CData Python Connector for SAP ERP

Build 26.0.9655

CData Python Connector for SAP ERP

Overview

The CData Python Connector for SAP ERP allows developers to write Python scripts with connectivity to SAP ERP. The connector wraps the complexity of accessing SAP ERP 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 data in SAP ERP.
  • 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 SAP ERP.

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 SAP ERP data to tools such as Pandas or Petl.

SQLAlchemy ORM

SQLAlchemy can be leveraged to model the tables in SAP ERP 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.

Connection String Options

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

CData Python Connector for SAP ERP

Getting Started

Connecting to SAP ERP

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 SAP ERP can be installed and used in Python 3.10 or newer.

SAP ERP Version Support

The connector enables relational access to tables, queries, and function modules in your SAP R/3, NetWeaver, or ERP/ECC 6.0+ system. See Supported Editions and Content for further details about what editions of SAP and content is supported.

See Also

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

CData Python Connector for SAP ERP

Package Installation

Dependencies

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

Installation

The CData Python Connector for SAP ERP 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_saperp_connector-26.0.9655-cp310-abi3-win_amd64.whl

Linux:

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

macOS:

pip install cdata_saperp_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_saperp_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_saperp" 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_saperp folder is trivial to find:

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

CData Python Connector for SAP ERP

Establishing a Connection

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

  1. Import the module as follows:
    import cdata.saperp 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("Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")

Connecting with the RFC APIs

The CData Python Connector for SAP ERP uses the SAP RFC interface to connect to an SAP system. The ConnectionType specifies the RFC API you want to use to connect.

You must obtain the SAP libraries corresponding to your RFC API to connect.

Required RFCs

The RFCs used by the CData Python Connector for SAP ERP are listed as follows. If any listed below are not available, some or all functionality may not work. T-Code SE37 may be used to view available function modules in SAP.

  • DDIF_FIELDINFO_GET
  • RFC_GET_FUNCTION_INTERFACE
  • RFC_GET_STRUCTURE_DEFINITION
  • RFC_GET_SYSTEM_INFO
  • RFC_GET_UNICODE_STRUCTURE
  • RFC_READ_TABLE
  • SLDAG_CHECK_FOR_UNICODE

Connecting to SAP ERP

Set the following to connect:

  • Host: The host name of the target system. Host names can be regular host names defined in a hosts file, an IP address like 123.123.123.123, or an SAProuter address such as "/H/hostname/S/port/H/host/S/port/ ..."
  • User: The user that is authenticating to the SAP system.
  • Password: The password used to authenticate to the SAP system.
  • Client: The client authenticating to the SAP system.
  • SystemNumber: The number by which the target system is defined.
  • Language: The ISO 639-1 language code you use to log into SAP ERP. The default is "EN".

To connect to a machine different from the Host machine, substitute Host with the following:

  • GatewayHost: The gateway host you wish to connect to. If not specified, the provider will attempt to connect to the SAP system specified by Host.
  • GatewayService: The gateway service you wish to connect to. If not specified, the SAP system will use the default "sapgw##" where the "##" is the SystemNumber.

To connect to a distributed system or systems with other configurations, see Fine-Tuning Data Access.

Certificates

In addition to User and Password, the CData Python Connector for SAP ERP also supports certificate authentication. To use certificate authentication, set the X509Certificate connection property to either point to a file that contains an X509 certificate in PEM format, or the PEM blob directly used for authentication during SAP Logon. In addition to setting X509Certificate, you will need to specify the appropriate SNC connection properties. The SNC connection properties are described under Fine-Tuning Data Access.

CData Python Connector for SAP ERP

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 SAP ERP 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:
    [saperp.cpython-311-x86_64-linux-gnu.so]
  • For Mac:
    [saperp.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.saperp 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 SAP ERP

Configuring Dependencies

If you're using the CData Python Connector for SAP ERP on Windows, use the RFC APIs to connect to the SAP system.

For Mac or Linux, follow the JCo JAR file instructions below.

Connect Using the Classic RFC SDK

To use the Classic RFC SDK without Unicode support provided with the library librfc32.dll, set ConnectionType to Classic. Place the assembly in a location where it is accessible at run time, such as system32 or the bin folder in your installation directory or your path.

Connect Using the Classic RFC SDK with Unicode Support

To use the Classic RFC SDK with Unicode support, set ConnectionType to Classic_Unicode.

Place the following assemblies in a location where they are accessible at run time, such as system32 or the bin folder in your installation directory.

  • librfc32u.dll
  • icudt50.dll
  • icuin50.dll
  • icuuc50.dll

Note: Earlier SAP configurations may have used version 34 of the ICU libraries. However, version 50 is required for compatibility with supported SAP RFC SDK versions.

Connect Using the NetWeaver RFC SDK

Prior to connecting, you must have a valid S-User Id and be able to access the SAP software downloading site. You also must be able to download the SAP content from the SAP portal. To download the necessary SDK, follow these steps:

  1. Navigate to https://me.sap.com/softwarecenter.
  2. On the "Downloads" page, search for sap nw rfc.
  3. Click SAP NW FRC SDK 7.50.
  4. Select the platform you use and then download.

To use the NetWeaver RFC SDK, set ConnectionType to NetWeaver.

Place the following assemblies in a location where they are accessible at run time, such as system32 or the bin folder in your installation directory.

For SDK version 7.50, ensure the following DLLs are available:

  • sapnwrfc.dll
  • icudt50.dll
  • icuin50.dll
  • icuuc50.dll
  • libicudecnumber.dll
  • libsapucum.dll

Connect Using SOAP Interface and RFC URL

To connect using the SOAP interface, set the following:

The SOAP service must be enabled in your SAP system for this type of connection to work properly.

Connect Using the JCo JAR File

The CData Python Connector for SAP ERP relies on the SAP RFC to execute queries and retrieve data from SAP. The RFC depends on the JCo (Java Connector) JAR file.

To access the RFC SDK used to communicate with SAP, you can use the SAP JCo (Java Connector). You need to include the sapjco3.jar in your CLASS_PATH specified in the INI file and ensure that the native library location for the JAR is set to the folder containing the sapjco3 library.

You must also ensure that the bitness (32-bit or 64-bit) of the libraries matches the bitness of the Java Virtual Machine (JVM) on which your application is running. A mismatch between these can lead to errors where the JVM cannot load the native library, resulting in a failure to establish a connection to the SAP system. Before downloading, check your system's architecture and download the corresponding version of the library.

  • On Windows, place the sapjco3.dll in the same directory as the sapjco3.jar.
  • On Linux, place the libsapjco3.so file in the same directory as the sapjco3.jar.
  • On Mac OS X, place the libsapjco3.jnilib file in the same directory as the sapjco3.jar.

Follow these steps to download the relevant jar file:

  1. Open the SAP Java Connector.
  2. Select the Jco version that matches your platform.
  3. Click the download link. This opens the login page.
  4. Login to the SAP site with a valid S-User ID.
  5. Download the package.

CData Python Connector for SAP ERP

Supported Editions and Content

Ways to Communicate with SAP

The CData Python Connector for SAP ERP can communicate with SAP R/3 systems using the following methods:

  • Business Application Programming Interface (BAPIs)
  • Remote Function Calls (RFCs)
  • SAP Tables
  • SAP Queries
  • IDoc Messages

Terminology

SAP: The term SAP is an umbrella term for all supported SAP editions. This in general indicates SAP ECC version 6+ and SAP S/4 Hana on-premise, but includes other editions that also support the RFC SDK. For the CData Python Connector for SAP ERP to work, it requires a connection to an edition of SAP that supports the RFC SDK.

Function Module: A function module is a type of program or function in SAP that can be used to execute almost any operation. These modules can be tested and written in SAP via the SE37 TCode.

RFC: A Remote Function Call (RFC) is a type of function module that has been modeled as an API call that can be executed by external applications. This includes using libraries distributed by SAP that are installed on the SAP server, and may also be downloaded from sap.com. Specific RFCs may or may not be maintained across SAP upgrades. There are standard RFCs supplied by SAP, and thus may have differences or may not exist in older editions. Custom RFCs can (and frequently are) built to support integrations, and must be maintained by the SAP customer. By convention, custom RFCs begin with the letter Z.

BAPI: A Business API (BAPI) is a type of RFC distributed and maintained by SAP to give access to business logic operations. BAPIs have methods that are specific to a type of business object. For example, there are about 60 BAPIs related solely to the Customer object. In practice, only a few are typically used.

SAP Table: An SAP table is a table that stores data in SAP. These are not the same as business objects. For instance, there is no Purchase Order table in SAP. Instead, there are many tables that include purchase order data in them, such as EBAN, EBKN, EINA, EKPO, etc. Custom tables by convention begin with the letter Z.

SAP Queries: An SAP Query is a saved object in SAP that details information to retrieve from one or more tables. These are typically used for reporting purposes.

SAP Editions

Our support for RFC connections means any edition of SAP that supports an RFC connection and the specific RFCs we require for the connection will work. Specifically, we support connections to:

  • SAP BW
  • SAP ECC
  • SAP ERP
  • SAP R/3
  • SAP S/4 Hana on-premise

Other editions that support RFC connections may also be supported.

Available Content

The following SAP content is accessible from the CData Python Connector for SAP ERP:

SAP Tables: SAP Tables are exposed as views automatically via the TableMode connection property. If you know exactly which SAP Tables you want to work with, you can specify them via the Views connection property, which overrides TableMode. Because they contain pieces of the business objects, SAP discourages directly modifying the tables themselves. Instead, it recommends using BAPIs to modify any tablular data. For this reason, our tools do not support direct modification of SAP Tables.

