CData Python Connector for Zoho Projects

Build 26.0.9655

CData Python Connector for Zoho Projects

Overview

The CData Python Connector for Zoho Projects allows developers to write Python scripts with connectivity to Zoho Projects. The connector wraps the complexity of accessing Zoho Projects 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 Zoho Projects.
  • 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 Zoho Projects.

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 Zoho Projects data to tools such as Pandas or Petl.

SQLAlchemy ORM

SQLAlchemy can be leveraged to model the tables in Zoho Projects 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 Zoho Projects entities.

Connection String Options

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

CData Python Connector for Zoho Projects

Getting Started

Connecting to Zoho Projects

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 Zoho Projects can be installed and used in Python 3.10 or newer.

Zoho Projects Version Support

The connector leverages the Zoho Projects API (both restapi and the v3 API are used) to enable bidirectional access to project management data from Zoho Projects.

See Also

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

CData Python Connector for Zoho Projects

Package Installation

Dependencies

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

Installation

The CData Python Connector for Zoho Projects 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_zohoprojects_connector-26.0.9655-cp310-abi3-win_amd64.whl

Linux:

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

macOS:

pip install cdata_zohoprojects_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_zohoprojects_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_zohoprojects" 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_zohoprojects folder is trivial to find:

import os
import cdata.zohoprojects
path = os.path.abspath(cdata.zohoprojects.__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-zohoprojects-connector

CData Python Connector for Zoho Projects

Establishing a Connection

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

  1. Import the module as follows:
    import cdata.zohoprojects 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("InitiateOAuth=GETANDREFRESH;")

Connecting to Zoho Projects

Set Region to the Top Level Domain (TLD) in the server URL.

Authenticating to Zoho Projects

Zoho Projects provides two ways to connect to data:

  • To connect to your own local data via the desktop (non-browser connection), use the CData-supplied embedded OAuth application.
  • To connect to shared data over the network (browser connection), use a custom OAuth application.

The following subsections describe how to authenticate to Zoho Projects from three common authentication flows:

  • Desktop: a connection to a server on the user's local machine, frequently used for testing and prototyping. Authenticated via either embedded OAuth or custom OAuth.
  • Web: access to data via a shared website. Authenticated via custom OAuth only.
  • Headless Server: a dedicated computer that provides services to other computers and their users, which is configured to operate without a monitor and keyboard. Authenticated via embedded OAuth or custom OAuth.

For information about how to create a custom OAuth application, and why you might want to create one even for auth flows that have embedded OAuth credentials, see Creating a Custom OAuth Application.

For a complete list of connection string properties available in Zoho Projects, see Connection.

Desktop Applications

CData provides an embedded OAuth application that simplifies authentication at the desktop. You can also authenticate from the desktop via a custom OAuth application, which you configure and register at the Zoho Projects console. For further information, see Creating a Custom OAuth Application.

Before you connect, set the following variables:

  • InitiateOAuth: GETANDREFRESH. Used to automatically get and refresh the OAuthAccessToken.
  • Custom OAuth applications only:
    • OAuthClientId: The client Id assigned when you registered your custom OAuth application.
    • OAuthClientSecret: The client secret assigned when you registered your custom OAuth application.
    • CallbackURL: The redirect URI defined when you registered your custom OAuth application.

When you connect, the connector opens Zoho Projects's OAuth endpoint in your default browser. Log in and grant permissions to the application.

After you grant permissions to the application, the connector completes the OAuth process:

  1. The connector obtains an access token from Zoho Projects and uses it to request data.
  2. The OAuth values are saved in the path specified in OAuthSettingsLocation. These values persist across connections.

When the access token expires, the connector refreshes it automatically.

Web Applications

Authenticating via the Web requires you to create and register a custom OAuth application with Zoho Projects, as described in Creating a Custom OAuth Application. You can then use the connector to get and manage the OAuth token values.

This section describes how to get the OAuth access token, how to have the driver refresh the OAuth access token automatically, and how to refresh the OAuth access token manually.

Get the OAuth access token:

  1. Set the following connection properties to obtain the OAuthAccessToken:

  2. Call stored procedures to complete the OAuth exchange:
    • Call the GetOAuthAuthorizationURL stored procedure. Set the AuthMode input to WEB and the CallbackURL to the Redirect URI you specified in your application settings. The stored procedure returns the URL to the OAuth endpoint.
    • Navigate to the URL that the stored procedure returned in Step 1. Log in and authorize the web application. You are redirected back to the callback URL.
    • Call the GetOAuthAccessToken stored procedure. Set the AuthMode input to WEB. Set the Verifier input to the code parameter in the query string of the redirect URI.

After you obtain the access and refresh tokens, you can connect to data and refresh the OAuth access token automatically.

Automatic refresh of the OAuth access token:

To have the connector automatically refresh the OAuth access token, do the following:

  1. The first time you connect to data, set the following connection parameters:
  2. On subsequent data connections, set the following:

Manual refresh of the OAuth access token:

The only value needed to manually refresh the OAUth access token is the OAuth refresh token.

  1. To manually refresh the OAuthAccessToken after the ExpiresIn period (returned by GetOAuthAccessToken) has elapsed, call the RefreshOAuthAccessToken stored procedure.
  2. Set the following connection properties:

  3. Call RefreshOAuthAccessToken with OAuthRefreshToken set to the OAuth refresh token returned by GetOAuthAccessToken.
  4. After the new tokens have been retrieved, set the OAuthAccessToken property to the value returned by RefreshOAuthAccessToken. This opens a new connection.

Store the OAuth refresh token so that you can use it to manually refresh the OAuth access token after it has expired.

Headless Machines

If you need to log in to a resource that resides on a headless machine, you must authenticate on another device that has an internet browser. You can do this in either of the following ways:

  • Option 1: Obtain the OAuthVerifier value.
  • Option 2: Install the connector on a machine with an internet browser and transfer the OAuth authentication values after you authenticate through the usual browser-based flow.

After you execute either Option 1 or Option 2, configure the driver to automatically refresh the access token on the headless machine.

Option 1: Obtaining and Exchanging a Verifier Code

To obtain a verifier code, you must authenticate at the OAuth authorization URL. Do the following:

  1. Authenticate from the machine with an internet browser, and obtain the OAuthVerifier connection property.

    If you are using the embedded OAuth application, call the GetOAuthAuthorizationURL stored procedure. Open the URL returned by the stored procedure in a browser.

    If you are using a custom OAuth application, set the following properties:

  2. Call the GetOAuthAuthorizationURL stored procedure. The stored procedure returns the CallbackURL established when the custom OAuth application was registered. (See Creating a Custom OAuth Application.)

    Copy this URL and paste it into a new browser tab.

  3. Log in and grant permissions to the connector. The OAuth application redirects you the redirect URI, with a parameter called code appended. Note the value of this parameter; you will need it later, to configure the OAuthVerifier connection property.

  4. Exchange the OAuth verifier code for OAuth refresh and access tokens. On the headless machine, set the following connection properties to obtain the OAuth authentication values:

    • InitiateOAuth: REFRESH.
    • OAuthVerifier: The noted verifier code (the value of the code parameter in the redirect URI).
    • OAuthSettingsLocation: Persist the encrypted OAuth authentication values to the specified file.
    • Custom OAuth applications only:

  5. Test the connection to generate the OAuth settings file.

  6. After you re-set the following properties, you are ready to connect:

    • InitiateOAuth: REFRESH.
    • OAuthSettingsLocation: The file containing the encrypted OAuth authentication values. To enable the automatic refreshing of the access token, be sure that this file gives read and write permissions to the connector.
    • Custom OAuth applications only:
      • OAuthClientId: The client Id assigned when you registered your application.
      • OAuthClientSecret: The client secret assigned when you registered your application.

Option 2: Transferring OAuth Settings

Prior to connecting on a headless machine, you must install and create a connection with the driver on a device that supports an internet browser. Set the connection properties as described above in "Desktop Applications".

After completing the instructions in "Desktop Applications", the resulting authentication values are encrypted and written to the path specified by OAuthSettingsLocation. The default filename is OAuthSettings.txt.

Test the connection to generate the OAuth settings file, then copy the OAuth settings file to your headless machine.

To connect to data via the headless machine, set the following connection properties:

  • InitiateOAuth: REFRESH
  • OAuthSettingsLocation: The path to the OAuth settings file you copied from the machine with the browser. To enable automatic refreshing of the access token, ensure that this file gives read and write permissions to the connector.
  • Custom OAuth applications only:
    • OAuthClientId: The client Id assigned when you registered your custom OAuth application.
    • OAuthClientSecret: The client secret assigned when you registered your custom OAuth application.

CData Python Connector for Zoho Projects

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 Zoho Projects 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:
    [zohoprojects.cpython-311-x86_64-linux-gnu.so]
  • For Mac:
    [zohoprojects.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.zohoprojects 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 Zoho Projects

Creating a Custom OAuth Application

Creating a Custom OAuth Application

CData embeds OAuth Application Credentials with CData branding that can be used when connecting to Zoho Projects via a desktop application or a headless machine. If you want to use the embedded OAuth application, all you need to do to connect is to:

  • get and set the OAuthAccessToken, and
  • set the necessary configuration parameters.

(For information on getting and setting the OAuthAccessToken and other configuration parameters, see the Desktop Authentication section of "Establishing a Connection".)

However, you must create a custom OAuth application to connect to Zoho Projects via the Web. And since custom OAuth applications seamlessly support all three commonly-used auth flows, you might want to create custom OAuth applications (use your own OAuth Application Credentials) for those auth flows anyway.

Custom OAuth applications are useful if you want to:

  • control branding of the authentication dialog;
  • control the redirect URI that the application redirects the user to after the user authenticates; or
  • customize the permissions that you are requesting from the user.

Procedure

To create a custom OAuth application and obtain the OAuthClientId, OAuthClientSecret, and CallbackURL:

  1. Navigate to the Zoho Developer Console.
  2. Click Add Client, then Server-Based Application.
  3. Enter the client name, homepage URL, and redirect URL.
  4. If the user will connect via either desktop or Web, set a callback URL:
    • For desktop applications, set the callback URL to http://localhost:33333, or another port number of your choice.
    • For Web applications, set a callback URL to specify what page the user should land on after they grant your application access.
  5. Click Create.

CData Python Connector for Zoho Projects

Changelog

General Changes

DateVersionSourceCategoryTypeDescription
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.
2026-01-1325.0.9509GeneralAdded
  • 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.
2025-10-3025.0.9434PythonChanged
  • 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.
2025-07-0725.0.9319Zoho ProjectsRemoved
  • Removed the AccountsServer and APIDomain connection properties, which had previously been deprecated.
2025-07-0325.0.9315Zoho ProjectsAdded
  • Added Scope connection property.
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).
2025-02-1524.0.9177GeneralAdded
  • 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.
2024-11-2724.0.9097GeneralAdded
  • Added ThreadId to LogModule output. Logfile lines now include the Thread ID associated with the action being performed.
2024-06-1924.0.8936Zoho ProjectsRemoved
  • Removed the StartDate, EndDate and ViewType columns from the Timelogs and MyTimeLogs views.
2024-06-1924.0.8936Zoho ProjectsAdded
  • Users can use the operators >,>=,<,<=,= for the Date column in the Timelogs and MyTimelogs views.
2024-06-1924.0.8936Zoho ProjectsChanged
  • The Date column in the Timelogs and MyTimelogs views now return the actual value from the API instead of mirroring the criteria value.
2024-06-0524.0.8922PythonAdded
  • Added support for Python 3.12.
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
2023-11-0923.0.8713Zoho ProjectsAdded
  • New custom_date values is added for the ViewType column in the MyTimelogs and Timelogs tables. The StartDate and EndDate columns that are requird for this ViewType were also added in.
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.
2023-04-1923.0.8509Zoho ProjectsAdded
  • Added ProjectId and ProjectName columns to MyTimelogs view.
2023-04-0623.0.8496Zoho ProjectsAdded
  • Added Region connection property, which determines the domain based on the value.
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.
2022-05-2422.0.8179Zoho ProjectsChanged
  • Changed provider name to Zoho Projects.
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 Zoho Projects

Using the Connector

This section provides a walk-through for writing Zoho Projects 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 Zoho Projects, see Package Installation and Establishing a Connection.

For information on how to connect with the zohoprojects.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 Zoho Projects 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 Zoho Projects

Connecting

Connecting with the cdata.zohoprojects 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.zohoprojects as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;")

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

CData Python Connector for Zoho Projects

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, Name FROM Portals")
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, Name FROM Portals WHERE Id = ?"
params = ["123456"]
cur = conn.execute(cmd, params)
rs = cur.fetchall()
for row in rs:
	print(row)

CData Python Connector for Zoho Projects

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 Portals (Id, Name) 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 Portals SET Name = ? WHERE Id = ?"
params = ["John", "6"]
cur = conn.execute(cmd, params)
print("Records affected: ", cur.rowcount)

Delete

The following example removes an existing record from the table:

cmd = "DELETE FROM Portals WHERE Id = ?"
params = ["6"]
cur = conn.execute(cmd, params)
print("Records affected: ", cur.rowcount)

CData Python Connector for Zoho Projects

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 ApproveTimelog LogId = ?"
params = ["78910"]
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 = ["78910"]
cur.callproc("ApproveTimelog", params)

CData Python Connector for Zoho Projects

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 Zoho Projects Integration Quickstarts

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

CData Python Connector for Zoho Projects

From SQLAlchemy

The CData Python Connector for Zoho Projects 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 Zoho Projects 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 Zoho Projects

Connecting

Connecting With a Dialect URL

Establishing a connection using SQLAlchemy requires a specific URL format.
from sqlalchemy import create_engine
engine = create_engine("zohoprojects:///?InitiateOAuth=GETANDREFRESH;")

For SQLAlchemy 2.0, the dialect name is zohoprojects_2. To establish a connection, use the following URL format:

from sqlalchemy import create_engine
engine = create_engine("zohoprojects_2:///?InitiateOAuth=GETANDREFRESH;")

CData Python Connector for Zoho Projects

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 Portals(Base):
	__tablename__ = "Portals"
	Id = Column(String, primary_key=True)
	Id = Column(String)
	Name = 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)
Portals = abase.classes.Portals

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)
Portals_table = Table("Portals", meta)
insp.reflect_table(Portals_table, ["Id","Name"])

CData Python Connector for Zoho Projects

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("zohoprojects:///?InitiateOAuth=GETANDREFRESH;")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Portals).filter_by(Id="123456"):
	print("Id: ", instance.Id)
	print("Id: ", instance.Id)
	print("Name: ", instance.Name)
	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:
Portals_table = Portals.metadata.tables["Portals"]
for instance in session.execute(Portals_table.select().where(Portals_table.c.Id == "123456")):
	print("Id: ", instance.Id)
	print("FullName: ", instance.Name)
	print("City: ", instance.BillingCity)
	print("---------")

CData Python Connector for Zoho Projects

Executing JOINs

Implicit Joining

If mapped classes of related Zoho Projects 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 Zoho Projects

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(Portals).order_by(Portals.AnnualRevenue)
for instance in rs:
	print("Id: ", instance.Id)
	print("Id: ", instance.Id)
	print("Name: ", instance.Name)
	print("---------")

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

rs = session.execute(Portals_table.select().order_by(Portals_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(Portals.Id).label("CustomCount"), Portals.Id).group_by(Portals.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(Portals_table.select().with_only_columns([func.count(Portals_table.c.Id).label("CustomCount"), Portals_table.c.Id]).group_by(Portals_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(Portals).limit(25).offset(100)
for instance in rs:
	print("Id: ", instance.Id)
	print("Id: ", instance.Id)
	print("Name: ", instance.Name)
	print("---------")

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

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

CData Python Connector for Zoho Projects

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(Portals.Id).label("CustomCount"), Portals.Id).group_by(Portals.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(Portals_table.select().with_only_columns([func.count(Portals_table.c.Id).label("CustomCount"), Portals_table.c.Id])group_by(Portals_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(Portals.AnnualRevenue).label("CustomSum"), Portals.Id).group_by(Portals.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(Portals_table.select().with_only_columns([func.sum(Portals_table.c.AnnualRevenue).label("CustomSum"), Portals_table.c.Id]).group_by(Portals_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(Portals.AnnualRevenue).label("CustomAvg"), Portals.Id).group_by(Portals.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(Portals_table.select().with_only_columns([func.avg(Portals_table.c.AnnualRevenue).label("CustomAvg"), Portals_table.c.Id]).group_by(Portals_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(Portals.AnnualRevenue).label("CustomMax"), func.min(Portals.AnnualRevenue).label("CustomMin"), Portals.Id).group_by(Portals.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(Portals_table.select().with_only_columns([func.max(Portals_table.c.AnnualRevenue).label("CustomMax"), func.min(Portals_table.c.AnnualRevenue).label("CustomMin"), Portals_table.c.Id]).group_by(Portals_table.c.Id))
for instance in rs:

CData Python Connector for Zoho Projects

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:

Portals_table = Portals.metadata.tables["Portals"]

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(Portals_table.insert(), {"Id": "Jon Doe", "Name": "John"})

Update

The following example modifies an existing record in the table:

session.execute(Portals_table.update().where(Portals_table.c.Id == "6").values(Id="Jon Doe", Name="John"))

Delete

The following example removes an existing record from the table:

session.execute(Portals_table.delete().where(Portals_table.c.Id == "6"))

CData Python Connector for Zoho Projects

From Pandas

When combined with the connector, Pandas can be used to generate data frames that contain your Zoho Projects 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("zohoprojects:///?InitiateOAuth=GETANDREFRESH;")

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,
	   Name,
     $exNumericCol;
	FROM Portals;""", 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"], "Name": ["John"]})
df.to_sql("Portals", con=engine, if_exists="append", index=False)

CData Python Connector for Zoho Projects

From Matplotlib

Matplotlib contains a number of tools that can graphically model Zoho Projects 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 Zoho Projects 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 Zoho Projects

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 Zoho Projects, you can use the connector's connect function to create a connection using a valid Zoho Projects connection string. If you prefer not to use a direct connection, you can use a SQLAlchemy engine.
import petl as etl
import cdata.zohoprojects as mod
cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;")

Extract, Transform, and Load the Zoho Projects Data

Create a SQL query string and store the query results in a DataFrame.
sql = "SELECT	Id, Name FROM Portals "
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 Zoho Projects tables using Petl's appenddb function.
table1 = [['Id','Name'],['Jon Doe','John']]
etl.appenddb(table1,cnxn,'Portals')

CData Python Connector for Zoho Projects

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 Zoho Projects

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.zohoprojects as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_tables"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

Views


import cdata.zohoprojects as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;")
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 Zoho Projects

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.zohoprojects as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_tablecolumns WHERE TableName = 'Portals'"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

CData Python Connector for Zoho Projects

Procedures

Procedures

A system table called "sys_procedures" is queried to obtain the available stored procedures that are executed:
import cdata.zohoprojects as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;")
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.zohoprojects as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'ApproveTimelog'"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

CData Python Connector for Zoho Projects

SQL Compliance

The CData Python Connector for Zoho Projects 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 Zoho Projects 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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Portals
  2. Rename a column:
    SELECT [Name] AS MY_Name FROM Portals
  3. Cast a column's data as a different data type:
    SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM Portals
  4. Search data:
    SELECT * FROM Portals WHERE Id = '123456'
  5. Return the number of items matching the query criteria:
    SELECT COUNT(*) AS MyCount FROM Portals 
  6. Return the number of unique items matching the query criteria:
    SELECT COUNT(DISTINCT Name) FROM Portals 
  7. Return the unique items matching the query criteria:
    SELECT DISTINCT Name FROM Portals 
  8. Sort a result set in ascending order:
    SELECT Id, Name FROM Portals  ORDER BY Name ASC
  9. Restrict a result set to the specified number of rows:
    SELECT Id, Name FROM Portals 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 Portals WHERE Id = @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 Zoho Projects.

