjusted, this indicates the version number of this transaction. Incremented each time the transaction is adjusted.

Date Date False

The date on which this transaction occurred.

ModifiedUserId Int False

The user ID of the user who last modified this record.

Region String False

The two-or-three character ISO region code of the region for this transaction.

ReferenceCode String False

A user-defined reference code for this transaction.

Reconciled Bool False

If this transaction has been reconciled against the company's ledger, this value is set to true.

Type [KEY] String False

The type of the transaction.

Commit Boolean False

Wether to commit a transaction on creation. Used only on inserts

CompanyCode String False

The code of the company that recorded this transaction.

CData Python Connector for Avalara

Upcs

Upcs table for AvalaraAvatax data provider.

A UPC represents a single Universal Product Code in your catalog and matches this product to the tax code identified by this UPC.

Insert

To create a UPC object CompanyId, Upc and Description are required fields.

INSERT INTO Upcs (CompanyId, Upc, Description) VALUES (283040, '023032550992', 'Yarn')

Update

To update a Upc, you need to specify Id and CompanyId in WHERE clause.

UPDATE Upcs SET LegacyTaxCode = 'PS081282' WHERE Id = 123456789 AND CompanyId = 283040

Delete

To delete a Upc, you need to specify Id and CompanyId in WHERE clause.

DELETE FROM Upcs WHERE Id = 123456789 AND CompanyId = 283040

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number for this UPC.

CompanyId [KEY] Int False

The unique ID number of the company to which this UPC belongs.

ModifiedUserId Int False

The user ID of the user who last modified this record.

CreatedUserId Int False

The User ID of the user who created this record.

Upc String False

The 12-14 character Universal Product Code, European Article Number, or Global Trade Identification Number.

ModifiedDate Datetime False

The date/time when this record was last modified.

EndDate Date False

If this UPC expired or will expire on a certain date, this contains the last date on which the UPC was effective.

LegacyTaxCode String False

Legacy Tax Code applied to any product sold with this UPC.

Usage Int False

A usage identifier for this UPC code.

IsSystem Int False

A flag indicating whether this UPC code is attached to the AvaTax system or to a company.

EffectiveDate Date False

If this UPC became effective on a certain date, this contains the first date on which the UPC was effective.

Description String False

Description of the product to which this UPC applies.

CreatedDate Datetime False

The date when this record was created.

PageKey String False

CData Python Connector for Avalara

Users

Users table for AvalaraAvatax data provider.

Insert

To create a new user the following fields should be specified. A newly created user will receive an email inviting them to create their password. This means that you must provide a valid email address for all user accounts created.

INSERT INTO Users (AccountId, UserName, FirstName, LastName, Email, securityRoleId) VALUES (2000137504, 'user123', 'James', 'Smith', 'smith@gmail.com', 'AccountUser')

Update

Only user selectable fields can be updated. To update a user, you need to specify Id and AccountId in WHERE clause.

UPDATE Users SET IsActive = true WHERE Id = 332668 AND AccountId = 2000137504

Delete

To delete a user, you need to specify Id and AccountId in WHERE clause.

DELETE FROM Users WHERE Id = 332668 AND AccountId = 2000137504

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this user.

AccountId [KEY] Int False

The unique ID number of the account to which this user belongs.

PostalCode String False

The postal code in which this user resides.

SecurityRoleId String False

The security level for this user.

ModifiedDate Datetime False

The date/time when this record was last modified.

PasswordStatus String False

The status of the user's password. For a new user created, this is always going to be `UserMustChange`.

Email String False

The email address to be used to contact this user. If the user has forgotten a password, an email can be sent to this email address with information on how to reset this password.

UserName String False

The username which is used to log on to the AvaTax website, or to authenticate against API calls.

CompanyId Int False

If this user is locked to one company (and its children), this is the unique ID number of the company to which this user belongs.

FirstName String False

The first or given name of the user.

LastName String False

The last or family name of the user.

IsActive Bool False

True if this user is currently active.

CreatedDate Datetime False

The date when this record was created.

PageKey String False

CData Python Connector for Avalara

Views

Views are similar to tables in the way that data is represented; however, views are read-only.

Queries can be executed against a view as if it were a normal table.

CData Python Connector for Avalara Views

Name Description
BatchFiles BatchFiles view for AvalaraAvatax data provider.
CustomerCustomFields CustomerCustomFields view for AvalaraAvatax data provider.
CustomerExposureZones CustomerExposureZones view for AvalaraAvatax data provider.
FilingCalendarAvailablePOA FilingCalendarAvailablePOA view for AvalaraAvatax data provider.
ItemClassifications ItemClassifications view for AvalaraAvatax data provider.
ItemParameters ItemParameters view for AvalaraAvatax data provider.
LocationSettings LocationSettings view for AvalaraAvatax data provider.
Nexus Nexus table for AvalaraAvatax data provider.
NoticeComments NoticeComments view for AvalaraAvatax data provider.
NoticeFinances NoticeFinances view for AvalaraAvatax data provider.
NoticeResponsibility NoticeResponsibility view for AvalaraAvatax data provider.
NoticeRootCause NoticeRootCause view for AvalaraAvatax data provider.
PostalCodes PostalCodes view for the Avalara Avatax data provider.
Regions Regions view for the Avalara Avatax data provider.
ReportParameters ReportParameters view for AvalaraAvatax data provider.
Reports Reports table for AvalaraAvatax data provider.
Subscriptions Subscriptions table for AvalaraAvatax data provider.
TaxRatesByAddress Retrieve real-time estimated tax rates based on an address using the Avalara Avatax data provider.
TaxRatesByZipCode Retrieve estimated tax rates by zip code for a specific date using the Avalara Avatax data provider.
TransactionAddresses TransactionAddresses view for AvalaraAvatax data provider.
TransactionInvoiceMessages TransactionInvoicemessages view for AvalaraAvatax data provider.
TransactionLocationTypes TransactionLocationTypes view for AvalaraAvatax data provider.
TransactionMessages TransactionMessages view for AvalaraAvatax data provider.
TransactionParameters TransactionParameters view for AvalaraAvatax data provider.
TransactionSummary TransactionSummary view for AvalaraAvatax data provider.
TransactionTaxDetailsByTaxType TransactionTaxdetailsbytaxtype view for AvalaraAvatax data provider.

CData Python Connector for Avalara

BatchFiles

BatchFiles view for AvalaraAvatax data provider.

Columns

Name Type Description
Id [KEY] Int The unique ID number assigned to this batch file.
BatchId Int The unique ID number of the batch that this file belongs to.
CompanyId [KEY] Int The Company ID number of the company that owns this batch.
Name String Logical Name of file.
ContentLength Int Size of content, in bytes.
FilePath String Path to the file - name/S3 key.
FileExtension String File extension (e.g. CSV).
FileLocalPath String Local path of the file.
ErrorCount Int Number of errors that occurred when processing this file.
ContentType String Content mime type (e.g. text/csv). This is used for HTTP downloading.

CData Python Connector for Avalara

CustomerCustomFields

CustomerCustomFields view for AvalaraAvatax data provider.

Select

To retrieve records from CustomerCustomFields view, at least CompanyId or CompanyId and CompanyCode should be specified in the WHERE clause. The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. CompanyId and CompanyCode support server side filtering with the = operator. The rest of the filter is executed client side within the connector. For example, the following query is processed server side:

SELECT * FROM CustomerCustomFields WHERE CompanyId = '247015' AND CustomerCode = 'CC001'

Columns

Name Type Description
CompanyId [KEY] String The company Id of the parent record.
CustomerCode [KEY] String The customer code this record is associated to.
Name String The name of the custom field.
Value String The value of the custom field.

CData Python Connector for Avalara

CustomerExposureZones

CustomerExposureZones view for AvalaraAvatax data provider.

Select

To retrieve records from CustomerExposureZones view, at least CompanyId or CompanyId and CompanyCode should be specified in the WHERE clause. The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. CompanyId and CompanyCode support server side filtering with the = operator. The rest of the filter is executed client side within the connector. For example, the following query is processed server side:

SELECT * FROM CustomerExposureZones WHERE CompanyId = '247015' AND CustomerCode = 'CC001'

Columns

Name Type Description
Id Int A unique ID number representing this exposure zone.
CompanyId [KEY] Int The unique ID number of the AvaTax company that recorded this customer.
CustomerCode [KEY] String The customer code this record is associated to.
Name String The short name of this exposure zone, suitable for use in a drop-down list.
Country String Two character ISO 3166 county code for the country component of this exposure zone.
Created Datetime The date when this record was created.
Region String Two or three character ISO 3166 region, province, or state name of this exposure zone.
Description String A more complete description of this exposure zone, suitable for use as a tooltip or help text.
Modified Datetime The date/time when this record was last modified.
Tag String A tag indicating

CData Python Connector for Avalara

FilingCalendarAvailablePOA

FilingCalendarAvailablePOA view for AvalaraAvatax data provider.

Table Specific Information

Select

To retrieve records from FilingCalendarAvailablePOA table, at least CompanyId should be specified in the Where clause. The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. Most of the columns support server side filtering with the following operators: =,>,<,<=,>=,IN,NOT,IN,AND,OR,LIKE. The rest of the filter is executed client side within the connector. For example, the following query is processed server side:

SELECT * FROM FilingCalendarAvailablePOA WHERE CompanyId = '247015' AND Filename = 'MyFileName'

Columns

Name Type Description
CompanyId [KEY] String Company Id of the parent record.
Bytes String Bytes of the file.
Filename String Original filename.
Success Bool True if this download succeeded.
ContentType String Mime content type.

CData Python Connector for Avalara

ItemClassifications

ItemClassifications view for AvalaraAvatax data provider.

Columns

Name Type Description
CompanyId [KEY] String The CompanyId of the parent record.
ItemId [KEY] String The unique ID number of the item this product belongs to.
SystemCode String The system code in which the product belongs.
ProductCode String The product code of an item in a given system.

CData Python Connector for Avalara

ItemParameters

ItemParameters view for AvalaraAvatax data provider.

Columns

Name Type Description
Id [KEY] Int The id of the parameter.
CompanyId [KEY] String The CompanyId of the parent record.
ItemId [KEY] Int The item id.
Name String The parameter's name.
Unit String The unit of measurement code for the parameter.
Value String The value for the parameter.

CData Python Connector for Avalara

LocationSettings

LocationSettings view for AvalaraAvatax data provider.

Columns

Name Type Description
CompanyId [KEY] String CompanyId of the parent record.
LocationId [KEY] String The LocationId that this setting is associated to.
QuestionId Int The unique ID number of the location question answered.
QuestionName String The name of the question.
Value String The answer the user provided.

CData Python Connector for Avalara

Nexus

Nexus table for AvalaraAvatax data provider.

Insert

To create a nexus declaration for your company, you must first obtain a list of Avalara-defined nexus querying NexusDefinitions table. Once you have determined which nexus you wish to declare, you should customize only the user-selectable fields in this object. The user selectable fields for the nexus object are CompanyId, EffectiveDate, EndDate, LocalNexusTypeId, TaxId, NexusTypeId, HasPermanentEstablishment, and IsSellerImporterOfRecord. When calling CreateNexus or UpdateNexus, all values in your nexus object except for the user-selectable fields must match an Avalara-defined system nexus object. If any data does not match, AvaTax may not recognize your nexus declaration. To create a Nexus you must specify Country, Region, JurisdictionTypeId, JurisCode, JurisName, ShortName, NexusTaxTypeGroup of an existing Avalara-defined system nexus object and optionally any other selectable field.

INSERT INTO Nexus (CompanyId, Country, Region, JurisdictionTypeId, JurisCode, JurisName, ShortName, NexusTaxTypeGroup, EffectiveDate) VALUES (283040, 'US', 'US', 'Country', 'US', 'UNITED STATES', 'UNITED STATES', 'Hospitality', '2019-11-08')

Update

Only user selectable fields can be updated. To update a nexus object, you need to specify Id and CompanyId in WHERE clause.

UPDATE Nexus SET HasPermanentEstablishment = true WHERE Id = 20684351 AND CompanyId = 283040

Delete

To delete a nexus object, you need to specify Id and CompanyId in WHERE clause.

DELETE FROM Nexus WHERE Id = 20684351 AND CompanyId = 283040

Columns

Name Type ReadOnly Description
Id [KEY] Int False

The unique ID number of this declaration of nexus.

CompanyId [KEY] Int False

The unique ID number of the company that declared nexus.

TaxAuthorityId Int False

A unique ID number of the tax authority that is associated with this nexus.

IsSellerImporterOfRecord Bool False

For nexus declarations at the country level, specifies whether this company is considered the importer of record in this nexus region. Set this value to `true` to consider your company as the importer of record and collect these taxes. Leave this value as false or null and taxes will be calculated as if your company is not the importer of record.

StateAssignedNo String False

The state assigned number of this jurisdiction.

Sourcing String False

Indicates whether this nexus is defined as origin or destination nexus.

JurisName String False

The common name of the jurisdiction in which this company declared nexus.

TaxId String False

Optional - the tax identification number under which you declared nexus.

JurisCode String False

The code identifying the jurisdiction in which this company declared nexus.

EffectiveDate Date False

The date when this nexus began. If not known, set to null.

CreatedUserId Int False

The User ID of the user who created this record.

Region String False

Name or ISO 3166 code identifying the region within the country.

ModifiedDate Datetime False

The date/time when this record was last modified.

NexusTaxTypeGroup String False

The type of nexus that this company is declaring. Replaces NexusTypeId.

ShortName String False

The short name of the jurisdiction.

IsSSTActive Bool False

For the United States, this flag indicates whether this particular nexus falls within a U.S.

JurisdictionTypeId String False

The type of the jurisdiction in which this company declared nexus.

HasLocalNexus Bool False

True if you are also declaring local nexus within this jurisdiction. Many U.S. states have options for declaring nexus in local jurisdictions as well as within the state.

ModifiedUserId Int False

The user ID of the user who last modified this record.

Country String False

Name or ISO 3166 code identifying the country in which this company declared nexus.

HasPermanentEstablishment Bool False

Set this value to true if your company has a permanent establishment within this jurisdiction.

NexusTypeId String False

The type of nexus that this company is declaring.

EndDate Date False

If this nexus will end or has ended on a specific date, set this to the date when this nexus ends.

LocalNexusTypeId String False

If you are declaring local nexus within this jurisdiction, this indicates whether you are declaring only a specified list of local jurisdictions, all state-administered local jurisdictions, or all local jurisdictions.

SignatureCode String False

The signature code of the boundary region as defined by Avalara.

CreatedDate Datetime False

The date when this record was created.

PageKey String False

Nexus table for AvalaraAvatax data provider.