BAPIs and RFCs: BAPIs and RFCs are exposed directly as stored procedures. By default, all RFCs starting with the keyword BAPI are displayed as an available stored procedure. This behavior can be modified by changing the StoredProcedureFilter connection property.

SAP Queries: SAP Queries are also exposed as views, but they are turned off by default. They are less commonly required than SAP Tables and BAPIs. If you want to expose SAP Queries, change the QueryMode connection property.

Raw IDoc and IDoc XML: Intermediate Document (IDoc) files are SAP objects that carry business transaction data from one system to another in the form of an electronic message. IDocs transfer data from SAP to non-SAP systems via Electronic Data Interchange (EDI) systems. When the transfer is between two SAP systems, IDocs employ ALE technology.

For further information, see Data Model.

CData Python Connector for SAP ERP

Accessing SAP Entities

The number of entities in an SAP system can make it difficult to work with when all the entities are surfaced at the same time. The following sections provide an overview of how to choose the SAP entities you want to work with.

See Data Model for more information on working with SAP entities.

Filtering SAP Entities

The following connection properties provide basic functionality to select the entities you need:

  • TableMode: Filters tables from the DD02L system table in SAP.
  • QueryMode: Filters queries by your SAP workspace.
  • StoredProcedureFilter: Filters SAP function modules, which are modeled as stored procedures.
Users who need more control over SAP entities can use schema files; saving schemas to a file provides an easy way to include views and stored procedures individually: The Location folder contains the entities you want to surface. Set the GenerateSchemaFiles connection property along with Location to generate schema files at run time.

CData Python Connector for SAP ERP

Using a Custom Read Table Function

RFC_READ_TABLE

The connector uses the SAP RFC_READ_TABLE function to get data from SAP tables. However, it has certain limitations.

As an example, consider the DATA_BUFFER_EXCEEDED exception. The SAP RFC_READ_TABLE has a fixed size of 512 bytes. It can buffer for each row of data, and thus you cannot select more columns than the amount that would fit in this buffer. If you select more than 512 bytes, an exception will occur indicating that you have exceeded the maximum buffer size allowed per row and need to select fewer columns.

RFC_READ_TABLE2

The connector also supports the RFC_READ_TABLE2 table read function. You can switch the active table read function to RFC_READ_TABLE2 by setting ReadTableFunction to "/SAPDS/RFC_READ_TABLE2".

Custom Read Table Functions

Install a Custom Read Table RFC

The connector includes the code for Z_CUSTOM_READ_TABLE, a custom read-table RFC that is similar to the SAP RFC_READ_TABLE, but with a larger buffer to address the DATA_BUFFER_EXCEEDED problem as well as bypass other RFC_READ_TABLE limitations.

Follow the steps below to use the included custom read-table RFC to bypass limitations with the default RFC_READ_TABLE.

  1. Use the RFC_READ_TABLE function as a template for the new function: Select transaction code SE37 and the SDTX Function Group and copy RFC_READ_TABLE to a new function group or your working function group. In this example, RFC_READ_TABLE is copied to "Z_CUSTOM_READ_TABLE".
  2. On the Attributes tab of the SAP screen, select "Remote Enabled Module".
  3. On the Tables tab, set the DATA parameter to "CHAR8000" (you may need to right-click and then click "Display <-> Change")
  4. On the Source Code tab, paste the example source code for the replacement RFC_READ_TABLE function module located in the "db" subfolder of the installation directory. The code is located in Z_CUSTOM_READ_TABLE.txt, though Z_CUSTOM_READ_TABLE_752.txt is preferred if your SAP ERP instance is running ABAP version 7.52 or later (see section below). Click Save.
  5. Define the imports, tables, and exceptions as documented in the provided custom read table.
  6. Activate the function module and in your connection string set ReadTableFunction to Z_CUSTOM_READ_TABLE, or the name of your function module.

The ABAP 7.52 Custom Read Table

Along with Z_CUSTOM_READ_TABLE.txt, there is also a Z_CUSTOM_READ_TABLE_752.txt file, designed for ABAP version 7.52 and above.

It is mostly the same as Z_CUSTOM_READ_TABLE, but it takes advantage of newly available keywords in ABAP 7.52 to perform paging within the database instead of in the ABAP script itself. This makes paging far more efficient and causes a very noticeable performance boost when working with large tables.

It is recommended to use the Z_CUSTOM_READ_TABLE_752 RFC if at all possible.

CData Python Connector for SAP ERP

Fine-Tuning Data Access

Fine Tuning Data Access

  • UseSimpleNames: SAP ERP supports attribute names with special characters that many database-oriented tools do not support. You can use this property to replace any nonalphanumeric character with an underscore.
  • InitialValueMode: Set this to return null or the exact value returned by SAP for fields that have an undefined or unknown value. By default the connector returns null.

Connecting to a Distributed SAP System

If you are connecting to a distributed SAP system, such as a system using load balancing, you must set the following additional properties. An administrator can obtain these connection properties on the Connection tab of the System Entry Properties dialog.

  • SystemId: Set this property to the value in the System Id box.

    The SystemId property is the System Id or R3Name of the SAP system. The system Id is a string with a maximum of three characters.

  • MessageServer: Set this property to the value in the Message Server box. If a value is specified in the SAProuter box, prepend the value in the SAProuter box onto the value for the MessageServer connection string property.

    The MessageServer property must be specified when connecting to an SAP system using load balancing.

  • Group: If a value is specified, set this property to the value in the Group/Server box.

    The Group property specifies the logon group being used. The default in most SAP systems will be PUBLIC.

If you are using a message server service other than HTTP, set MessageServerService.

Connecting to a Custom Application Server

If you are connecting to an SAP system with a dedicated application server or a custom application server, you can obtain the following connection properties on the Connection tab of the System Entry Properties dialog.

  • SystemId: Set this property to the value in the System Id box.

    The SystemId property is the System Id or R3Name of the SAP system. The system Id is a string with a maximum of three characters.

  • Host: Set this property to the value in the Application Server box.

    The Host property specifies the host name of the target system. This value can be a regular host name, IP address, or SAProuter address.

  • SystemNumber: Set this property to the value in the SystemNumber box.

    The SystemNumber property defines the target system.

Configuring Secure Network Connections

If the administrator has configured Secure Network Communication (SNC), you need to set the following additional properties. You can obtain the following SNC connection string properties on the Network tab of the System Entry Properties dialog.

  • SNCMode: If the "Activate Secure Network Connections" checkbox is enabled, set the SNCMode connection string property to True. If this checkbox is disabled, set the SNCMode connection property to False.

    The SNCMode connection property is a boolean value determining if you are using SNC. The default value is False.

  • SNCPartnerName: Set this property to the value in the SNC Name box.

    The SNCPartnerName property specifies the application server's SNC name. For example: p:CN=IDS, OU=IT, O=CSW, C=DE

  • SNCName: Optional. Set this property to the value in the SNC Name box.

    The SNCName property specifies the name of the SNC connection. Set this property to make sure that the correct SNC name is used for the connection.

  • SNCQop: Set this property to the selected option in the Secure Network Settings section. For example, if the Integrity option is selected, set the SNCQop property to 3.

    The SNCQop property specifies the level (or quality) of data protection. If this property is not specified, the integer -1 is set for this property. Valid values are 1, 2, 3, 8, or 9, which correspond to the following protection levels:

    1 Apply authentication only. The identities of communication partners are verified.
    2 Apply integrity protection. The SAP system detects any changes or manipulation of the data exchanged.
    3 Apply privacy protection. This level provides integrity and authentication. The SAP system encrypts the messages being transferred. No one but the two communication partners can read or tamper with the data. This is the maximum level of protection.
    8 Apply the default protection.
    9 Apply the maximum protection.

  • SNCLibPath: Set this property to the path and filename of your SNC library.

    The SNCLibPath property specifies the full path to the security library you are using. For example, C:\Secude\secude.xll.