    SELECT * FROM Portals WHERE UserType = 'Active'
    

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 Zoho Projects

Aggregate Functions

COUNT

Returns the number of rows matching the query criteria.

SELECT COUNT(*) FROM Portals WHERE Id = '123456'

COUNT(DISTINCT)

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

SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Portals WHERE Id = '123456'

AVG

Returns the average of the column values.

SELECT Name, AVG(AnnualRevenue) FROM Portals WHERE Id = '123456'  GROUP BY Name

MIN

Returns the minimum column value.

SELECT MIN(AnnualRevenue), Name FROM Portals WHERE Id = '123456' GROUP BY Name

MAX

Returns the maximum column value.

SELECT Name, MAX(AnnualRevenue) FROM Portals WHERE Id = '123456' GROUP BY Name

SUM

Returns the total sum of the column values.

SELECT SUM(AnnualRevenue) FROM Portals WHERE Id = '123456'

CData Python Connector for Zoho Projects

JOIN Queries

The CData Python Connector for Zoho Projects 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 t.Id, t.Name, t.Key, c.Content, c.AddedPersonName FROM Tasks t INNER JOIN TaskComments c ON t.Id = c.TaskId

Left Join

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

 SELECT t.Id, t.Name, t.Key, c.Content, c.AddedPersonName FROM Tasks t LEFT JOIN TaskComments c ON t.Id = c.TaskId

CData Python Connector for Zoho Projects

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 Portals

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, Name, RANK() OVER (ORDER BY Name) AS Rank FROM Portals

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

SELECT Id, Name, RANK() OVER (PARTITION BY Id ORDER BY Name) AS Rank FROM Portals

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, Name, DENSE_RANK() OVER (PARTITION BY Id ORDER BY Name) AS Rank FROM Portals

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

SELECT Id, Name, DENSE_RANK() OVER (PARTITION BY Id ORDER BY Name) AS Rank FROM Portals

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 Zoho Projects

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 Zoho Projects

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 Portals (Name) VALUES ('John')

CData Python Connector for Zoho Projects

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 Portals SET Name='John' WHERE Id = @myId

CData Python Connector for Zoho Projects

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 Portals WHERE Id = @myId

CData Python Connector for Zoho Projects

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 Portals

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

CACHE CachedPortals SELECT * FROM Portals

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 CachedPortals SELECT * FROM Portals 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 Name even though the cache table CachedPortals has all the columns in Portals.

CACHE CachedPortals SCHEMA ONLY SELECT * FROM Portals
CACHE CachedPortals SELECT Id, Name FROM Portals

CData Python Connector for Zoho Projects

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 Zoho Projects

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 Zoho Projects

Data Model

Overview

The connector exposes all of the portals and projects tied to your Zoho Projects account, so you can access all of your Zoho Projects data with a single connection.

You can access:

  • portal-specific data
  • project-specific data
  • data pertaining to all portals

User Portals

The connector models each portal associated with your account as a catalog, named after the portal, containing a portal-specific schema called "ZohoProjects".

The User Portals section is a generic example of such a portal-specific schema.

User Projects

The connector models each portal associated with your account as a catalog, named after the portal. For every project in each of these catalogs, there is a project-specific schema, which is named after the project.

The User Projects section is a generic example of such a project-specific schema.

All Portals

The All Portals section contains data pertaining to all portals tied to your account.

CData Python Connector for Zoho Projects

User Portals

Overview

The connector models each portal associated with your account as a catalog, named after the portal, containing a portal-specific schema called "ZohoProjects".

Tables

Tables describes the available tables. Tables are statically defined to model Zoho Projects entities such as contacts, teams, projects, etc.

Views

Views describes the available views. Views are read-only tables that are statically defined to model Zoho Projects entities such as project and task layouts.

CData Python Connector for Zoho Projects

Tables

The connector models the entities for which Zoho Projects provides full or limited CRUD support as tables.

It models each portal tied to your account as a schema with the following tables.

Navigate to an individual table's page for a breakdown of its columns, as well as its supported filters and CRUD operations.

CData Python Connector for Zoho Projects Tables

Name Description
Contacts Fetches all client contacts from a portal.
PortalClients Returns the list of client companies in the portal.
ProjectGroups Gets all the groups for the specified project.
Projects Gets all the projects for the logged in user.
Tags Fetches all the tags present in a specific portal.
Teams Fetch the team details from the portal.
Users Gets the details of all the users in a specific project.

CData Python Connector for Zoho Projects

Contacts

Fetches all client contacts from a portal.

Select

  • ClientId is required to retrieve Contacts.
For example, the following query is processed server side:
SELECT * FROM Contacts WHERE ClientId = '123456000000045005'

Insert

To create a new Contact you can specify the following fields:

  • ClientId
  • FirstName
  • LastName
  • Email
  • InvoiceRate
  • WorkProjects


INSERT INTO Contacts (WorkProjects, ClientId, FirstName, LastName, Email, Invoicerate)
VALUES ('123456000000031899', '123456000000039025', 'TestFirstname222', 'TestLastname222', 'testemail@example.com', '15')

Update

To update a Contact specify the Id field.

UPDATE Contacts
	SET FirstName = 'updatedname', LastName = 'updatedlastname', email = 'updatedemail@example.com'
	WHERE Id = '166135000000038075'

Delete

Contacts can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM Contacts WHERE Id = '123456000000040053' 

Columns

Name Type ReadOnly Description
ClientId String False

Contact Client Id.

Id [KEY] String False

Contact Id.

CrmContactId String False

Contact Crm Contact Id.

DisplayName String False

Contact Display Name.

FirstName String False

Contact First Name.

LastName String False

Contact Last Name.

Email String False

Contact Email.

InvoiceRate String False

Contact Invoice Rate.

WorkProjects String False

Array of Project Ids. Multiple Ids can be separated with comma.

CData Python Connector for Zoho Projects

PortalClients

Returns the list of client companies in the portal.

Select

You can use the below query to get all Portal Clients:
SELECT * FROM PortalClients

Insert

To create a new PortalClient you can specify the following fields:

  • Name
  • City
  • Country
  • State
  • FirstAddress
  • SecondAddress
  • WebAddress
  • ZipCode
  • UserEmail
  • WorkProjects
  • PrimaryClient


INSERT INTO PortalClients (Name, UserEmail, WebAddress, FirstAddress, SecondAddress, City, State, Country, PrimaryClient, ZipCode)
VALUES ('Company12', 'email1@example.com', 'www.example.com', 'Address line 1', 'Address line 2', 'Budapest', 'Hungary', 'Hungary', 'Yes', '1025')

Columns

Name Type ReadOnly Description
Id [KEY] String False

Client Id.

Name String False

Client Name.

City String False

Client City.

Country String False

Client Country.

State String False

Client State.

CrmAccountId String False

Client Crm Account Id.

FirstAddress String False

Client First Address.

SecondAddress String False

Client Second Address.

WebAddress String False

Client Web Address.

ZipCode String False

Client Zip Code.

UserId String False

Client User Id.

UserName String False

Client User Name.

UserEmail String False

Client User Email.

UserZpuid String False

Client User Zpuid.

WorkProjects String False

Client Work Projects.

PrimaryClient String False

Client Primary Client.

The allowed values are Yes, No.

CData Python Connector for Zoho Projects

ProjectGroups

Gets all the groups for the specified project.

Select

You can use the below query to get all ProjectGroups:
SELECT * FROM ProjectGroups

Insert

To create a new ProjectGroup you can use the below query:

INSERT INTO ProjectGroups (name) VALUES ('New Project Group')

Delete

ProjectGroups can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM ProjectGroups WHERE Id = '123456000000045018'  

Columns

Name Type ReadOnly Description
Id [KEY] String False

Project Group Id.

Name String False

Project Group Name.

Default Boolean False

Is Default Project Group.

CData Python Connector for Zoho Projects

Projects

Gets all the projects for the logged in user.

Select

Columns that support the = operator:
  • Id
  • CreatedDate
  • Status
  • LastModifiedTime

Columns that support the = and IN operator:
  • GroupId
  • Assignee

For example, the following query is processed server side:
SELECT * FROM Projects WHERE Id = '123456000000039053' 

Insert

To create a new Project you can specify the following fields:

  • Name
  • BillingStatus
  • BillingType
  • Currency
  • Description
  • Public
  • OwnerId
  • BudgetType
  • BudgetValue
  • Rate
  • BudgetTrackingMethod
  • FixedCost
  • TemplateId
  • Threshold
  • StartDate
  • EndDate
  • EnableRollup

To create a new Project specify the following fields:

INSERT INTO Projects (Name, BudgetType, BudgetValue, BillingStatus, BillingType, Currency, Description, Public, BudgetType, BudgetTrackingMethod)
VALUES ('New Project', '2', '2.5', 'Billable', '2', 'EUR', 'TestDescription 123', 'no', '2', '4')

Update

You can use the below query to update a Project:

UPDATE Projects 
	SET Currency = 'USD', SingleLinCustomField = 'New Custom Field Value' 
	WHERE Id = '123456000000039053'

Delete

Projects can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM Projects WHERE Id = '123456000000039053' 

Columns

Name Type ReadOnly Description
Id [KEY] String False

Project Id.

Name String False

Project Name.

Key String False

Project Key.

BugsEnabled Boolean False

Project Bugs Enabled.

BillingStatus String False

Project Billing Status.

The allowed values are Billable, Non Billable.

BillingType String False

Mention the billing method for invoicing. (1 = Based on project hours, 2 = Based on staff hours, 3 = Fixed cost for project, 4 = Based on task / issue hours).

The allowed values are 1, 2, 3, 4.

BugClientPermission String False

Project Bug Client Permission.

BugsClosed Integer False

Project Bugs Closed.

BugsOpen Integer False

Project Bugs Open.

BugsDefaultView String False

Project Bugs Default View.

BugsPrefix String False

Project Bugs Prefix.

CreatedDate Date False

Project Created Date.

CreatedDateTime Datetime False

Project Created Date Time.

CustomStatusColor String False

Project Custom Status Color.

CustomStatusId String False

Project Custom Status Id.

CustomStatusName String False

Project Custom Status Name.

Currency String False

The default currency of your project. Example: USD, INR, etc.

CurrencySymbol String False

Project Currency Symbol.

Description String False

Project Description.

EnabledTabs String False

Project Enabled Tabs.

ChatEnabled Boolean False

Project Chat Enabled.

ClientAssignBug String False

Project Client Assign Bug.

Public String False

Project Public.

The allowed values are yes, no.

SprintsProject Boolean False

Project Sprints Project.

Strict String False

Project Strict.

BugLayoutId String False

Project Bug Layout Id.

BugLayoutName String False

Project Bug Layout Name.

ProjectLayoutId String False

Project Project Layout Id.

ProjectLayoutName String False

Project Project Layout Name.

TaskLayoutId String False

Project Task Layout Id.

TaskLayoutName String False

Project Task Layout Name.

ActivityUrl String False

Project Activity Url.

BugUrl String False

Project Bug Url.

DocumentUrl String False

Project Document Url.

EventUrl String False

Project Event Url.

FolderUrl String False

Project Folder Url.

ForumUrl String False

Project Forum Url.

MilestoneUrl String False

Project Milestone Url.

SelfUrl String False

Project Self Url.

StatusUrl String False

Project Status Url.

TaskUrl String False

Project Task Url.

TasklistUrl String False

Project Tasklist Url.

TimesheetUrl String False

Project Timesheet Url.

UserUrl String False

Project User Url.

MilestoneClosed Integer False

Project Milestone Closed.

MilestoneOpen Integer False

Project Milestone Open.

OwnerId String False

Project Owner Id.

OwnerName String False

Project Owner Name.

OwnerZpUid String False

Project Owner Zp Uid.

ProfileId Long False

Project Profile Id.

ProjectPercent String False

Project Project Percent.

Role String False

Project Role.

ShowProjectOverview Boolean False

Project Show Project Overview.

Status String False

Project Status.

The allowed values are active, archived, template.

SettingsDate Boolean False

Project Settings Date.

SettingsLogHours Boolean False

Project Settings Log Hours.

SettingsPercentage Boolean False

Project Settings Percentage.

SettingsPlan Boolean False

Project Settings Plan.

SettingsWorkHours Boolean False

Project Settings Work Hours.

TaskClosed Integer False

Project Task Closed.

TaskOpen Integer False

Project Task Open.

TaskbugPrefix String False

Project Taskbug Prefix.

UpdatedDate Date False

Project Updated Date.

UpdatedDateTime Datetime False

Project Updated Date Time.

WorkspaceId String False

Project Workspace Id.

BudgetType String False

Type of your budget. Accepted values 0, 1, 2, 3, 4, 5 and 6. (0 = None, 1 = Based on amount, 2 = Based on hours, 3 = Based on milestone amount, 4 = Based on milestone hours, 5 = Based on task amount and 6 = Based on task hours).

The allowed values are 1, 2, 3, 4, 5, 6.

BudgetTypeValue String False

Project Budget Type Value.

BudgetValue String False

Project Budget Value.

Rate String False

Project Rate.

BudgetTrackingMethod String False

Method to track your project budget. Accepted values 1, 2, and 4. (1 = Project hours, 2 = Staff hours, 4 = Task / Issue hours).

FixedCost String False

Project Fixed Cost.

TemplateId String False

Project Template Id.

Threshold String False

Specify the budget threshold limit (Amount or hours)..

StartDate String False

Project Start Date.

EndDate String False

Project End Date.

EnableRollup String False

Project Enable Rollup.

The allowed values are Yes, No.

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
LastModifiedTime Datetime

Project Last Modified Time.

GroupId String

Project Group Id.

Assignee String

Project Assignee.

CData Python Connector for Zoho Projects

Tags

Fetches all the tags present in a specific portal.

Select

You can use the below query to get all Tags:
SELECT * FROM Tags

Insert

To create a new Tag you can specify the following fields:

INSERT INTO Tags (Name, ColorClass) VALUES ('New Tag', 'bg-tag16') 

Update

To update a Tag specify the Id field.

UPDATE Tags SET Name = 'Updated Name', ColorClass = 'bg-tag99' WHERE Id = '123456000000043057'

Delete

Tags can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM Tags WHERE Id = '123456000000043057' 

Columns

Name Type ReadOnly Description
Id [KEY] String False

Tag Id.

Name String False

Tag Name.

ColorClass String False

Tag Color Class.

CreatedBy String False

Tag Created By.

CreatedByName String False

Tag Created By Name.

CreatedByEmail String False

Tag Created By Email.

CreatedByFirstName String False

Tag Created By First Name.

CreatedByLastName Unknown False

Tag Created By Last Name.

CreatedByIsClientUser Boolean False

Tag Created By Is Client User.

CreatedByZpuid String False

Tag Created By Zpuid.

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
Tags String

CData Python Connector for Zoho Projects

Teams

Fetch the team details from the portal.

Select

You can use the below query to get all Teams:
SELECT * FROM Teams

Insert

To create a new Team you can specify the following fields:

  • GroupName
  • EmailAlias
  • UserIdArr
  • ProjIds
  • TeamLead


INSERT INTO Teams (GroupName, UserIdArr, TeamLead, ProjIds)" +
VALUES ('TestTeam5', '["123456000000031003", "123456000000032055"]', '123456000000032055', '["123456000000031899"]

Update

To update a Team specify the GroupId field.

UPDATE Teams
SET TeamLead = '123456000000031003', 
	UserIdArr = '["123456000000031003", "123456000000032055"]',
	ProjIds = '["123456000000031899"]', 
	GroupName = 'TestTeam5' 
WHERE GroupId = '123456000000036001'

Delete

Teams can be deleted by providing the GroupId and issuing a DELETE statement.

DELETE FROM Teams WHERE GroupId = '123456000000044025' 

Columns

Name Type ReadOnly Description
GroupId [KEY] String False

Group Id of the team.

GroupName String False

Group Name of the team.

CreatedBy String False

Team Created By.

CreatedTime String False

Created Time of the team.

Description String False

Description of the team.

EmailAlias String False

Email Id of the team.

EmailVerified Boolean False

Email Verified of the team.

OrgId String False

Organization Id of the team.

OwnerEmail String False

Owner Email of the team.

OwnerName String False

Owner Name of the team.

OwnerZpuid String False

Owner Zpuid of the team.

OwnerZuid String False

Owner Zuid of the team.

Prefix String False

Prefix of the team.

UpdatedBy String False

Updated By of the team.

UpdatedTime String False

Updated Time of the team.

HasGroupEdit Boolean False

Has Group Edit of the team.

ProjectCount Integer False

Project Count of the team.

UserCount Integer False

User Count of the team.

UserIdArr String False

Array of multiple Zpuid.

UserObj String False

User Object of the team.

ProjIds String False

Array of multiple project Ids.

TeamLead String False

ZPuid of the team lead.

CData Python Connector for Zoho Projects

Users

Gets the details of all the users in a specific project.

Columns

Name Type ReadOnly Description
Id [KEY] String False

User Id.

Name String False

User Name.

Active Boolean False

User Active.

ChatAccess Boolean False

User Chat Access.

Email String False

User Email.

PortalProfileName String False

User Portal Profile Name.

PortalRoleId String False

User Portal Role Id.

PortalRoleName String False

User Portal Role Name.