Insert

To create a nexus declaration for your company, you must first obtain a list of Avalara-defined nexus querying NexusDefinitions table. Once you have determined which nexus you wish to declare, you should customize only the user-selectable fields in this object. The user selectable fields for the nexus object are CompanyId, EffectiveDate, EndDate, LocalNexusTypeId, TaxId, NexusTypeId, HasPermanentEstablishment, and IsSellerImporterOfRecord. When calling CreateNexus or UpdateNexus, all values in your nexus object except for the user-selectable fields must match an Avalara-defined system nexus object. If any data does not match, AvaTax may not recognize your nexus declaration. To create a Nexus you must specify Country, Region, JurisdictionTypeId, JurisCode, JurisName, ShortName, NexusTaxTypeGroup of an existing Avalara-defined system nexus object and optionally any other selectable field.

INSERT INTO Nexus (CompanyId, Country, Region, JurisdictionTypeId, JurisCode, JurisName, ShortName, NexusTaxTypeGroup, EffectiveDate) VALUES (283040, 'US', 'US', 'Country', 'US', 'UNITED STATES', 'UNITED STATES', 'Hospitality', '2019-11-08')

Update

Only user selectable fields can be updated. To update a nexus object, you need to specify Id and CompanyId in WHERE clause.

UPDATE Nexus SET HasPermanentEstablishment = true WHERE Id = 20684351 AND CompanyId = 283040

Delete

To delete a nexus object, you need to specify Id and CompanyId in WHERE clause.

DELETE FROM Nexus WHERE Id = 20684351 AND CompanyId = 283040

Columns

Name Type Description
Id [KEY] Int The unique ID number of this declaration of nexus.
TaxAuthorityId Int A unique ID number of the tax authority that is associated with this nexus.
IsSellerImporterOfRecord Bool For nexus declarations at the country level, specifies whether this company is considered the importer of record in this nexus region. Set this value to `true` to consider your company as the importer of record and collect these taxes. Leave this value as false or null and taxes will be calculated as if your company is not the importer of record.
StateAssignedNo String The state assigned number of this jurisdiction.
Sourcing String Indicates whether this nexus is defined as origin or destination nexus.
JurisName String The common name of the jurisdiction in which this company declared nexus.
TaxId String Optional - the tax identification number under which you declared nexus.
JurisCode String The code identifying the jurisdiction in which this company declared nexus.
EffectiveDate Date The date when this nexus began. If not known, set to null.
CreatedUserId Int The User ID of the user who created this record.
Region String Name or ISO 3166 code identifying the region within the country.
ModifiedDate Datetime The date/time when this record was last modified.
NexusTaxTypeGroup String The type of nexus that this company is declaring. Replaces NexusTypeId.
ShortName String The short name of the jurisdiction.
IsSSTActive Bool For the United States, this flag indicates whether this particular nexus falls within a U.S.
JurisdictionTypeId String The type of the jurisdiction in which this company declared nexus.
HasLocalNexus Bool True if you are also declaring local nexus within this jurisdiction. Many U.S. states have options for declaring nexus in local jurisdictions as well as within the state.
ModifiedUserId Int The user ID of the user who last modified this record.
Country String Name or ISO 3166 code identifying the country in which this company declared nexus.
HasPermanentEstablishment Bool Set this value to true if your company has a permanent establishment within this jurisdiction.
NexusTypeId String The type of nexus that this company is declaring.
EndDate Date If this nexus will end or has ended on a specific date, set this to the date when this nexus ends.
LocalNexusTypeId String If you are declaring local nexus within this jurisdiction, this indicates whether you are declaring only a specified list of local jurisdictions, all state-administered local jurisdictions, or all local jurisdictions.
SignatureCode String The signature code of the boundary region as defined by Avalara.
CreatedDate Datetime The date when this record was created.
PageKey String

Pseudo-Columns

Pseudo column fields are used in the WHERE clause of SELECT statements and offer more granular control over the data returned from the data source.

Name Type Description
Rows@Next String Identifier for the next page of results. Do not set this value manually.

CData Python Connector for Avalara

NoticeComments

NoticeComments view for AvalaraAvatax data provider.

Columns

Name Type Description
Id [KEY] Int The unique ID number of this notice.
CompanyId [KEY] Int The company ID to which this file will be attached.
NoticeId [KEY] Int The ID of the notice this comment is attached too.
ModifiedUserId Int The user ID of the user who last modified this record.
AttachmentUploadRequest String An attachment to the detail
ResourceFileTypeId Int The resource type ID of this file.
Name String The original name of this file.
Content String This stream contains the bytes of the file being uploaded.
Length Int Length of the file in bytes.
Username String The username adding the file
AccountId Int The account ID to which this file will be attached.
Date Datetime The date this comment was entered
ResourceFileId Int resourceFileId
ModifiedDate Datetime The date/time when this record was last modified.
CommentTypeId Int taxNoticeCommentTypeId
Comment String TaxNoticeComment
CommentType String taxNoticeCommentType
CommentUserName String TaxNoticeCommentUserName
TaxNoticeFileName String TaxNoticeFileName
CommentLink String TaxNoticeCommentLink
CommentUserId Int TaxNoticeCommentUserId

CData Python Connector for Avalara

NoticeFinances

NoticeFinances view for AvalaraAvatax data provider.

Columns

Name Type Description
Id [KEY] Int The Unique Id of the Finance Model.
CompanyId [KEY] Int The company ID to which this file will be attached.
NoticeId Int The unique ID of the the tax notice associated with the the finance detail.
NoticeNumber String The sequential number of the notice.
Penalty String The amount of penalty listed on the notice.
TaxAbated String The amount of tax abated on the notice.
ResourceFileId Int The ResourceFileId of the finance detail attachment.
CreatedUserId Int The User ID of the user who created this record.
ModifiedDate Datetime The date/time when this record was last modified.
TaxDue String The amount of tax due on the notice.
Interest String The amount of interest listed on the notice.
AttachmentUploadRequest String An attachment to the finance detail.
ResourceFileTypeId Int The resource type ID of this file.
Name String The original name of this file.
Content String This stream contains the bytes of the file being uploaded..
Length Int Length of the file in bytes.
Username String The username adding the file.
AccountId Int The account ID to which this file will be attached.
Credits String The amount of credits listed on the notice.
CspFeeRefund String The amount of CSP Fee Refund on the notice.
NoticeDate Datetime The date of the notice.
ModifiedUserId Int The user ID of the user who last modified this record.
CustomerPenalty String The amount of customer penalty on the notice.
DueDate Datetime The due date of the notice.
CustomerInterest String The amount of customer interest on the notice.
FileName String The name of the file attached to the finance detail.
CreatedDate Datetime The date when this record was created.

CData Python Connector for Avalara

NoticeResponsibility

NoticeResponsibility view for AvalaraAvatax data provider.

Columns

Name Type Description
Id [KEY] Int The unique ID number of this filing frequency.
CompanyId [KEY] String The CompanyId of the parent record.
NoticeId Int TaxNoticeId
TaxNoticeResponsibilityId Int TaxNoticeResponsibilityId
Description String The description name of this filing frequency.

CData Python Connector for Avalara

NoticeRootCause

NoticeRootCause view for AvalaraAvatax data provider.

Columns

Name Type Description
Id [KEY] Int The unique ID number of this filing frequency.
CompanyId [KEY] String The CompanyId of the parent record.
NoticeId [KEY] Int TaxNoticeId
Description String The description name of this root cause.
TaxNoticeRootCauseId Int TaxNoticeRootCauseId

CData Python Connector for Avalara

PostalCodes

PostalCodes view for the Avalara Avatax data provider.

Select

The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. Most of the columns support server side filtering with the following operators: =,>,<,<=,>=,IN,NOT,IN,AND,OR,LIKE. The rest of the filter is executed client side within the connector.

  • IncludeExpiredPostalCodes supports the '=' comparison operator.
For example, the following query is processed server side:
SELECT * FROM PostalCodes WHERE EffectiveDate >= '2018-09-01' AND EffectiveDate <= '2022-02-01' AND Region='NY' AND TaxRegionId  IN ('4001027','4001022')
SELECT * FROM PostalCodes WHERE IncludeExpiredPostalCodes = true

Columns

Name Type Description
PostalCode [KEY] String The postal code.
Country String The country in which this postal code is located.
Region String The region, state, or province where this postal code is located.
TaxRegionId Int An Avalara-assigned tax region Id associated with the postal code.
EffectiveDate Date The date the postal code becomes active.
EndDate Date The date the postal code expires.
IncludeExpiredPostalCodes Bool If set to true, returns expired postal codes. Defaults to false.

CData Python Connector for Avalara

Regions

Regions view for the Avalara Avatax data provider.

Select

The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. Most columns except for LocalizedNames support server side filtering with the following operators: =,>,<,<=,>=,IN,NOT,IN,AND,OR,LIKE. The rest of the filter is executed client side within the connector. For example, the following query is processed server side:

SELECT * FROM Regions where CountryCode='US' AND IsRegionTaxable=false AND Code!='MT' AND (Name LIKE '%KA' OR NAME LIKE 'OR%')

Columns

Name Type Description
CountryCode String The two-character ISO 3166 country code this region belongs to.
Code String The three-character ISO 3166 region code.
Name String The full name, in uppercase, using localized characters specific to this region.
LocalizedNames String A list of localized names in various languages.
Classification String The term used in the local language that describes this region.
IsRegionTaxable Bool Indicates whether the region collects tax. This field is only populated for the US and is null for all other countries.
StreamlinedSalesTax Bool In the US, this flag indicates whether a state participates in the Streamlined Sales Tax program. For countries outside the US, this flag is null.

CData Python Connector for Avalara

ReportParameters

ReportParameters view for AvalaraAvatax data provider.

Columns

Name Type Description
ReportId [KEY] String The Id of the parent Report.
CurrencyCode String The currency code used for your report.
State String The state filter used for your report.
DateFormat String The date format used for your report.
StartDate Datetime The start date filter used for your report.
Country String The country filter used for your report.
Culture String The culture used your report.
DateFilter String The date type filter used for your report.
EndDate Datetime The end date filter used for your report.
DocType String The doc type filter used for your report.

CData Python Connector for Avalara

Reports

Reports table for AvalaraAvatax data provider.

Columns

Name Type Description
Id [KEY] Int The unique identifier of the report task.
CompletedDate Datetime The time when the report was finished building, if completed.
CreatedUser String The userName of the user who initiated the report task.
CreatedUserId Int The Id of the user who initiated this task.
File String The name of the report file, if available.
Status String The current status of the report building task.
ReportType String The type of the report: ExportDocumentLine, etc.
AccountId Int The ID of the account the reported transactions are from.
Format String The format of the report file.
CompanyId Int The ID of the company the reported transactions are from.
LinkedParameters String The parametes used to build the report.
CurrencyCode String The currency code used for your report.
State String The state filter used for your report.
DateFormat String The date format used for your report.
StartDate Datetime The start date filter used for your report.
Country String The country filter used for your report.
Culture String The culture used your report.
DateFilter String The date type filter used for your report.
EndDate Datetime The end date filter used for your report.
DocType String The doc type filter used for your report.
CreatedDate Datetime The time when the report task was initiated.
Size Int The size of the report file, if available.
PageKey String

CData Python Connector for Avalara

Subscriptions

Subscriptions table for AvalaraAvatax data provider.

Select

The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. Most of the columns support server side filtering with the following operators: =,>,<,<=,>=,IN,NOT,IN,AND,OR,LIKE. The rest of the filter is executed client side within the connector. For example, the following query is processed server side:

SELECT * FROM Subscriptions WHERE SubscriptionDescription LIKE 'AVA%'

Columns

Name Type Description
Id [KEY] Int The unique ID number of this subscription.
AccountId [KEY] Int The unique ID number of the account this subscription belongs to.
ModifiedUserId Int The user ID of the user who last modified this record.
CreatedUserId Int The User ID of the user who created this record.
ModifiedDate Datetime The date/time when this record was last modified.
EndDate Date If the subscription has ended or will end, this date indicates when the subscription ends.
SubscriptionTypeId Int The unique ID number of the service that the account is subscribed to. If this is provided, subscription description is ignored.
EffectiveDate Date The date when the subscription began.
CreatedDate Datetime The date when this record was created.
SubscriptionDescription String A friendly description of the service that the account is subscribed to. You can either provide the subscription type Id or this but not both. If subscription type Id is provided, then this information is ignored and this field will be updated with the information from subscription type id.
PageKey String

CData Python Connector for Avalara

TaxRatesByAddress

Retrieve real-time estimated tax rates based on an address using the Avalara Avatax data provider.

Select

The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. The rest of the filter is executed client side within the connector.

  • PostalCode supports the '=' comparison operator.
  • Region supports the '=' comparison operator.
  • City supports the '=' comparison operator.
  • Line1 supports the '=' comparison operator.
  • Line2 supports the '=' comparison operator.
  • Line3 supports the '=' comparison operator.
For example, the following query is processed server side:
SELECT * FROM TaxRatesByAddress WHERE PostalCode='99950' AND Region='AK' AND City='KETCHIKAN' AND Line1='Whale Pass'

Columns

Name Type Description
Rate Decimal The sales tax rate for general tangible personal property in this jurisdiction.
Name String A readable name of the tax or taxing jurisdiction related to this tax rate.
Type String The type of jurisdiction associated with this tax rate.
PostalCode String The postal code of the location.
Region String Name or ISO 3166 code identifying the region within the country.
City String The city name of the location.
Line1 String The street address of the location.
Line2 String The street address of the location.
Line3 String The street address of the location.

CData Python Connector for Avalara

TaxRatesByZipCode

Retrieve estimated tax rates by zip code for a specific date using the Avalara Avatax data provider.

Select

The connector will use the Avalara API to process WHERE clause conditions built with the following columns and operators. The rest of the filter is executed client side within the connector.

  • StateAbbreviation supports the '=' comparison operator.
  • Date supports the '=' comparison operator.
For example, the following query is processed server side:
SELECT * FROM TaxRatesByZipCode WHERE StateAbbreviation='NY' AND Date='2020-01-01'

Columns

Name Type Description
ZipCode [KEY] String The five digit zip code for this record.
StateAbbreviation String A valid two-character US state abbreviation for this record.
CountyName String A valid county name for this record. Zip codes may span multiple counties.
CityName String A valid city name for this record. Zip codes may span multiple cities.
StateSalesTax Decimal The state component of the sales tax rate.
StateUseTax Decimal The state component of the use tax rate.
CountySalesTax Decimal The county component of the sales tax rate.
CountyUseTax Decimal The county component of the use tax rate.
CitySalesTax Decimal The city component of the sales tax rate.
CityUseTax Decimal The city component of the use tax rate.
TotalSalesTax Decimal The total sales tax rate for this postal code. This value may differ from the sum of state, county, and city taxes due to special jurisdiction rules.
TotalUseTax Decimal The total use tax rate for this postal code. This value may differ from the sum of state, county, and city rates due to special tax jurisdiction rules.
TaxShippingAlone Bool Whether shipping is taxable.
TaxShippingAndHandlingTogether Bool Whether shipping and handling are taxable when sent together.
Date Date The date for which the point-of-sale data is calculated. Defaults to today.

CData Python Connector for Avalara

TransactionAddresses

TransactionAddresses view for AvalaraAvatax data provider.