CData Python Connector for SAP ERP

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).
2026-04-2126.0.9607SAP ERPData ModelChanged
  • Changed how SAP Export parameters are exposed in stored procedure metadata. Export parameters are no longer listed as OUT parameters. For table and structure type Export parameters, nested columns are now returned as result columns. For simple Export parameters, the parameter value is returned as a result column.
2026-04-1526.0.9601GeneralQuery ExecChanged
  • String comparisons using GREATER, LESS, and CONTAINS operators are now case-insensitive by default.
2026-04-1326.0.9599SAP ERPData ModelChanged
  • Fixed an issue where the driver returned an error when encountering a (`/`) prefix in exchange rate columns. This slash has been replaced by a minus sign (-) in query results, which represents an indirect (reciprocal) exchange rate rather than a negative value.
2026-04-1026.0.9596SAP ERPConnectionAdded
  • Added the JCOSerializationFormat connection property for connection type JCO. This property resolves I/O errors caused by invalid data.
2026-04-0126.0.9587SAP ERPConnectionRemoved
  • Removed the BatchSize connection property.
2026-03-3126.0.9586SAP ERPData ModelRemoved
  • The IsCreatable column has been removed from sys_tables.
2026-02-1225.0.9539SAP ERPChanged
  • In stored procedure result sets, date fields without a set value now return NULL instead of the default 0000-01-01.
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.
2025-12-1125.0.9476SAP ERPAdded
  • Added the following new filter options to the TableMode connection property: AppendTable, Custom, InternalTable, and View.
  • Added a new connection property named CustomTableFilter.
2025-12-0525.0.9470GeneralAdded
  • Added support for the INSERT INTO SELECT statement, with driver-side execution for providers that do not support the operation natively.
2025-11-2025.0.9455SAP ERPAdded
  • A new column named SAPTableClass has been added to sys_tables.
2025-10-3125.0.9435SAP ERPChanged
  • Implemented fallback handling for the PaginationScheme connection property. When using the Key pagination scheme, if a table does not support the ORDER BY clause or lacks a primary key, the driver now falls back to the Default pagination scheme and logs an informational message instead of throwing an exception.
2025-10-3025.0.9434PythonChanged
  • Updated embedded JRE to jre-17.0.17+10 (Linux x64 / MacOs x64).
2025-10-2325.0.9427SAP ERPChanged
  • Pagination has been implemented on the Z_CUSTOM_READ_TABLE, Z_CUSTOM_READ_TABLE_750, and Z_CUSTOM_READ_TABLE_752 Remote Function Calls (RFCs).
  • A new FetchSize import parameter has been added to the Z_CUSTOM_READ_TABLE, Z_CUSTOM_READ_TABLE_750 and Z_CUSTOM_READ_TABLE_752 RFCs.
  • The Z_CUSTOM_READ_TABLE_750 and Z_CUSTOM_READ_TABLE_752 RFCs now optimize query logic and support fetching only the columns specified.
2025-10-1725.0.9421SAP ERPAdded
  • Pagination functionality for sys_tables has been implemented. The PaginationScheme property is functional for sys_tables as well.
2025-10-0625.0.9410GeneralAdded
  • Support for parsing datetime formats using ".S" and ",S" for milliseconds and nanoseconds.
2025-09-1625.0.9390SAP ERPAdded
  • Added the Z_CUSTOM_READ_TABLE_750 script. Z_CUSTOM_READ_TABLE_750 is recommended for use with SAP ABAP 750 and 751.
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.
2025-08-0725.0.9350SAP ERPAdded
  • Added the PaginationScheme connection property.
2025-07-1425.0.9326SAP ERPChanged
  • Exposed the option "cloud" for the SAPEdition connection property in CData Sync.
2025-07-1025.0.9322SAP ERPAdded
  • Added support for USE_ET_DATA_4_RETURN and ET_DATA parameters in the Z_CUSTOM_READ_TABLE and Z_CUSTOM_READ_TABLE_752 scripts.
    • The DATA table parameter is limited to a maximum length of 8000, while the ET_DATA exporting parameter has no length restriction.
    • The USE_ET_DATA_4_RETURN importing parameter specifies whether the ET_DATA exporting parameter is used to store the table data. The default value is true.
2025-07-0725.0.9319PythonRemoved
  • Removed the 32-bit version of Windows Python.
2025-07-0225.0.9314PythonRemoved
  • Removed support for Python 3.9.
2025-06-2525.0.9307GeneralRemoved
  • Removed the "ADLS Gen 1" value from the ConnectionType property.
2025-06-2525.0.9307PythonAdded
  • Added support for Python 3.13 in Windows, Linux, and Mac editions.
2025-06-2525.0.9307PythonRemoved
  • Removed support for Python 3.8 as it is no longer supported.
2025-06-2025.0.9302GeneralAdded
  • Created the following functions:
    • TEXT_ENCODE: encodes a string into a different charset (UTF8 → UTF7 and returns a binary array as the result).
    • TEXT_DECODE: takes a binary array and decodes it back into a string when provided the charset.
    • BASE64_ENCODE: takes a binary array and encodes it as a base64 string (varchar).
    • BASE64_DECODE: takes a base 64-encoded string and decodes it into a binary array.
2025-06-1825.0.9300GeneralChanged
  • The internal code for exception handling has been refactored. Exception messages returned during certain error conditions may now have different wording or formatting.
2025-05-2725.0.9278GeneralRemoved
  • Removed the "Proprietary" enum option from ProxyAuthscheme.
2025-05-1925.0.9270SAP ERPAdded
  • Added two columns to sys_tablecolumns: SAPDataType and SAPColLength.
2025-05-1525.0.9266SAP ERPAdded
  • Added support for SAP server-side UPPER() and LOWER() functions in filters when using RFC_READ_TABLE (with ET_DATA) or Z_CUSTOMER_READ_TABLE (version 752).
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).
2025-04-0125.0.9222SAP ERPAdded
  • Added the column "SAPTableType" to the sytem table SYS_TABLES. This column shows the SAP native table type of the table, such as SAPTable and SAPQuery.
2025-02-1524.0.9177GeneralAdded
  • Added support for converting unsigned integer types to the nearest signed data type that has enough precision to hold the unsigned value.This is done for JDBC only because it does not have support for unsigned data types.
2024-12-1824.0.9118SAP ERPAdded
  • Added the MapRAWToVarchar connection property. When set to True, this property maps the SAP RAW and LRAW types to Varchar type.
2024-12-1724.0.9117SAP ERPAdded
  • Added the MapNUMCToVarchar connection property. This property allows the client to map SAP NUMC and ACCP fields as numeric types.
2024-11-2724.0.9097GeneralAdded
  • Added ThreadId to LogModule output. Logfile lines now include the Thread ID associated with the action being performed.
2024-08-2824.0.9006SAP ERPAdded
  • Added support for connecting to SAP S/4 HANA Cloud.
  • Added the SAPEdition connection property, which specifies whether the driver connects to SAP S/4 HANA Cloud or SAP S/4 HANA OnPremise.
  • Added the CloudServerPort connection property, which specifies the port the driver uses when connecting to an SAP S/4 HANA Cloud server.
2024-08-1324.0.8991SAP ERPAdded
  • Added the SupportServerSideCount connection property.
2024-07-0724.0.8954SAP ERPAdded
  • Added a new property, BAPINameSeparator, which specifies a separator to be used to concatenate table and column names in the stored procedure's output parameter.
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.
2024-05-0924.0.8895SAP ERPAdded
  • Added a new property "ReadTableDelimiter". It allows the client to specify the import parameter "Delimiter" when calling the RFC_READ_TABLE function to retrieve the table data.
2024-03-1923.0.8844SAP ERPAdded
  • Added a new property "WitespaceToNull". It allows to indicate whether to read the empty value as the original value or as NULL.
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
2023-12-1123.0.8745SAP ERPAdded
  • Added a new property "SNCSSO". When connecting via SNC mode, it permits users to determine whether to utilize SNC credentials for authenticating the caller.
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
2023-11-0623.0.8710SAP ERPAdded
  • Added an extra column "SAPParameterStructInfo" in the CData system table SYS_PROCEDUREPARAMETERS. The column stores the JSON format structure info of the SAPTable or SAPStructure type.
2023-08-2923.0.8641PythonAdded
  • Added support for SQLAlchemy 2.0.
2023-08-1523.0.8627SAP ERPChanged
  • Added an parameter "RESULT_TABLE" for stored Procedure. It specifies the current data rows belong to which output table in the resultset.
2023-07-0523.0.8586SAP ERPChanged
  • Updated the Z_CUSTOMER_READ_TABLE. It uses the ORDER BY PRIMARY KEY to sort the result set.
2023-06-2023.0.8571GeneralAdded
  • Added the new sys_lastresultinfo system table.
2023-06-1523.0.8566SAP ERPAdded
  • Added a new property "CheckDecimalNotation". It enables clients to decide whether to use the Decimal Notation of the SAP user profile for formatting decimal data.
2023-06-0523.0.8556SAP ERPChanged
  • The connection property "TrimStrings" is exposed, which governs the string trimming behavior. Its enumerations encompass four possible values: "TrimRight" / "TrimLeft" / "TrimAll" / "None", with "TrimAll" being the default setting.
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.
2023-03-0922.0.8468SAP ERPAdded
  • Added support to use the SAP Data Services function "/SAPDS/RFC_READ_TABLE2" as the read table function of the SAP ERP Server.
2023-02-1722.0.8448SAP ERPChanged
  • Added support for returning UUID raw data types as varbinary. Previously, these types were returned as varchar.
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.
2022-05-1822.0.8173PythonAdded
  • 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.
2021-04-2321.0.7783GeneralChanged
  • Updated how display sizes are determined for varchar primary key and foreign key columns so they will match the reported length of the column.
2021-04-1621.0.7776GeneralChanged
  • 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 SAP ERP

Using the Connector

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

For information on how to connect with the saperp.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.

Executing Stored Procedures

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

CData Python Connector for SAP ERP

Connecting

Connecting with the cdata.saperp 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.saperp as mod
conn = mod.connect("Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")

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

CData Python Connector for SAP ERP

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 MANDT, MATNR FROM MARA")
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 MANDT, MATNR FROM MARA WHERE ERNAM = ?"
params = ["BEHRMANN"]
cur = conn.execute(cmd, params)
rs = cur.fetchall()
for row in rs:
	print(row)

CData Python Connector for SAP ERP

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 CreateTableSchema Table = ?"
params = ["CSKS"]
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 = ["CSKS"]
cur.callproc("CreateTableSchema", params)

CData Python Connector for SAP ERP

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 SAP ERP Integration Quickstarts

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

CData Python Connector for SAP ERP

From SQLAlchemy

The CData Python Connector for SAP ERP 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 SAP ERP 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.