ProfileId String False

User Profile Id.

ProfileType String False

User Profile Type.

ProjectProfileId String False

User Project Profile Id.

Role String False

User Role.

The allowed values are manager, employee, contractor.

RoleId String False

User Role Id.

RoleName String False

User Role Name.

Zpuid String False

User Zpuid.

WorkProjects String False

User Work Projects.

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
UserType String

User Type.

The allowed values are active, inactive.

CData Python Connector for Zoho Projects

Views

The connector models the entities for which Zoho Projects only provides read-only access as views.

It exposes each portal tied to your account as a schema with the following views.

Navigate to an individual view's page for a breakdown of its columns and supported filters.

CData Python Connector for Zoho Projects Views

Name Description
MyBugs Lists all the bugs created by you or assigned to you.
MyMilestones Get all the milestones assigned to a particular user in the given project.
MyTasks Gets all your tasks in the portal.
MyTimelogs Gets the time logs under a specific bug.
ProjectCustomFields Gets all the project custom fields.
ProjectCustomStatus Gets list of all project custom status.
ProjectLayouts Gets list of project layouts.
TaskLayouts View the list of all the task layouts available in your portal.
TaskStatusHistory Fetches status history of tasks from the Portal.
TimesheetCustomFields Fetch all timesheet custom fields across the project.
PortalUsersRemaining Gets the details of all users in a specific portal.

CData Python Connector for Zoho Projects

MyBugs

Lists all the bugs created by you or assigned to you.

Select

This is a portal-level view.
  • StatusType, Owner, ViewType and ViewType support the following operator: =.
  • CreatedDate and LastModifiedTime support: ORDER
For example, the following query is processed server side:
SELECT * FROM MyBugs WHERE Owner = '12345021738' AND ViewType = 'owned' AND StatusType = 'open' ORDER BY CreatedDate

Columns

Name Type Description
Id [KEY] String Bug Id.
Key String Bug Key.
Title String Bug Title.
AssigneeId String Bug Assignee Id.
AssigneeName String Bug Assignee Name.
AssigneeZpuid String Bug Assignee ZPUID.
AttachmentCount String Bug Attachment Count.
BugPrefix String Bug Prefix.
ClassificationId Long Bug Classification Id.
ClassificationType String Bug Classification Type.
Closed Boolean Bug Closed.
CommentCount String Bug Comment Count.
CreatedDate Date Bug Created Date.
CreatedDateTime Datetime Bug Created Date Time.
Description String Bug Description.
DueDate Date Bug Due Date.
DueDateTime Date Bug Due Date Time.
Flag String Bug Flag.
LinkSelfUrl String Bug Link Self Url.
LinkTimesheetUrl String Bug Link Timesheet Url.
ModuleId Long Bug Module Id.
ModuleName String Bug Module Name.
ProjectId Long Bug Project Id.
ProjectIdString String Bug Project Id String.
ProjectName String Bug Project Name.
ReportedPerson String Bug Reported Person.
ReporterId String Bug Reporter Id.
ReproducibleId Long Bug Reproducible Id.
ReproducibleType String Bug Reproducible Type.
SeverityId Long Bug Severity Id.
SeverityType String Bug Severity Type.
StatusId Long Bug Status Id.
StatusType String Bug Status Type.

The allowed values are open, closed.

UpdatedDate Date Bug Updated Date.
UpdatedDateTime Datetime Bug Updated Date Time.
UpdatedTimeLong Long Bug Updated Time Long.

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
Owner String Bug Owner.
ViewType String Bug View Type.

The allowed values are reported, owned.

LastModifiedTime Datetime Bug Last Modified Time.

CData Python Connector for Zoho Projects

MyMilestones

Get all the milestones assigned to a particular user in the given project.

Select

This is a portal-level view.
  • ProjectId and Flag support the following operator: =.
  • ProjectId supports the operator: IN
  • CreatedDate and LastModifiedTime support: ORDER
For example, the following query is processed server side:
SELECT * FROM MyMilestones WHERE ProjectId IN ('12345000000030899', '12345000000033005') AND Flag = 'internal' ORDER BY CreatedDate

Columns

Name Type Description
ProjectId String Project Id.
Id [KEY] String Milestone Id.
Name String Milestone Name.
Closed Boolean Milestone Closed.
CreatedDate Date Milestone Created Date.
CreatedDateTime Datetime Milestone Created Date Time.
EndDate Date Milestone End Date.
EndDateTime Datetime Milestone End Date Time.
Flag String Milestone Flag.

The allowed values are internal, external.

IsWorkfieldRemoved Boolean Milestone Is Work Field Removed.
LastUpdatedDate Date Milestone Last Updated Date.
LastUpdatedDateTime Datetime Milestone Last Updated Date Time.
SelfUrl String Milestone Self Url.
StatusUrl String Milestone Status Url.
OwnerId String Milestone Owner Id.
OwnerName String Milestone Owner Name.
OwnerZpuid String Milestone Owner ZPUID.
ProjectName String Milestone Project Name.
Sequence Integer Milestone Sequence.
StartDate Date Milestone Start Date.
StartDateTime Datetime Milestone Start Date Time.
Status String Milestone Status.
StatusColorCode String Milestone Status Color Code.
StatusId String Milestone Status Id.
StatusName String Milestone Status Name.

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
LastModifiedTime Datetime Milestone Last Modified Time.

CData Python Connector for Zoho Projects

MyTasks

Gets all your tasks in the portal.

Select

This is a portal-level view. Columns that support the = operator:
  • Id
  • CreatedBy
  • MilestoneId
  • Priority
  • TasklistId
  • Owner
  • Status
  • Time
  • LastModifiedTime
  • ViewId

For example, the following query is processed server side:
SELECT * FROM MyTasks WHERE MilestoneId = '12345600000123' AND Priority = 'High' 

Columns

Name Type Description
ProjectId String Project Id.
Id [KEY] String Task Id.
Name String Task Name.
Key String Task Key.
BillingType String Task Billing Type.
Completed Boolean Task Completed.
CreatedBy String Task Created By.
CreatedByEmail String Task Created By Email.
CreatedByZpuid String Task Created By Zpuid.
CreatedPerson String Task Created Person.
CreatedDate Date Task Created Date.
CreatedDateTime Datetime Task Created Date Time.
Description String Task Description.
Owners String Task Owners.
Duration String Task Duration.
DurationType String Task Duration Type.
EndDate Date Task End Date.
EndDateTime Datetime Task End Date Time.
CommentAdded Boolean Task Comment Added.
DocsAssociated Boolean Task Docs Associated.
ForumAssociated Boolean Task Forum Associated.
RecurrenceSet Boolean Task Recurrence Set.
ReminderSet Boolean Task Reminder Set.
Parent Boolean Task Parent.
LastUpdatedDate Date Task Last Updated Date.
LastUpdatedDateTime Datetime Task Last Updated Date Time.
LinkSelfUrl String Task Link Self Url.
LinkTimesheetUrl String Task Link Timesheet Url.
LinkWebUrl String Task Link Web Url.
LogHoursBillableHours String Task Log Hours Billable Hours.
LogHoursNonBillableHours String Task Log Hours Non Billable Hours.
MilestoneId String Task Milestone Id.
OrderSequence Integer Task Order Sequence.
PercentComplete String Task Percent Complete.
Priority String Task Priority.

The allowed values are none, low, medium, high.

StartDate Date Task Start Date.
StartDateTime Datetime Task Start Date Time.
StatusColorCode String Task Status Color Code.
StatusId String Task Status Id.
StatusName String Task Status Name.
StatusType String Task Status Type.
Subtasks Boolean Task Subtasks.
TaskFollowers String Task Task Followers.
TaskFollowerSize Integer Task Task Follower Size.
TasklistId String Task Tasklist Id.
TasklistIdString String Task Tasklist Id String.
TasklistName String Task Tasklist Name.
Work String Task Work.
WorkForm String Task Work Form.
WorkType String Task Work Type.
GroupNameAssociatedTeamsAnyTeam String Task Group Name Associated Teams Any Team.
GroupNameAssociatedTeamsCount Integer Task Group Name Associated Teams Count.
GroupNameIsTeamUnassigned Boolean Task Group Name Is Team Unassigned.

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
Owner String Task Owner.
Status String Task Status.

The allowed values are completed, notcompleted.

Time String Task Time.

The allowed values are overdue, today, tomorrow.

LastModifiedTime Datetime Task Last Modified Time.
CustomViewId String Task Custom View Id.

CData Python Connector for Zoho Projects

MyTimelogs

Gets the time logs under a specific bug.

Select

This is a portal-level view. Columns that support the = operator:
  • BillStatus
  • User
  • ComponentType

Columns that support the >,>=,=,<,<= operators:
  • Date
  • LastModifiedDate

For example, the following queries are processed server side:
SELECT * FROM MyTimelogs WHERE User = '123450000123'

SELECT * FROM MyTimelogs WHERE Date > '2024-01-01'

SELECT * FROM MyTimelogs WHERE LastModifiedDate > '2024-01-01'
Querying MyTimeLogs without filters will return data for only the current month:
SELECT * FROM MyTimelogs

Columns

Name Type Description
Id [KEY] String Time Log Id.
AddedByName String Time Log Added By Name.
AddedByZpuid String Time Log Added By Zpuid.
AddedByZuid Long Time Log Added By Zuid.
ApprovalStatus String Time Log Approval Status.
ApproverName String Time Log Approver Name.
BillStatus String Time Log Bill Status.

The allowed values are all, billable, non billable.

CreatedDate Date Time Log Created Date.
CreatedDateTime Datetime Time Log Created Date Time.
StartTime Datetime Time Log Start Time.
EndTime Datetime Time Log End Time.
Notes String Time Log Notes.
HoursDisplay String Time Log Hours Display.
Hours Integer Time Log Hours.
Minutes Integer Time Log Minutes.
IsParent Boolean Time Log Is Parent.
IsSubTask Boolean Time Log Is Sub Task.
LastModifiedDate Date Time Log Last Modified Date.
LastModifiedDateTime Datetime Time Log Last Modified Date Time.
LinkSelfUrl String Time Log Link Self Url.
LogDate Date Time Log Date.
LogDateTime Datetime Time Log Date Time.
OwnerId String Time Log Owner Id.
OwnerName String Time Log Owner Name.
SubTaskLevel String Time Log Sub Task Level.
TaskName String Time Log Task Name.
TaskListId Long Time Log Task List Id.
TaskListName String Time Log Task List Name.
TotalMinutes Integer Time Log Total Minutes.
ProjectId String Time Log Project Id.
ProjectName String Time Log Project Name.
Date Date Time Log Date.
User String Time Log User.
ComponentType String Time Log Component Type.

The allowed values are bug, task, general.

CData Python Connector for Zoho Projects

ProjectCustomFields

Gets all the project custom fields.

Select

You can use the below query to get all Project Custom Fields:
SELECT * FROM ProjectCustomFields

Columns

Name Type Description
Id [KEY] String Custom Field Id.
Name String Custom Field Name.
FieldType String Custom Field Type.
FieldId String Field Id.
PII Boolean Custom Field PII.
Encrypted Boolean Encrypted.
DefaultValue String Custom Field Default Value.
PickList String Custom Field Pick List Options.

CData Python Connector for Zoho Projects

ProjectCustomStatus

Gets list of all project custom status.

Select

You can use the below query to get all Project Custom Statuses:
SELECT * FROM ProjectCustomStatus

Columns

Name Type Description
Id [KEY] String Portal Id.
Name String Portal Name.
Closed Boolean Portal Closed.
Default Boolean Portal Default.
HasDefaultValue Boolean Portal Has Default Value.
Sequence Int Portal Sequence.
StatusColor String Portal Status Color.
StatusColorHexcode String Portal Status Color Hex Code.

CData Python Connector for Zoho Projects

ProjectLayouts

Gets list of project layouts.

Select

You can use the below query to get all Project Layouts:
SELECT * FROM ProjectLayouts

Columns

Name Type Description
Id [KEY] String Project Layout Id.
Name String Project Layout Name.
Default Boolean Is Default Project Layout.

CData Python Connector for Zoho Projects

TaskLayouts

View the list of all the task layouts available in your portal.

Select

This is a portal-level view. You can use the below query to get all Task Layouts:
SELECT * FROM TaskLayouts

Columns

Name Type Description
Id [KEY] String Task Layout Id.
Name String Task Layout Name.
Default Boolean Task Layout Default.

CData Python Connector for Zoho Projects

TaskStatusHistory

Fetches status history of tasks from the Portal.

Select

This is a portal-level view.
  • LastModifiedTime supports: ORDER
You can use the below query to get all Task Layouts:
SELECT * FROM TaskStatusHistory ORDER BY LastModifiedTime

Columns

Name Type Description
Id [KEY] String Task Status History Id.
Name String Task Status History Name.
StatusId String Task Status History Status Id.
StatusName String Task Status History Status Name.
PreviousStatusId String Task Status History Previous Status Id.
PreviousStatusName String Task Status History Previous Status Name.
UpdatedStatusId String Task Status History Updated Status Id.
UpdatedStatusName String Task Status History Updated Status Name.
TransitionTimeMillis String Task Status History Transition Time Millis.
TransitionTimeDuration String Task Status History Transition Time Duration.
UpdatedBy String Task Status History Updated By.
UpdatedByName String Task Status History Updated By Name.
UpdatedByEmail String Task Status History Updated By Email.
UpdatedOn Datetime Task Status History Updated On.

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
LastModifiedTime Datetime Task Status History Last Modified Time.

CData Python Connector for Zoho Projects

TimesheetCustomFields

Fetch all timesheet custom fields across the project.

Select

This is a portal-level view. You can use the below query to get all Timesheet Custom Fields:
SELECT * FROM TimesheetCustomFields

Columns

Name Type Description
Id [KEY] String Time Sheet Custom Field Id.
FieldName String Time Sheet Custom Field Name.
DataType String Time Sheet Custom Field Data Type.
UniqueColumn String Time Sheet Custom Field Unique Column.

CData Python Connector for Zoho Projects

PortalUsersRemaining

Gets the details of all users in a specific portal.

Columns

Name Type Description
AvailableUsersCount String Available User Count.

CData Python Connector for Zoho Projects

User Projects

Overview

The connector models each portal associated with your account as a catalog, named after the portal. For every project in each of these catalogs, there is a project-specific schema, which is named after the project.

Tables

Tables describes the available tables. Tables are statically defined to model Zoho Projects entities such as bugs, events, tasks, etc.

Views

Views describes the available views. Views are read-only tables that are statically defined to model Zoho Projects entities such as activities, clients, documents, etc.

CData Python Connector for Zoho Projects

Tables

The connector models the entities for which Zoho Projects provides full or limited CRUD support as tables.

It models each project tied to your account as a schema with the following tables.

Navigate to an individual table's page for a breakdown of its columns, as well as its supported filters and CRUD operations.

CData Python Connector for Zoho Projects Tables

Name Description
BugAssociatedTasks Fetches the details of the task associated with a bug.
BugComments Fetch comments for the bug.
BugEntityProperties Retrieves the data stored against an entity. The argument of this method should be the key that was used when the same data was stored.
BugFollowers Get list of followers for the bug.
Bugs Gets all the tasks in the given project. It fetches only the main tasks and not the subtasks.
BugTimelogs Gets the time logs under a specific bug.
Events Fetches all the tags present in a specific portal.
ForumCategories Gets all the forum categories.
ForumComments Gets all the forum comments.
Forums Gets all the forums in the given project.
Milestones Gets list of project layouts.
ProjectEntityProperties Retrieves the data stored against an entity. The argument of this method should be the key that was used when the same data was stored.
ProjectUsers Gets the details of all the users in a specific project.
Statuses Gets the statuses for the given project.
TaskActivities Retrieve details of who modified a specific task and when.
TaskComments Get all the task comments.
TaskCustomfields Usage information for the operation TaskCustomfields.rsd.
TaskEntityProperties Retrieves the data stored against an entity. The argument of this method should be the key that was used when the same data was stored.
Tasklists Get all the task lists in the given project.
Tasks Gets all the tasks in the given project. It fetches only the main tasks and not the subtasks.
TaskSubtasks View all the subtasks of the given task.
TaskTimelogs Gets the time logs under a specific task.
TeamUsers Fetch details of a particular team.

CData Python Connector for Zoho Projects

BugAssociatedTasks

Fetches the details of the task associated with a bug.

Table Specific Information

This table shows associations between Bugs and Tasks.

Select

  • BugId supports the following operator: =.
For example, the following query is processed server side:
SELECT * FROM BugAssociatedTasks WHERE BugId = '123439000000045005'

Insert

To add a new bug-task association specify the BugId and TaskId fields.

INSERT INTO BugAssociatedTasks (BugId, TaskId) VALUES ('123418000000045005', '["123418000000044005"]') 

Delete

To delete an existing bug-task association specify the BugId and TaskId fields.

DELETE FROM BugAssociatedTasks WHERE BugId = '123418000000045005' AND TaskId = '123418000000044005'

Columns

Name Type ReadOnly Description
BugId String False

Bug Id.

TaskId String False

Associated Task Id.

TaskName String False

Associated Task Name.

Prefix String False

Associated Task Prefix.

ProjectId String False

Associated Task Project Id.

TaskOwners String False

Associated Task Owners.

TaskPercentageCompleted String False

Associated Task Percentage Completed.

TaskPriority String False

Associated Task Priority.

TaskListId String False

Associated Task List Id.

CData Python Connector for Zoho Projects

BugComments

Fetch comments for the bug.

Select

  • BugId is required to retrieve Bug Comments.
For example, the following query is processed server side:
SELECT * FROM BugComments WHERE BugId = '123456000000045005'

Insert

To add a Bug Comment specify the BugId and Comment fields.

INSERT INTO BugComments (BugId, Comment) VALUES ('123456000000045005', 'Test Comment #1')

Delete

Bug Comments can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM BugComments WHERE BugId = '123456000000045005' AND Id = '123456000000045042'

Columns

Name Type ReadOnly Description
BugId [KEY] String False

Bug Id.

Id [KEY] String False

Bug Comment Id.

Comment String False

Bug Comment Content.

AddedBy String False

Bug Comment Added By.

AddedPersonName String False

Bug Comment Added Person Name.

CreatedDate Date False

Bug Comment Created Date.

CreatedDateTime Datetime False

Bug Comment Created Date Time.

UpdatedBy String False

Bug Comment Updated By.

UpdatedPerson String False

Bug Comment Updated Person.

UpdatedDate Date False

Bug Comment Updated Date.

UpdatedDateTime Datetime False

Bug Comment Updated Date Time.