Columns

Name Type Description
Id Long The unique ID number of this address.
TransactionId Long The unique ID number of the document to which this address belongs.
TransactionCode [KEY] String A unique customer-provided code identifying this transaction.
TransactionStatus String The status of the transaction to which this line item belongs.
PostalCode String The postal code or zip code for the address.
Longitude String Longitude for this address
TaxRegionId Int The unique ID number of the tax region for this address.
Country String The ISO 3166 country code
City String The city for the address.
Latitude String Latitude for this address
Region String The ISO 3166 region code. E.g., the second part of ISO 3166-2.
Line3 String The third line of the address.
Line2 String The second line of the address.
Line1 String The first line of the address.
BoundaryLevel String The boundary level at which this address was validated.
CompanyCode String The code of the company that recorded this transaction.

CData Python Connector for Avalara

TransactionInvoiceMessages

TransactionInvoicemessages view for AvalaraAvatax data provider.

Columns

Name Type Description
TransactionId [KEY] Long The transaction code of the parent record.
TransactionCode [KEY] String A unique customer-provided code identifying this transaction.
TransactionStatus String The status of the transaction to which this line item belongs.
LineNumbers String The applicable tax line numbers and codes.
Content String The content of the invoice message.
CompanyCode String The code of the company that recorded this transaction.

CData Python Connector for Avalara

TransactionLocationTypes

TransactionLocationTypes view for AvalaraAvatax data provider.

Columns

Name Type Description
TransactionId Long Transaction ID
TransactionCode [KEY] String A unique customer-provided code identifying this transaction.
TransactionStatus String The status of the transaction to which this line item belongs.
TransactionAddressId Long Address ID for the transaction.
TransactionLocationTypeId Int Location type ID for this location type in transaction.
LocationTypeCode String Location type code
CompanyCode String The code of the company that recorded this transaction.

CData Python Connector for Avalara

TransactionMessages

TransactionMessages view for AvalaraAvatax data provider.

Columns

Name Type Description
TransactionId [KEY] Long The transaction id of the parent record.
TransactionCode [KEY] String The transaction code of the parent record.
TransactionStatus String The status of the transaction to which this line item belongs.
RefersTo String Information about what object in your request this message refers to.
Summary String A brief summary of what this message tells us.
Severity String A category that indicates how severely this message affects the results.
Source String The name of the code or service that generated this message.
Details String Detailed information that explains what the summary provided.
CompanyCode String The code of the company that recorded this transaction.

CData Python Connector for Avalara

TransactionParameters

TransactionParameters view for AvalaraAvatax data provider.

Columns

Name Type Description
TransactionId [KEY] Long The transaction id of the parent record.
TransactionCode [KEY] String The transaction code of the parent record.
TransactionStatus String The status of the transaction to which this line item belongs.
Name String The name of the parameter.
Unit String The unit of measure of the parameter value.
Value String The value of the parameter.
CompanyCode String The code of the company that recorded this transaction.

CData Python Connector for Avalara

TransactionSummary

TransactionSummary view for AvalaraAvatax data provider.

Columns

Name Type Description
TransactionId [KEY] Long The transaction id this summary is associated to.
TransactionCode [KEY] String A unique customer-provided code identifying this transaction.
TransactionStatus String The status of the transaction to which this line item belongs.
StateAssignedNo String The state assigned number of the jurisdiction that collects this tax.
JurisName String The name of the jurisdiction that collects this tax.
TaxGroup String Group code when special grouping is enabled.
JurisCode String Jurisdiction Code for the taxing jurisdiction
Region String Two or three character ISO region, state or province code, if applicable.
JurisType String The type of jurisdiction that collects this tax.
RateTypeCode String Indicates the code of the rate type.
TaxSubType String The tax subtype of this tax.
NonTaxable String The amount of the transaction that was non-taxable.
TaxName String The name of the tax.
TaxAuthorityType Int The unique ID of the Tax Authority Type that collects this tax.
Tax String Tax amount - The calculated tax (Base * Rate).
Taxable String Tax Base - The adjusted taxable amount.
Country String Two character ISO-3166 country code.
TaxCalculated String The amount of tax that AvaTax calculated for the transaction.
Exemption String The amount of the transaction that was exempt.
TaxType String The tax type of this tax.
Rate String Tax Rate - The rate of taxation, as a fraction of the amount.
CompanyCode String The code of the company that recorded this transaction.

CData Python Connector for Avalara

TransactionTaxDetailsByTaxType

TransactionTaxdetailsbytaxtype view for AvalaraAvatax data provider.

Columns

Name Type Description
TransactionId [KEY] String
TransactionCode String A unique customer-provided code identifying this transaction.
TransactionStatus String The status of the transaction to which this line item belongs.
TotalNonTaxable String Total non taxable by tax type.
LinkedTaxSubTypeDetails String Tax subtype details.
TotalExempt String Total exempt by tax type.
TotalTaxable String Total taxable amount by tax type.
TotalTax String Total tax by tax type.
TaxType String Tax Type.
CompanyCode String The code of the company that recorded this transaction.

CData Python Connector for Avalara

Stored Procedures

Stored procedures are function-like interfaces that extend the functionality of the connector beyond simple SELECT/INSERT/UPDATE/DELETE operations with Avalara.

Stored procedures accept a list of parameters, perform their intended function, and then return any relevant response data from Avalara, along with an indication of whether the procedure succeeded or failed.

CData Python Connector for Avalara Stored Procedures

Name Description
CommitTransaction Commit a transaction for reporting.
DownloadBatch Download a single batch file.
RefundTransaction Refund a transaction.
VoidTransaction Void a transaction.

CData Python Connector for Avalara

CommitTransaction

Commit a transaction for reporting.

Input

Name Type Required Description
TransactionCode String True Code of the transaction to commit.

CData Python Connector for Avalara

DownloadBatch

Download a single batch file.

Input

Name Type Required Description
CompanyId String True The ID of the company that owns this batch
BatchId String True The ID of the batch object.
FileId String True The primary key of this batch file object.
FilePath String False The full path (including the file's name) where the file will be downloaded.

Result Set Columns

Name Type Description
FileData String The file's data encoded in Base64 will be outputted if FilePath and FileStream are not set.

CData Python Connector for Avalara

RefundTransaction

Refund a transaction.

Input

Name Type Required Description
TransactionCode String True Code of the transaction to refund.
RefundTransactionCode String True The transaction code for the refund. This code will be saved to the ReturnInvoice transaction, and does not need to match the code of the original sale.
RefundDate String True The date of the refund.
RefundType String True Type of this refund. To submit a full refund, specify Full. To refund only specific lines from the transaction, specify Partial and indicate the lines you wish to apply in the refundLines field. To refund the tax that was paid in the previous transaction, specify TaxOnly. To issue a percentage-based discount, specify Percentage.
RefundPercentage String False The percentage for refund. This value only applies if you choose Percentage or Partial refund type.
RefundLines String False A comma separated list of the line numbers to refund for.
ReferenceCode String False A user-defined reference field containing information about this refund.

CData Python Connector for Avalara

VoidTransaction

Void a transaction.

Input

Name Type Required Description
TransactionCode String True Code of the transaction to void.

CData Python Connector for Avalara

System Tables

You can query the system tables described in this section to access schema information, information on data source functionality, and batch operation statistics.

Schema Tables

The following tables return database metadata for Avalara:

Data Source Tables

The following tables return information about how to connect to and query the data source:

  • sys_connection_props: Returns information on the available connection properties.
  • sys_sqlinfo: Describes the SELECT queries that the connector can offload to the data source.

Query Information Tables

The following table returns query statistics for data modification queries

  • sys_identity: Returns information about batch operations or single updates.

CData Python Connector for Avalara

sys_catalogs

Lists the available databases.

The following query retrieves all databases determined by the connection string:

SELECT * FROM sys_catalogs

Columns

Name Type Description
CatalogName String The database name.

CData Python Connector for Avalara

sys_schemas

Lists the available schemas.

The following query retrieves all available schemas:

          SELECT * FROM sys_schemas
          

Columns

Name Type Description
CatalogName String The database name.
SchemaName String The schema name.

CData Python Connector for Avalara

sys_tables

Lists the available tables.

The following query retrieves the available tables and views:

          SELECT * FROM sys_tables
          

Columns

Name Type Description
CatalogName String The database containing the table or view.
SchemaName String The schema containing the table or view.
TableName String The name of the table or view.
TableType String The table type (table or view).
Description String A description of the table or view.
IsUpdateable Boolean Whether the table can be updated.
IsInsertable Boolean Whether the table can be inserted into.
IsDeleteable Boolean Whether rows can be deleted from the table.

CData Python Connector for Avalara

sys_tablecolumns

Describes the columns of the available tables and views.

The following query returns the columns and data types for the Transactions table:

SELECT ColumnName, DataTypeName FROM sys_tablecolumns WHERE TableName = 'Transactions' 

Columns

Name Type Description
CatalogName String The name of the database containing the table or view.
SchemaName String The schema containing the table or view.
TableName String The name of the table or view containing the column.
ColumnName String The column name.
DataTypeName String The data type name.
DataType Int32 An integer indicating the data type. This value is determined at run time based on the environment.
Length Int32 The storage size of the column.
DisplaySize Int32 The designated column's normal maximum width in characters.
NumericPrecision Int32 The maximum number of digits in numeric data. The column length in characters for character and date-time data.
NumericScale Int32 The column scale or number of digits to the right of the decimal point.
IsNullable Boolean Whether the column can contain null.
Description String A brief description of the column.
Ordinal Int32 The sequence number of the column.
IsAutoIncrement String Whether the column value is assigned in fixed increments.
IsGeneratedColumn String Whether the column is generated.
IsHidden Boolean Whether the column is hidden.
IsArray Boolean Whether the column is an array.
IsReadOnly Boolean Whether the column is read-only.
IsKey Boolean Indicates whether a field returned from sys_tablecolumns is the primary key of the table.
ColumnType String The role or classification of the column in the schema. Possible values include SYSTEM, LINKEDCOLUMN, NAVIGATIONKEY, REFERENCECOLUMN, and NAVIGATIONPARENTCOLUMN.
ColumnCapabilities Int32 A bit mask denoting the column's write capabilities. The value is the sum of the following: 1 if the column is required for INSERTs, 2 if the column is allowed for INSERTs, and 4 if the column is allowed for UPDATEs. A value of 0 indicates that the write capabilities of the column are unknown or that the column is read-only.

CData Python Connector for Avalara

sys_procedures

Lists the available stored procedures.

The following query retrieves the available stored procedures:

          SELECT * FROM sys_procedures
          

Columns

Name Type Description
CatalogName String The database containing the stored procedure.
SchemaName String The schema containing the stored procedure.
ProcedureName String The name of the stored procedure.
Description String A description of the stored procedure.
ProcedureType String The type of the procedure, such as PROCEDURE or FUNCTION.

CData Python Connector for Avalara

sys_procedureparameters

Describes stored procedure parameters.

The following query returns information about all of the input parameters for the SelectEntries stored procedure:

SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'SelectEntries' AND Direction = 1 OR Direction = 2

To include result set columns in addition to the parameters, set the IncludeResultColumns pseudo column to True:

SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'SelectEntries' AND IncludeResultColumns='True'

Columns

Name Type Description
CatalogName String The name of the database containing the stored procedure.
SchemaName String The name of the schema containing the stored procedure.
ProcedureName String The name of the stored procedure containing the parameter.
ColumnName String The name of the stored procedure parameter.
Direction Int32 An integer corresponding to the type of the parameter: input (1), input/output (2), or output(4). input/output type parameters can be both input and output parameters.
DataType Int32 An integer indicating the data type. This value is determined at run time based on the environment.
DataTypeName String The name of the data type.
NumericPrecision Int32 The maximum precision for numeric data. The column length in characters for character and date-time data.
Length Int32 The number of characters allowed for character data. The number of digits allowed for numeric data.
NumericScale Int32 The number of digits to the right of the decimal point in numeric data.
IsNullable Boolean Whether the parameter can contain null.
IsRequired Boolean Whether the parameter is required for execution of the procedure.
IsArray Boolean Whether the parameter is an array.
Description String The description of the parameter.
Ordinal Int32 The index of the parameter.
Values String The values you can set in this parameter are limited to those shown in this column. Possible values are comma-separated.
SupportsStreams Boolean Whether the parameter represents a file that you can pass as either a file path or a stream.
IsPath Boolean Whether the parameter is a target path for a schema creation operation.
Default String The value used for this parameter when no value is specified.
SpecificName String A label that, when multiple stored procedures have the same name, uniquely identifies each identically-named stored procedure. If there's only one procedure with a given name, its name is simply reflected here.
IsCDataProvided Boolean Whether the procedure is added/implemented by CData, as opposed to being a native Avalara procedure.

Pseudo-Columns

Name Type Description
IncludeResultColumns Boolean Whether the output should include columns from the result set in addition to parameters. Defaults to False.

CData Python Connector for Avalara

sys_keycolumns

Describes the primary and foreign keys.

The following query retrieves the primary key for the Transactions table:

         SELECT * FROM sys_keycolumns WHERE IsKey='True' AND TableName='Transactions' 
          

Columns

Name Type Description
CatalogName String The name of the database containing the key.
SchemaName String The name of the schema containing the key.
TableName String The name of the table containing the key.
ColumnName String The name of the key column.
IsKey Boolean Whether the column is a primary key in the table referenced in the TableName field.
IsForeignKey Boolean Whether the column is a foreign key referenced in the TableName field.
PrimaryKeyName String The name of the primary key.
ForeignKeyName String The name of the foreign key.
ReferencedCatalogName String The database containing the primary key.
ReferencedSchemaName String The schema containing the primary key.
ReferencedTableName String The table containing the primary key.
ReferencedColumnName String The column name of the primary key.

CData Python Connector for Avalara

sys_foreignkeys

Describes the foreign keys.

The following query retrieves all foreign keys which refer to other tables:

         SELECT * FROM sys_foreignkeys WHERE ForeignKeyType = 'FOREIGNKEY_TYPE_IMPORT'
          

Columns

Name Type Description
CatalogName String The name of the database containing the key.
SchemaName String The name of the schema containing the key.
TableName String The name of the table containing the key.
ColumnName String The name of the key column.
PrimaryKeyName String The name of the primary key.
ForeignKeyName String The name of the foreign key.
ReferencedCatalogName String The database containing the primary key.
ReferencedSchemaName String The schema containing the primary key.
ReferencedTableName String The table containing the primary key.
ReferencedColumnName String The column name of the primary key.
ForeignKeyType String Designates whether the foreign key is an import (points to other tables) or export (referenced from other tables) key.

CData Python Connector for Avalara

sys_primarykeys

Describes the primary keys.

The following query retrieves the primary keys from all tables and views:

         SELECT * FROM sys_primarykeys
          

Columns

Name Type Description
CatalogName String The name of the database containing the key.
SchemaName String The name of the schema containing the key.
TableName String The name of the table containing the key.
ColumnName String The name of the key column.
KeySeq String The sequence number of the primary key.
KeyName String The name of the primary key.

CData Python Connector for Avalara

sys_indexes

Describes the available indexes. By filtering on indexes, you can write more selective queries with faster query response times.