CData Python Connector for SAP ERP

Connecting

Connecting With a Dialect URL

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

Format 1


from sqlalchemy import create_engine
engine = create_engine("saperp:///?Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")

Format 2


from sqlalchemy import create_engine
engine = create_engine("saperp://EXT90033:xxx@/?Host=sap.mydomain.com;Client=800;SystemNumber=09;ConnectionType=Classic;")

For SQLAlchemy 2.0, the dialect name is saperp_2. To establish a connection, use the following URL format:

from sqlalchemy import create_engine
engine = create_engine("saperp_2:///?Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")

CData Python Connector for SAP ERP

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 MARA(Base):
	__tablename__ = "MARA"
	Id = Column(String, primary_key=True)
	MANDT = Column(String)
	MATNR = 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)
MARA = abase.classes.MARA

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)
MARA_table = Table("MARA", meta)
insp.reflect_table(MARA_table, ["Id","MATNR"])

CData Python Connector for SAP ERP

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("saperp:///?Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(MARA).filter_by(ERNAM="BEHRMANN"):
	print("Id: ", instance.Id)
	print("MANDT: ", instance.MANDT)
	print("MATNR: ", instance.MATNR)
	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:
MARA_table = MARA.metadata.tables["MARA"]
for instance in session.execute(MARA_table.select().where(MARA_table.c.ERNAM == "BEHRMANN")):
	print("Id: ", instance.Id)
	print("FullName: ", instance.Name)
	print("City: ", instance.BillingCity)
	print("---------")

CData Python Connector for SAP ERP

Executing JOINs

Implicit Joining

If mapped classes of related SAP ERP 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 SAP ERP

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(MARA).order_by(MARA.AnnualRevenue)
for instance in rs:
	print("Id: ", instance.Id)
	print("MANDT: ", instance.MANDT)
	print("MATNR: ", instance.MATNR)
	print("---------")

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

rs = session.execute(MARA_table.select().order_by(MARA_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(MARA.Id).label("CustomCount"), MARA.MANDT).group_by(MARA.MANDT)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("MANDT: ", instance.MANDT)
	print("---------")

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

rs = session.execute(MARA_table.select().with_only_columns([func.count(MARA_table.c.Id).label("CustomCount"), MARA_table.c.MANDT]).group_by(MARA_table.c.MANDT))
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(MARA).limit(25).offset(100)
for instance in rs:
	print("Id: ", instance.Id)
	print("MANDT: ", instance.MANDT)
	print("MATNR: ", instance.MATNR)
	print("---------")

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

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

CData Python Connector for SAP ERP

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(MARA.Id).label("CustomCount"), MARA.MANDT).group_by(MARA.MANDT)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("MANDT: ", instance.MANDT)
	print("---------")

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

rs = session.execute(MARA_table.select().with_only_columns([func.count(MARA_table.c.Id).label("CustomCount"), MARA_table.c.MANDT])group_by(MARA_table.c.MANDT))
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(MARA.AnnualRevenue).label("CustomSum"), MARA.MANDT).group_by(MARA.MANDT)
for instance in rs:
	print("Sum: ", instance.CustomSum)
	print("MANDT: ", instance.MANDT)
	print("---------")

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

rs = session.execute(MARA_table.select().with_only_columns([func.sum(MARA_table.c.AnnualRevenue).label("CustomSum"), MARA_table.c.MANDT]).group_by(MARA_table.c.MANDT))
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(MARA.AnnualRevenue).label("CustomAvg"), MARA.MANDT).group_by(MARA.MANDT)
for instance in rs:
	print("Avg: ", instance.CustomAvg)
	print("MANDT: ", instance.MANDT)
	print("---------")

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

rs = session.execute(MARA_table.select().with_only_columns([func.avg(MARA_table.c.AnnualRevenue).label("CustomAvg"), MARA_table.c.MANDT]).group_by(MARA_table.c.MANDT))
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(MARA.AnnualRevenue).label("CustomMax"), func.min(MARA.AnnualRevenue).label("CustomMin"), MARA.MANDT).group_by(MARA.MANDT)
for instance in rs:
	print("Max: ", instance.CustomMax)
	print("Min: ", instance.CustomMin)
	print("MANDT: ", instance.MANDT)
	print("---------")

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

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

CData Python Connector for SAP ERP

From Pandas

When combined with the connector, Pandas can be used to generate data frames that contain your SAP ERP 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("saperp:///?Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")

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
	   MANDT,
	   MATNR,
     $exNumericCol;
	FROM MARA;""", engine)
print(df)

CData Python Connector for SAP ERP

From Matplotlib

Matplotlib contains a number of tools that can graphically model SAP ERP 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 SAP ERP data. For example, the following plot generates and displays a bar graph relating MANDT and AnnualRevenue values:

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

CData Python Connector for SAP ERP

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 SAP ERP, you can use the connector's connect function to create a connection using a valid SAP ERP connection string. If you prefer not to use a direct connection, you can use a SQLAlchemy engine.
import petl as etl
import cdata.saperp as mod
cnxn = mod.connect("Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")

Extract, Transform, and Load the SAP ERP Data

Create a SQL query string and store the query results in a DataFrame.
sql = "SELECT	MANDT, MATNR FROM MARA "
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')

CData Python Connector for SAP ERP

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 SAP ERP

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.saperp as mod
conn = mod.connect("Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_tables"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

Views


import cdata.saperp as mod
conn = mod.connect("Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")
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 SAP ERP

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.saperp as mod
conn = mod.connect("Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_tablecolumns WHERE TableName = 'MARA'"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

CData Python Connector for SAP ERP

Procedures

Procedures

A system table called "sys_procedures" is queried to obtain the available stored procedures that are executed:
import cdata.saperp as mod
conn = mod.connect("Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")
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.saperp as mod
conn = mod.connect("Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'CreateTableSchema'"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

CData Python Connector for SAP ERP

Advanced Features

This section details a selection of advanced features of the SAP ERP connector.

User Defined Views

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

SSL Configuration

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

Firewall and Proxy

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

Caching Data

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

Query Processing

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

For further information, see Query Processing.

Logging

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

Exception Handling

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

CData Python Connector for SAP ERP

User Defined Views

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

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

There are two ways to create user defined views:

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

Defining Views Using a Configuration File

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

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

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

For example:

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

Defining Views Using DDL Statements

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

Create a View

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

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

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

Alter a View

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

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

The view is then updated in the JSON configuration file.

Drop a View

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

DROP LOCAL VIEW [MyViewName]

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

Schema for User Defined Views

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

Working with User Defined Views

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

CData Python Connector for SAP ERP

SSL Configuration

Customizing the SSL Configuration

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

To specify another certificate, see the SSLServerCert connection property.

CData Python Connector for SAP ERP

Firewall and Proxy

Connecting Through a Firewall or Proxy

HTTP Proxies

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

To authenticate to an HTTP proxy, set the following:

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

Other Proxies

Set the following properties:

CData Python Connector for SAP ERP

Caching Data

Caching Data

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

Contents

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

Configuring the Cache Connection

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

Caching Metadata

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

Automatically Caching Data

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

Explicitly Caching Data

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

Data Type Mapping

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

CData Python Connector for SAP ERP

Configuring the Cache Connection

Configuring the Caching Database

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

CacheLocation

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

CacheConnection

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

CacheDriver and CacheProvider

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

CData Python Connector for SAP ERP

Automatically Caching Data

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

If replication is enabled, the data is generated once and then copied to local and cloud data stores. With incremental updates, the connector achieves a performance advantage over dropping the cached tables and retrieving the entire table again on every refresh. With iterative updates, the connector only performs the query from the last time that the date was refreshed. If replication is not enabled, updates to the cache require downloading the entire data set.

Configuring Automatic Caching

To automatically update the cache and return results from the local cache, set the following connection string properties:

  • AutoCache: This property automatically updates the cache when the value is set to true.
  • CacheTolerance: This property ensures that the data retrieved from the database is the most current version. The default value is 600 seconds (10 minutes). The connector checks with the data source for newer records after the tolerance interval has expired. Otherwise, it returns the data directly from the cache.

Caching the MARA Table

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

SELECT MANDT, MATNR FROM MARA WHERE ERNAM = 'BEHRMANN'

Common Use Case

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

CData Python Connector for SAP ERP

Explicitly Caching Data

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

Creating the Cache

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

CACHE SELECT * FROM tableName WHERE ...

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

Updating the Cache

This section describes two ways to update the cache.

Updating with the SELECT Statement

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

CACHE SELECT * FROM MARA WHERE ERNAM = 'BEHRMANN'

Updating with the TRUNCATE Statement

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

  CACHE WITH TRUNCATE SELECT * FROM MARA WHERE ERNAM = 'BEHRMANN'
  

Query the Data in Online or Offline Mode

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

Online: Select Cached Tables

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

SELECT * FROM MARA#CACHE

Offline: Select Cached Tables

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

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

SELECT * FROM MARA WHERE ERNAM='BEHRMANN' ORDER BY MATNR ASC

Delete Data from the Cache

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

Common Use Case

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

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

CData Python Connector for SAP ERP

Data Type Mapping

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

Data Type Mapping

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

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

CData Python Connector for SAP ERP

Query Processing

Query Processing

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

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

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

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

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

More Information

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

CData Python Connector for SAP ERP

Logging

Logging

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

Basic Logging

To begin capturing connector logging, set these properties:

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

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

Log Verbosity

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

The following list describes each level:

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

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

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

Sensitive Data

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

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

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

Advanced Logging

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

Example property value:

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

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

The available modules and submodules are:

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

CData Python Connector for SAP ERP

Exception Handling

Exception Handling

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

Error Codes

The error code classifies the type of error.

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

SQL State

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

Some of the common SQL states are listed below:

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

Error Message

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

CData Python Connector for SAP ERP

SQL Compliance

SELECT Statements

See SELECT 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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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> 
    ]
  ] 
}

<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 MARA
  2. Rename a column:
    SELECT [MATNR] AS MY_MATNR FROM MARA
  3. Cast a column's data as a different data type:
    SELECT CAST(AnnualRevenue AS VARCHAR) AS Str_AnnualRevenue FROM MARA
  4. Search data:
    SELECT * FROM MARA WHERE ERNAM = 'BEHRMANN'
  5. Return the number of items matching the query criteria:
    SELECT COUNT(*) AS MyCount FROM MARA 
  6. Return the number of unique items matching the query criteria:
    SELECT COUNT(DISTINCT MATNR) FROM MARA 
  7. Return the unique items matching the query criteria:
    SELECT DISTINCT MATNR FROM MARA 
  8. Sort a result set in ascending order:
    SELECT MANDT, MATNR FROM MARA  ORDER BY MATNR ASC
  9. Restrict a result set to the specified number of rows:
    SELECT MANDT, MATNR FROM MARA 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 MARA WHERE ERNAM = @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 SAP ERP.