CData Python Connector for Zoho Projects

BugEntityProperties

Retrieves the data stored against an entity. The argument of this method should be the key that was used when the same data was stored.

Table Specific Information

Entity-properties are key-value pairs stored against the bug entities. They can be used for storing details that are needed for API integrations but don't have to be visible in the UI. The key has to be a String and the Value could be a simple string or a json object. You can store multiple key-value pair for a single entity. These entity properties can be stored / retrieved / updated / deleted using the following queries.

Select

  • BugId is required to retrieve Bug Entity Properties.
For example, the following query is processed server side:
SELECT * FROM BugEntityProperties WHERE BugId = '123456000000034087' AND PropertyKey = 'key1' 

Insert

To add a new Bug Entity Property specify the BugId, PropertyKey and PropertyValue fields.

INSERT INTO BugEntityProperties (BugId, PropertyKey, PropertyValue) VALUES ('123456000000034087', 'key1', 'This is a test value')

Update

ZohoProjects allows updates for the PropertyValue column.

UPDATE BugEntityProperties SET PropertyValue = 'This is an updated property value' WHERE BugId = '123456000000034087' AND PropertyKey = 'key1'

Delete

Bug Entity Properties can be deleted by providing Id, BugId, PropertyKey and issuing a DELETE statement.

DELETE FROM BugEntityProperties WHERE BugId = '166135000000034087' AND PropertyKey = 'key1' AND Id = '166135000000035001'

Columns

Name Type ReadOnly Description
Id [KEY] String False

Bug Entity Property Id.

BugId [KEY] String False

Bug Id.

PropertyKey [KEY] String False

Bug Entity Property Key.

PropertyValue String False

Bug Entity Property Value.

CData Python Connector for Zoho Projects

BugFollowers

Get list of followers for the bug.

Select

  • BugId is required to retrieve Bug Followers.
For example, the following query is processed server side:
SELECT * FROM BugFollowers WHERE BugId = '123456000000042110'

Insert

To add a Bug Follower specify the BugId and Follower fields.

INSERT INTO BugFollowers (BugId, BugFollowers) VALUES ('123456000000042110', '12345649448')

Delete

Bug Followers can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM BugFollowers WHERE BugId = '123456000000042110'  AND  FollowerId = '12345649448'

Columns

Name Type ReadOnly Description
BugId [KEY] String False

Bug Id.

FollowerId String False

Bug Follower Id.

FollowerName String False

Bug Follower Name.

BugFollowers String False

Bug Followers.

CData Python Connector for Zoho Projects

Bugs

Gets all the tasks in the given project. It fetches only the main tasks and not the subtasks.

Select

Columns that support the = operator:
  • Id
  • CreatedTime
  • Flag
  • StatusType
  • CustomViewId

Columns that support the = and IN operator:
  • AssigneeId
  • ClassificationId
  • EscalationLevel
  • ModuleId
  • SeverityId
  • StatusId
  • ReporterId
  • MilestoneId
  • AffectedMilestoneId

For example, the following query is processed server side:
SELECT * FROM Bugs 
	WHERE ReporterId IN ('12341021738')
	AND AssigneeId IN ('12341021738')
	AND ClassificationId IN ('123456000000030015')
	AND EscalationLevel IN ('0')
	AND Flag = 'Internal'
	AND ModuleId IN ('123456000000030145')
	AND SeverityId IN ('123456000000030151')
	AND StatusId IN ('123456000000030083')

Insert

To create a new Bug, you can specify the following fields:

  • Title
  • AssigneeId
  • ClassificationId
  • Description
  • DueDate
  • Flag
  • ModuleId
  • ReproducibleId
  • SeverityId
  • HourlyRate
  • BugFollowers
  • MilestoneId

To create a new Bug, specify the following fields:

INSERT INTO Bugs (Title, Description, AssigneeId, flag, ClassificationId, DueDate, ModuleId, SeverityId, ReproducibleId, HourlyRate, CustomField1)
VALUES ('SQL Inserted Bug #5', 'Test Description', '12341249448', 'Internal', '123456000000031015', '2022-03-20', '123456000000031145', '123456000000031149', '123456000000031053', '2', 'TestCustomField')

Update

You can use the below query to update a bug:

UPDATE Bugs
SET Title = 'SQL Inserted Bug #5',
    Description = 'Another Test Description',
    AssigneeId = '20081249448',
    ClassificationId = '165818000000031015',
    DueDate = '2022-03-20',
    ModuleId = '165818000000031145',
    SeverityId = '165818000000031149',
    ReproducibleId = '165818000000031053',
    HourlyRate = '2',
    cf1 = 'Custom Field Edited #1'
WHERE Id = '165818000000042126'

Delete

Bugs can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM Bugs WHERE Id = '123456000000042126' 

Columns

Name Type ReadOnly Description
Id [KEY] String False

Bug Id.

Key String False

Bug Key.

Title String False

Bug Title.

AssigneeId String False

Bug Assignee Id.

AssigneeName String False

Bug Assignee Name.

AssigneeZpuid String False

Bug Assignee ZPUID.

AttachmentCount String False

Bug Attachment Count.

BugNumber String False

Bug Number.

BugPrefix String False

Bug Prefix.

ClassificationId Long False

Bug Classification Id.

ClassificationType String False

Bug Classification Type.

Closed Boolean False

Bug Closed.

CommentCount String False

Bug Comment Count.

CreatedTime Date False

Bug Created Time.

CreatedDateTime Datetime False

Bug Created Date Time.

Description String False

Bug Description.

DueDate Date False

Bug Due Date.

DueDateTime Datetime False

Bug Due Date Time.

EscalationLevel String False

Bug Escalation Level.

Flag String False

Bug Flag.

The allowed values are internal, external.

LinkSelfUrl String False

Bug Link Self Url.

LinkTimesheetUrl String False

Bug Link Timesheet Url.

LinkWebUrl String False

Bug Link Web Url.

ModuleId Long False

Bug Module Id.

ModuleName String False

Bug Module Name.

ReportedPerson String False

Bug Reported Person.

ReporterEmail String False

Bug Reporter Email.

ReporterId String False

Bug Reporter Id.

ReporterNonZuser String False

Bug Reporter Non User.

ReproducibleId Long False

Bug Reproducible Id.

ReproducibleType String False

Bug Reproducible Type.

SeverityId Long False

Bug Severity Id.

SeverityType String False

Bug Severity Type.

StatusColorcode String False

Bug Status Color Code.

StatusId String False

Bug Status Id.

StatusType String False

Bug Status Type.

The allowed values are open, closed.

UpdatedDate Date False

Bug Updated Date.

UpdatedDateTime Datetime False

Bug Updated Date Time.

GroupNameAssociatedTeamsAnyTeam String False

Bug Group Name Associated Teams by Any Team.

GroupNameAssociatedTeamsCount Integer False

Bug Group Name Associated Teams Count.

GroupNameIsTeamUnassigned Boolean False

Bug Group Name Is Team Unassigned.

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
HourlyRate String

Bug Hourly Rate.

BugFollowers String

Bug Bug Followers.

CustomViewId String

Bug Custom View Id.

MilestoneId String

Bug Milestone Id.

AffectedMilestoneId String

Bug Affected Milestone Id.

CData Python Connector for Zoho Projects

BugTimelogs

Gets the time logs under a specific bug.

Select

  • BugId is required to retrieve Bug Time Logs.
For example, the following query is processed server side:
SELECT * FROM BugTimelogs WHERE BugId = '123456000000045005'

Insert

To add a Bug TimeLog specify the BugId and Follower fields.

INSERT INTO BugTimelogs (BugId, LogDate, BillStatus, HoursDisplay, Notes)
VALUES ('123456000000045005', '2022-03-03', 'Non Billable', '01:20', 'This is a test timelog')

Update

To update a Bug TimeLog specify the BugId and Id fields.

UPDATE BugTimelogs
	SET Notes = 'This is an updated SQL Note'
	WHERE BugId = '165818000000045005' AND Id = '123456000000044025'

Delete

Bug TimeLogs can be deleted by providing the BugId and Id and issuing a DELETE statement.

DELETE FROM BugTimelogs WHERE BugId = '123456000000045005' AND Id = '123456000000044025'

Columns

Name Type ReadOnly Description
BugId [KEY] String False

Bug Id.

Id [KEY] String False

Bug Time Log Id.

AddedByName String False

Bug Time Log Added By Name.

AddedByZpuid String False

Bug Time Log Added By ZPUID.

AddedByZuid Long False

Bug Time Log Added By ZUID.

ApprovalStatus String False

Bug Time Log Approval Status.

ApproverName String False

Bug Time Log Approver Name.

BillStatus String False

Bug Time Log Bill Status.

The allowed values are Billable, Non Billable.

BugTitle String False

Bug Time Log Bug Title.

CreatedDate Date False

Bug Time Log Created Date.

CreatedDateTime Datetime False

Bug Time Log Created Date Time.

Hours Integer False

Bug Time Log Hours.

Minutes Integer False

Bug Time Log Minutes.

HoursDisplay String False

Bug Time Log Hours Display.

LastModifiedDate Date False

Bug Time Log Last Modified Date.

LastModifiedDateTime Datetime False

Bug Time Log Last Modified Date Time.

LinkSelfUrl String False

Bug Time Log Link Self Url.

LogDate Date False

Bug Time Log Date.

LogDateTime Datetime False

Bug Time Log Date Time.

Notes Unknown False

Bug Time Log Notes.

OwnerId String False

Bug Time Log Owner Id.

OwnerName String False

Bug Time Log Owner Name.

TotalMinutes Integer False

Bug Time Log Total Minutes.

CData Python Connector for Zoho Projects

Events

Fetches all the tags present in a specific portal.

Select

  • Status supports the following operator =.
For example, the following query is processed server side:
SELECT * FROM Events WHERE Status = 'open'

Insert

To create a new Event you can specify the following fields:

  • Title
  • DurationHour
  • DurationMinutes
  • Location
  • Participants
  • Reminder
  • Repeat
  • ScheduledOn
  • RepeatTimes


INSERT INTO Events (Title, ScheduledOn, DurationHour, DurationMinutes, Participants, Reminder, Repeat, Location)
	VALUES ('SQL Event #2', '2022-03-20T18:00:00', '2', '30', '20081249448', '15 mins', 'only once', 'Test Location 2')

Update

To update an Event specify the Id field.

UPDATE Events
	SET title = 'Updated Title #1', DurationHour = '4', DurationMinutes = '10', ScheduledOn = '2022-05-01T23:12:00', Participants = '20081249448'
	WHERE Id = '123456000000045018'

Delete

Events can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM Events WHERE Id = '123456000000045018'  

Columns

Name Type ReadOnly Description
Id [KEY] String False

Event Id.

Title String False

Event Title.

CreatedBy String False

Event Created By.

CreatedByZpuid String False

Event Created By ZPUID.

CreatedOn Long False

Event Created On.

DurationHour String False

Event Duration Hour.

DurationMinutes String False

Event Duration Minutes.

Location String False

Event Location.

Occurred Integer False

Event Occurred.

Occurrences Integer False

Event Occurrences.

Participants String False

Event Participants.

ProjectName String False

Event Project Name.

Reminder String False

Event Reminder.

The allowed values are on time, 15 mins, 30 mins, 1 hour, 2 hours, 6 hours, 12 hours, 1 day.

Repeat String False

Event Repeat.

The allowed values are only once, everyday, everyweek, everymonth, everyyear.

ScheduledOn String False

Event Scheduled On.

ScheduledOnLong String False

Event Scheduled On Long.

ScheduledOnTo String False

Event Scheduled On To.

ScheduledOnToLong String False

Event Scheduled On To Long.

RepeatTimes String False

Event Repeat Times.

The allowed values are 2, 3, 4, 5, 6, 7, 8, 9, 10.

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
Status String

Event Status.

The allowed values are open, closed.

CData Python Connector for Zoho Projects

ForumCategories

Gets all the forum categories.

Select

You can use the below query to get all ForumCategories:
SELECT * FROM ForumCategories

Insert

To create a new Forum Category you can use the below query:

INSERT INTO ForumCategories (name) VALUES ('New Forum Category')

Delete

ForumCategories can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM ForumCategories WHERE Id = '123456000000045018'

Columns

Name Type ReadOnly Description
Id [KEY] String False

Forum Category Id.

Name String False

Forum Category Name.

CData Python Connector for Zoho Projects

ForumComments

Gets all the forum comments.

Select

  • ForumId is required to retrieve Forum Comments.
You can use the below query to get all Forum Comments:
SELECT * FROM ForumComments WHERE ForumId = '123456000000045018'

Insert

To create a new Forum Comment you can use the below query:

INSERT INTO ForumComments (ForumId, Content, ParentId) 
VALUES ('123456000000045028', 'Forum Comment Reply', '123456000000043083')

Delete

Forum Comments can be deleted by providing the Id, ForumId and issuing a DELETE statement.

DELETE FROM ForumComments WHERE Id = '123456000000043083' AND ForumId = '123456000000045028'

Columns

Name Type ReadOnly Description
ForumId [KEY] Long False

Forum Id.

Id [KEY] String False

Forum Comment Id.

Content String False

Forum Comment Content.

Type String False

Forum Comment Type.

Attachments String False

Forum Comment Attachments.

IsBestAnswer Boolean False

Forum Comment Is Best Answer.

Level String False

Forum Comment Level.

ParentId String False

Forum Comment Parent Id.

ParentPostedBy String False

Forum Comment Parent Posted By.

ParentPostedByZpuid String False

Forum Comment Parent Posted By ZPUID.

PostDate Date False

Forum Comment Post Date.

PostDateTime Datetime False

Forum Comment Post Date Time.

PostedBy String False

Forum Comment Posted By.

PostedByZpuid String False

Forum Comment Posted By Zpuid.

PostedPerson String False

Forum Comment Posted Person.

RootId String False

Forum Comment Root Id.

ThirdPartyAttachments String False

Forum Comment Third Party Attachments.

CData Python Connector for Zoho Projects

Forums

Gets all the forums in the given project.

Select

  • Id and CategoryId support the following operator: =.
For example, the following query is processed server side:
SELECT * FROM Forums WHERE Id = '123456000000043771' 

Insert

To create a new Forum, you can specify the following fields:

  • Name
  • Type
  • CategoryId
  • Content
  • Flag
  • IsAnnouncementPost
  • IsStickyPost
  • Notify

To create a new Forum, you can use the below query:

INSERT INTO Forums (Name, Type, CategoryId, Content, Flag, IsAnnouncementPost, IsStickyPost)
VALUES ('Forum Post', 'normal', '123456000000039039', 'Content for Forum Post', 'internal', false, false)

Update

To update a Forum, specify the Id field.

UPDATE Forums
	SET Name = 'Updated Post Name', CategoryId = '123456000000093039', Content = 'Updated forum post content' 
	WHERE Id = '123456000000043771' 

Delete

Forums can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM Forums WHERE Id = '123456000000043771' 

Columns

Name Type ReadOnly Description
Id [KEY] String False

Forum Id.

Name String False

Forum Name.

Type String False

Forum Type.

The allowed values are normal, question.

Attachments String False

Forum Attachments.

CategoryId String False

Forum Category Id.

CategoryName String False

Forum Category Name.

CommentCount Integer False

Forum Comment Count.

Content String False

Forum Content.

Flag String False

Forum Flag.

IsAnnouncementPost Boolean False

Forum Is Announcement Post.

IsStickyPost Boolean False

Forum Is Sticky Post.

LastActivityDate Date False

Forum Last Activity Date.

LastActivityDateTime Datetime False

Forum Last Activity Date Time.

LastModifiedDate Date False

Forum Last Modified Date.

LastModifiedDateTime Datetime False

Forum Last Modified Date Time.

LinkSelfUrl String False

Forum Link Self Url.

PostDate Date False

Forum Post Date.

PostDateTime Datetime False

Forum Post Date Time.

PostedBy String False

Forum Posted By.

PostedByZpuid String False

Forum Posted By ZPUID.

PostedPerson String False

Forum Posted Person.

ThirdPartyAttachments String False

Forum Third Party Attachments.

Notify String False

Enter the user mail Ids to be notified (Multiple emails can be comma-separated).

CData Python Connector for Zoho Projects

Milestones

Gets list of project layouts.

Select

Columns that support the = operator:
  • Id
  • Flag
  • OwnerId
  • Status
  • DisplayType
  • LastModifiedTime

For example, the following query is processed server side:
SELECT * FROM Milestones WHERE Id = '123456000000043771' WHERE flag = 'internal' 

Insert

To create a new Milestone you can specify the following fields:

  • Name
  • Flag
  • StartDate
  • EndDate
  • OwnerId

To create a new Milestone you can use the below query:

INSERT INTO Milestones (name, StartDate, EndDate, OwnerId, flag) 
VALUES ('New Milestone name', '2022-03-01', '2022-03-10', '1234567890', 'internal')

Update

To update a Milestone specify the Id field.

UPDATE Milestones 
	SET Name = 'Updated Name',
		Flag = 'external',
		StartDate = '2022-02-01',
		EndDate = '2022-03-01',
		OwnerId = '1234567890' " +
	WHERE Id = '123456000000043021'

Delete

Milestones can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM Milestones WHERE Id = '123456000000043021' 

Columns

Name Type ReadOnly Description
Id [KEY] String False

Project Milestone Id.

Name String False

Project Milestone Name.

Flag String False

Milestone Flag.

The allowed values are internal, external.

Closed Boolean False

Milestone Closed.

CreatedDate Date False

Milestone Created Date.

CreatedDateTime Datetime False

Milestone Created Date Time.

StartDate Date False

Milestone Start Date.

StartDateTime Datetime False

Milestone Start Date Time.

EndDate Date False

Milestone End Date.

EndDateTime Datetime False

Milestone End Date Time.

Actual Integer False

Milestone Actual.

ActualCostFormatted String False

Milestone Actual Cost Formatted.

ActualHoursFormatted String False

Milestone Actual Hours Formatted.

Balance Integer False

Milestone Balance.

BalanceCostFormatted String False

Milestone Balance Cost Formatted.

BcyActual Integer False

Milestone Bcy Actual.

BcyActualCost String False

Milestone Bcy Actual Cost.

BcyForecasted Integer False

Milestone Bcy Forecasted.

BcyForecastedCost String False

Milestone Bcy Forecasted Cost.

BcyPlanned Integer False

Milestone Bcy Planned.

BcyPlannedCost String False

Milestone Bcy Planned Cost.

BudgetType Integer False

Milestone Budget Type.

CurrencyCode String False

Milestone Currency Code.