The following query retrieves all indexes that are not primary keys:

          SELECT * FROM sys_indexes WHERE IsPrimary='false'
          

Columns

Name Type Description
CatalogName String The name of the database containing the index.
SchemaName String The name of the schema containing the index.
TableName String The name of the table containing the index.
IndexName String The index name.
ColumnName String The name of the column associated with the index.
IsUnique Boolean True if the index is unique. False otherwise.
IsPrimary Boolean True if the index is a primary key. False otherwise.
Type Int16 An integer value corresponding to the index type: statistic (0), clustered (1), hashed (2), or other (3).
SortOrder String The sort order: A for ascending or D for descending.
OrdinalPosition Int16 The sequence number of the column in the index.

CData Python Connector for Avalara

sys_connection_props

Returns information on the available connection properties and those set in the connection string.

The following query retrieves all connection properties that have been set in the connection string or set through a default value:

SELECT * FROM sys_connection_props WHERE Value <> ''

Columns

Name Type Description
Name String The name of the connection property.
ShortDescription String A brief description.
Type String The data type of the connection property.
Default String The default value if one is not explicitly set.
Values String A comma-separated list of possible values. A validation error is thrown if another value is specified.
Value String The value you set or a preconfigured default.
Required Boolean Whether the property is required to connect.
Category String The category of the connection property.
IsSessionProperty String Whether the property is a session property, used to save information about the current connection.
Sensitivity String The sensitivity level of the property. This informs whether the property is obfuscated in logging and authentication forms.
PropertyName String A camel-cased truncated form of the connection property name.
Ordinal Int32 The index of the parameter.
CatOrdinal Int32 The index of the parameter category.
Hierarchy String Shows dependent properties associated that need to be set alongside this one.
Visible Boolean Informs whether the property is visible in the connection UI.
ETC String Various miscellaneous information about the property.

CData Python Connector for Avalara

sys_sqlinfo

Describes the SELECT query processing that the connector can offload to the data source.

See SQL Compliance for SQL syntax details.

Discovering the Data Source's SELECT Capabilities

Below is an example data set of SQL capabilities. Some aspects of SELECT functionality are returned in a comma-separated list if supported; otherwise, the column contains NO.

NameDescriptionPossible Values
AGGREGATE_FUNCTIONSSupported aggregation functions.AVG, COUNT, MAX, MIN, SUM, DISTINCT
COUNTWhether COUNT function is supported.YES, NO
IDENTIFIER_QUOTE_OPEN_CHARThe opening character used to escape an identifier.[
IDENTIFIER_QUOTE_CLOSE_CHARThe closing character used to escape an identifier.]
SUPPORTED_OPERATORSA list of supported SQL operators.=, >, <, >=, <=, <>, !=, LIKE, NOT LIKE, IN, NOT IN, IS NULL, IS NOT NULL, AND, OR
GROUP_BYWhether GROUP BY is supported, and, if so, the degree of support.NO, NO_RELATION, EQUALS_SELECT, SQL_GB_COLLATE
OJ_CAPABILITIESThe supported varieties of outer joins supported.NO, LEFT, RIGHT, FULL, INNER, NOT_ORDERED, ALL_COMPARISON_OPS
OUTER_JOINSWhether outer joins are supported.YES, NO
SUBQUERIESWhether subqueries are supported, and, if so, the degree of support.NO, COMPARISON, EXISTS, IN, CORRELATED_SUBQUERIES, QUANTIFIED
STRING_FUNCTIONSSupported string functions.LENGTH, CHAR, LOCATE, REPLACE, SUBSTRING, RTRIM, LTRIM, RIGHT, LEFT, UCASE, SPACE, SOUNDEX, LCASE, CONCAT, ASCII, REPEAT, OCTET, BIT, POSITION, INSERT, TRIM, UPPER, REGEXP, LOWER, DIFFERENCE, CHARACTER, SUBSTR, STR, REVERSE, PLAN, UUIDTOSTR, TRANSLATE, TRAILING, TO, STUFF, STRTOUUID, STRING, SPLIT, SORTKEY, SIMILAR, REPLICATE, PATINDEX, LPAD, LEN, LEADING, KEY, INSTR, INSERTSTR, HTML, GRAPHICAL, CONVERT, COLLATION, CHARINDEX, BYTE
NUMERIC_FUNCTIONSSupported numeric functions.ABS, ACOS, ASIN, ATAN, ATAN2, CEILING, COS, COT, EXP, FLOOR, LOG, MOD, SIGN, SIN, SQRT, TAN, PI, RAND, DEGREES, LOG10, POWER, RADIANS, ROUND, TRUNCATE
TIMEDATE_FUNCTIONSSupported date/time functions.NOW, CURDATE, DAYOFMONTH, DAYOFWEEK, DAYOFYEAR, MONTH, QUARTER, WEEK, YEAR, CURTIME, HOUR, MINUTE, SECOND, TIMESTAMPADD, TIMESTAMPDIFF, DAYNAME, MONTHNAME, CURRENT_DATE, CURRENT_TIME, CURRENT_TIMESTAMP, EXTRACT
REPLICATION_SKIP_TABLESIndicates tables skipped during replication.
REPLICATION_TIMECHECK_COLUMNSA string array containing a list of columns which will be used to check for (in the given order) to use as a modified column during replication.
IDENTIFIER_PATTERNString value indicating what string is valid for an identifier.
SUPPORT_TRANSACTIONIndicates if the provider supports transactions such as commit and rollback.YES, NO
DIALECTIndicates the SQL dialect to use.
KEY_PROPERTIESIndicates the properties which identify the uniform database.
SUPPORTS_MULTIPLE_SCHEMASIndicates if multiple schemas may exist for the provider.YES, NO
SUPPORTS_MULTIPLE_CATALOGSIndicates if multiple catalogs may exist for the provider.YES, NO
DATASYNCVERSIONThe CData Data Sync version needed to access this driver.Standard, Starter, Professional, Enterprise
DATASYNCCATEGORYThe CData Data Sync category of this driver.Source, Destination, Cloud Destination
SUPPORTSENHANCEDSQLWhether enhanced SQL functionality beyond what is offered by the API is supported.TRUE, FALSE
SUPPORTS_BATCH_OPERATIONSWhether batch operations are supported.YES, NO
SQL_CAPAll supported SQL capabilities for this driver.SELECT, INSERT, DELETE, UPDATE, TRANSACTIONS, ORDERBY, OAUTH, ASSIGNEDID, LIMIT, LIKE, BULKINSERT, COUNT, BULKDELETE, BULKUPDATE, GROUPBY, HAVING, AGGS, OFFSET, REPLICATE, COUNTDISTINCT, JOINS, DROP, CREATE, DISTINCT, INNERJOINS, SUBQUERIES, ALTER, MULTIPLESCHEMAS, GROUPBYNORELATION, OUTERJOINS, UNIONALL, UNION, UPSERT, GETDELETED, CROSSJOINS, GROUPBYCOLLATE, MULTIPLECATS, FULLOUTERJOIN, MERGE, JSONEXTRACT, BULKUPSERT, SUM, SUBQUERIESFULL, MIN, MAX, JOINSFULL, XMLEXTRACT, AVG, MULTISTATEMENTS, FOREIGNKEYS, CASE, LEFTJOINS, COMMAJOINS, WITH, LITERALS, RENAME, NESTEDTABLES, EXECUTE, BATCH, BASIC, INDEX
PREFERRED_CACHE_OPTIONSA string value specifies the preferred cacheOptions.
ENABLE_EF_ADVANCED_QUERYIndicates if the driver directly supports advanced queries coming from Entity Framework. If not, queries will be handled client side.YES, NO
PSEUDO_COLUMNSA string array indicating the available pseudo columns.
MERGE_ALWAYSIf the value is true, The Merge Mode is forcibly executed in Data Sync.TRUE, FALSE
REPLICATION_MIN_DATE_QUERYA select query to return the replicate start datetime.
REPLICATION_MIN_FUNCTIONAllows a provider to specify the formula name to use for executing a server side min.
REPLICATION_START_DATEAllows a provider to specify a replicate startdate.
REPLICATION_MAX_DATE_QUERYA select query to return the replicate end datetime.
REPLICATION_MAX_FUNCTIONAllows a provider to specify the formula name to use for executing a server side max.
IGNORE_INTERVALS_ON_INITIAL_REPLICATEA list of tables which will skip dividing the replicate into chunks on the initial replicate.
CHECKCACHE_USE_PARENTIDIndicates whether the CheckCache statement should be done against the parent key column.TRUE, FALSE
CREATE_SCHEMA_PROCEDURESIndicates stored procedures that can be used for generating schema files.

The following query retrieves the operators that can be used in the WHERE clause:

SELECT * FROM sys_sqlinfo WHERE Name = 'SUPPORTED_OPERATORS'
Note that individual tables may have different limitations or requirements on the WHERE clause; refer to the Data Model section for more information.

Columns

Name Type Description
NAME String A component of SQL syntax, or a capability that can be processed on the server.
VALUE String Detail on the supported SQL or SQL syntax.

CData Python Connector for Avalara

sys_identity

Returns information about attempted modifications.

The following query retrieves the Ids of the modified rows in a batch operation:

         SELECT * FROM sys_identity
          

Columns

Name Type Description
Id String The database-generated Id returned from a data modification operation.
Batch String An identifier for the batch. 1 for a single operation.
Operation String The result of the operation in the batch: INSERTED, UPDATED, or DELETED.
Message String SUCCESS or an error message if the update in the batch failed.

CData Python Connector for Avalara

sys_information

Describes the available system information.

The following query retrieves all columns:

SELECT * FROM sys_information

Columns

NameTypeDescription
ProductStringThe name of the product.
VersionStringThe version number of the product.
DatasourceStringThe name of the datasource the product connects to.
NodeIdStringThe unique identifier of the machine where the product is installed.
HelpURLStringThe URL to the product's help documentation.
LicenseStringThe license information for the product. (If this information is not available, the field may be left blank or marked as 'N/A'.)
LocationStringThe file path location where the product's library is stored.
EnvironmentStringThe version of the environment or rumtine the product is currently running under.
DataSyncVersionStringThe tier of CData Sync required to use this connector.
DataSyncCategoryStringThe category of CData Sync functionality (e.g., Source, Destination).

CData Python Connector for Avalara

Connection String Options

The connection string properties are the various options that can be used to establish a connection. This section provides a complete list of the options you can configure in the connection string for this provider. Click the links for further details.

For more information on establishing a connection, see Establishing a Connection.

Authentication


PropertyDescription
AuthSchemeThe scheme used for authentication. Accepted entries are Basic and LicenseKey.
UseSandboxA boolean indicating whether you are using a Sandbox account. The provider makes requests to the production environment by default.
UserSpecifies the authenticating user's user ID.
PasswordSpecifies the authenticating user's password.
AccountIdThe account ID number of your Avalara account.
LicenseKeyThe license key generated by an account administrator on the Avalara website.

Connection


PropertyDescription
CompanyCodeOnly transaction information tied to this company code will be returned.

SSL


PropertyDescription
SSLServerCertSpecifies the certificate to be accepted from the server when connecting using TLS/SSL.

Firewall


PropertyDescription
FirewallTypeSpecifies the protocol the provider uses to tunnel traffic through a proxy-based firewall.
FirewallServerIdentifies the IP address, DNS name, or host name of a proxy used to traverse a firewall and relay user queries to network resources.
FirewallPortSpecifies the TCP port to be used for a proxy-based firewall.
FirewallUserIdentifies the user ID of the account authenticating to a proxy-based firewall.
FirewallPasswordSpecifies the password of the user account authenticating to a proxy-based firewall.

Proxy


PropertyDescription
ProxyAutoDetectSpecifies whether the provider checks your system proxy settings for existing proxy server configurations, rather than using a manually specified proxy server.
ProxyServerIdentifies the hostname or IP address of the proxy server through which you want to route HTTP traffic.
ProxyPortIdentifies the TCP port on your specified proxy server that has been reserved for routing HTTP traffic to and from the client.
ProxyAuthSchemeSpecifies the authentication method the provider uses when authenticating to the proxy server specified in the ProxyServer connection property.
ProxyUserProvides the username of a user account registered with the proxy server specified in the ProxyServer connection property.
ProxyPasswordSpecifies the password of the user specified in the ProxyUser connection property.
ProxySSLTypeSpecifies the SSL type to use when connecting to the proxy server specified in the ProxyServer connection property.
ProxyExceptionsSpecifies a semicolon-separated list of destination hostnames or IPs that are exempt from connecting through the proxy server set in the ProxyServer connection property.

Logging


PropertyDescription
LogfileSpecifies the file path to the log file where the provider records its activities, such as authentication, query execution, and connection details.
VerbositySpecifies the verbosity level of the log file, which controls the amount of detail logged. Supported values range from 1 to 5.
LogModulesSpecifies the core modules to include in the log file. Use a semicolon-separated list of module names. By default, all modules are logged.
MaxLogFileSizeSpecifies the maximum size of a single log file in bytes. For example, '10 MB'. When the file reaches the limit, the provider creates a new log file with the date and time appended to the name.
MaxLogFileCountSpecifies the maximum number of log files the provider retains. When the limit is reached, the oldest log file is deleted to make space for a new one.

Schema


PropertyDescription
LocationSpecifies the location of a directory containing schema files that define tables, views, and stored procedures. Depending on your service's requirements, this may be expressed as either an absolute path or a relative path.
BrowsableSchemasOptional setting that restricts the schemas reported to a subset of all available schemas. For example, BrowsableSchemas=SchemaA,SchemaB,SchemaC .
TablesOptional setting that restricts the tables reported to a subset of all available tables. For example, Tables=TableA,TableB,TableC .
ViewsOptional setting that restricts the views reported to a subset of the available tables. For example, Views=ViewA,ViewB,ViewC .

Caching


PropertyDescription
AutoCacheSpecifies whether the content of tables targeted by SELECT queries is automatically cached to the specified cache database.
CacheProviderThe namespace of an ADO.NET provider. The specified provider is used as the target database for all caching operations.
CacheDriverThe driver class of a JDBC driver. The specified driver is used to connect to the target database for all caching operations.
CacheConnectionSpecifies the connection string for the specified cache database.
CacheLocationSpecifies the path to the cache when caching to a file.
CacheToleranceNotes the tolerance, in seconds, for stale data in the specified cache database. Requires AutoCache to be set to True.
OfflineGets the data from the specified cache database instead of live Avalara data.
CacheMetadataDetermines whether the provider caches table metadata to a file-based cache database.