    SELECT * FROM MARA WHERE Pseudo = '@Pseudo'
    

Aggregate Functions

For SELECT examples using aggregate functions, see Aggregate Functions.

JOIN Queries

See JOIN Queries for SELECT query examples using JOINs.

Date Literal Functions

Date Literal Functions contains SELECT examples with date literal functions.

Window Functions

See Window Functions for SELECT examples containing window functions.

Table-Valued Functions

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

CData Python Connector for SAP ERP

Aggregate Functions

COUNT

Returns the number of rows matching the query criteria.

SELECT COUNT(*) FROM MARA WHERE ERNAM = 'BEHRMANN'

COUNT(DISTINCT)

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

SELECT COUNT(DISTINCT MANDT) AS DistinctValues FROM MARA WHERE ERNAM = 'BEHRMANN'

AVG

Returns the average of the column values.

SELECT MATNR, AVG(AnnualRevenue) FROM MARA WHERE ERNAM = 'BEHRMANN'  GROUP BY MATNR

MIN

Returns the minimum column value.

SELECT MIN(AnnualRevenue), MATNR FROM MARA WHERE ERNAM = 'BEHRMANN' GROUP BY MATNR

MAX

Returns the maximum column value.

SELECT MATNR, MAX(AnnualRevenue) FROM MARA WHERE ERNAM = 'BEHRMANN' GROUP BY MATNR

SUM

Returns the total sum of the column values.

SELECT SUM(AnnualRevenue) FROM MARA WHERE ERNAM = 'BEHRMANN'

CData Python Connector for SAP ERP

JOIN Queries

The CData Python Connector for SAP ERP 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 MARA.MTART, MARC.WERKS FROM MARA, MARC WHERE MARA.MATNR = MARC.MATNR

Left Join

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

SELECT MARA.MTART, MARC.WERKS FROM MARA LEFT JOIN MARC ON MARA.MATNR = MARC.MATNR

CData Python Connector for SAP ERP

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 MARA

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 MANDT, MATNR, RANK() OVER (ORDER BY MATNR) AS Rank FROM MARA

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

SELECT MANDT, MATNR, RANK() OVER (PARTITION BY MANDT ORDER BY MATNR) AS Rank FROM MARA

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 MANDT, MATNR, DENSE_RANK() OVER (PARTITION BY MANDT ORDER BY MATNR) AS Rank FROM MARA

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

SELECT MANDT, MATNR, DENSE_RANK() OVER (PARTITION BY MANDT ORDER BY MATNR) AS Rank FROM MARA

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 SAP ERP

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 SAP ERP

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 MARA

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

CACHE CachedMARA SELECT * FROM MARA

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 CachedMARA SELECT * FROM MARA 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 MANDT and MATNR even though the cache table CachedMARA has all the columns in MARA.

CACHE CachedMARA SCHEMA ONLY SELECT * FROM MARA
CACHE CachedMARA SELECT MANDT, MATNR FROM MARA

CData Python Connector for SAP ERP

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 SAP ERP

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 SAP ERP

Data Model

The CData Python Connector for SAP ERP dynamically retrieves schemas for SAP tables, queries, and function modules at run time. However, since it can be inefficient to retrieve the metadata for the entire SAP system, the connector also applies default filters to represent only a slice of your SAP system.

Below is an explanation of how the connector models each type of SAP object. How the connector determines what to display is highly customizable; see Accessing SAP Entities for more information on selecting the SAP objects you want.

SAP Tables

SAP tables are listed as views. This is because SAP strongly discourages directly making changes to SAP tables. Instead, function modules such as BAPIs should be used for making changes to table data. See Function Modules below for more on that.

Table data is retrieved from SAP using either the RFC_READ_TABLE or Z_CUSTOM_READ_TABLE function module if you have it installed. These give access to basic SQL support, but more complex queries such as joins and group by must be handled locally. More complex queries are handled automatically by the connector.

See Using a Custom Read Table Function for more information on circumventing limitations with RFC_READ_TABLE.

SAP Queries

Just like tables, you can also work with SAP queries as relational views. By default they are turned off to try and avoid cluttering the connector with too many options. They can be turned on by using the QueryMode connection property.

Unlike tables, SAP queries might require certain values to be specified as inputs. You can specify these query inputs as part of the predicate in the SQL. For instance:

SELECT * FROM Z_SAP_QUERY WHERE InputName='x'
All SAP query views include a Variant column that you can also input as part of the projection.

Be aware that values that are only inputs in an SAP query are reflected back in the results as the same value that was specified. This does not actually indicate that SAP returned the value that way. It is just something that is required to keep the SQL statement valid.

Function Modules

Function modules in SAP can be used for almost any task. These include the very RFC calls that the connector makes such as RFC_READ_TABLE and function modules that modify data such as BAPI_PO_CREATE.

You can execute a function module directly as a stored procedure. SAP function modules accept and return primitive values and complex structures; the corresponding stored procedures accept and return SQL types and tables. For instance:

EXEC STFC_CONNECTION

For a more complex example, try RFC_READ_TABLE:

  EXEC RFC_READ_TABLE @QUERY_TABLE='MARA', @FIELDS='FIELDS#TEMP', @ROWCOUNT=1

In the above example, the RFC_READ_TABLE function module is executed to return the MARA table. The QUERY_TABLE and ROWCOUNT parameters are passed in as primitive values. In this function module, FIELDS is an input table. To provide this input, you can populate a temporary table with the #TEMP syntax and INSERT statements. For example:

  INSERT INTO FIELDS#TEMP (FIELDNAME) VALUES ('MANDT');
  INSERT INTO FIELDS#TEMP (FIELDNAME) VALUES ('MATNR');
  INSERT INTO FIELDS#TEMP (FIELDNAME) VALUES ('ERSDA');
  INSERT INTO FIELDS#TEMP (FIELDNAME) VALUES ('ERNAM');

Alternatively, JSON or XML can be used to submit tabular data for environments where the #TEMP tables would be difficult to use. For example:

  EXEC RFC_READ_TABLE OPTIONS='{ \"TEXT\": \"TABNAME LIKE ''MARA%''\" }', QUERY_TABLE='DD02L', ROWCOUNT='1', ReturnTables='DATA'

Customizing Stored Procedure Schemas

Instead of using the dynamic, in-memory schemas, you can use GenerateSchemaFiles to save static schema files that are easy to customize. A common use case is to remove extra unwanted inputs and outputs that the connector may report for a stored procedure.

In SAP, there is nothing in the metadata that distinguishes tables in function modules as either inputs or outputs. Since there is no way to know which tables are actually used for inputs and which are used for outputs, the connector reports the tables as being available for both inputs and outputs.

To generate the schema file, set GenerateSchemaFiles to "OnUse" and call the stored procedure. Also, set the Location property to the folder where you want the schema to be output.

To modify the schema file, open the generated schema file in the Location folder with any text editor. Then find the <input> or <output> tags that are not needed and remove them. Refresh the connection in the connector to pick up the schema and your changes.

CData Python Connector for SAP ERP

Views

Views are similar to tables in the way that data is represented; however, views are read-only.

Queries can be executed against a view as if it were a normal table.

CData Python Connector for SAP ERP Views

Name Description
SearchFunctions View listing all SAP remote-enabled function modules available in the connected SAP system, useful for discovery and integration.

CData Python Connector for SAP ERP

SearchFunctions

View listing all SAP remote-enabled function modules available in the connected SAP system, useful for discovery and integration.

Columns

Name Type Description
Name String Name of the SAP remote-enabled function module returned by the search.
Group String Function group that the SAP function belongs to, typically representing a logical module or area.

CData Python Connector for SAP ERP

Stored Procedures

Stored procedures are function-like interfaces that extend the functionality of the connector beyond simple SELECT operations with SAP ERP.

Stored procedures accept a list of parameters, perform their intended function, and then return any relevant response data from SAP ERP, along with an indication of whether the procedure succeeded or failed.

CData Python Connector for SAP ERP Stored Procedures

Name Description
ClearCache Clears the JCoRepository cache to refresh metadata definitions for SAP functions and tables, ensuring the latest versions are used.
CreateFunctionSchema Generates an .rsd schema file based on the metadata of a specified SAP function module, enabling integration tools to map its structure.
CreateQuerySchema Builds a schema file for a specified SAP query, allowing external tools to understand the input and output fields for data extraction.
CreateSchema Creates a schema file for a specified SAP table or view, facilitating structured access to SAP data from external applications.
CreateTableSchema Generates a schema file for a specific SAP table using RFC_READ_TABLE, enabling data retrieval from the SAP backend through remote function calls.
ListQueries Retrieves metadata about available SAP queries and their fields, helping users select the correct query structure for data extraction.
PushIDoc Sends IDoc or IDoc XML data to an SAP system using synchronous or asynchronous modes. Useful for B2B messaging, system integration, or transactional updates.

CData Python Connector for SAP ERP

ClearCache

Clears the JCoRepository cache to refresh metadata definitions for SAP functions and tables, ensuring the latest versions are used.

Stored Procedure-Specific Information

This stored procedure has no input parameters.

To execute this procedure, enter:

    EXEC ClearCache

CData Python Connector for SAP ERP

CreateFunctionSchema

Generates an .rsd schema file based on the metadata of a specified SAP function module, enabling integration tools to map its structure.