Difference Integer False

Milestone Difference.

DifferenceFormatted String False

Milestone Difference Formatted.

Forecasted Integer False

Milestone Forecasted.

ForecastedCostFormatted String False

Milestone Forecasted Cost Formatted.

ForecastedHoursFormatted String False

Milestone Forecasted Hours Formatted.

LastCalculatedTime String False

Milestone Last Calculated Time.

Planned Integer False

Milestone Planned.

PlannedCostFormatted String False

Milestone Planned Cost Formatted.

PlannedHoursFormatted String False

Milestone Planned Hours Formatted.

IsWorkfieldRemoved Boolean False

Milestone Is Work Field Removed.

LastUpdatedDate Date False

Milestone Last Updated Date.

LastUpdatedDateTime Datetime False

Milestone Last Updated Date Time.

SelfUrl String False

Milestone Self Url.

StatusUrl String False

Milestone Status Url.

OwnerId String False

Milestone Owner Id.

OwnerName String False

Milestone Owner Name.

OwnerZpuid String False

Milestone Owner ZPUID.

ProjectId String False

Project Id.

ProjectName String False

Project Name.

Sequence Integer False

Milestone Sequence.

Status String False

Status.

The allowed values are completed, notcompleted.

StatusColorCode String False

Status Color Code.

StatusId String False

Status Id.

StatusName String False

Status Name.

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
DisplayType String

Milestone Display Type.

The allowed values are upcoming, delayed.

LastModifiedTime Datetime

Milestone Last Modified Time.

CData Python Connector for Zoho Projects

ProjectEntityProperties

Retrieves the data stored against an entity. The argument of this method should be the key that was used when the same data was stored.

Table Specific Information

Entity-properties are key-value pairs stored against the project entities. They can be used for storing details that are needed for API integrations but don't have to be visible in the UI. Key has to be a String and the Value could be a simple string or a json object. You can store multiple key-value pair for a single entity. These entity properties can be stored / retrieved / updated / deleted using the below queries.

Select

  • PropertyKey is required to retrieve ProjectEntityProperties.
For example, the following query is processed server side:
SELECT * FROM ProjectEntityProperties WHERE PropertyKey = 'key1' 

Insert

To add a new Project Entity Property specify the PropertyKey and PropertyValue fields.

INSERT INTO ProjectEntityProperties (PropertyKey, PropertyValue) VALUES ('key1', 'This is a test value')

Update

ZohoProjects allows updates for the PropertyValue column.

UPDATE ProjectEntityProperties SET PropertyValue = 'This is an updated property value' WHERE PropertyKey = 'key1'

Delete

Project Entity Properties can be deleted by providing Id, PropertyKey and issuing a DELETE statement.

DELETE FROM ProjectEntityProperties WHERE PropertyKey = 'key1' AND Id = '166135000000035001'

Columns

Name Type ReadOnly Description
Id [KEY] String False

Project Entity Property Id.

PropertyKey [KEY] String False

Project Entity Property Key.

PropertyValue String False

Project Entity Property Value.

CData Python Connector for Zoho Projects

ProjectUsers

Gets the details of all the users in a specific project.

Columns

Name Type ReadOnly Description
Id [KEY] String False

User Id.

Name String False

User Name.

Active Boolean False

User Active.

ChatAccess Boolean False

User Chat Access.

Email String False

User Email.

PortalProfileName String False

User Portal Profile Name.

PortalRoleId String False

User Portal Role Id.

PortalRoleName String False

User Portal Role Name.

ProfileId String False

User Profile Id.

ProfileType String False

User Profile Type.

ProjectProfileId String False

User Project Profile Id.

Role String False

User Role.

The allowed values are manager, employee, contractor.

RoleId String False

User Role Id.

RoleName String False

User Role Name.

Zpuid String False

User ZPUID.

WorkProjects String False

User Work Projects.

UserType String False

User User Type.

The allowed values are active, inactive.

CData Python Connector for Zoho Projects

Statuses

Gets the statuses for the given project.

Select

You can use the below query to get all Statuses:
SELECT * FROM Statuses

Insert

To create a new Status you can specify the following fields:

INSERT INTO Statuses (Content) VALUES ('My Custom Status')

Columns

Name Type ReadOnly Description
Id [KEY] String False

Status Id.

Content String False

Status Content.

PostedBy String False

Status Posted By.

PostedPerson String False

Status Posted Person.

PostedDate Date False

Status Posted Date.

PostedDateTime Datetime False

Status Posted Date Time.

CData Python Connector for Zoho Projects

TaskActivities

Retrieve details of who modified a specific task and when.

Select

  • TaskId is required to retrieve Forum Comments.
You can use the below query to get all Activities for a given Task:
SELECT * FROM TaskActivities WHERE TaskId = '123456789' 

Columns

Name Type ReadOnly Description
TaskId String False

Task Id.

Id [KEY] String False

Task Activity Id.

Name String False

Task Activity Name.

ActivityBy String False

Task Activity By.

OldValue Unknown False

Task Activity Old Value.

NewValue Unknown False

Task Activity New Value.

State String False

Task Activity State.

Time Date False

Task Activity Time.

DateTime Datetime False

Task Activity Date Time.

Zuid String False

Task Activity ZUID.

CData Python Connector for Zoho Projects

TaskComments

Get all the task comments.

Select

  • TaskId is required to retrieve Task Comments.
  • LastModifiedTime supports the following operator: =.
For example, the following query is processed server side:
SELECT * FROM TaskComments WHERE TaskId = '123456000000040013'

Insert

To add a Task Comment specify the TaskId and Comment fields.

INSERT INTO TaskComments (TaskId, content) VALUES ('123456000000040013', 'SQL Comment #6')

Update

To update a Task Comments specify the Id field.

UPDATE TaskComments
	SET Content = 'Updated forum post content' 
	WHERE Id = '123456000000043771' AND TaskId = '123456000000040013'

Delete

Task Comments can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM TaskComments WHERE TaskId = '123456000000045005' AND Id = '123456000000045042' 

Columns

Name Type ReadOnly Description
TaskId [KEY] String False

Task Id.

Id [KEY] String False

Task Comment Id.

Content String False

Task Comment Content.

AddedPersonId String False

Task Comment Added Person Id.

AddedPersonName String False

Task Comment Added Person Name.

AddedVia String False

Task Comment Added Via.

Attachments String False

Task Comment Attachments.

CreatedDate Date False

Task Comment Created Date.

CreatedDateTime Datetime False

Task Comment Created Date Time.

LastModifiedDate Date False

Task Comment Last Modified Date.

LastModifiedDateTime Datetime False

Task Comment Last Modified Date Time.

ProjectName String False

Task Comment Project Name.

SprintsNotesId Integer False

Task Comment Sprints Notes Id.

ThirdPartyAttachments String False

Task Comment Third Party Attachments.

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
LastModifiedTime Datetime

Task Comment Last Modified Time.

CData Python Connector for Zoho Projects

TaskCustomfields

Usage information for the operation TaskCustomfields.rsd.

Columns

Name Type ReadOnly Description
ColumnName [KEY] String False

Task Custom Field Column Name.

ColumnType [KEY] String False

Task Custom Field Column Type.

DisplayName [KEY] String False

Task Custom Field Display Name.

IsDefault [KEY] String False

Task Custom Field Is Default.

IsEncrypted [KEY] String False

Task Custom Field Is Encrypted.

IsMandatory String False

Task Custom Field Is Mandatory.

CData Python Connector for Zoho Projects

TaskEntityProperties

Retrieves the data stored against an entity. The argument of this method should be the key that was used when the same data was stored.

Table Specific Information

Entity-properties are key-value pairs stored against the Task entities. They can be used for storing details that are needed for API integrations but don't have to be visible in the UI. Key has to be a String and the Value could be a simple string or a json object. You can store multiple key-value pair for a single entity. These entity properties can be stored / retrieved / updated / deleted using the below queries.

Select

  • TaskId is required to retrieve Task Entity Properties.
For example, the following query is processed server side:
SELECT * FROM TaskEntityProperties WHERE TaskId = '123456000000034087' AND PropertyKey = 'key1' 

Insert

To add a new Task Entity Property specify the TaskId, PropertyKey and PropertyValue fields.

INSERT INTO TaskEntityProperties (TaskId, PropertyKey, PropertyValue) VALUES ('123456000000034087', 'key1', 'This is a test value')

Update

ZohoProjects allows updates for the PropertyValue column.

UPDATE TaskEntityProperties SET PropertyValue = 'This is an updated property value' WHERE TaskId = '123456000000034087' AND PropertyKey = 'key1'

Delete

Task Entity Properties can be deleted by providing Id, TaskId, PropertyKey and issuing a DELETE statement.

DELETE FROM TaskEntityProperties WHERE TaskId = '166135000000034087' AND PropertyKey = 'key1' AND Id = '166135000000035001'

Columns

Name Type ReadOnly Description
Id [KEY] String False

Task Entity Property Id.

TaskId [KEY] String False

Task Id.

PropertyKey [KEY] String False

Task Entity Property Key.

PropertyValue String False

Task Entity Property Value.

CData Python Connector for Zoho Projects

Tasklists

Get all the task lists in the given project.

Select

  • MilestoneId and Flag support the following operator: =.
For example, the following query is processed server side:
SELECT * FROM Tasklists WHERE MilestoneId = '12345600000123' AND Flag = 'internal' 

Insert

To create a new Tasklist you can specify the following fields:

  • Name
  • MilestoneId
  • TaskTemplateId
  • ShiftDays
  • Flag


INSERT INTO Tasklists (name, flag, ShiftDays)
VALUES ('New Tasklist #2', 'internal', '2022-03-10T01:00:00Z')

Update

To update a Tasklist specify the Id field.

UPDATE Tasklists SET Name = 'SQL Updated tasklist #7' WHERE Id = '123456000000041033'

Delete

Tasklists can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM Tasklists WHERE Id = '123456000000041033'

Columns

Name Type ReadOnly Description
Id [KEY] String False

Tasklist Id.

Name String False

Tasklist Name.

Completed Boolean False

Tasklist Completed.

CreatedDate Date False

Tasklist Created Date.

CreatedDateTime Datetime False

Tasklist Created Date Time.

LastUpdatedDate Date False

Tasklist Last Updated Date.

LastUpdatedDateTime Datetime False

Tasklist Last Updated Date Time.

LinkSelfUrl String False

Tasklist Link Self Url.

LinkTaskUrl String False

Tasklist Link Task Url.

MilestoneClosed Boolean False

Tasklist Milestone Closed.

MilestoneCreatedDate Date False

Tasklist Milestone Created Date.

MilestoneCreatedDateTime Datetime False

Tasklist Milestone Created Date Time.

MilestoneEndDate Date False

Tasklist Milestone End Date.

MilestoneEndDateTime Datetime False

Tasklist Milestone End Date Time.

MilestoneFlag String False

Tasklist Milestone Flag.

MilestoneId String False

Tasklist Milestone Id.

MilestoneIsWorkfieldRemoved Boolean False

Tasklist Milestone Is Workfield Removed.

MilestoneLastUpdatedDate Date False

Tasklist Milestone Last Updated Date.

MilestoneLastUpdatedDateTime Datetime False

Tasklist Milestone Last Updated Date Time.

MilestoneLinkSelfUrl String False

Tasklist Milestone Link Self Url.

MilestoneLinkStatusUrl String False

Tasklist Milestone Link Status Url.

MilestoneName String False

Tasklist Milestone Name.

MilestoneOwnerId String False

Tasklist Milestone Owner Id.

MilestoneOwnerName String False

Tasklist Milestone Owner Name.

MilestoneOwnerZpuid String False

Tasklist Milestone Owner Zpuid.

MilestoneProjectId String False

Tasklist Milestone Project Id.

MilestoneProjectName String False

Tasklist Milestone Project Name.

MilestoneSequence Integer False

Tasklist Milestone Sequence.

MilestoneStartDate Date False

Tasklist Milestone Start Date.

MilestoneStartDateTime Datetime False

Tasklist Milestone Start Date Time.

MilestoneStatus String False

Tasklist Milestone Status.

MilestoneStatusDetColorcode String False

Tasklist Milestone Status Det Colorcode.

MilestoneStatusDetId String False

Tasklist Milestone Status Det Id.

MilestoneStatusDetName String False

Tasklist Milestone Status Det Name.

Rolled Boolean False

Tasklist Rolled.

Sequence Integer False

Tasklist Sequence.

TaskCountOpen Integer False

Tasklist Task Count Open.

TaskTemplateId String False

Id of the task list template.

ShiftDays Datetime False

The ISO 8601 Datetime from which the Task start date is calculated, based on shift days.

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
Flag String

Tasklist Flag.

The allowed values are internal, external.

CData Python Connector for Zoho Projects

Tasks

Gets all the tasks in the given project. It fetches only the main tasks and not the subtasks.

Select

Columns that support the = operator:
  • Id
  • CreatedBy
  • MilestoneId
  • Priority
  • TasklistId
  • Owner
  • Status
  • Time
  • LastModifiedTime
  • ViewId

  • CreatedDate and LastModifiedTime support: ORDER
For example, the following query is processed server side:
SELECT * FROM Tasks WHERE MilestoneId = '12345600000123' AND Priority = 'High' ORDER BY CreatedDate

Insert

To create a new Task you can specify the following fields:

  • Name
  • Description
  • Owners
  • Duration
  • DurationType
  • EndDate
  • Priority
  • StartDate
  • TasklistId
  • Work
  • GroupNameAssociatedTeamsAnyTeam
  • RatePerHour
  • ReminderString
  • Recurrence
  • BudgetValue
  • BudgetThreshold


INSERT INTO Tasks (Name, Description, Duration, DurationType, Priority,  BudgetValue)
VALUES ('New Task #2', 'This is a test description', '5', 'hrs', 'High', '1000')

Update

To update a Task specify the Id field.

UPDATE Tasks SET Priority = 'Low' WHERE Id = '123456000000034003'

Delete

Tasks can be deleted by providing the Id and issuing a DELETE statement.

DELETE FROM Tasks WHERE Id = '123456000000034003'

Columns

Name Type ReadOnly Description
Id [KEY] String False

Task Id.

Name String False

Task Name.

Key String False

Task Key.

BillingType String False

Task Billing Type.

Completed Boolean False

Task Completed.

CreatedBy String False

Task Created By.

CreatedByEmail String False

Task Created By Email.

CreatedByZpuid String False

Task Created By Zpuid.

CreatedPerson String False

Task Created Person.

CreatedDate Date False

Task Created Date.

CreatedDateTime Datetime False

Task Created Date Time.

Description String False

Task Description.

Owners String False

Task Owners.

Duration String False

Task Duration.

DurationType String False

Task Duration Type.

The allowed values are days, hrs.

EndDate Date False

Task End Date.

EndDateTime Datetime False

Task End Date Time.

CommentAdded Boolean False

Task Comment Added.

DocsAssociated Boolean False

Task Docs Associated.

ForumAssociated Boolean False

Task Forum Associated.

RecurrenceSet Boolean False

Task Recurrence Set.

ReminderSet Boolean False

Task Reminder Set.

Parent Boolean False

Task Parent.

LastUpdatedDate Date False

Task Last Updated Date.

LastUpdatedDateTime Datetime False

Task Last Updated Date Time.

LinkSelfUrl String False

Task Link Self Url.

LinkTimesheetUrl String False

Task Link Timesheet Url.

LinkWebUrl String False

Task Link Web Url.

LogHoursBillableHours String False

Task Log Hours Billable Hours.

LogHoursNonBillableHours String False

Task Log Hours Non Billable Hours.

MilestoneId String False

Task Milestone Id.

OrderSequence Integer False

Task Order Sequence.

PercentComplete String False

Task Percent Complete.

Priority String False

Task Priority.

The allowed values are none, low, medium, high.

StartDate Date False

Task Start Date.

StartDateTime Datetime False

Task Start Date Time.

StatusColorCode String False

Task Status Color Code.

StatusName String False

Task Status Name.

StatusId String False

Task Status Id.

StatusType String False

Task Status Type.

Subtasks Boolean False

Task Subtasks.

TaskFollowers String False

Task Task Followers.

TaskFollowerSize Integer False

Task Task Follower Size.

TasklistId String False

Tasklist Id.

TasklistName String False

Tasklist Name.

Work String False

Task Work.

WorkForm String False

Task Work Form.

WorkType String False

Task Work Type.

The allowed values are work_hrs_per_day.

GroupNameAssociatedTeamsAnyTeam String False

Task Group Name Associated Teams Any Team.

GroupNameAssociatedTeamsCount Integer False

Task Group Name Associated Teams Count.

GroupNameIsTeamUnassigned Boolean False

Task Group Name Is Team Unassigned.

RatePerHour String False

Task Rate Per Hour.

ReminderString String False

Task Reminder String.

Recurrence String False

Task Recurrence.

BudgetValue String False

Task Budget Value.

BudgetThreshold String False

Task Budget Threshold.

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
Owner String

Task Owner.

Status String

Task Status.

The allowed values are completed, notcompleted.

Time String

Task Time.

The allowed values are overdue, today, tomorrow.

LastModifiedTime Datetime

Task Last Modified Time.

ViewId String

Task View Id.

CData Python Connector for Zoho Projects

TaskSubtasks

View all the subtasks of the given task.

Select

  • TaskId is required to retrieve Task Subtasks.
You can use the below query to get all Task Subtasks:
SELECT * FROM TaskSubtasks WHERE TaskId = '12345600000123' 

Insert

To create a new Task you can specify the following fields:

  • TaskId
  • Name
  • Description
  • Duration
  • DurationType
  • Priority
  • StartDate
  • EndDate
  • PersonResponsible


INSERT INTO TaskSubtasks (TaskId, Name, StartDate, EndDate, Duration, DurationType, Priority, Description)
VALUES ('165818000000040013', 'Sql Subtask #4', '2022-03-01', '2022-03-10', '2', 'hrs', 'High', 'Test description of the subtask')

Columns

Name Type ReadOnly Description
TaskId String False

Task Id.

Id [KEY] String False

Subtask Id.

Name String False

Subtask Name.

Key String False

Subtask Key.

BillingType String False

Subtask Billing Type.

Completed Boolean False

Subtask Completed.

CreatedBy String False

Subtask Created By.

CreatedByEmail String False

Subtask Created By Email.

CreatedByZpuid String False

Subtask Created By Zpuid.

CreatedPerson String False

Subtask Created Person.

CreatedTime Date False

Subtask Created Time.

CreatedDateTime Datetime False

Subtask Created Date Time.

Depth Integer False

Subtask Depth.

Description String False

Subtask Description.