Miscellaneous


PropertyDescription
GenerateSchemaFilesIndicates the user preference as to when schemas should be generated and saved.
IncludeAdjustedTransactionsWhether or not to include adjusted transactions in the transaction listing.
MaxRowsSpecifies the maximum number of rows returned for queries that do not include either aggregation or GROUP BY.
OtherSpecifies advanced connection properties for specialized scenarios. Use this property only under the guidance of our Support team to address specific issues.
PagesizeThe maximum number of results to return per page from Avalara when using client paging.
PseudoColumnsSpecifies the pseudocolumns to expose as table columns, expressed as a string in the format 'TableName=ColumnName;TableName=ColumnName'.
ReadonlyToggles read-only access to Avalara from the provider.
RTKSpecifies the runtime key for licensing the provider. If unset or invalid, the provider defaults to the standard licensing method. This property is only required in environments where the standard licensing method is unsupported or requires a runtime key.
TimeoutSpecifies the maximum time, in seconds, that the provider waits for a server response before throwing a timeout error.
UserDefinedViewsSpecifies a filepath to a JSON configuration file that defines custom views. The provider automatically detects and uses the views specified in this file.
CData Python Connector for Avalara

Authentication

This section provides a complete list of the Authentication properties you can configure in the connection string for this provider.


PropertyDescription
AuthSchemeThe scheme used for authentication. Accepted entries are Basic and LicenseKey.
UseSandboxA boolean indicating whether you are using a Sandbox account. The provider makes requests to the production environment by default.
UserSpecifies the authenticating user's user ID.
PasswordSpecifies the authenticating user's password.
AccountIdThe account ID number of your Avalara account.
LicenseKeyThe license key generated by an account administrator on the Avalara website.
CData Python Connector for Avalara

AuthScheme

The scheme used for authentication. Accepted entries are Basic and LicenseKey.

Possible Values

Basic, LicenseKey

Data Type

string

Default Value

"Basic"

Remarks

  • Basic: Set this to use Basic User / Password authentication.
  • LicenseKey: Set to this to perform the authentication using the AccountId and the LicenseKey properties.

CData Python Connector for Avalara

UseSandbox

A boolean indicating whether you are using a Sandbox account. The provider makes requests to the production environment by default.

Data Type

bool

Default Value

false

Remarks

If you are using a production account, this property can be left blank.

CData Python Connector for Avalara

User

Specifies the authenticating user's user ID.

Data Type

string

Default Value

""

Remarks

The authenticating server requires both User and Password to validate the user's identity.

CData Python Connector for Avalara

Password

Specifies the authenticating user's password.

Data Type

string

Default Value

""

Remarks

The authenticating server requires both User and Password to validate the user's identity.

CData Python Connector for Avalara

AccountId

The account ID number of your Avalara account.

Data Type

string

Default Value

""

Remarks

The Account Id is listed in the upper right hand corner of the Avalara admin console.

CData Python Connector for Avalara

LicenseKey

The license key generated by an account administrator on the Avalara website.

Data Type

string

Default Value

""

Remarks

You can generate a license key as follows:

  1. Log into Avalara as an account administrator.
  2. Select Settings.
  3. Select Reset License Key.

CData Python Connector for Avalara

Connection

This section provides a complete list of the Connection properties you can configure in the connection string for this provider.


PropertyDescription
CompanyCodeOnly transaction information tied to this company code will be returned.
CData Python Connector for Avalara

CompanyCode

Only transaction information tied to this company code will be returned.

Data Type

string

Default Value

"DEFAULT"

Remarks

Only transaction information tied to this company code will be returned.

CData Python Connector for Avalara

SSL

This section provides a complete list of the SSL properties you can configure in the connection string for this provider.


PropertyDescription
SSLServerCertSpecifies the certificate to be accepted from the server when connecting using TLS/SSL.
CData Python Connector for Avalara

SSLServerCert

Specifies the certificate to be accepted from the server when connecting using TLS/SSL.

Data Type

string

Default Value

""

Remarks

If you are using a TLS/SSL connection, use this property to specify the TLS/SSL certificate to be accepted from the server. If you specify a value for this property, all other certificates that are not trusted by the machine are rejected.

This property can take the following forms:

Description Example
A full PEM Certificate (example shortened for brevity) -----BEGIN CERTIFICATE-----
MIIChTCCAe4CAQAwDQYJKoZIhv......Qw==
-----END CERTIFICATE-----
A path to a local file containing the certificate C:\cert.cer
The public key (example shortened for brevity) -----BEGIN RSA PUBLIC KEY-----
MIGfMA0GCSq......AQAB
-----END RSA PUBLIC KEY-----
The MD5 Thumbprint (hex values can also be either space- or colon-separated) ecadbdda5a1529c58a1e9e09828d70e4
The SHA1 Thumbprint (hex values can also be either space- or colon-separated) 34a929226ae0819f2ec14b4a3d904f801cbb150d

Note: It is possible to use '*' to signify that all certificates should be accepted, but due to security concerns this is not recommended.

CData Python Connector for Avalara

Firewall

This section provides a complete list of the Firewall properties you can configure in the connection string for this provider.


PropertyDescription
FirewallTypeSpecifies the protocol the provider uses to tunnel traffic through a proxy-based firewall.
FirewallServerIdentifies the IP address, DNS name, or host name of a proxy used to traverse a firewall and relay user queries to network resources.
FirewallPortSpecifies the TCP port to be used for a proxy-based firewall.
FirewallUserIdentifies the user ID of the account authenticating to a proxy-based firewall.
FirewallPasswordSpecifies the password of the user account authenticating to a proxy-based firewall.
CData Python Connector for Avalara

FirewallType

Specifies the protocol the provider uses to tunnel traffic through a proxy-based firewall.

Possible Values

NONE, TUNNEL, SOCKS4, SOCKS5

Data Type

string

Default Value

"NONE"

Remarks

A proxy-based firewall (or proxy firewall) is a network security device that acts as an intermediary between user requests and the resources they access. The proxy accepts the request of an authenticated user, tunnels through the firewall, and transmits the request to the appropriate server.

Because the proxy evaluates and transfers data backets on behalf of the requesting users, the users never connect directly with the servers, only with the proxy.

Note: By default, the connector connects to the system proxy. To disable this behavior and connect to one of the following proxy types, set ProxyAutoDetect to false.

The following table provides port number information for each of the supported protocols.

Protocol Default Port Description
TUNNEL 80 The port where the connector opens a connection to Avalara. Traffic flows back and forth via the proxy at this location.
SOCKS4 1080 The port where the connector opens a connection to Avalara. SOCKS 4 then passes theFirewallUser value to the proxy, which determines whether the connection request should be granted.
SOCKS5 1080 The port where the connector sends data to Avalara. If the SOCKS 5 proxy requires authentication, set FirewallUser and FirewallPassword to credentials the proxy recognizes.

To connect to HTTP proxies, use ProxyServer and ProxyPort. To authenticate to HTTP proxies, use ProxyAuthScheme, ProxyUser, and ProxyPassword.

CData Python Connector for Avalara

FirewallServer

Identifies the IP address, DNS name, or host name of a proxy used to traverse a firewall and relay user queries to network resources.

Data Type

string

Default Value

""

Remarks

A proxy-based firewall (or proxy firewall) is a network security device that acts as an intermediary between user requests and the resources they access. The proxy accepts the request of an authenticated user, tunnels through the firewall, and transmits the request to the appropriate server.

Because the proxy evaluates and transfers data backets on behalf of the requesting users, the users never connect directly with the servers, only with the proxy.

CData Python Connector for Avalara

FirewallPort

Specifies the TCP port to be used for a proxy-based firewall.

Data Type

int

Default Value

0

Remarks

A proxy-based firewall (or proxy firewall) is a network security device that acts as an intermediary between user requests and the resources they access. The proxy accepts the request of an authenticated user, tunnels through the firewall, and transmits the request to the appropriate server.

Because the proxy evaluates and transfers data backets on behalf of the requesting users, the users never connect directly with the servers, only with the proxy.

CData Python Connector for Avalara

FirewallUser

Identifies the user ID of the account authenticating to a proxy-based firewall.

Data Type

string

Default Value

""

Remarks

A proxy-based firewall (or proxy firewall) is a network security device that acts as an intermediary between user requests and the resources they access. The proxy accepts the request of an authenticated user, tunnels through the firewall, and transmits the request to the appropriate server.

Because the proxy evaluates and transfers data backets on behalf of the requesting users, the users never connect directly with the servers, only with the proxy.

CData Python Connector for Avalara

FirewallPassword

Specifies the password of the user account authenticating to a proxy-based firewall.

Data Type

string

Default Value

""

Remarks

A proxy-based firewall (or proxy firewall) is a network security device that acts as an intermediary between user requests and the resources they access. The proxy accepts the request of an authenticated user, tunnels through the firewall, and transmits the request to the appropriate server.

Because the proxy evaluates and transfers data backets on behalf of the requesting users, the users never connect directly with the servers, only with the proxy.

CData Python Connector for Avalara

Proxy

This section provides a complete list of the Proxy properties you can configure in the connection string for this provider.


PropertyDescription
ProxyAutoDetectSpecifies whether the provider checks your system proxy settings for existing proxy server configurations, rather than using a manually specified proxy server.
ProxyServerIdentifies the hostname or IP address of the proxy server through which you want to route HTTP traffic.
ProxyPortIdentifies the TCP port on your specified proxy server that has been reserved for routing HTTP traffic to and from the client.
ProxyAuthSchemeSpecifies the authentication method the provider uses when authenticating to the proxy server specified in the ProxyServer connection property.
ProxyUserProvides the username of a user account registered with the proxy server specified in the ProxyServer connection property.
ProxyPasswordSpecifies the password of the user specified in the ProxyUser connection property.
ProxySSLTypeSpecifies the SSL type to use when connecting to the proxy server specified in the ProxyServer connection property.
ProxyExceptionsSpecifies a semicolon-separated list of destination hostnames or IPs that are exempt from connecting through the proxy server set in the ProxyServer connection property.
CData Python Connector for Avalara

ProxyAutoDetect

Specifies whether the provider checks your system proxy settings for existing proxy server configurations, rather than using a manually specified proxy server.

Data Type

bool

Default Value

true

Remarks

When this connection property is set to True, the connector checks your system proxy settings for existing proxy server configurations (no need to manually supply proxy server details).

This connection property takes precedence over other proxy settings. If you want to configure the connector to connect to a specific proxy server, set ProxyAutoDetect to False.

On Windows, the connector reads the proxy settings from the Internet Options in the registry, specifically the registry key HKCU\SOFTWARE\Microsoft\Windows\CurrentVersion\Internet Settings\. On Windows 10 and later, this corresponds to the Proxy Settings found in the Windows Settings.

Note that these settings apply only to the current user of the machine. If you're running an application as a service, the connector does not read your own user's settings. You must instead manually supply the proxy settings in the connector's connection properties.

On Mac, the connector reads proxy settings from the system-configured CFNetwork settings.

On Linux, this property is unsupported, and is set to False by default.

To connect to an HTTP proxy, see ProxyServer. For other proxies, such as SOCKS or tunneling, see FirewallType.

CData Python Connector for Avalara

ProxyServer

Identifies the hostname or IP address of the proxy server through which you want to route HTTP traffic.

Data Type

string

Default Value

""

Remarks

The connector only routes HTTP traffic through the proxy server specified in this connection property when ProxyAutoDetect is set to False.

If ProxyAutoDetect is set to True (the default), the connector instead routes HTTP traffic through the proxy server specified in your system proxy settings.

CData Python Connector for Avalara

ProxyPort

Identifies the TCP port on your specified proxy server that has been reserved for routing HTTP traffic to and from the client.

Data Type

int

Default Value

80

Remarks

The connector only routes HTTP traffic through the ProxyServer port specified in this connection property when ProxyAutoDetect is set to False.

If ProxyAutoDetect is set to True (the default), the connector instead routes HTTP traffic through the proxy server port specified in your system proxy settings.

For other proxy types, see FirewallType.

CData Python Connector for Avalara

ProxyAuthScheme

Specifies the authentication method the provider uses when authenticating to the proxy server specified in the ProxyServer connection property.

Possible Values

BASIC, DIGEST, NONE, NEGOTIATE, NTLM

Data Type

string

Default Value

"BASIC"

Remarks

Note: The connector only uses this ProxyAuthScheme when ProxyAutoDetect is set to False. If ProxyAutoDetect is set to True (the default), the connector instead uses the authentication method specified in your system proxy settings.

Supported authentication types :

  • BASIC: The connector performs HTTP basic authentication.
  • DIGEST: The connector performs HTTP digest authentication.
  • NTLM: The connector retrieves an NTLM token.
  • NEGOTIATE: The connector retrieves an NTLM or Kerberos token based on the applicable protocol for authentication.
  • NONE: Signifies that the ProxyServer does not require authentication.

For all values other than NONE, you must also set the ProxyUser and ProxyPassword connection properties.

If you need to use another authentication type, such as SOCKS 5 authentication, see FirewallType.

CData Python Connector for Avalara

ProxyUser

Provides the username of a user account registered with the proxy server specified in the ProxyServer connection property.

Data Type

string

Default Value

""

Remarks

The ProxyUser and ProxyPassword connection properties are used to connect and authenticate against the HTTP proxy specified in ProxyServer.

After selecting one of the available authentication types in ProxyAuthScheme, set this property as follows:

ProxyAuthScheme Value Value to set for ProxyUser
BASIC The username of a user registered with the proxy server.
DIGEST The username of a user registered with the proxy server.
NEGOTIATE The username of a Windows user who is a valid user in the domain or trusted domain that the proxy server is part of, in the format user@domain or domain\user.
NTLM The username of a Windows user who is a valid user in the domain or trusted domain that the proxy server is part of, in the format user@domain or domain\user.
NONE Do not set the ProxyPassword connection property.

Note: The connector only uses this username if ProxyAutoDetect is set to False. If ProxyAutoDetect is set to True (the default), the connector instead uses the username specified in your system proxy settings.

CData Python Connector for Avalara

ProxyPassword

Specifies the password of the user specified in the ProxyUser connection property.

Data Type

string

Default Value

""

Remarks

The ProxyUser and ProxyPassword connection properties are used to connect and authenticate against the HTTP proxy specified in ProxyServer.

After selecting one of the available authentication types in ProxyAuthScheme, set this property as follows:

ProxyAuthScheme Value Value to set for ProxyPassword
BASIC The password associated with the proxy server user specified in ProxyUser.
DIGEST The password associated with the proxy server user specified in ProxyUser.
NEGOTIATE The password associated with the Windows user account specified in ProxyUser.
NTLM The password associated with the Windows user account specified in ProxyUser.
NONE Do not set the ProxyPassword connection property.

For SOCKS 5 authentication or tunneling, see FirewallType.

Note: The connector only uses this password if ProxyAutoDetect is set to False. If ProxyAutoDetect is set to True (the default), the connector instead uses the password specified in your system proxy settings.

CData Python Connector for Avalara

ProxySSLType

Specifies the SSL type to use when connecting to the proxy server specified in the ProxyServer connection property.

Possible Values

AUTO, ALWAYS, NEVER, TUNNEL

Data Type

string

Default Value

"AUTO"

Remarks

This property determines when to use SSL for the connection to the HTTP proxy specified by ProxyServer. You can set this connection property to the following values :

AUTODefault setting. If ProxyServer is set to an HTTPS URL, the connector uses the TUNNEL option. If ProxyServer is set to an HTTP URL, the component uses the NEVER option.
ALWAYSThe connection is always SSL enabled.
NEVERThe connection is not SSL enabled.
TUNNELThe connection is made through a tunneling proxy. The proxy server opens a connection to the remote host and traffic flows back and forth through the proxy.