Input

Name Type Description
Function String Name of the SAP function module for which the schema will be generated.
FunctionDescription String Optional user-provided description of the SAP function module being processed.
ReturnTables String Comma-separated list of SAP function tables to include in the schema. Use an asterisk (*) to return all available tables.

The default value is *.

SchemaType String Specifies the schema format to generate, such as a flat schema or one using nested structures.

The allowed values are StoredProcedure, View.

The default value is StoredProcedure.

Result Set Columns

Name Type Description
Result String Indicates whether the schema generation process completed successfully.
SchemaFile String Path or name of the generated schema file representing the structure of the SAP function.
Columns String Total number of columns detected and included in the generated schema.

CData Python Connector for SAP ERP

CreateQuerySchema

Builds a schema file for a specified SAP query, allowing external tools to understand the input and output fields for data extraction.

Input

Name Type Description
Query String The query for which to generate a schema. This must match the query defined in SAP Query (SQ01).
UserGroup String The SAP user group that owns or has access to the specified query.
Variant String The default variant to apply when executing the query. This can predefine field selections and filters.
QueryDescription String Optional description of the SAP query, used for documentation or display purposes.
Workspace String Optional workspace name for organizing or categorizing the generated schema.

The allowed values are Global, Local.

The default value is Global.

TableName String Name to assign to the resulting table or schema file. If not specified, the query name is used by default.

Result Set Columns

Name Type Description
Result String Indicates whether the schema generation succeeded or failed.
SchemaFile String Path or filename of the generated schema file that represents the structure of the query results.
Columns String Total number of columns identified in the query and included in the generated schema.

CData Python Connector for SAP ERP

CreateSchema

Creates a schema file for a specified SAP table or view, facilitating structured access to SAP data from external applications.

Stored Procedure-Specific Information

To execute this procedure, enter:
    EXEC CreateSchema TableName = 'MARA', FileName = 'C:\schemas\MARA.rsd'

The TableName input specifies the SAP table or view, and the FileName input defines the path for the generated schema file.

Input

Name Type Description
TableName String Name of the SAP table or view to generate a schema for. This is used to retrieve metadata from the SAP system.
FileName String Full path and filename for the generated schema file. For example: 'C:\\Users\\User\\Desktop\\SmartSheet\\sheet.rsd'.

Result Set Columns

Name Type Description
Result String Indicates whether the schema creation process was successful or failed.

CData Python Connector for SAP ERP

CreateTableSchema

Generates a schema file for a specific SAP table using RFC_READ_TABLE, enabling data retrieval from the SAP backend through remote function calls.

Input

Name Type Description
Table String Name of the SAP table to generate a schema for. This is typically used with RFC_READ_TABLE to retrieve metadata and data.
TableDescription String Optional user-defined description of the SAP table for documentation purposes.

Result Set Columns

Name Type Description
Result String Indicates whether the schema generation was successful or encountered an error.
SchemaFile String Name or path of the generated schema file that represents the structure of the SAP table.
Columns String Number of columns identified in the specified SAP table and included in the schema.

CData Python Connector for SAP ERP

ListQueries

Retrieves metadata about available SAP queries and their fields, helping users select the correct query structure for data extraction.

Stored Procedure-Specific Information

To execute this procedure, enter:
    EXEC ListQueries UserGroup = 'ZGROUP', Query = 'ZQUERY', Workspace = 'Global'

The UserGroup input specifies the SAP user group, and the Query input filters results to a specific query name.

Input

Name Type Description
UserGroup String SAP user group for which to list available queries. User groups control access to queries in SAP Query (SQ01).
Query String Optional filter to return a specific query by name within the specified user group.
Workspace String Optional name of the workspace used to organize the query metadata results.

The allowed values are Global, Local.

The default value is Global.

Result Set Columns

Name Type Description
QueryName String Name of the SAP query returned in the result set.
UserGroup String SAP user group associated with the returned query.
Variant String Default variant configured for the query, used to prefill selection criteria and layout options.

CData Python Connector for SAP ERP

PushIDoc

Sends IDoc or IDoc XML data to an SAP system using synchronous or asynchronous modes. Useful for B2B messaging, system integration, or transactional updates.

Input

Name Type Description
IDocFile String Full file path to the IDoc or IDoc XML file to be sent to the SAP system.
FileType String Format of the file being uploaded, such as 'IDoc' for standard format or 'XML' for structured XML content.

The allowed values are XML, IDoc.

The default value is IDoc.

Mode String Specifies how the IDoc should be sent. Options include synchronous (immediate response) or asynchronous (background processing).

The allowed values are Sync, ASync.

The default value is ASync.

Result Set Columns

Name Type Description
Result String Indicates whether the IDoc was successfully transmitted to SAP. Returns 'Success' or 'Failure'.
Message String Descriptive message returned by SAP or the interface, especially useful for identifying errors if the transmission fails.

CData Python Connector for SAP ERP

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 SAP ERP:

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

sys_tablecolumns

Describes the columns of the available tables and views.

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

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

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 SAP ERP

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 SAP ERP

sys_procedureparameters

Describes stored procedure parameters.

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

SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'CreateTableSchema' 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 = 'CreateTableSchema' 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 SAP ERP 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 SAP ERP

sys_keycolumns

Describes the primary and foreign keys.

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

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

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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
ConnectionTypeThe method used to connect to SAP ERP data.
ConnectionSchemeSpecifies whether to connect to an SAP system with a message server (GroupServer) or without one (ApplicationServer).
HostHost name of the target SAP system.
SystemNumberThe instance number associated with the server specified in the Host connection property.
UserThe user that is authenticating to the SAP system.
PasswordThe password used to authenticate to the SAP system.
ClientThe name of the SAP client, among those in the targeted SAP installation, that you want to connect to.
X509CertificateThe X509 certificate used for login as an alternative to logging in with User and Password.
MessageServerThe host name or IP address of the message server (central load balancing server) you want to use to connect to SAP data.
GroupThe Logon Group on your message server to which the current user belongs.
SystemIdThe System Id or R3Name of the message server specified in the MessageServer connection property.
RFCURLThe URL of the SOAP interface you want to use to connect to SAP.
MessageServerServiceThe name of the service where the message server specified in the MessageServer connection property can be reached.

Security


PropertyDescription
SNCModeSpecifies whether to use Secure Network Communications (SNC).
SNCNameAn optional input with the name of your SNC connection.
SNCQopThe quality of protection for your SNC connection.
SNCPartnerNameThe SNC name of the SAP instance you want to connect to.
SNCLibPathAn optional input detailing the path and file name of the SAP cryptographic library.
SNCSSOSpecifies whether to connect via the SAP SSO (using the Secure Login Library).

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

Miscellaneous


PropertyDescription
SAPEditionThe edition of SAP you want to use.
BAPINameSeparatorA prefix used to differentiate columns in a query result that originated in different tables, but have the same name. Each of these columns is given a prefix consisting of the name its containing table, followed by the character(s) specified in this connection property.
CharsetThe system code page to use when converting SAP Unicode byte arrays to strings.
CheckDecimalNotationSpecifies whether to read decimal values using the decimal notation specified in the user profile of the connected SAP user.
CustomTableFilterSpecifies which SAP ERP tables are displayed as views when the TableMode is set to 'Custom'.
DestinationThe name of a destination, defined in a local saprfc.ini or sapnwrfc.ini file. When this connection property is set, the connection details embedded in this destination are used to connect.
EndianTypeThe endian type of your SAP server.
GatewayHostThe gateway host you want to connect to.
GatewayServiceThe port used to connect to the SAP Gateway server specified in the GatewayHost connection property.
GenerateSchemaFilesDetermines how and when schema files are generated.
IncludeMetadataDescriptionControls whether the provider retrieves descriptions for tables, columns, or both from SAP metadata.
InitialValueModeControls whether empty column values are displayed as NULL or an initial (non-NULL) value.
LanguageThe ISO 639-1 language code used by your SAP system.
LocationThe path where generated schema files are placed.
MapNUMCToVarcharSpecifies whether to map SAP table fields of NUMC and ACCP types to Varchar type.
MapRAWToVarcharSpecifies whether to map the SAP RAW and LRAW types to Varchar type.
MaxRowsSpecifies the maximum number of rows returned for queries that do not include either aggregation or GROUP BY.
OtherSpecifies advanced connection properties for specialized scenarios. Use this property only under the guidance of our Support team to address specific issues.
PagesizeThe maximum number of records per page the provider returns when requesting data from SAP ERP. Only used for SAP tables.
PaginationSchemeDetermines how to handle the pagination query.
PseudoColumnsSpecifies the pseudocolumns to expose as table columns, expressed as a string in the format 'TableName=ColumnName;TableName=ColumnName'.
QueryModeDetermines which SAP Queries are displayed as views, if any.
ReadTableDelimiterThe delimiter used by the read table function specified in the ReadTableFunction connection property.
ReadTableFunctionThe function to use for reading table data.
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.
StoredProcedureFilterA filter controlling which function modules are reported as stored procedures.
SupportServerSideCountEnables server-side execution of the COUNT function in supported SAP installations.
TableModeSpecifies which SAP ERP tables are displayed as views.
TimeoutSpecifies the maximum time, in seconds, that the provider waits for a server response before throwing a timeout error.
TrimStringsSpecifies which, if any, leading and trailing whitespaces are omitted from varchar columns.
UseInternalNamesSpecifies whether to use the internal names of columns in query results rather than the display name.
UseLabelsControls whether the human-readable names or internal names of tables and columns are displayed in query results.
UserDefinedViewsSpecifies a filepath to a JSON configuration file that defines custom views. The provider automatically detects and uses the views specified in this file.
UseSimpleNamesSpecifies whether or not simple names should be used for tables and columns.
UseUnicodeRFCSpecifies whether to use the RFC_GET_UNICODE_STRUCTURE function module to get structure information.
WhitespaceToNullSpecifies whether to return string fields with an empty value as null.
CData Python Connector for SAP ERP