DetailsOwners String False

Subtask Details Owners.

Duration String False

Subtask Duration.

DurationType String False

Subtask Duration Type.

The allowed values are days, hrs.

IsCommentAdded Boolean False

Subtask Is Comment Added.

IsDocsAssociated Boolean False

Subtask Is Docs Associated.

IsForumAssociated Boolean False

Subtask Is Forum Associated.

IsRecurrenceSet Boolean False

Subtask Is Recurrence Set.

IsReminderSet Boolean False

Subtask Is Reminder Set.

IsParent Boolean False

Subtask Is Parent.

LastUpdatedTime Date False

Subtask Last Updated Time.

LastUpdatedDateTime Datetime False

Subtask Last Updated Date Time.

LinkSelfUrl String False

Subtask Link Self Url.

LinkTimesheetUrl String False

Subtask Link Timesheet Url.

LinkWebUrl String False

Subtask Link Web Url.

LogBillableHours String False

Subtask Log Billable Hours.

LogNonBillableHours String False

Subtask Log Non Billable Hours.

MilestoneId String False

Subtask Milestone Id.

OrderSequence Integer False

Subtask Order Sequence.

ParentTaskId String False

Subtask Parent Task Id.

PercentComplete String False

Subtask Percent Complete.

Priority String False

Subtask Priority.

The allowed values are none, low, medium, high.

RootTaskId String False

Subtask Root Task Id.

StatusColorCode String False

Subtask Status Color Code.

StatusId String False

Subtask Status Id.

StatusName String False

Subtask Status Name.

StatusType String False

Subtask Status Type.

Subtasks Boolean False

Subtask Subtasks.

TaskFollowers String False

Subtask Task Followers.

TaskFollowerSize Integer False

Subtask Task Follower Size.

TasklistId String False

Subtask Tasklist Id.

TasklistName String False

Subtask Tasklist Name.

Work String False

Subtask Work.

WorkForm String False

Subtask Work Form.

WorkType String False

Subtask Work Type.

GroupNameAssociatedTeamsAnyTeam String False

Subtask Group Name Associated Teams Any Team.

GroupNameAssociatedTeamsCount Integer False

Subtask Group Name Associated Teams Count.

GroupNameIsTeamUnassigned Boolean False

Subtask Group Name Is Team Unassigned.

StartDate Date False

Subtask Start Date.

EndDate Date False

Subtask End Date.

PersonResponsible String False

Subtask Person Responsible.

CData Python Connector for Zoho Projects

TaskTimelogs

Gets the time logs under a specific task.

Select

  • TaskId is required to retrieve Task Time Logs.
For example, the following query is processed server side:
SELECT * FROM TaskTimelogs WHERE TaskId = '123456000000045005'

Insert

To create a new Task Timelog you can specify the following fields:

  • TaskId
  • BillStatus
  • Notes
  • HoursDisplay
  • LogDate
  • OwnerId


INSERT INTO TaskTimelogs (TaskId, LogDate, BillStatus, HoursDisplay, Notes) " +
VALUES ('123456000000040013', '2022-03-03', 'Non Billable', '01:20', 'This is a test timelog')

Update

To update a Task TimeLog specify the TaskId and Id fields.

UPDATE TaskTimelogs
	SET Notes = 'This is an updated SQL Note'
	WHERE TaskId = '165818000000040013' AND Id = '165818000000045001'

Delete

Task TimeLogs can be deleted by providing the TaskId and Id and issuing a DELETE statement.

DELETE FROM TaskTimelogs WHERE TaskId = '123456000000045005' AND Id = '123456000000044025'

Columns

Name Type ReadOnly Description
TaskId [KEY] String False

Task Id.

Id [KEY] String False

Task Time Log Id.

AddedByName String False

Task Time Log Added By Name.

AddedByZpuid String False

Task Time Log Added By Zpuid.

AddedByZuid Long False

Task Time Log Added By Zuid.

ApprovalStatus String False

Task Time Log Approval Status.

ApproverName String False

Task Time Log Approver Name.

BillStatus String False

Task Time Log Bill Status.

The allowed values are Billable, Non Billable.

CreatedDate Date False

Task Time Log Created Date.

CreatedDateTime Datetime False

Task Time Log Created Date Time.

StartTime Datetime False

Task Time Log Start Time.

EndTime Datetime False

Task Time Log End Time.

Notes String False

Task Time Log Notes.

HoursDisplay String False

Task Time Log Hours Display.

Hours Integer False

Task Time Log Hours.

Minutes Integer False

Task Time Log Minutes.

IsParent Boolean False

Task Time Log Is Parent.

IsSubTask Boolean False

Task Time Log Is Sub Task.

LastModifiedDate Date False

Task Time Log Last Modified Date.

LastModifiedDateTime Datetime False

Task Time Log Last Modified Date Time.

LinkSelfUrl String False

Task Time Log Link Self Url.

LogDate Date False

Task Time Log Date.

LogDateTime Datetime False

Task Time Log Date Time.

OwnerId String False

Task Time Log Owner Id.

OwnerName String False

Task Time Log Owner Name.

SubTaskLevel String False

Task Time Log Sub Task Level.

TaskName String False

Task Time Log Task Name.

TaskListId Long False

Task Time Log Task List Id.

TaskListName String False

Task Time Log Task List Name.

TotalMinutes Integer False

Task Time Log Total Minutes.

CData Python Connector for Zoho Projects

TeamUsers

Fetch details of a particular team.

Select

  • GroupId is required to retrieve Team Users.
You can use the below query to get all Team Users:
SELECT * FROM TeamUsers WHERE GroupId = '123456000000033021'

Insert

To create a new Team you must specify the following fields:

  • GroupId
  • Zpuid


INSERT INTO TeamUsers (GroupId, ZPUID)
VALUES ('123456000000034163', '123456000000031003')

Delete

TeamUsers can be deleted by providing the GroupId and Id and issuing a DELETE statement.

DELETE FROM TeamUsers WHERE GroupId = '123456000000034163' AND Id = '123456000000031003'

Columns

Name Type ReadOnly Description
ProjectId String False

Project Id.

GroupId String False

Team Id.

Id [KEY] String False

User Id.

Name String False

User Name.

AddedBy String False

User Added By.

AddedTime String False

User Added Time.

Confirmed String False

User Confirmed.

CreatedBy String False

User Created By.

CreatedTime String False

User Created Time.

CreatedUser String False

User Created User.

Description String False

User Description.

DisplayName String False

User Display Name.

Email String False

User Email.

EntityType String False

User Entity Type.

FirstName String False

User First Name.

IsClient Boolean False

User Is Client.

IsDefault Boolean False

User Is Default.

LastAccessedTime String False

User Last Accessed Time.

LastName String False

User Last Name.

LastUpdatedTime String False

User Last Updated Time.

RoleId String False

User Role Id.

RoleName String False

User Role Name.

Type String False

User Type.

UpdatedBy String False

User Updated By.

UpdatedDate String False

User Updated Date.

UpdatedDateTime String False

User Updated Date Time.

UserStatus String False

User User Status.

Zpuid String False

User Zpuid.

Zuid String False

User Zuid.

CData Python Connector for Zoho Projects

Views

The connector models the entities for which Zoho Projects only provides read-only access as views.

It exposes each project tied to your account as a schema with the following views.

Navigate to an individual view's page for a breakdown of its columns and supported filters.

CData Python Connector for Zoho Projects Views

Name Description
Activities List all the recent activities of the project.
BugActivities Gets all the activities for the given bug.
BugAttachments Get details of attachments for a bug.
BugCustomFields Gets all the custom fields in the given project.
BugResolution Get bug's resolution.
Clients Returns the list of client companies associated with a specific project Id.
Documents List all the recent activities of the project.
TaskAttachments Retrieve details of attachments associated to the task.
Timelogs Gets the time logs under a specific bug.

CData Python Connector for Zoho Projects

Activities

List all the recent activities of the project.

Select

This is a project-level view. You can use the below query to get all Activities:
SELECT * FROM Activities

Columns

Name Type Description
Id [KEY] String Project Activity Id.
Name String Project Activity Name.
Activity By String Project Activity Author.
Activity For String Project Activity For Entity.
Display Time String Project Activity Display Time.
State String Project Activity State.
Time String Project Activity Time.

CData Python Connector for Zoho Projects

BugActivities

Gets all the activities for the given bug.

Select

This is a bug-level view.
  • BugId is required to retrieve BugActivities.
You can use the below query to get all BugActivities:
SELECT * FROM BugActivities WHERE BugId = '12345600001'

Columns

Name Type Description
BugId String Bug Id.
Action String Bug Activity Action.
Type String Bug Activity Type.
PreviousValue String Bug Activity Previous Value.
CurrentValue String Bug Activity Current Value.
ActionBy String Bug Activity Action By.
ActionField String Bug Activity Action Field.
ActionDate Date Bug Activity Action Date.
ActionDateTime Datetime Bug Activity Action Date Time.
Zuid [KEY] String Bug Activity ZUID.

CData Python Connector for Zoho Projects

BugAttachments

Get details of attachments for a bug.

Columns

Name Type Description
BugId String Bug Id.
AttachmentId Long Attachment Id.
FileName String Attached File Name.
FileType String Attached File Type.
FileSize Integer Attached File Size.
FileEncAttachParam String Attached File Enc Attach Param.
FileUri String Attached File Uri.
AttachedDate Date Attached Date.
AttachedDateTime Datetime Attached Date Time.
AuthorId String Attachment Author Id.
AuthorName String Attachment Author Name.
IsDocsAttachment Boolean Is Docs Attachment.

CData Python Connector for Zoho Projects

BugCustomFields

Gets all the custom fields in the given project.

Select

This is a project-level view. You can use the below query to get all BugCustomFields:
SELECT * FROM BugCustomFields WHERE BugId = '12345600001'

Columns

Name Type Description
LabelName String Bug Custom Field Label Name.
ColumnName String Bug Custom Field Column Name.
DefaultValue String Bug Custom Field Default Value.
FieldType String Bug Custom Field Field Type.
IsEnc Boolean Bug Custom Field Is Enc.
IsMandatory Boolean Bug Custom Field Is Mandatory.
IsPi Boolean Bug Custom Field Is Pi.
IsVisible Boolean Bug Custom Field Is Visible.
NewColumnName String Bug Custom Field New Column Name.
PicklistValues String Bug Custom Field Picklist Values.

CData Python Connector for Zoho Projects

BugResolution

Get bug's resolution.

Columns

Name Type Description
BugId String Bug Id.
Resolver String Bug Resolver.
ResolverId String Bug Resolver Id.
Resolution String Bug Resolution.
ResolutionThirdPartyAttachments String Bug Resolution Third Party Attachments.
ResolvedDate Date Bug Resolved Date.
ResolvedDateTime Datetime Bug Resolved Date Time.
ResolverZpuid String Bug Resolver ZPUID.

CData Python Connector for Zoho Projects

Clients

Returns the list of client companies associated with a specific project Id.

Select

This is a project-level view.
  • Id supports the following operator: =.
For example, the following query is processed server side:
SELECT * FROM Clients WHERE Id = '12345600001'

Columns

Name Type Description
Id [KEY] String Client Id.
Name String Client Name.
City String Client City.
Country String Client Country.
CrmAccountId String Client Crm Account Id.
FirstAddress String Client First Address.
SecondAddress String Client Second Address.
State String Client State.
WebAddress String Client Web Address.
ZipCode String Client Zip Code.
UserId String Client User Id.
UserName String Client User Name.
UserEmail String Client User Email.
UserZpuid String Client User ZPUID.

CData Python Connector for Zoho Projects

Documents

List all the recent activities of the project.

Columns

Name Type Description
Id [KEY] String Project Activity Id.
Name String Project Activity Name.
Activity By String Project Activity Author.
Activity For String Project Activity For.
Display Time String Project Activity Display Time.
State String Project Activity State.
Time String Project Activity Time.

CData Python Connector for Zoho Projects

TaskAttachments

Retrieve details of attachments associated to the task.

Select

This is a project-level view.
  • TaskId is required to retrieve TaskAttachments.
You can use the below query to get all TaskAttachments:
SELECT * FROM TaskAttachments WHERE TaskId = '123456000000112'

Columns

Name Type Description
TaskId String Task Id.
Id [KEY] String Task Attachment Id.
AuthorId String Task Attachment Author Id.
ContentType String Task Attachment Content Type.
DocsDownloadUrl String Task Attachment Docs Download Url.
DownloadUrl String Task Attachment Download.
Extension String Task Attachment Extension.
Filename String Task Attachment Filename.
Owner String Task Attachment Owner.
Size Integer Task Attachment size in bytes..
TaskId Long Task Attachment Task Id.
ThumbnailUrl String Task Attachment Thumbnail Url.
UploadedTime Long Task Attachment Uploaded Time.

CData Python Connector for Zoho Projects

Timelogs

Gets the time logs under a specific bug.

Select

This is a project-level view. Columns that support the = operator:
  • BillStatus
  • User
  • ComponentType

Columns that support the >,>=,=,<,<= operators:
  • Date
  • LastModifiedDate

For example, the following queries are processed server side:
SELECT * FROM Timelogs WHERE Date > '2024-01-01'

SELECT * FROM Timelogs WHERE LastModifiedDate > '2024-01-01'
Querying Timelogs without filters will return data for only the current month:
SELECT * FROM Timelogs

Columns

Name Type Description
Id [KEY] String Time Log Id.
AddedByName String Time Log Added By Name.
AddedByZpuid String Time Log Added By Zpuid.
AddedByZuid Long Time Log Added By Zuid.
ApprovalStatus String Time Log Approval Status.
ApproverName String Time Log Approver Name.
BillStatus String Time Log Bill Status.

The allowed values are all, billable, non billable.

CreatedDate Date Time Log Created Date.
CreatedDateTime Datetime Time Log Created Date Time.
StartTime Datetime Time Log Start Time.
EndTime Datetime Time Log End Time.
Notes String Time Log Notes.
HoursDisplay String Time Log Hours Display.
Hours Integer Time Log Hours.
Minutes Integer Time Log Minutes.
IsParent Boolean Time Log Is Parent.
IsSubTask Boolean Time Log Is Sub Task.
LastModifiedDate Date Time Log Last Modified Date.
LastModifiedDateTime Datetime Time Log Last Modified Date Time.
LinkSelfUrl String Time Log Link Self Url.
LogDate Date Time Log Date.
LogDateTime Datetime Time Log Date Time.
OwnerId String Time Log Owner Id.
OwnerName String Time Log Owner Name.
SubTaskLevel String Time Log Sub Task Level.
TaskName String Time Log Task Name.
TaskListId Long Time Log Task List Id.
TaskListName String Time Log Task List Name.
TotalMinutes Integer Time Log Total Minutes.
Date Date Time Log Date.
User String Time Log User.
ComponentType String Time Log Component Type.

The allowed values are bug, task, general.

CData Python Connector for Zoho Projects

All Portals

Overview

The connector models information about all of the portals attached to your account in the "ZohoProjects" schema in the "CData" catalog.

Tables

The Tables section contains a single table, Portals, which stores information about your account's portals, such as company names, profile names, and portal roles.

Stored Procedures

Stored Procedures are function-like interfaces to Zoho Projects. Stored procedures allow you to execute operations to Zoho Projects, including approving timelogs and reordering tasks.

CData Python Connector for Zoho Projects

Tables

The connector models account-level information about all portals as a single "Portals" table.

CData Python Connector for Zoho Projects Tables

Name Description
Portals Gets all the portals for the logged in user.

CData Python Connector for Zoho Projects

Portals

Gets all the portals for the logged in user.

Select

The connector will use the Zoho Projects 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.

  • Id and ViewId support the following operator: =.
For example, the following query is processed server side:
SELECT * FROM Portals WHERE Id = '20081021809'

Columns

Name Type ReadOnly Description
Id [KEY] String False

Portal Id.

Name String False

Portal Name.

CompanyName String False

Portal Company Name.

AvailableClients Integer False

Portal Available Clients.

AvailableUsers Integer False

Portal Available Users.

AvailableProjects Integer False

Portal Available Projects.

BugPlan String False

Portal Bug Plan.

BugPlural String False

Bug Plural.

BugSingular String False

Bug Singular.

CanAddTemplate Boolean False

Can Add Portal Template.

CanCreateProject Boolean False

Can Create Portal Project.

Default Boolean False

Default Portal.

ExtensionsAppSettings String False

Portal Extensions Locations App Settings.

ExtensionsAttachmentPicker String False

Portal Extensions Locations Attachment Picker.

ExtensionsBlueprintDuring String False

Portal Extensions Locations Blueprint During.

ExtensionsIssueTab String False

Portal Extensions Locations Issue Tab.

ExtensionsIssuedetailsRightpanel String False

Portal Extensions Locations Issue Details Right Panel.

ExtensionsProjectTab String False

Portal Extensions Locations Project Tab.

ExtensionsTaskTab String False

Portal Extensions Locations Task Tab.

ExtensionsTaskTransition String False

Portal Extensions Locations Task Transition.

ExtensionsTaskdetailsRightpanel String False

Portal Extensions Locations Task Details Right Panel.

ExtensionsTopBand String False

Portal Extensions Locations Top Band.

GmtTimeZone String False

Portal GMT Time Zone.

GmtTimeZoneOffset Integer False

Portal GMT Time Zone Offset.

MeetingEnabled Boolean False

Portal Meeting Enabled.

PeopleEnabled Boolean False

Portal People Enabled.

CrmPartner Boolean False

Portal CRM Partner.

DisplayProjectPrefix Boolean False

Portal Display Project Prefix.

DisplayTaskPrefix Boolean False

Portal Display Task Prefix.

NewPlan Boolean False

Portal New Plan.

SprintsIntegrated Boolean False

Portal Sprints Integrated.

TagsAvailable Boolean False

Portal Tags Available.

TimeLogRestricted Boolean False

Portal Time Log Restricted.

ProjectsModuleId String False

Portal Projects Module Id.

TasksModuleId String False

Portal Tasks Module Id.

ProjectUrl String False

Portal Project URL.

LocaleCode String False

Portal Locale Code.

LocaleCountry String False

Portal Locale Country.

Language String False

Portal Language.

LoginZpuid Long False

Portal Login ZPUID.

MaxClients Integer False

Portal Max Clients.

MaxUsers Integer False

Portal Max Users.

NewUserPlan Boolean False

Portal New User Plan.

PercentageCalculation String False

Portal Percentage Calculation.

Plan String False

Portal Plan.

ProfileId Long False

Portal Profile Id.

ProfileName String False

Portal Profile Name.