CData Python Connector for Avalara

ProxyExceptions

Specifies a semicolon-separated list of destination hostnames or IPs that are exempt from connecting through the proxy server set in the ProxyServer connection property.

Data Type

string

Default Value

""

Remarks

The ProxyServer is used for all addresses, except for addresses defined in this property. Use semicolons to separate entries.

Note: The connector uses the system proxy settings by default, without further configuration needed. If you want to explicitly configure proxy exceptions for this connection, set ProxyAutoDetect to False.

CData Python Connector for Avalara

Logging

This section provides a complete list of the Logging properties you can configure in the connection string for this provider.


PropertyDescription
LogfileSpecifies the file path to the log file where the provider records its activities, such as authentication, query execution, and connection details.
VerbositySpecifies the verbosity level of the log file, which controls the amount of detail logged. Supported values range from 1 to 5.
LogModulesSpecifies the core modules to include in the log file. Use a semicolon-separated list of module names. By default, all modules are logged.
MaxLogFileSizeSpecifies the maximum size of a single log file in bytes. For example, '10 MB'. When the file reaches the limit, the provider creates a new log file with the date and time appended to the name.
MaxLogFileCountSpecifies the maximum number of log files the provider retains. When the limit is reached, the oldest log file is deleted to make space for a new one.
CData Python Connector for Avalara

Logfile

Specifies the file path to the log file where the provider records its activities, such as authentication, query execution, and connection details.

Data Type

string

Default Value

""

Remarks

This property specifies the location and name of the log file where the connector records its operations, including authentication events, query execution, and connection details. If the specified file does not exist, the connector creates it. Ensure that the user or the service running the connector has write access to the specified path or file. Without sufficient permissions, the log file is not created.

Sensitive information from the connection string, such as passwords and tokens, is automatically masked in the logs. However, sensitive information present in the data itself may not be masked.

If you specify a relative path for Logfile, and if the Location property is set, that directory is used as the base path for the log file.

Additional properties allow you to customize logging behavior:

CData Python Connector for Avalara

Verbosity

Specifies the verbosity level of the log file, which controls the amount of detail logged. Supported values range from 1 to 5.

Data Type

string

Default Value

"1"

Remarks

This property defines the level of detail the connector includes in the log file. Higher verbosity levels increase the detail of the logged information, but may also result in larger log files and slower performance due to the additional data being captured.

The default verbosity level is 1, which is recommended for regular operation. Higher verbosity levels are primarily intended for debugging purposes. For more information on each level, refer to Logging.

When combined with the LogModules property, Verbosity can refine logging to specific categories of information.

CData Python Connector for Avalara

LogModules

Specifies the core modules to include in the log file. Use a semicolon-separated list of module names. By default, all modules are logged.

Data Type

string

Default Value

""

Remarks

The connector writes details about each operation it performs into the logfile specified by the Logfile connection property.

Each of these logged operations are assigned to a themed category called a module, and each module has a corresponding short code used to labels individual connector operations as belonging to that module.

When this connection property is set to a semicolon-separated list of module codes, only operations belonging to the specified modules are written to the logfile. Note that this only affects which operations are logged moving forward and doesn't retroactively alter the existing contents of the logfile. For example: INFO;EXEC;SSL;META;

By default, logged operations from all modules are included.

You can explicitly exclude a module by prefixing it with a "-". For example: -HTTP

To apply filters to submodules, identify them with the syntax <module name>.<submodule name>. For example, the following value causes the connector to only log actions belonging to the HTTP module, and further refines it to exclude actions belonging to the Res submodule of the HTTP module: HTTP;-HTTP.Res

Note that the logfile filtering triggered by the Verbosity connection property takes precedence over the filtering imposed by this connection property. This means that operations of a higher verbosity level than the level specified in the Verbosity connection property are not printed in the logfile, even if they belong to one of the modules specified in this connection property.

The available modules and submodules are:

Module Name Module Description Submodules
INFO General Information. Includes the connection string, product version (build number), and initial connection messages.
  • Connec – Information related to creating or destroying connections.
  • Messag – Generic label for messages pertaining to connections, the connection string, and product version. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
EXEC Query Execution. Includes execution messages for user-written SQL queries, parsed SQL queries, and normalized SQL queries. Success/failure messages for queries and query pages appear here as well.
  • Messag – Messages pertaining to query execution. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
  • Normlz – Query normalization steps. Query normalization is when the product takes the user-submitted query and rewrites the query to get the same results with optimal performance.
  • Origin – This label applies to any messages recording a user's original query (the exact, unaltered, non-normalized query executed by the user).
  • Page – Messages related to query paging.
  • Parsed – Query parsing steps. Parsing is the process of converting the user-submitted query into a standardized format for easier processing.
HTTP HTTP protocol messages. Includes HTTP requests/responses (including POST messages), as well as Kerberos related messages.
  • KERB – HTTP requests related to Kerberos.
  • Messag – Messages pertaining to HTTP protocols. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
  • Unpack – This label applies to messages about zipped data being returned from the service API and unpacked by the product.
  • Res – Messages containing HTTP responses.
  • Req – Messages containing HTTP requests.
WSDL Messages pertaining to the generation of WSDL/XSD files.
SSL SSL certificate messages.
  • Certif – Messages pertaining to SSL certificates.
AUTH Authentication related failure/success messages.
  • Messag – Messages pertaining to authentication. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
  • OAuth – Messages related to OAuth authentication.
  • Krbros – Kerberos-related authentication messages.
SQL Includes SQL transactions, SQL bulk transfer messages, and SQL result set messages.
  • Bulk – Messages pertaining to bulk query execution.
  • Cache – Messages related to reading row data from and writing row data to the product's cache for better performance.
  • Messag – Messages pertaining to SQL transactions. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
  • ResSet – Query resultsets.
  • Transc – Messages related to handling transactions, including information about the number of jobs executed and backup table handling.
META Metadata cache and schema messages.
  • Cache – Messages related to reading from and modifying column and table definitions in the product's cache for better performance.
  • Schema – Messages related to retrieving metadata from or modifying the service schema.
  • MemSto – Messages related to writing to or reading from in-memory metadata cache.
  • Storag – Messages relating to storing metadata on disk or in an external data store, rather than in memory.
FUNC Information related to executing SQL functions.
  • Errmsg – Error messages related to executing SQL functions.
TCP Incoming and outgoing raw bytes on TCP transport layer messages.
  • Send – Raw data sent via the TCP protocol.
  • Receiv – Raw data received via the TCP protocol.
FTP Messages pertaining to the File Transfer Protocol.
  • Info – Status messages related to communication in the FTP protocol.
  • Client – Messages related to actions taken by the FTP client (the product) during FTP communication.
  • Server – Messages related to actions taken by the FTP server during FTP communication.
SFTP Messages pertaining to the Secure File Transfer Protocol.
  • Info – Status messages related to communication in the SFTP protocol.
  • To_Server – Messages related to actions taken by the SFTP client (the product) during SFTP communication.
  • From_Server – Messages related to actions taken by the SFTP server during SFTP communication.
POP Messages pertaining to data transferred via the Post Office Protocol.
  • Client – Messages related to actions taken by the POP client (the product) during POP communication.
  • Server – Messages related to actions taken by the POP server during POP communication.
  • Status – Status messages related to communication in the POP protocol.
SMTP Messages pertaining to data transferred via the Simple Mail Transfer Protocol.
  • Client – Messages related to actions taken by the SMTP client (the product) during SMTP communication.
  • Server – Messages related to actions taken by the SMTP server during SMTP communication.
  • Status – Status messages related to communication in the SMTP protocol.
CORE Messages relating to various internal product operations not covered by other modules.
DEMN Messages related to SQL remoting.
CLJB Messages about bulk data uploads (cloud job).
  • Commit – Submissions for bulk data uploads.
SRCE Miscellaneous messages produced by the product that don't belong in any other module.
TRANCE Advanced messages concerning low-level product operations.

CData Python Connector for Avalara

MaxLogFileSize

Specifies the maximum size of a single log file in bytes. For example, '10 MB'. When the file reaches the limit, the provider creates a new log file with the date and time appended to the name.

Data Type

string

Default Value

"100MB"

Remarks

For values lower than 100 KB, the connector uses 100 KB as the minimum allowable size.

To control the total number of log files retained, use the MaxLogFileCount property in conjunction with this property. Together, these properties allow you to manage the size and retention of log files effectively.

CData Python Connector for Avalara

MaxLogFileCount

Specifies the maximum number of log files the provider retains. When the limit is reached, the oldest log file is deleted to make space for a new one.

Data Type

int

Default Value

-1

Remarks

Each log file name includes the date and time for easier identification.

This property accepts the following values:

  • A value of 2 or higher sets the maximum number of log files retained.
  • A value of 1 retains only one log file. When it reaches the maximum size, the file is deleted and replaced by a new one, leaving no history beyond the current log.
  • A value of 0 or negative indicates no limit on the number of log files, and logging continues indefinitely.

To manage log file size, use the MaxLogFileSize property. The two properties work together to control the size and retention of log files in the logging folder.

CData Python Connector for Avalara

Schema

This section provides a complete list of the Schema properties you can configure in the connection string for this provider.


PropertyDescription
LocationSpecifies the location of a directory containing schema files that define tables, views, and stored procedures. Depending on your service's requirements, this may be expressed as either an absolute path or a relative path.
BrowsableSchemasOptional setting that restricts the schemas reported to a subset of all available schemas. For example, BrowsableSchemas=SchemaA,SchemaB,SchemaC .
TablesOptional setting that restricts the tables reported to a subset of all available tables. For example, Tables=TableA,TableB,TableC .
ViewsOptional setting that restricts the views reported to a subset of the available tables. For example, Views=ViewA,ViewB,ViewC .
CData Python Connector for Avalara

Location

Specifies the location of a directory containing schema files that define tables, views, and stored procedures. Depending on your service's requirements, this may be expressed as either an absolute path or a relative path.

Data Type

string

Default Value

"%APPDATA%\\CData\\Avalara Data Provider\\Schema"

Remarks

The Location property is only needed if you want to either customize definitions (for example, change a column name, ignore a column, etc.) or extend the data model with new tables, views, or stored procedures.

If left unspecified, the default location is %APPDATA%\\CData\\Avalara Data Provider\\Schema, where %APPDATA% is set to the user's configuration directory:

Platform %APPDATA%
Windows The value of the APPDATA environment variable
Linux ~/.config

CData Python Connector for Avalara

BrowsableSchemas

Optional setting that restricts the schemas reported to a subset of all available schemas. For example, BrowsableSchemas=SchemaA,SchemaB,SchemaC .

Data Type

string

Default Value

""

Remarks

Listing all available database schemas can take extra time, thus degrading performance. Providing a list of schemas in the connection string saves time and improves performance.

CData Python Connector for Avalara

Tables

Optional setting that restricts the tables reported to a subset of all available tables. For example, Tables=TableA,TableB,TableC .

Data Type

string

Default Value

""

Remarks

Listing all available tables from some databases can take extra time, thus degrading performance. Providing a list of tables in the connection string saves time and improves performance.

If there are lots of tables available and you already know which ones you want to work with, you can use this property to restrict your viewing to only those tables. To do this, specify the tables you want in a comma-separated list. Each table should be a valid SQL identifier with any special characters escaped using square brackets, double-quotes or backticks. For example, Tables=TableA,[TableB/WithSlash],WithCatalog.WithSchema.`TableC With Space`.

Note: If you are connecting to a data source with multiple schemas or catalogs, you must specify each table you want to view by its fully qualified name. This avoids ambiguity between tables that may exist in multiple catalogs or schemas.

CData Python Connector for Avalara

Views

Optional setting that restricts the views reported to a subset of the available tables. For example, Views=ViewA,ViewB,ViewC .

Data Type

string

Default Value

""

Remarks

Listing all available views from some databases can take extra time, thus degrading performance. Providing a list of views in the connection string saves time and improves performance.

If there are lots of views available and you already know which ones you want to work with, you can use this property to restrict your viewing to only those views. To do this, specify the views you want in a comma-separated list. Each view should be a valid SQL identifier with any special characters escaped using square brackets, double-quotes or backticks. For example, Views=ViewA,[ViewB/WithSlash],WithCatalog.WithSchema.`ViewC With Space`.

Note: If you are connecting to a data source with multiple schemas or catalogs, you must specify each view you want to examine by its fully qualified name. This avoids ambiguity between views that may exist in multiple catalogs or schemas.

CData Python Connector for Avalara

Caching

This section provides a complete list of the Caching properties you can configure in the connection string for this provider.


PropertyDescription
AutoCacheSpecifies whether the content of tables targeted by SELECT queries is automatically cached to the specified cache database.
CacheProviderThe namespace of an ADO.NET provider. The specified provider is used as the target database for all caching operations.
CacheDriverThe driver class of a JDBC driver. The specified driver is used to connect to the target database for all caching operations.
CacheConnectionSpecifies the connection string for the specified cache database.
CacheLocationSpecifies the path to the cache when caching to a file.
CacheToleranceNotes the tolerance, in seconds, for stale data in the specified cache database. Requires AutoCache to be set to True.
OfflineGets the data from the specified cache database instead of live Avalara data.
CacheMetadataDetermines whether the provider caches table metadata to a file-based cache database.
CData Python Connector for Avalara

AutoCache

Specifies whether the content of tables targeted by SELECT queries is automatically cached to the specified cache database.

Data Type

bool

Default Value

false

Remarks

When this connection property is set to True, the connector automatically caches the contents of tables targeted by SELECT queries. The content of these tables is cached to the cache database specified by the CacheConnection and CacheProvider connection properties.

See Also

For additional information, see:

  • CacheMetadata: With CacheMetadata enabled, all retrieved metadata is mirrored in the cache database. This means that any subsequent attempts by the connector to discover metadata are much faster, as this metadata is then read directly from the cache database, without needing to spend time requesting metadata from Avalara.
  • Explicitly Caching Data: This topic provides examples for using AutoCache in Offline mode.
  • CACHE Statements: You can use the CACHE statement to explicitly cache the content of any table targeted by a SELECT query.

CData Python Connector for Avalara

CacheProvider

The namespace of an ADO.NET provider. The specified provider is used as the target database for all caching operations.

Data Type

string

Default Value

""

Remarks

You can cache to ADO.NET providers saved in your ADO.NET global assembly cache (GAC).

CData ADO.NET providers automatically register themselves with the GAC during installation, so you don't need to do so manually.

Third-party ADO.NET providers may or may not automatically register themselves with the GAC during installation. If you want to cache to a third-party ADO.NET provider, consult the documentation for that provider to determine what steps (if any) you must take to register them with the GAC. Once they have been registered, you can supply their namespace in this connection property.

You must also set the CacheConnection connection property to provide a connection string for the specified ADO.NET provider.

The following sections show connection examples and address other requirements for several popular database providers. Refer to CacheConnection for more information on typical connection properties.