Authentication

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


PropertyDescription
ConnectionTypeThe method used to connect to SAP ERP data.
ConnectionSchemeSpecifies whether to connect to an SAP system with a message server (GroupServer) or without one (ApplicationServer).
HostHost name of the target SAP system.
SystemNumberThe instance number associated with the server specified in the Host connection property.
UserThe user that is authenticating to the SAP system.
PasswordThe password used to authenticate to the SAP system.
ClientThe name of the SAP client, among those in the targeted SAP installation, that you want to connect to.
X509CertificateThe X509 certificate used for login as an alternative to logging in with User and Password.
MessageServerThe host name or IP address of the message server (central load balancing server) you want to use to connect to SAP data.
GroupThe Logon Group on your message server to which the current user belongs.
SystemIdThe System Id or R3Name of the message server specified in the MessageServer connection property.
RFCURLThe URL of the SOAP interface you want to use to connect to SAP.
MessageServerServiceThe name of the service where the message server specified in the MessageServer connection property can be reached.
CData Python Connector for SAP ERP

ConnectionType

The method used to connect to SAP ERP data.

Possible Values

Classic, Classic_Unicode, NetWeaver, Soap

Data Type

string

Default Value

"NetWeaver"

Remarks

The connector connects to your SAP ERP data using the specified method.

Available methods include:

  • Use SOAP to connect using the SAP SOAP Framework.
    • You must also set the RFCURL connection property when using this method.

CData Python Connector for SAP ERP

ConnectionScheme

Specifies whether to connect to an SAP system with a message server (GroupServer) or without one (ApplicationServer).

Possible Values

ApplicationServer, GroupServer

Data Type

string

Default Value

"ApplicationServer"

Remarks

Set this connection property to one of the following values:

ApplicationServer (default) Connect to the SAP system directly without using a message server.
GroupServer Connect to the SAP system using a message server. Choose this option if you are using a load-balancing server.

CData Python Connector for SAP ERP

Host

Host name of the target SAP system.

Data Type

string

Default Value

""

Remarks

This connection property is required when the ConnectionScheme connection property is set to ApplicationServer and ConnectionType is set to a value other than SOAP.

Host names can be regular host names defined in a hosts file, an IP address like 123.123.123.123, or an SAProuter address such as "/H/hostname/S/port/H/host/S/port/ ..."

You can find this value in SAP Logon by right-clicking a connection, selecting Properties, and inspecting the Connection tab's Application Server field.

CData Python Connector for SAP ERP

SystemNumber

The instance number associated with the server specified in the Host connection property.

Data Type

string

Default Value

"0"

Remarks

This connection property is always required, except when the ConnectionType connection property is set to SOAP.

The valid range of values for this connection propery is 0 to 99. Typically, this value is 0.

You can find this value in SAP Logon by right-clicking a connection, selecting Properties, and inspecting the Instance Number field in the Connection tab.

CData Python Connector for SAP ERP

User

The user that is authenticating to the SAP system.

Data Type

string

Default Value

""

Remarks

Client, User, and Password are needed for authentication to the R/3 server.

CData Python Connector for SAP ERP

Password

The password used to authenticate to the SAP system.

Data Type

string

Default Value

""

Remarks

Client, User, and Password are needed for authentication to the R/3 server.

CData Python Connector for SAP ERP

Client

The name of the SAP client, among those in the targeted SAP installation, that you want to connect to.

Data Type

string

Default Value

""

Remarks

In order to connect with your SAP ERP data via the connector, you must specify a client name.

You can find the available client values in the MANDT column of the T000 SAP table.

You can access this table either using t-code SE16 in the SAP UI or in the table list of the connector (this table is accessible when TableMode is set to TransparentCustomer).

CData Python Connector for SAP ERP

X509Certificate

The X509 certificate used for login as an alternative to logging in with User and Password.

Data Type

string

Default Value

""

Remarks

This connection property is only supported when you are connecting using SNC (in which case the SNCMode connection property should be set to True).

Set this connection property to a path pointing to a file containing:

  • An X509 certificate in PEM format, or
  • A PEM blob with the "-----BEGIN ..." header, or
  • A PEM blob without the "-----BEGIN ..." header

CData Python Connector for SAP ERP

MessageServer

The host name or IP address of the message server (central load balancing server) you want to use to connect to SAP data.

Data Type

string

Default Value

""

Remarks

This connection property must be set when connecting to an SAP system that uses load balancing (in which case the ConnectionScheme connection property should be set to GroupServer).

When this connection property is set, the message server specified in the value of this connection property is used to connect instead of an individual application server.

CData Python Connector for SAP ERP

Group

The Logon Group on your message server to which the current user belongs.

Data Type

string

Default Value

""

Remarks

This connection property is mainly used for connection to an SAP system that uses load balancing. In such situations, you must also set ConnectionScheme to GroupServer.

The default group name in most SAP systems is "PUBLIC".

CData Python Connector for SAP ERP

SystemId

The System Id or R3Name of the message server specified in the MessageServer connection property.

Data Type

string

Default Value

""

Remarks

This connection property is required when connecting to a message server.

You can find this value in SAP Logon by right-clicking a connection, selecting Properties, and inspecting the System ID field in the Connection tab.

CData Python Connector for SAP ERP

RFCURL

The URL of the SOAP interface you want to use to connect to SAP.

Data Type

string

Default Value

""

Remarks

If connecting to SAP through the SOAP interface, this property must be set to the SOAP URL of your SAP system.

An example of this is http://localhost:8000/sap/bc/soap/rfc.

The SOAP service must be enabled in your SAP system for this type of connection to work properly.

The process for enabling the SOAP service varies across different SAP versions. If you want to enable the SOAP service in your SAP installation, please contact your SAP administrator for assistance.

CData Python Connector for SAP ERP

MessageServerService

The name of the service where the message server specified in the MessageServer connection property can be reached.

Data Type

string

Default Value

""

Remarks

This connection property is required when the ConnectionScheme connection property is set to GroupServer.

To find the value for this connection property, open the SAP GUI and navigate as follows:

  • Use T-code "SMMS" to open the message server monitor.
  • Select the message server you specified in the MessageServer connection property.
  • In the menu bar, Navigate to Goto > Parameters > Change. This opens the Profile Parameters window.
  • In the Profile Parameters window, note the value in the New Value column for the parameter "rdisp/msserv".
  • Set this connection property to the noted value.

If not specified, the connector connects with HTTP.

On Windows machines, the mappings between these services and their ports are stored on C:\windows\system32\drivers\etc\services.

On Unix machines, these mappings are stored in the /etc/services file or on the domain name server.

CData Python Connector for SAP ERP

Security

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


PropertyDescription
SNCModeSpecifies whether to use Secure Network Communications (SNC).
SNCNameAn optional input with the name of your SNC connection.
SNCQopThe quality of protection for your SNC connection.
SNCPartnerNameThe SNC name of the SAP instance you want to connect to.
SNCLibPathAn optional input detailing the path and file name of the SAP cryptographic library.
SNCSSOSpecifies whether to connect via the SAP SSO (using the Secure Login Library).
CData Python Connector for SAP ERP

SNCMode

Specifies whether to use Secure Network Communications (SNC).

Data Type

bool

Default Value

false

Remarks

SAP Secure Network Communications (SNC) provides an interface for augmenting SAP with additional non-native security features.

If you have SNC features enabled in your SAP instance, set this connection property to True.

If your SAP instance has SNC features enabled, you must describe the details of your SNC configuration to the connector to connect.

See the SNCSSO, SNCName, SNCLibPath, SNCPartnerName, SNCQop connection properties for more information.

You can only enable SNC security features when the ConnectionType connection property is set to CLASSIC, CLASSIC_UNICODE, or NETWEAVER.

CData Python Connector for SAP ERP

SNCName

An optional input with the name of your SNC connection.

Data Type

string

Default Value

""

Remarks

Although this parameter is optional, it is recommended that you set it in order to ensure that the correct SNC name is used for the connection.

To find the value you need to specify, open SAP Logon, right-click your connection and select Properties. In the System Entry Properties dialog, click the Network tab and look at the value in Secure Network Settings -> SNC Name.

CData Python Connector for SAP ERP

SNCQop

The quality of protection for your SNC connection.

Data Type

string

Default Value

""

Remarks

You can set an integer up to 9 depending on your application server.

Valid values are 1, 2, 3, 8, or 9, which correspond to the following protection levels:

1Apply authentication only.
2Apply integrity protection (authentication).
3Apply privacy protection (integrity and authentication).
8Apply the default protection.
9Apply the maximum protection.

CData Python Connector for SAP ERP

SNCPartnerName

The SNC name of the SAP instance you want to connect to.

Data Type

string

Default Value

""

Remarks

Setting this connection property is required when using SNC (when the SNCMode connection property is set to True).

The value for this connection property can be found as follows:

  • In the SAP GUI use T-Code "RZ11" to access the Profile Parameter Maintenance form.
  • In the Profile Parameter Maintenance form's Parameter Name field, type "snc/identity/as" and click Display.
  • Under Value of Profile Parameter snc/identity/as, note the value for the Default Profile.
  • Set this connection property to the noted value.

CData Python Connector for SAP ERP

SNCLibPath

An optional input detailing the path and file name of the SAP cryptographic library.