ProfileType Integer False

Portal Profile Type.

ActiveProjects Integer False

Portal Active Projects.

ProjectPrefix String False

Portal Project Prefix.

Role String False

Portal Role.

RoleId String False

Portal Role Id.

RoleName String False

Portal Role Name.

BusinessHoursEnd Integer False

Portal Business Hours End.

BusinessHoursStart Integer False

Portal Business Hours Start.

DateFormat String False

Portal Date Format.

DefaultCurrency String False

Portal Default Currency.

DefaultDependencyType String False

Portal Default Dependency Type.

BudgetPermission Boolean False

Portal Budget Permission.

Holidays String False

Portal Holidays.

BudgetEnabled Boolean False

Portal Budget Enabled.

LastSyncTime String False

Portal Last Sync Time.

StartDayOfWeek String False

Portal Start Day of Week.

TaskDateFormat String False

Portal Task Date Format.

TaskDurationType String False

Portal Task Duration Type.

TimeZone String False

Portal Time Zone.

EditTimeLogRestricted Boolean False

Portal Edit Time Log Restricted.

LogFutureTimeAllowed Boolean False

Portal Log Future Time Allowed.

LogPastTimeAllowed Boolean False

Portal Log Past Time Allowed.

DefaultBillingStatus String False

Portal Default billing Status.

TimesheetApprovalEnabled Boolean False

Portal Timesheet Approval Enabled.

WorkingDays String False

Portal Working Days.

SprintsProjectPermission Boolean False

Portal Sprints Project Permission.

StorageType String False

Portal Storage Type.

TrialEnabled Boolean False

Portal Trial Enabled.

LogHrRestrictedByWorkHr Boolean False

Portal Log Hr restricted by Work Hr.

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
ViewId String

CData Python Connector for Zoho Projects

Stored Procedures

Stored procedures are function-like interfaces that enable the connector to perform actions beyond the scope of basic data access. They accept a list of parameters, perform an action, and return response data from Zoho Projects and/or a confirmation of the success or failure of the procedure.

The full list of procedures is provided below. Navigate to an individual procedure's page for a breakdown of its functionality, inputs, and outputs.

CData Python Connector for Zoho Projects Stored Procedures

Name Description
AddUserToClientCompany Adds user to an existing client company.
ApproveTimelog Approve general/bug/task time log.
AssociateBugs Associate related bugs to a task.
AssociateContacts Associates a tag with a specific entity in a specific project.
AssociateTags Associates a tag with a specific entity in a specific project.
DissociateBugs Associate related bugs to a task.
DissociateContacts Dissociate a client contact from a project.
DissociateTags Dissociates a tag with a specific entity in a specific project.
ForumFollow Follow a forum post.
ForumSelectBestAnswer Unfollow a forum post.
ForumUnfollow Unfollow a forum post.
ForumUnselectBestAnswer Unfollow a forum post.
GetOAuthAccessToken Gets an authentication token from ZohoProjects.
GetOAuthAuthorizationURL Gets the authorization URL that must be opened separately by the user to grant access to your application. Only needed when developing Web apps. You will request the OAuthAccessToken from this URL.
RefreshOAuthAccessToken Refreshes the OAuth access token used for authentication with ZohoProjects.
SelectTeamLead Update the team lead.
TaskFollow Follow a task in the given project.
TaskMove Moves a task from one tasklist to another tasklist. The target tasklist can be of the same project or different project.
TaskReorder Reorders the tasks in the given project. Task will be reordered in-between two tasks based on the previous and next task Ids.
TaskUnfollow Unfollow a task in the given project.

CData Python Connector for Zoho Projects

AddUserToClientCompany

Adds user to an existing client company.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC AddUserToClientCompany PortalId = '12345317133', CompanyId = '123456000000039025', ContactEmail = 'test@example.com'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
CompanyId String True Specify the client company Id.
ContactEmail String True Email Id of the client user.
WorkProjects String False Multiple project Ids are separated using comma.
ProfileId String False Specify Profile Id. profile_id is obtained from Get Portal Users API.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

ApproveTimelog

Approve general/bug/task time log.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC ApproveTimelog PortalId = '12345317133', ProjectId = '123456000000031899', LogId = '123456000000031977', Approval = 'approve', Reason = 'Submitted timelog is approved', EntityType = 'general', EntityId = '1234560001'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
LogId String True Specify the log Id.
EntityType String False Specify the entity type to approve the log time.

The allowed values are task, bug, general.

EntityId String False Id of entity specified by parameter 'EntityType'
Approval String True The time log is approved if the given value is approve

The allowed values are approve, pending, reject.

Reason String False Reason should be mentioned if the time log is rejected. The reason shouldn't exceed 250 characters.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

AssociateBugs

Associate related bugs to a task.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC AssociateBugs PortalId = '12345317133', ProjectId = '123456000000031899', TaskId = '123456000000031977', BugId = '123456000000034087'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
TaskId String True Specify the task Id.
BugId String True Id for multiple bugs must be separated by commas.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

AssociateContacts

Associates a tag with a specific entity in a specific project.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC AssociateContacts PortalId = '12345317133', ProjectId = '123456000000031899', ContactId = '1234560000000123456'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
ContactId String True Array of client contact Ids. Multiple Ids can be separated by comma.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

AssociateTags

Associates a tag with a specific entity in a specific project.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC AssociateTags PortalId = '12345317133', ProjectId = '123456000000031899', TagId = '123456000000031977', EntityType = 'Task',  EntityId = '123456000000034087'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
TagId String True Specify the tag Id.
EntityType String True Specify the entity type to approve the log time.

The allowed values are Project, Milestone, Tasklist, Task, Bug, Forum, Status.

EntityId String True Id of entity specified by parameter 'EntityType'

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

DissociateBugs

Associate related bugs to a task.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC DissociateBugs PortalId = '12345317133', ProjectId = '123456000000031899', TaskId = '123456000000031977', BugId = '123456000000034087'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
TaskId String True Specify the task Id.
BugId String True Id for multiple bugs must be separated by commas.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

DissociateContacts

Dissociate a client contact from a project.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC DissociateContacts PortalId = '12345317133', ProjectId = '123456000000031899', ContactId = '1234560000000123456'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
ContactId String True Array of client contact Ids.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

DissociateTags

Dissociates a tag with a specific entity in a specific project.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC DissociateTags PortalId = '12345317133', ProjectId = '123456000000031899', TagId = '123456000000031977', EntityType = 'Task',  EntityId = '123456000000034087'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
TagId String True Specify the tag Id.
EntityType String True Specify the entity type to approve the log time.

The allowed values are Project, Milestone, Tasklist, Task, Bug, Forum, Status.

EntityId String True Id of entity specified by parameter 'EntityType'

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

ForumFollow

Follow a forum post.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC ForumFollow PortalId = '12345317133', ProjectId = '123456000000031899', ForumId = '123456000000034053'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
ForumId String True Specify the tag Id.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

ForumSelectBestAnswer

Unfollow a forum post.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC ForumSelectBestAnswer PortalId = '12345317133', ProjectId = '123456000000031899', ForumId = '123456000000034053', CommentId = '123456000000039021'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
ForumId String True Specify the forum Id.
CommentId String True Specify the comment Id.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

ForumUnfollow

Unfollow a forum post.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC ForumUnfollow PortalId = '12345317133', ProjectId = '123456000000031899', ForumId = '123456000000034053'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
ForumId String True Specify the tag Id.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

ForumUnselectBestAnswer

Unfollow a forum post.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC ForumUnselectBestAnswer PortalId = '12345317133', ProjectId = '123456000000031899', ForumId = '123456000000034053', CommentId = '123456000000039021'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
ForumId String True Specify the forum Id.
CommentId String True Specify the comment Id.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

GetOAuthAccessToken

Gets an authentication token from ZohoProjects.

Input

Name Type Required Description
AuthMode String False The type of authentication mode to use. Select App for getting authentication tokens via a desktop app. Select Web for getting authentication tokens via a Web app.

The allowed values are APP, WEB.

The default value is APP.

Scope String False A comma-separated list of permissions to request from the user. Please check the ZohoProjects API for a list of available permissions.

The default value is ZohoProjects.portals.ALL,ZohoProjects.projects.ALL,ZohoProjects.status.ALL,ZohoProjects.milestones.ALL,ZohoProjects.tasklists.ALL,ZohoProjects.tasks.ALL,ZohoProjects.tags.ALL,ZohoProjects.bugs.ALL,ZohoProjects.events.ALL,ZohoProjects.forums.ALL,ZohoProjects.users.ALL,ZohoProjects.clients.ALL,ZohoProjects.documents.ALL,ZohoProjects.search.READ,ZohoProjects.entity_properties.ALL,ZohoProjects.activities.READ,ZohoProjects.timesheets.ALL.

CallbackUrl String False The URL the user will be redirected to after authorizing your application. This value must match the Redirect URL you have specified in the ZohoProjects app settings. Only needed when the Authmode parameter is Web.
Verifier String False The verifier returned from ZohoProjects after the user has authorized your app to have access to their data. This value will be returned as a parameter to the callback URL.
State String False Indicates any state which may be useful to your application upon receipt of the response. Your application receives the same value it sent, as this parameter makes a round-trip to the ZohoProjects authorization server and back. Uses include redirecting the user to the correct resource in your site, nonces, and cross-site-request-forgery mitigations.
AccountsServer String False The full Account Server URL that will be used to retrieve the OAuth Access Token.

Result Set Columns

Name Type Description
OAuthAccessToken String The access token used for communication with ZohoProjects.
OAuthRefreshToken String A token that may be used to obtain a new access token.
ExpiresIn String The remaining lifetime on the access token. A -1 denotes that it will not expire.
AccountsServer String The full Account Server URL.
APIDomain String The full URL of the API domain.

CData Python Connector for Zoho Projects

GetOAuthAuthorizationURL

Gets the authorization URL that must be opened separately by the user to grant access to your application. Only needed when developing Web apps. You will request the OAuthAccessToken from this URL.

Input

Name Type Required Description
CallbackUrl String False The URL the user will be redirected to after authorizing your application. This value must match the Redirect URL in the ZohoProjects app settings.
Scope String False A comma-separated list of scopes to request from the user. Please check the ZohoProjects API documentation for a list of available permissions.

The default value is ZohoProjects.portals.ALL,ZohoProjects.projects.ALL,ZohoProjects.status.ALL,ZohoProjects.milestones.ALL,ZohoProjects.tasklists.ALL,ZohoProjects.tasks.ALL,ZohoProjects.tags.ALL,ZohoProjects.bugs.ALL,ZohoProjects.events.ALL,ZohoProjects.forums.ALL,ZohoProjects.users.ALL,ZohoProjects.clients.ALL,ZohoProjects.documents.ALL,ZohoProjects.search.READ,ZohoProjects.entity_properties.ALL,ZohoProjects.activities.READ,ZohoProjects.timesheets.ALL.

State String False Indicates any state which may be useful to your application upon receipt of the response. Your application receives the same value it sent, as this parameter makes a round-trip to the ZohoProjects authorization server and back. Uses include redirecting the user to the correct resource in your site, nonces, and cross-site-request-forgery mitigations.

Result Set Columns

Name Type Description
URL String The authorization URL, entered into a Web browser to obtain the verifier token and authorize your app.

CData Python Connector for Zoho Projects

RefreshOAuthAccessToken

Refreshes the OAuth access token used for authentication with ZohoProjects.

Input

Name Type Required Description
OAuthRefreshToken String True The refresh token returned from the original authorization code exchange.
AccountsServer String False The full Account Server URL that will be used to retrieve a new access token.

Result Set Columns

Name Type Description
OAuthAccessToken String The access token returned from ZohoProjects. This can be used in subsequent calls to other operations for this particular service.
OAuthRefreshToken String A token that may be used to obtain a new access token.
ExpiresIn String The remaining lifetime on the access token.

CData Python Connector for Zoho Projects

SelectTeamLead

Update the team lead.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC SelectTeamLead PortalId = '12345317133', ProjectId = '123456000000031899', UserId = '123456000000033053'

Input

Name Type Required Description
PortalId String False Specify the portal Id.
TeamId String False Specify the group Id.
UserId String False ZPUID of the team lead.

Result Set Columns

Name Type Description
Success String Specifies whether the update was successful.

CData Python Connector for Zoho Projects

TaskFollow

Follow a task in the given project.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC TaskFollow PortalId = '12345317133', ProjectId = '123456000000031899', TaskId = '123456000000034053', UserId = '123456000000039021'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
TaskId String True Specify the task Id.
UserId String True User Id for multiple followers must be separated by commas.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

TaskMove

Moves a task from one tasklist to another tasklist. The target tasklist can be of the same project or different project.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC TaskMove PortalId = '12345317133', ProjectId = '123456000000031899', TaskId = '123456000000034053', FromTasklist = '123456000000031932', ToTasklist = '123456000000031941'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
TaskId String True Specify the task Id.
FromTasklist String True Id of the tasklist in which the task exists.
ToTasklist String True Id of the tasklist to which the task has to be moved.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

TaskReorder

Reorders the tasks in the given project. Task will be reordered in-between two tasks based on the previous and next task Ids.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC TaskReorder PortalId = '12345317133', ProjectId = '123456000000031899', TaskId = '123456000000034053', PreviousTaskId = '123456000000031932', NextTaskId = '123456000000031941'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
TaskId String True Specify the Task Id.
PreviousTaskId String True Specify the previous Task Id.
NextTaskId String True Specify the next Task Id.

Result Set Columns

Name Type Description
Success String Specifies whether the update was successful.

CData Python Connector for Zoho Projects

TaskUnfollow

Unfollow a task in the given project.

Procedure-Specific Information

An example query for executing this stored procedure is shown below:
EXEC TaskUnfollow PortalId = '12345317133', ProjectId = '123456000000031899', TaskId = '123456000000034053', UserId = '123456000000039021'

Input

Name Type Required Description
PortalId String True Specify the portal Id.
ProjectId String True Specify the group Id.
TaskId String True ZPUID of the team lead.
UserId String True User Id for multiple followers must be separated by commas.

Result Set Columns

Name Type Description
Success String Specifies whether the execution was successful.

CData Python Connector for Zoho Projects

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 Zoho Projects:

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

sys_tablecolumns

Describes the columns of the available tables and views.

The following query returns the columns and data types for the Portals table:

SELECT ColumnName, DataTypeName FROM sys_tablecolumns WHERE TableName = 'Portals' 

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 Zoho Projects

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 Zoho Projects

sys_procedureparameters

Describes stored procedure parameters.

The following query returns information about all of the input parameters for the ApproveTimelog stored procedure:

SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'ApproveTimelog' 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 = 'ApproveTimelog' 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 Zoho Projects 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 Zoho Projects

sys_keycolumns

Describes the primary and foreign keys.

The following query retrieves the primary key for the Portals table:

         SELECT * FROM sys_keycolumns WHERE IsKey='True' AND TableName='Portals' 
          

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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
RegionThe Top Level Domain (TLD) in the server URL.

Connection


PropertyDescription
PortalIdRestrict exposed entities based on the Portal Id. If left empty all available portals will be exposed.
ProjectIdRestrict exposed entities based on the Project Id. If left empty, all available portals will be exposed.

OAuth


PropertyDescription
InitiateOAuthSpecifies the process for obtaining or refreshing the OAuth access token, which maintains user access while an authenticated, authorized user is working.
OAuthClientIdSpecifies the client ID (also known as the consumer key) assigned to your custom OAuth application. This ID is required to identify the application to the OAuth authorization server during authentication.
OAuthClientSecretSpecifies the client secret assigned to your custom OAuth application. This confidential value is used to authenticate the application to the OAuth authorization server. (Custom OAuth applications only.).
OAuthAccessTokenSpecifies the OAuth access token used to authenticate requests to the data source. This token is issued by the authorization server after a successful OAuth exchange.
OAuthSettingsLocationSpecifies the location of the settings file where OAuth values are saved.
CallbackURLIdentifies the URL users return to after authenticating to Zoho Projects via OAuth (Custom OAuth applications only).
ScopeSpecifies the scope of the authenticating user's access to the application, to ensure they get appropriate access to data. If a custom OAuth application is needed, this is generally specified at the time the application is created.
OAuthVerifierSpecifies a verifier code returned from the OAuthAuthorizationURL . Used when authenticating to OAuth on a headless server, where a browser can't be launched. Requires both OAuthSettingsLocation and OAuthVerifier to be set.
OAuthRefreshTokenSpecifies the OAuth refresh token used to request a new access token after the original has expired.
OAuthExpiresInSpecifies the duration in seconds, of an OAuth Access Token's lifetime. The token can be reissued to keep access alive as long as the user keeps working.
OAuthTokenTimestampDisplays a Unix epoch timestamp in milliseconds that shows how long ago the current access token was created.

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 Zoho Projects data.
CacheMetadataDetermines whether the provider caches table metadata to a file-based cache database.

Miscellaneous


PropertyDescription
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.
PagesizeSpecifies the maximum number of records per page the provider returns when requesting data from Zoho Projects.
PseudoColumnsSpecifies the pseudocolumns to expose as table columns, expressed as a string in the format 'TableName=ColumnName;TableName=ColumnName'.
ReadonlyToggles read-only access to Zoho Projects 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 Zoho Projects

Authentication

This section provides a complete list of the Authentication properties you can configure in the connection string for this provider.


PropertyDescription
RegionThe Top Level Domain (TLD) in the server URL.
CData Python Connector for Zoho Projects

Region

The Top Level Domain (TLD) in the server URL.

Possible Values

US, Europe, India, Australia, Japan, China

Data Type

string

Default Value

"US"

Remarks

If your account resides in a domain other than the US, then change the Region accordingly. You only need to supply this when using your own OAuth access token with InitiateOAuth=Off. Otherwise, the Region will be retrieved from the OAuth flow. This table lists all possible values:

Region Domain
US .com
Europe .eu
India .in
Australia .com.au
Japan .jp
China .com.cn

CData Python Connector for Zoho Projects

Connection

This section provides a complete list of the Connection properties you can configure in the connection string for this provider.


PropertyDescription
PortalIdRestrict exposed entities based on the Portal Id. If left empty all available portals will be exposed.
ProjectIdRestrict exposed entities based on the Project Id. If left empty, all available portals will be exposed.
CData Python Connector for Zoho Projects

PortalId

Restrict exposed entities based on the Portal Id. If left empty all available portals will be exposed.

Data Type

string

Default Value

""

Remarks

Restrict exposed entities based on the Portal Id. If left empty all available portals will be exposed.

CData Python Connector for Zoho Projects

ProjectId

Restrict exposed entities based on the Project Id. If left empty, all available portals will be exposed.