SQLite

You can use the Microsoft ADO.NET Provider for SQLite to cache to SQLite databases.

CacheProvider=Microsoft.Data.Sqlite;CacheConnection='DataSource=C:\\Users\\Public\\cache.db;'User=MyUser;Password=MyPassword;

MySQL

To cache to MySQL, you can use the CData ADO.NET Provider for MySQL:
Cache Provider=System.Data.CData.MySQL;Cache Connection='Server=localhost;Port=3306;Database=cache;User=root;Password=123456';User=myUser;Password=myPassword;Security Token=myToken;

SQL Server

You can use the Microsoft .NET Framework Provider for SQL Server, included in the .NET Framework, to cache to SQL Server:

Cache Provider=System.Data.SqlClient;Cache Connection="Server=MyMACHINE\MyInstance;Database=SQLCACHE;User Id=root;Password=admin";User=MyUser;Password=MyPassword;

Oracle

To cache to Oracle, you can use the Oracle Data Provider for .NET, as shown in the following example:

Cache Provider=Oracle.DataAccess.Client;Cache Connection='User Id=scott;Password=tiger;Data Source=ORCL';User=MyUser;Password=MyPassword;

The Oracle Data Provider for .NET also requires the Oracle Database Client. When you download the Oracle Database Client, ensure that its bitness matches the bitness of your machine. When you install, select either the Runtime or Administrator installation type. The Instant Client is not sufficient.

PostgreSQL

To cache to PostgreSQL, you can use the CData ADO.NET Provider for PostgreSQL:
Cache Provider=System.Data.CData.PostgreSQL;Cache Connection='Server=localhost;Port=5432;Database=cache;User=postgres;Password=123456';User=myUser;Password=myPassword;Security Token=myToken;

CData Python Connector for Avalara

CacheDriver

The driver class of a JDBC driver. The specified driver is used to connect to the target database for all caching operations.

Data Type

string

Default Value

""

Remarks

You can cache to any database for which you have a JDBC driver, including CData JDBC drivers.

Note: You must add the JAR file of the specified JDBC driver to the classpath. For CData JDBC drivers, you can find this JAR file in the "lib" subfolder of that driver's installation directory.

You must also set the CacheConnection connection property to provide a connection string for the specified JDBC driver.

For Linux systems and macOS, you need to create a config.ini file on the installation path of the driver (site-packages/cdata). The config.ini file has the following format (the driver and the path of the JDBC driver):

[salesforce.cpython-38-x86_64-linux-gnu.so]
CLASSPATH = /home/usrname/Downloads/lib/cdata.jdbc.postgresql.jar

Examples

The following examples show how to cache to several major databases. For more information on the JDBC URL syntax and typical connection properties, see CacheConnection.

Derby and Java DB

Java DB is the Oracle distribution of Derby. You must add the Derby JDBC driver's JAR file, derbytools.jar, to your classpath to cache to Java DB.

The Derby JDBC driver's JAR file is bundled in db-derby-10.17.1.0-bin.zip, which you can download from this page. You can find derbytools.jar in the "lib" subfolder of this zip file.

After adding derbytools.jar to the classpath, you can cache to a Java DB database as follows:

jdbc:avalara:CacheDriver=org.apache.derby.jdbc.EmbeddedDriver;CacheConnection='jdbc:derby:sample';User=MyUser;Password=MyPassword;
To cache to an in-memory database, use a JDBC URL like the following:
jdbc:avalara:CacheDriver=org.apache.derby.jdbc.EmbeddedDriver;CacheConnection='jdbc:derby:memory';User=MyUser;Password=MyPassword;

SQLite

The following is a JDBC URL for the SQLite JDBC driver:

jdbc:avalara:CacheDriver=org.sqlite.JDBC;CacheConnection='jdbc:sqlite:C:/Temp/sqlite.db';User=MyUser;Password=MyPassword;

MySQL

The following is a JDBC URL for the CData JDBC Driver for MySQL:

  jdbc:avalara:Cache Driver=cdata.jdbc.mysql.MySQLDriver;Cache Connection='jdbc:mysql:Server=localhost;Port=3306;Database=cache;User=root;Password=123456';User=MyUser;Password=MyPassword;
  

SQL Server

The following JDBC URL uses the Microsoft JDBC Driver for SQL Server:

jdbc:avalara:Cache Driver=com.microsoft.sqlserver.jdbc.SQLServerDriver;Cache Connection='jdbc:sqlserver://localhost\sqlexpress:7437;user=sa;password=123456;databaseName=Cache';User=MyUser;Password=MyPassword;

Oracle

The following is a JDBC URL for the Oracle Thin Client:

jdbc:avalara:Cache Driver=oracle.jdbc.OracleDriver;CacheConnection='jdbc:oracle:thin:scott/tiger@localhost:1521:orcldb';User=MyUser;Password=MyPassword;
NOTE: If using a version of Oracle older than 9i, the cache driver will instead be oracle.jdbc.driver.OracleDriver .

PostgreSQL

The following JDBC URL uses the official PostgreSQL JDBC driver:

jdbc:avalara:CacheDriver=cdata.jdbc.postgresql.PostgreSQLDriver;CacheConnection='jdbc:postgresql:User=postgres;Password=admin;Database=postgres;Server=localhost;Port=5432;';User=MyUser;Password=MyPassword;

CData Python Connector for Avalara

CacheConnection

Specifies the connection string for the specified cache database.

Data Type

string

Default Value

""

Remarks

The target cache database is determined by a combination of this connection property and the CacheProvider connection property. Both properties are required to use the specified cache database.

The connection string specified in this connection property is passed directly to the specified in the CacheProvider connection property. Consult the documentation for the specified for more information on its available connection properties.

Examples of common cache database settings can be found below.

SQLite

MySQL

The following are typical connection properties:

  • Server: The IP address or domain name of the server hosting the MySQL database that you want to cache to.
  • Port: The port on the specified server where your MySQL instance is running.
  • Database: The name of the MySQL database that you want to cache to. Must match the name of a MySQL database hosted on the specified server.
  • User: The username of a user registered with the selected MySQL database.
  • Password: The password associated with the specified MySQL user.

SQL Server

The following are typical SQL Server connection properties:

  • Server: The name or network address of the computer running SQL Server. To connect to a named instance instead of the default instance, specify the host name and the instance name, separated by a backslash.
  • Port: The port on the specified server where your SQL Server instance is running.
  • Database: The name of the SQL Server database you want to cache to. Must match the name of a SQL Server database hosted on the specified server.
  • Integrated Security: To use the current Windows account for authentication, set this option to True. To authenticate with User and Password instead, set this option to False.
  • User Id: The username of a user registered with the selected SQL Server database. This property is only needed if you are not using integrated security.
  • Password: The password associated with the specified SQL Server user. This property is only needed if you are not using integrated security.

Oracle

The following are typical connection properties:

  • Data Source: The connect descriptor that identifies the Oracle database. This can be a TNS connect descriptor, an Oracle Net Services name that resolves to a connect descriptor, or, after version 11g, an Easy Connect naming (the host name of the Oracle server with an optional port and service name).

  • User Id: The username of a user registered with the selected Oracle database.
  • Password: The password associated with the specified Oracle user.

PostgreSQL

The following are typical connection properties:

  • Host: The address of the server hosting the PostgreSQL database.
  • Port: The port on the specified host server where your PostgreSQL database is hosted.
  • Database: The name of the PostgreSQL database you want to cache to. Must match the name of a PostgreSQL database hosted on the specified server.
  • User name: The username of a user registered with the selected PostgreSQL database.
  • Password: The password associated with the specified user.

CData Python Connector for Avalara

CacheLocation

Specifies the path to the cache when caching to a file.

Data Type

string

Default Value

"%APPDATA%\\CData\\Avalara Data Provider"

Remarks

The CacheLocation is a simple, file-based cache.

If left unspecified, the default location is %APPDATA%\\CData\\Avalara Data Provider, where %APPDATA% is set to the user's configuration directory:

Platform %APPDATA%
Windows The value of the APPDATA environment variable
Linux ~/.config

See Also

  • AutoCache: Set to implicitly create and maintain a cache for later offline use.
  • CacheMetadata: Set to persist the Avalara catalog in CacheLocation.

CData Python Connector for Avalara

CacheTolerance

Notes the tolerance, in seconds, for stale data in the specified cache database. Requires AutoCache to be set to True.

Data Type

int

Default Value

600

Remarks

When you execute a query for tables in the cache, the connector checks the time elapsed since the last update to the cache.

If the last update to the cache is older than the value of this connection property (measured in seconds), the connector refreshes the cache.

Otherwise, the connector returns data directly from the cache.

CData Python Connector for Avalara

Offline

Gets the data from the specified cache database instead of live Avalara data.

Data Type

bool

Default Value

false

Remarks

When this connection property is set to True, all queries execute against the cache database instead of the live Avalara data.

In this mode, some SQL operations like INSERT, UPDATE, DELETE, and CACHE are disabled.

CData Python Connector for Avalara

CacheMetadata

Determines whether the provider caches table metadata to a file-based cache database.

Data Type

bool

Default Value

false

Remarks

When this connection property is set to True, as you execute queries, table metadata in the Avalara catalog is cached to the cache database specified by CacheConnection and CacheProvider, or, if those connection properties are not set, to the user's home directory.

The location of your home directory varies by platform:

PlatformHome Directory
Windows %APPDATA%\\CData\\Avalara Data Provider
Mac ~/Library/Application Support/CData/Avalara Data Provider
Unix ~/.config/CData/Avalara Data Provider

A table's metadata is retrieved only once, when the table is queried for the first time.

When to Use CacheMetadata

When there are a large number of Avalara tables and columns for the connector to retrieve during metadata discovery, the connector may take a while to list all table metadata.

You may experience slow metadata retrieval when:

  • Your Avalara instance naturally has a large table count.
  • The connector has been configured, via its connection properties, to discover more tables than it would under its default configuration.
  • You make many short-lived connections to the connector.
With CacheMetadata enabled, all retrieved metadata is mirrored in the cache database. This means that any subsequent attempts by the connector to discover metadata are much faster, as this metadata is then read directly from the cache database, without needing to spend time requesting metadata from Avalara.

When Not to Use CacheMetadata

The connector automatically persists metadata in memory for up to an hour when you first discover the metadata for a table or view, so CacheMetadata is generally not necessary.

CacheMetadata is not ideal in scenarios where you are working with volatile metadata. The first time you query a table, the connector caches its metadata to the cache database file. This cache is not dynamically updated to reflect updates to the table schema, so you must delete and rebuild the cache database file to pick up new, changed, or deleted columns.

CData Python Connector for Avalara

Miscellaneous

This section provides a complete list of the Miscellaneous properties you can configure in the connection string for this provider.


PropertyDescription
GenerateSchemaFilesIndicates the user preference as to when schemas should be generated and saved.
IncludeAdjustedTransactionsWhether or not to include adjusted transactions in the transaction listing.
MaxRowsSpecifies the maximum number of rows returned for queries that do not include either aggregation or GROUP BY.
OtherSpecifies advanced connection properties for specialized scenarios. Use this property only under the guidance of our Support team to address specific issues.
PagesizeThe maximum number of results to return per page from Avalara when using client paging.
PseudoColumnsSpecifies the pseudocolumns to expose as table columns, expressed as a string in the format 'TableName=ColumnName;TableName=ColumnName'.
ReadonlyToggles read-only access to Avalara from the provider.
RTKSpecifies the runtime key for licensing the provider. If unset or invalid, the provider defaults to the standard licensing method. This property is only required in environments where the standard licensing method is unsupported or requires a runtime key.
TimeoutSpecifies the maximum time, in seconds, that the provider waits for a server response before throwing a timeout error.
UserDefinedViewsSpecifies a filepath to a JSON configuration file that defines custom views. The provider automatically detects and uses the views specified in this file.
CData Python Connector for Avalara

GenerateSchemaFiles

Indicates the user preference as to when schemas should be generated and saved.

Possible Values

Never, OnUse, OnStart, OnCreate

Data Type

string

Default Value

"Never"

Remarks

This property outputs schemas to .rsd files in the path specified by Location.

Available settings are the following:

  • Never: A schema file will never be generated.
  • OnUse: A schema file will be generated the first time a table is referenced, provided the schema file for the table does not already exist.
  • OnStart: A schema file will be generated at connection time for any tables that do not currently have a schema file.
  • OnCreate: A schema file will be generated by when running a CREATE TABLE SQL query.
Note that if you want to regenerate a file, you will first need to delete it.

Generate Schemas with SQL

When you set GenerateSchemaFiles to OnUse, the connector generates schemas as you execute SELECT queries. Schemas are generated for each table referenced in the query.

When you set GenerateSchemaFiles to OnCreate, schemas are only generated when a CREATE TABLE query is executed.

Generate Schemas on Connection

Another way to use this property is to obtain schemas for every table in your database when you connect. To do so, set GenerateSchemaFiles to OnStart and connect.

CData Python Connector for Avalara

IncludeAdjustedTransactions

Whether or not to include adjusted transactions in the transaction listing.

Data Type

bool

Default Value

false

Remarks

Whether or not to include adjusted transactions in the transaction listing.

CData Python Connector for Avalara

MaxRows

Specifies the maximum number of rows returned for queries that do not include either aggregation or GROUP BY.

Data Type

int

Default Value

-1

Remarks

The default value for this property, -1, means that no row limit is enforced unless the query explicitly includes a LIMIT clause. (When a query includes a LIMIT clause, the value specified in the query takes precedence over the MaxRows setting.)

Setting MaxRows to a whole number greater than 0 ensures that queries do not return excessively large result sets by default.

This property is useful for optimizing performance and preventing excessive resource consumption when executing queries that could otherwise return very large datasets.

CData Python Connector for Avalara

Other

Specifies advanced connection properties for specialized scenarios. Use this property only under the guidance of our Support team to address specific issues.

Data Type

string

Default Value

""

Remarks

This property allows advanced users to configure hidden properties for specialized situations, with the advice of our Support team. These settings are not required for normal use cases but can address unique requirements or provide additional functionality. To define multiple properties, use a semicolon-separated list.

Note: It is strongly recommended to set these properties only when advised by the Support team to address specific scenarios or issues.

Caching Configuration

PropertyDescription
CachePartial=TrueCaches only a subset of columns, which you can specify in your query.
QueryPassthrough=TruePasses the specified query to the cache database instead of using the SQL parser of the connector.

Integration and Formatting

PropertyDescription
DefaultColumnSizeSets the default length of string fields when the data source does not provide column length in the metadata. The default value is 2000.
ConvertDateTimeToGMT=TrueConverts date-time values to GMT, instead of the local time of the machine. The default value is False (use local time).
RecordToFile=filenameRecords the underlying socket data transfer to the specified file.

CData Python Connector for Avalara

Pagesize

The maximum number of results to return per page from Avalara when using client paging.