Data Type

string

Default Value

""

Remarks

Restrict exposed entities based on the Project Id. If left empty, all available portals will be exposed.

CData Python Connector for Zoho Projects

OAuth

This section provides a complete list of the OAuth properties you can configure in the connection string for this provider.


PropertyDescription
InitiateOAuthSpecifies the process for obtaining or refreshing the OAuth access token, which maintains user access while an authenticated, authorized user is working.
OAuthClientIdSpecifies the client ID (also known as the consumer key) assigned to your custom OAuth application. This ID is required to identify the application to the OAuth authorization server during authentication.
OAuthClientSecretSpecifies the client secret assigned to your custom OAuth application. This confidential value is used to authenticate the application to the OAuth authorization server. (Custom OAuth applications only.).
OAuthAccessTokenSpecifies the OAuth access token used to authenticate requests to the data source. This token is issued by the authorization server after a successful OAuth exchange.
OAuthSettingsLocationSpecifies the location of the settings file where OAuth values are saved.
CallbackURLIdentifies the URL users return to after authenticating to Zoho Projects via OAuth (Custom OAuth applications only).
ScopeSpecifies the scope of the authenticating user's access to the application, to ensure they get appropriate access to data. If a custom OAuth application is needed, this is generally specified at the time the application is created.
OAuthVerifierSpecifies a verifier code returned from the OAuthAuthorizationURL . Used when authenticating to OAuth on a headless server, where a browser can't be launched. Requires both OAuthSettingsLocation and OAuthVerifier to be set.
OAuthRefreshTokenSpecifies the OAuth refresh token used to request a new access token after the original has expired.
OAuthExpiresInSpecifies the duration in seconds, of an OAuth Access Token's lifetime. The token can be reissued to keep access alive as long as the user keeps working.
OAuthTokenTimestampDisplays a Unix epoch timestamp in milliseconds that shows how long ago the current access token was created.
CData Python Connector for Zoho Projects

InitiateOAuth

Specifies the process for obtaining or refreshing the OAuth access token, which maintains user access while an authenticated, authorized user is working.

Possible Values

OFF, REFRESH, GETANDREFRESH

Data Type

string

Default Value

"OFF"

Remarks

OAuth is an authorization framework that enables applications to obtain limited access to user accounts on an HTTP service. The OAuth flow defines the method to be used for:

  • Logging in users.
  • Exchanging user credentials for an OAuth access token to be used for authentication.
  • Providing limited access to applications.

The options for initiating and maintaining OAuth access are named for the parts of that flow that the connector handles:

OFF The connector provides no automatic OAuth flow initiation. The OAuth flow is handled entirely by the user.
This means that the user must refresh the token manually, and reconnect with an updated OAuthAccessToken property when the current token expires.
GETANDREFRESH The connector handles the entire OAuth flow (both GET and REFRESH). This means that if a token already exists, the connector refreshes it when necessary; if no token currently exists, the connector obtains it by prompting the user to login.
REFRESH The user obtains the OAuth Access Token and sets up the sequence for refreshing the OAuth Access Token. (The user is never prompted to log in to authenticate.) After the user logs in, the connector handles the refresh of the OAuth Access Token.

For more information on how to set up OAuth and use this property when configuring a connection, see Establishing a Connection.

CData Python Connector for Zoho Projects

OAuthClientId

Specifies the client ID (also known as the consumer key) assigned to your custom OAuth application. This ID is required to identify the application to the OAuth authorization server during authentication.

Data Type

string

Default Value

""

Remarks

This property is required in two cases:

  • When using a custom OAuth application, such as in web-based authentication flows, service-based authentication, or certificate-based flows that require application registration.
  • If the driver does not provide embedded OAuth credentials.

(When the driver provides embedded OAuth credentials, this value may already be provided by the connector and thus not require manual entry.)

OAuthClientId is generally used alongside other OAuth-related properties such as OAuthClientSecret and OAuthSettingsLocation when configuring an authenticated connection.

OAuthClientId is one of the key connection parameters that need to be set before users can authenticate via OAuth. You can usually find this value in your identity provider’s application registration settings. Look for a field labeled Client ID, Application ID, or Consumer Key.

While the client ID is not considered a confidential value like a client secret, it is still part of your application's identity and should be handled carefully. Avoid exposing it in public repositories or shared configuration files.

For more information on how this property is used when configuring a connection, see Establishing a Connection.

CData Python Connector for Zoho Projects

OAuthClientSecret

Specifies the client secret assigned to your custom OAuth application. This confidential value is used to authenticate the application to the OAuth authorization server. (Custom OAuth applications only.).

Data Type

string

Default Value

""

Remarks

This property (sometimes called the application secret or consumer secret) is required when using a custom OAuth application in any flow that requires secure client authentication, such as web-based OAuth, service-based connections, or certificate-based authorization flows. It is not required when using an embedded OAuth application.

The client secret is used during the token exchange step of the OAuth flow, when the driver requests an access token from the authorization server. If this value is missing or incorrect, authentication fails with either an invalid_client or an unauthorized_client error.

OAuthClientSecret is one of the key connection parameters that need to be set before users can authenticate via OAuth. You can obtain this value from your identity provider when registering the OAuth application.

Notes:

  • This value should be stored securely and never exposed in public repositories, scripts, or unsecured environments.
  • Client secrets may also expire after a set period. Be sure to monitor expiration dates and rotate secrets as needed to maintain uninterrupted access.

For more information on how this property is used when configuring a connection, see Establishing a Connection

CData Python Connector for Zoho Projects

OAuthAccessToken

Specifies the OAuth access token used to authenticate requests to the data source. This token is issued by the authorization server after a successful OAuth exchange.

Data Type

string

Default Value

""

Remarks

OAuthAccessToken is a temporary credential that authorizes access to protected resources. It is typically returned by the identity provider after the user or client application completes an OAuth authentication flow. This property is most commonly used in automated workflows or custom OAuth implementations where you want to manage token handling outside of the driver.

The OAuth access token has a server-dependent timeout, limiting user access. The timeout is set using the OAuthExpiresIn property. However, it can be reissued between requests to keep access alive as long as the user keeps working.

If InitiateOAuth is set to REFRESH, we recommend that you also set both OAuthExpiresIn and OAuthTokenTimestamp. The connector uses these properties to determine when the token expires so it can refresh most efficiently. If OAuthExpiresIn and OAuthTokenTimestamp are not specified, the connector refreshes the token immediately.

Note: Access tokens should be treated as sensitive credentials and stored securely. Avoid exposing them in logs, scripts, or configuration files that are not access-controlled.

For more information on how this property is used when configuring a connection, see Establishing a Connection.

CData Python Connector for Zoho Projects

OAuthSettingsLocation

Specifies the location of the settings file where OAuth values are saved.

Data Type

string

Default Value

"%APPDATA%\\CData\\ZohoProjects Data Provider\\OAuthSettings.txt"

Remarks

Storing OAuth settings in a central location avoids the need for users to enter OAuth connection properties manually each time they log in. It also enables credentials to be shared across connections or processes.

You can store OAuth values in a central file for shared access to those values, in either of the following ways:

  • Set InitiateOAuth to either GETANDREFRESH or REFRESH and specify a filepath to the OAuth settings file.
  • Use memory storage to load the credentials into static memory.

The following sections provide more detail on each of these methods.

Specifying the OAuthSettingsLocation Filepath

The default OAuth setting location is %APPDATA%\\CData\\ZohoProjects Data Provider\\OAuthSettings.txt, with %APPDATA% set to the user's configuration directory. Default values vary, depending on the user's operating system.

  • Windows (ODBC and Power BI): registry://%DSN%
  • Windows: %APPDATA%CDataZohoProjects Data Provider\OAuthSettings.txt
  • Mac: %APPDATA%/CData/ZohoProjects Data Provider/OAuthSettings.txt
  • Linux: %APPDATA%/CData/ZohoProjects Data Provider/OAuthSettings.txt

Loading Credentials Via Memory Storage

Memory locations are specified by using a value starting with memory://, followed by a unique identifier for that set of credentials (for example, memory://user1). The identifier can be anything you choose, but it should be unique to the user.

Unlike file-based storage, where credentials persist across connections, memory storage loads the credentials into static memory and the credentials are shared between connections using the same identifier for the life of the process. To persist credentials outside the current process, you must manually store the credentials prior to closing the connection. This enables you to set them in the connection when the process is started again.

To retrieve OAuth property values, query the sys_connection_props system table. If there are multiple connections using the same credentials, the properties are read from the previously closed connection.

Supported Storage Types

  • memory://: Stores OAuth tokens in-memory (unique identifier, shared within same process, etc.)
  • registry://: Only supported in the Windows ODBC and Power BI editions. Stores OAuth tokens in the registry under the DSN settings. Must end in a DSN name like registry://CData Python Connector for Zoho Projects Data Source, or registry://%DSN%.
  • %DSN%: The name of the DSN you are connecting with.
  • Default (no prefix): Stores OAuth tokens within files. The value can be either an absolute path, or a path starting with %APPDATA% or %PROGRAMFILES%.

For more information on how this property is used when configuring a connection, see Establishing a Connection.

CData Python Connector for Zoho Projects

CallbackURL

Identifies the URL users return to after authenticating to Zoho Projects via OAuth (Custom OAuth applications only).

Data Type

string

Default Value

""

Remarks

If you created a custom OAuth application, the OAuth authorization server redirects the user to this URL during the authentication process. This value must match the callback URL you specified when you configured the custom OAuth application.

CData Python Connector for Zoho Projects

Scope

Specifies the scope of the authenticating user's access to the application, to ensure they get appropriate access to data. If a custom OAuth application is needed, this is generally specified at the time the application is created.

Data Type

string

Default Value

""

Remarks

Scopes are set to define what kind of access the authenticating user will have; for example, read, read and write, restricted access to sensitive information. System administrators can use scopes to selectively enable access by functionality or security clearance.

When InitiateOAuth is set to GETANDREFRESH, you must use this property if you want to change which scopes are requested.

When InitiateOAuth is set to either REFRESH or OFF, you can change which scopes are requested using either this property or the Scope input.

CData Python Connector for Zoho Projects

OAuthVerifier

Specifies a verifier code returned from the OAuthAuthorizationURL . Used when authenticating to OAuth on a headless server, where a browser can't be launched. Requires both OAuthSettingsLocation and OAuthVerifier to be set.

Data Type

string

Default Value

""

Remarks

For detailed instructions about how to obtain the OAuthVerifier value, see Establishing a Connection.

CData Python Connector for Zoho Projects

OAuthRefreshToken

Specifies the OAuth refresh token used to request a new access token after the original has expired.

Data Type

string

Default Value

""

Remarks

The refresh token is used to obtain a new access token when the current one expires. It enables seamless authentication for long-running or automated workflows without requiring the user to log in again. This property is especially important in headless, CI/CD, or server-based environments where interactive authentication is not possible.

The refresh token is typically obtained during the initial OAuth exchange by calling the GetOAuthAccessToken stored procedure. After that, it can be set using this property to enable automatic token refresh, or passed to the RefreshOAuthAccessTokenproc; stored procedure if you prefer to manage the refresh manually.

When InitiateOAuth is set to REFRESH, the driver uses this token to retrieve a new access token automatically. After the first refresh, the driver saves updated tokens in the location defined by OAuthSettingsLocation, and uses those values for subsequent connections.

Note: The OAuthRefreshToken should be handled securely and stored in a trusted location. Like access tokens, refresh tokens can expire or be revoked depending on the identity provider’s policies.

For more information on how this property is used when configuring a connection, see Establishing a Connection.

CData Python Connector for Zoho Projects

OAuthExpiresIn

Specifies the duration in seconds, of an OAuth Access Token's lifetime. The token can be reissued to keep access alive as long as the user keeps working.

Data Type

string

Default Value

""

Remarks

The OAuth Access Token is assigned to an authenticated user, granting that user access to the network for a specified period of time. The access token is used in place of the user's login ID and password, which stay on the server.

An access token created by the server is only valid for a limited time. OAuthExpiresIn is the number of seconds the token is valid from when it was created. For example, a token generated at 2024-01-29 20:00:00 UTC that expires at 2024-01-29 21:00:00 UTC (an hour later) would have an OAuthExpiresIn value of 3600, no matter what the current time is.

To determine how long the user has before the Access Token will expire, check OAuthTokenTimestamp.

CData Python Connector for Zoho Projects

OAuthTokenTimestamp

Displays a Unix epoch timestamp in milliseconds that shows how long ago the current access token was created.

Data Type

string

Default Value

""

Remarks

The OAuth access token is assigned to an authenticated user, granting that user access to the network for a specified period of time. The access token is used in place of the user's login ID and password, which stay on the server.

An access token created by the server is only valid for a limited time. OAuthTokenTimestamp is the Unix timestamp when the server created the token. For example, OAuthTokenTimestamp=1706558400 indicates the OAuthAccessToken was generated by the server at 2024-01-29 20:00:00 UTC.

CData Python Connector for Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects. Traffic flows back and forth via the proxy at this location.
SOCKS4 1080 The port where the connector opens a connection to Zoho Projects. 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 Zoho Projects. 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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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\\ZohoProjects 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\\ZohoProjects 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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Zoho Projects data.
CacheMetadataDetermines whether the provider caches table metadata to a file-based cache database.
CData Python Connector for Zoho Projects

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 Zoho Projects.
  • 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 Zoho Projects

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;'InitiateOAuth=GETANDREFRESH;

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";InitiateOAuth=GETANDREFRESH;

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';InitiateOAuth=GETANDREFRESH;

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 Zoho Projects

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:zohoprojects:CacheDriver=org.apache.derby.jdbc.EmbeddedDriver;CacheConnection='jdbc:derby:sample';InitiateOAuth=GETANDREFRESH;
To cache to an in-memory database, use a JDBC URL like the following:
jdbc:zohoprojects:CacheDriver=org.apache.derby.jdbc.EmbeddedDriver;CacheConnection='jdbc:derby:memory';InitiateOAuth=GETANDREFRESH;

SQLite

The following is a JDBC URL for the SQLite JDBC driver:

jdbc:zohoprojects:CacheDriver=org.sqlite.JDBC;CacheConnection='jdbc:sqlite:C:/Temp/sqlite.db';InitiateOAuth=GETANDREFRESH;

MySQL

The following is a JDBC URL for the CData JDBC Driver for MySQL:

  jdbc:zohoprojects:Cache Driver=cdata.jdbc.mysql.MySQLDriver;Cache Connection='jdbc:mysql:Server=localhost;Port=3306;Database=cache;User=root;Password=123456';InitiateOAuth=GETANDREFRESH;
  

SQL Server

The following JDBC URL uses the Microsoft JDBC Driver for SQL Server:

jdbc:zohoprojects:Cache Driver=com.microsoft.sqlserver.jdbc.SQLServerDriver;Cache Connection='jdbc:sqlserver://localhost\sqlexpress:7437;user=sa;password=123456;databaseName=Cache';InitiateOAuth=GETANDREFRESH;

Oracle

The following is a JDBC URL for the Oracle Thin Client:

jdbc:zohoprojects:Cache Driver=oracle.jdbc.OracleDriver;CacheConnection='jdbc:oracle:thin:scott/tiger@localhost:1521:orcldb';InitiateOAuth=GETANDREFRESH;
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:zohoprojects:CacheDriver=cdata.jdbc.postgresql.PostgreSQLDriver;CacheConnection='jdbc:postgresql:User=postgres;Password=admin;Database=postgres;Server=localhost;Port=5432;';InitiateOAuth=GETANDREFRESH;

CData Python Connector for Zoho Projects

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 Zoho Projects

CacheLocation

Specifies the path to the cache when caching to a file.

Data Type

string

Default Value

"%APPDATA%\\CData\\ZohoProjects Data Provider"

Remarks

The CacheLocation is a simple, file-based cache.

If left unspecified, the default location is %APPDATA%\\CData\\ZohoProjects 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 Zoho Projects catalog in CacheLocation.

CData Python Connector for Zoho Projects

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 Zoho Projects

Offline

Gets the data from the specified cache database instead of live Zoho Projects 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 Zoho Projects data.

In this mode, some SQL operations like INSERT, UPDATE, DELETE, and CACHE are disabled.

CData Python Connector for Zoho Projects

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 Zoho Projects 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\\ZohoProjects Data Provider
Mac ~/Library/Application Support/CData/ZohoProjects Data Provider
Unix ~/.config/CData/ZohoProjects 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 Zoho Projects 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 Zoho Projects 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 Zoho Projects.

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 Zoho Projects

Miscellaneous

This section provides a complete list of the Miscellaneous properties you can configure in the connection string for this provider.


PropertyDescription
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.
PagesizeSpecifies the maximum number of records per page the provider returns when requesting data from Zoho Projects.
PseudoColumnsSpecifies the pseudocolumns to expose as table columns, expressed as a string in the format 'TableName=ColumnName;TableName=ColumnName'.
ReadonlyToggles read-only access to Zoho Projects 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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

Pagesize

Specifies the maximum number of records per page the provider returns when requesting data from Zoho Projects.

Data Type

int

Default Value

100

Remarks

When processing a query, instead of requesting all of the queried data at once from Zoho Projects, the connector can request the queried data in pieces called pages.

This connection property determines the maximum number of results that the connector requests per page.

Note: Setting large page sizes may improve overall query execution time, but doing so causes the connector to use more memory when executing queries and risks triggering a timeout.

CData Python Connector for Zoho Projects

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 Zoho Projects

Readonly

Toggles read-only access to Zoho Projects 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 Zoho Projects

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 Zoho Projects

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 Zoho Projects

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 Portals 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 Zoho Projects

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  4. If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License.
You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License.

5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions.

6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file.

7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) 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. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License.

8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages.

9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability.

END OF TERMS AND CONDITIONS

Eclipse Distribution License - v 1.0

All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

  • Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
  • Neither the name of the Eclipse Foundation, Inc. nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) 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 OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Eclipse Public License - v 2.0

THE ACCOMPANYING PROGRAM IS PROVIDED UNDER THE TERMS OF THIS ECLIPSE PUBLIC LICENSE ("AGREEMENT"). ANY USE, REPRODUCTION OR DISTRIBUTION OF THE PROGRAM CONSTITUTES RECIPIENT'S ACCEPTANCE OF THIS AGREEMENT.

1. DEFINITIONS "Contribution" means:

  • a) in the case of the initial Contributor, the initial content Distributed under this Agreement, and
  • b) in the case of each subsequent Contributor:
    • i) changes to the Program, and
    • 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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