Data Type

int

Default Value

1000

Remarks

The Pagesize property affects the maximum number of results to return per page from Avalara when using client paging. A higher value will return more results per page, but may also cause a timeout exception. If you must use client paging on your server and have a fast server, setting a higher Pagesize may be desirable. We recommend testing various sizes against a large resultset to determine what works best in your use case.

CData Python Connector for Avalara

PseudoColumns

Specifies the pseudocolumns to expose as table columns, expressed as a string in the format 'TableName=ColumnName;TableName=ColumnName'.

Data Type

string

Default Value

""

Remarks

This property allows you to define which pseudocolumns the connector exposes as table columns.

To specify individual pseudocolumns, use the following format:

Table1=Column1;Table1=Column2;Table2=Column3

To include all pseudocolumns for all tables use:

*=*

CData Python Connector for Avalara

Readonly

Toggles read-only access to Avalara from the provider.

Data Type

bool

Default Value

false

Remarks

When set to True, the connector allows only SELECT queries. Attempting an INSERT, UPDATE, DELETE, or stored procedure query fails with an error message.

CData Python Connector for Avalara

RTK

Specifies the runtime key for licensing the provider. If unset or invalid, the provider defaults to the standard licensing method. This property is only required in environments where the standard licensing method is unsupported or requires a runtime key.

Data Type

string

Default Value

""

Remarks

This property is typically unnecessary, as most configurations support a standard licensing mechanism.

Warning: The value of this property takes precedence over all existing licensing information. To avoid licensing errors, ensure the provided runtime key is correct.

CData Python Connector for Avalara

Timeout

Specifies the maximum time, in seconds, that the provider waits for a server response before throwing a timeout error.

Data Type

int

Default Value

60

Remarks

The timeout applies to each individual communication with the server rather than the entire query or operation. For example, a query could continue running beyond 60 seconds if each paging call completes within the timeout limit.

Timeout is set to 60 seconds by default. To disable timeouts, set this property to 0.

Disabling the timeout allows operations to run indefinitely until they succeed or fail due to other conditions such as server-side timeouts, network interruptions, or resource limits on the server.

Note: Use this property cautiously to avoid long-running operations that could degrade performance or result in unresponsive behavior.

CData Python Connector for Avalara

UserDefinedViews

Specifies a filepath to a JSON configuration file that defines custom views. The provider automatically detects and uses the views specified in this file.

Data Type

string

Default Value

""

Remarks

UserDefinedViews allows you to define and manage custom views through a JSON-formatted configuration file called UserDefinedViews.json. These views are automatically recognized by the connector and enable you to execute custom SQL queries as if they were standard database views. The JSON file defines each view as a root element with a child element called "query", which contains the SQL query for the view.

For example:

{
	"MyView": {
		"query": "SELECT * FROM Transactions WHERE MyColumn = 'value'"
	},
	"MyView2": {
		"query": "SELECT * FROM MyTable WHERE Id IN (1,2,3)"
	}
}

You can use this property to define multiple views in a single file and specify the filepath. For example:

UserDefinedViews=C:\Path\To\UserDefinedViews.json
When you specify a view in UserDefinedViews, the connector only sees that view.

For further information, see User Defined Views.

CData Python Connector for Avalara

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    • ii) additions to the Program;
    where such changes and/or additions to the Program originate from and are Distributed by that particular Contributor. A Contribution "originates" from a Contributor if it was added to the Program by such Contributor itself or anyone acting on such Contributor's behalf. Contributions do not include changes or additions to the Program that are not Modified Works.
"Contributor" means any person or entity that Distributes the Program. "Licensed Patents" mean patent claims licensable by a Contributor which are necessarily infringed by the use or sale of its Contribution alone or when combined with the Program.

"Program" means the Contributions Distributed in accordance with this Agreement.

"Recipient" means anyone who receives the Program under this Agreement or any Secondary License (as applicable), including Contributors.

"Derivative Works" shall mean any work, whether in Source Code or other form, that is based on (or derived from) the Program and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship.

"Modified Works" shall mean any work in Source Code or other form that results from an addition to, deletion from, or modification of the contents of the Program, including, for purposes of clarity any new file in Source Code form that contains any contents of the Program. Modified Works shall not include works that contain only declarations, interfaces, types, classes, structures, or files of the Program solely in each case in order to link to, bind by name, or subclass the Program or Modified Works thereof.

"Distribute" means the acts of a) distributing or b) making available in any manner that enables the transfer of a copy.

"Source Code" means the form of a Program preferred for making modifications, including but not limited to software source code, documentation source, and configuration files.

"Secondary License" means either the GNU General Public License, Version 2.0, or any later versions of that license, including any exceptions or additional permissions as identified by the initial Contributor.

2. GRANT OF RIGHTS

  • a) Subject to the terms of this Agreement, each Contributor hereby grants Recipient a non-exclusive, worldwide, royalty-free copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, Distribute and sublicense the Contribution of such Contributor, if any, and such Derivative Works.
  • b) Subject to the terms of this Agreement, each Contributor hereby grants Recipient a non-exclusive, worldwide, royalty-free patent license under Licensed Patents to make, use, sell, offer to sell, import and otherwise transfer the Contribution of such Contributor, if any, in Source Code or other form. This patent license shall apply to the combination of the Contribution and the Program if, at the time the Contribution is added by the Contributor, such addition of the Contribution causes such combination to be covered by the Licensed Patents. The patent license shall not apply to any other combinations which include the Contribution. No hardware per se is licensed hereunder.
  • c) Recipient understands that although each Contributor grants the licenses to its Contributions set forth herein, no assurances are provided by any Contributor that the Program does not infringe the patent or other intellectual property rights of any other entity. Each Contributor disclaims any liability to Recipient for claims brought by any other entity based on infringement of intellectual property rights or otherwise. As a condition to exercising the rights and licenses granted hereunder, each Recipient hereby assumes sole responsibility to secure any other intellectual property rights needed, if any. For example, if a third party patent license is required to allow Recipient to Distribute the Program, it is Recipient's responsibility to acquire that license before distributing the Program.
  • d) Each Contributor represents that to its knowledge it has sufficient copyright rights in its Contribution, if any, to grant the copyright license set forth in this Agreement.
  • e) Notwithstanding the terms of any Secondary License, no Contributor makes additional grants to any Recipient (other than those set forth in this Agreement) as a result of such Recipient's receipt of the Program under the terms of a Secondary License (if permitted under the terms of Section 3).

3. REQUIREMENTS 3.1 If a Contributor Distributes the Program in any form, then:

  • a) the Program must also be made available as Source Code, in accordance with section 3.2, and the Contributor must accompany the Program with a statement that the Source Code for the Program is available under this Agreement, and informs Recipients how to obtain it in a reasonable manner on or through a medium customarily used for software exchange; and
  • b) the Contributor may Distribute the Program under a license different than this Agreement, provided that such license:
    • i) effectively disclaims on behalf of all other Contributors all warranties and conditions, express and implied, including warranties or conditions of title and non-infringement, and implied warranties or conditions of merchantability and fitness for a particular purpose;
    • ii) effectively excludes on behalf of all other Contributors all liability for damages, including direct, indirect, special, incidental and consequential damages, such as lost profits;
    • iii) does not attempt to limit or alter the recipients' rights in the Source Code under section 3.2; and
    • iv) requires any subsequent distribution of the Program by any party to be under a license that satisfies the requirements of this section 3.
3.2 When the Program is Distributed as Source Code:
  • a) it must be made available under this Agreement, or if the Program (i) is combined with other material in a separate file or files made available under a Secondary License, and (ii) the initial Contributor attached to the Source Code the notice described in Exhibit A of this Agreement, then the Program may be made available under the terms of such Secondary Licenses, and
  • b) a copy of this Agreement must be included with each copy of the Program.
3.3 Contributors may not remove or alter any copyright, patent, trademark, attribution notices, disclaimers of warranty, or limitations of liability (‘notices') contained within the Program from any copy of the Program which they Distribute, provided that Contributors may add their own appropriate notices.

4. COMMERCIAL DISTRIBUTION Commercial distributors of software may accept certain responsibilities with respect to end users, business partners and the like. While this license is intended to facilitate the commercial use of the Program, the Contributor who includes the Program in a commercial product offering should do so in a manner which does not create potential liability for other Contributors. Therefore, if a Contributor includes the Program in a commercial product offering, such Contributor ("Commercial Contributor") hereby agrees to defend and indemnify every other Contributor ("Indemnified Contributor") against any losses, damages and costs (collectively "Losses") arising from claims, lawsuits and other legal actions brought by a third party against the Indemnified Contributor to the extent caused by the acts or omissions of such Commercial Contributor in connection with its distribution of the Program in a commercial product offering. The obligations in this section do not apply to any claims or Losses relating to any actual or alleged intellectual property infringement. In order to qualify, an Indemnified Contributor must: a) promptly notify the Commercial Contributor in writing of such claim, and b) allow the Commercial Contributor to control, and cooperate with the Commercial Contributor in, the defense and any related settlement negotiations. The Indemnified Contributor may participate in any such claim at its own expense.

For example, a Contributor might include the Program in a commercial product offering, Product X. That Contributor is then a Commercial Contributor. If that Commercial Contributor then makes performance claims, or offers warranties related to Product X, those performance claims and warranties are such Commercial Contributor's responsibility alone. Under this section, the Commercial Contributor would have to defend claims against the other Contributors related to those performance claims and warranties, and if a court requires any other Contributor to pay any damages as a result, the Commercial Contributor must pay those damages.

5. NO WARRANTY EXCEPT AS EXPRESSLY SET FORTH IN THIS AGREEMENT, AND TO THE EXTENT PERMITTED BY APPLICABLE LAW, THE PROGRAM IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, EITHER EXPRESS OR IMPLIED INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OR CONDITIONS OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Each Recipient is solely responsible for determining the appropriateness of using and distributing the Program and assumes all risks associated with its exercise of rights under this Agreement, including but not limited to the risks and costs of program errors, compliance with applicable laws, damage to or loss of data, programs or equipment, and unavailability or interruption of operations.

6. DISCLAIMER OF LIABILITY EXCEPT AS EXPRESSLY SET FORTH IN THIS AGREEMENT, AND TO THE EXTENT PERMITTED BY APPLICABLE LAW, NEITHER RECIPIENT NOR ANY CONTRIBUTORS SHALL HAVE ANY LIABILITY FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING WITHOUT LIMITATION LOST PROFITS), HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OR DISTRIBUTION OF THE PROGRAM OR THE EXERCISE OF ANY RIGHTS GRANTED HEREUNDER, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

7. GENERAL If any provision of this Agreement is invalid or unenforceable under applicable law, it shall not affect the validity or enforceability of the remainder of the terms of this Agreement, and without further action by the parties hereto, such provision shall be reformed to the minimum extent necessary to make such provision valid and enforceable.

If Recipient institutes patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Program itself (excluding combinations of the Program with other software or hardware) infringes such Recipient's patent(s), then such Recipient's rights granted under Section 2(b) shall terminate as of the date such litigation is filed.

All Recipient's rights under this Agreement shall terminate if it fails to comply with any of the material terms or conditions of this Agreement and does not cure such failure in a reasonable period of time after becoming aware of such noncompliance. If all Recipient's rights under this Agreement terminate, Recipient agrees to cease use and distribution of the Program as soon as reasonably practicable. However, Recipient's obligations under this Agreement and any licenses granted by Recipient relating to the Program shall continue and survive.

Everyone is permitted to copy and distribute copies of this Agreement, but in order to avoid inconsistency the Agreement is copyrighted and may only be modified in the following manner. The Agreement Steward reserves the right to publish new versions (including revisions) of this Agreement from time to time. No one other than the Agreement Steward has the right to modify this Agreement. The Eclipse Foundation is the initial Agreement Steward. The Eclipse Foundation may assign the responsibility to serve as the Agreement Steward to a suitable separate entity. Each new version of the Agreement will be given a distinguishing version number. The Program (including Contributions) may always be Distributed subject to the version of the Agreement under which it was received. In addition, after a new version of the Agreement is published, Contributor may elect to Distribute the Program (including its Contributions) under the new version.

Except as expressly stated in Sections 2(a) and 2(b) above, Recipient receives no rights or licenses to the intellectual property of any Contributor under this Agreement, whether expressly, by implication, estoppel or otherwise. All rights in the Program not expressly granted under this Agreement are reserved. Nothing in this Agreement is intended to be enforceable by any entity that is not a Contributor or Recipient. No third-party beneficiary rights are created under this Agreement.

Exhibit A – Form of Secondary Licenses Notice "This Source Code may also be made available under the following Secondary Licenses when the conditions for such availability set forth in the Eclipse Public License, v. 2.0 are satisfied: {name license(s), version(s), and exceptions or additional permissions here}."

Simply including a copy of this Agreement, including this Exhibit A is not sufficient to license the Source Code under Secondary Licenses.

If it is not possible or desirable to put the notice in a particular file, then You may include the notice in a location (such as a LICENSE file in a relevant directory) where a recipient would be likely to look for such a notice.

You may add additional accurate notices of copyright ownership.

GNU Classpath

Classpath is distributed under the terms of the GNU General Public License with the following clarification and special exception.

Linking this library statically or dynamically with other modules is making a combined work based on this library. Thus, the terms and conditions of the GNU General Public License cover the whole combination.

As a special exception, the copyright holders of this library give you permission to link this library with independent modules to produce an executable, regardless of the license terms of these independent modules, and to copy and distribute the resulting executable under terms of your choice, provided that you also meet, for each linked independent module, the terms and conditions of the license of that module. An independent module is a module which is not derived from or based on this library. If you modify this library, you may extend this exception to your version of the library, but you are not obligated to do so. If you do not wish to do so, delete this exception statement from your version.

As such, it can be used to run, create and distribute a large class of applications and applets. When GNU Classpath is used unmodified as the core class library for a virtual machine, compiler for the java languge, or for a program written in the java programming language it does not affect the licensing for distributing those programs directly.

OpenJDK Assembly Exception

The OpenJDK source code made available by Oracle America, Inc. (Oracle) at openjdk.java.net ("OpenJDK Code") is distributed under the terms of the GNU General Public License <http://www.gnu.org/copyleft/gpl.html> version 2 only ("GPL2"), with the following clarification and special exception.

Linking this OpenJDK Code statically or dynamically with other code is making a combined work based on this library. Thus, the terms and conditions of GPL2 cover the whole combination.

As a special exception, Oracle gives you permission to link this OpenJDK Code with certain code licensed by Oracle as indicated at http://openjdk.java.net/legal/exception-modules-2007-05-08.html ("Designated Exception Modules") to produce an executable, regardless of the license terms of the Designated Exception Modules, and to copy and distribute the resulting executable under GPL2, provided that the Designated Exception Modules continue to be governed by the licenses under which they were offered by Oracle.

As such, it allows licensees and sublicensees of Oracle's GPL2 OpenJDK Code to build an executable that includes those portions of necessary code that Oracle could not provide under GPL2 (or that Oracle has provided under GPL2 with the Classpath exception). If you modify or add to the OpenJDK code, that new GPL2 code may still be combined with Designated Exception Modules if the new code is made subject to this exception by its copyright holder.

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