Data Type

string

Default Value

""

Remarks

Set this connection property to the file path of the version of the SAP cryptographic library specific to your operating system.

On Windows systems, this assembly is called "sapcrypto.dll".

On Linux systems, this assembly is called "libsapcrypto.dll".

These libraries are available for download from SAP.

By default, the connector uses the library defined in the environment variable SNC_LIB.

CData Python Connector for SAP ERP

SNCSSO

Specifies whether to connect via the SAP SSO (using the Secure Login Library).

Possible Values

0, 1

Data Type

string

Default Value

"1"

Remarks

The default value is 1. Valid values are 0,1.

The SNCMode connection property must be set to True to use this feature.

Available values are:

0Use User/password or other non-SSO identity-related connection properties to authenticate.
1Authenticate via SNC SSO (using the Secure Login Library).

CData Python Connector for SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

Schema

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


PropertyDescription
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 SAP ERP

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 SAP ERP

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 SAP ERP

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 SAP ERP

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

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 SAP ERP.
  • 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 SAP ERP

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;'Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;

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";Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;

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';Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;

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 SAP ERP

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:saperp:CacheDriver=org.apache.derby.jdbc.EmbeddedDriver;CacheConnection='jdbc:derby:sample';Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;
To cache to an in-memory database, use a JDBC URL like the following:
jdbc:saperp:CacheDriver=org.apache.derby.jdbc.EmbeddedDriver;CacheConnection='jdbc:derby:memory';Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;

SQLite

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

jdbc:saperp:CacheDriver=org.sqlite.JDBC;CacheConnection='jdbc:sqlite:C:/Temp/sqlite.db';Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;

MySQL

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

  jdbc:saperp:Cache Driver=cdata.jdbc.mysql.MySQLDriver;Cache Connection='jdbc:mysql:Server=localhost;Port=3306;Database=cache;User=root;Password=123456';Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;
  

SQL Server

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

jdbc:saperp:Cache Driver=com.microsoft.sqlserver.jdbc.SQLServerDriver;Cache Connection='jdbc:sqlserver://localhost\sqlexpress:7437;user=sa;password=123456;databaseName=Cache';Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;

Oracle

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

jdbc:saperp:Cache Driver=oracle.jdbc.OracleDriver;CacheConnection='jdbc:oracle:thin:scott/tiger@localhost:1521:orcldb';Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;
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:saperp:CacheDriver=cdata.jdbc.postgresql.PostgreSQLDriver;CacheConnection='jdbc:postgresql:User=postgres;Password=admin;Database=postgres;Server=localhost;Port=5432;';Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;

CData Python Connector for SAP ERP

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 SAP ERP

CacheLocation

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

Data Type

string

Default Value

"%APPDATA%\\CData\\SAPERP Data Provider"

Remarks

The CacheLocation is a simple, file-based cache.

If left unspecified, the default location is %APPDATA%\\CData\\SAPERP 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 SAP ERP catalog in CacheLocation.

CData Python Connector for SAP ERP

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 SAP ERP

Offline

Gets the data from the specified cache database instead of live SAP ERP 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 SAP ERP data.

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

CData Python Connector for SAP ERP

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 SAP ERP 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\\SAPERP Data Provider
Mac ~/Library/Application Support/CData/SAPERP Data Provider
Unix ~/.config/CData/SAPERP 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 SAP ERP 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 SAP ERP 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 SAP ERP.

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 SAP ERP

Miscellaneous

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


PropertyDescription
SAPEditionThe edition of SAP you want to use.
BAPINameSeparatorA prefix used to differentiate columns in a query result that originated in different tables, but have the same name. Each of these columns is given a prefix consisting of the name its containing table, followed by the character(s) specified in this connection property.
CharsetThe system code page to use when converting SAP Unicode byte arrays to strings.
CheckDecimalNotationSpecifies whether to read decimal values using the decimal notation specified in the user profile of the connected SAP user.
CustomTableFilterSpecifies which SAP ERP tables are displayed as views when the TableMode is set to 'Custom'.
DestinationThe name of a destination, defined in a local saprfc.ini or sapnwrfc.ini file. When this connection property is set, the connection details embedded in this destination are used to connect.
EndianTypeThe endian type of your SAP server.
GatewayHostThe gateway host you want to connect to.
GatewayServiceThe port used to connect to the SAP Gateway server specified in the GatewayHost connection property.
GenerateSchemaFilesDetermines how and when schema files are generated.
IncludeMetadataDescriptionControls whether the provider retrieves descriptions for tables, columns, or both from SAP metadata.
InitialValueModeControls whether empty column values are displayed as NULL or an initial (non-NULL) value.
LanguageThe ISO 639-1 language code used by your SAP system.
LocationThe path where generated schema files are placed.
MapNUMCToVarcharSpecifies whether to map SAP table fields of NUMC and ACCP types to Varchar type.
MapRAWToVarcharSpecifies whether to map the SAP RAW and LRAW types to Varchar type.
MaxRowsSpecifies the maximum number of rows returned for queries that do not include either aggregation or GROUP BY.
OtherSpecifies advanced connection properties for specialized scenarios. Use this property only under the guidance of our Support team to address specific issues.
PagesizeThe maximum number of records per page the provider returns when requesting data from SAP ERP. Only used for SAP tables.
PaginationSchemeDetermines how to handle the pagination query.
PseudoColumnsSpecifies the pseudocolumns to expose as table columns, expressed as a string in the format 'TableName=ColumnName;TableName=ColumnName'.
QueryModeDetermines which SAP Queries are displayed as views, if any.
ReadTableDelimiterThe delimiter used by the read table function specified in the ReadTableFunction connection property.
ReadTableFunctionThe function to use for reading table data.
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.
StoredProcedureFilterA filter controlling which function modules are reported as stored procedures.
SupportServerSideCountEnables server-side execution of the COUNT function in supported SAP installations.
TableModeSpecifies which SAP ERP tables are displayed as views.
TimeoutSpecifies the maximum time, in seconds, that the provider waits for a server response before throwing a timeout error.
TrimStringsSpecifies which, if any, leading and trailing whitespaces are omitted from varchar columns.
UseInternalNamesSpecifies whether to use the internal names of columns in query results rather than the display name.
UseLabelsControls whether the human-readable names or internal names of tables and columns are displayed in query results.
UserDefinedViewsSpecifies a filepath to a JSON configuration file that defines custom views. The provider automatically detects and uses the views specified in this file.
UseSimpleNamesSpecifies whether or not simple names should be used for tables and columns.
UseUnicodeRFCSpecifies whether to use the RFC_GET_UNICODE_STRUCTURE function module to get structure information.
WhitespaceToNullSpecifies whether to return string fields with an empty value as null.
CData Python Connector for SAP ERP

SAPEdition

The edition of SAP you want to use.

Possible Values

OnPremise

Data Type

string

Default Value

"OnPremise"

Remarks

The CData Python Connector for SAP ERP only supports connections to on-premises SAP instances.

CData Python Connector for SAP ERP

BAPINameSeparator

A prefix used to differentiate columns in a query result that originated in different tables, but have the same name. Each of these columns is given a prefix consisting of the name its containing table, followed by the character(s) specified in this connection property.

Data Type

string

Default Value

"_"

Remarks

When a function module (the connector makes function modules available as stored procedures) selects from multiple structures that share one or more column names, each identically-named column is given a prefix consisting of the name its containing table, followed by the character(s) specified in this connection property.

For example, if this connection property is set to "_", and you execute a stored procedure corresponding to a function module which selects from the structures "X" and "Y", and those structures both contain a column called "FIELD", two columns appear in the query results: "X_FIELD" and "Y_FIELD".

CData Python Connector for SAP ERP

Charset

The system code page to use when converting SAP Unicode byte arrays to strings.

Data Type

string

Default Value

"UTF-8"

Remarks

SAP returns data in byte arrays, which the connector converts to a string.

This property specifies the code page the connector uses to do the conversion. For example, 'UTF-8'.

This property can be useful to fix Unicode-to-multibyte encoding problems. For instance, if you are on a U.S. machine and reading from a Japanese SAP server with Japanese characters, you may need to set Charset to 'shift_jis' to display the characters properly.

CData Python Connector for SAP ERP

CheckDecimalNotation

Specifies whether to read decimal values using the decimal notation specified in the user profile of the connected SAP user.

Data Type

bool

Default Value

false

Remarks

When this connection property is set to False (the default), decimal values are read in US format.

When this connection property is set to True, the connector detects the decimal format from the connected SAP user profile's decimal format setting. Set this connection property to True when the connector returns improperly formatted decimal values in query results.

CData Python Connector for SAP ERP

CustomTableFilter

Specifies which SAP ERP tables are displayed as views when the TableMode is set to 'Custom'.

Data Type

string

Default Value

""

Remarks

The connector lists SAP ERP tables as read-only views. If you need to write to SAP ERP tables, you can use BAPIs.

Most SAP ERP installations contain a very large number of tables. While the connector can list all tables as available views, this may result in long load times. This property allows you to define a custom filter against the DD02L system table to retrieve only the tables important to your use case.

To use this property, set the TableMode to Custom and define a valid SQL WHERE clause here (without the "WHERE" keyword). For example, to retrieve transparent tables used for application data:

CustomTableFilter = TABCLASS = 'TRANSP' AND CONTFLAG = 'A' AND AS4LOCAL = 'A'

Overriding Default Filtering Behavior

By default, the connector applies internal filters to exclude certain tables, such as those with names containing forward slashes. For example, Customer/Orders.

To override this behavior and explicitly include such tables, you can set a custom filter that matches your use case. For example, to retrieve only tables with slashes in their names:

CustomTableFilter = TABNAME LIKE '/%'

Note: Use custom filters with caution. Tables containing slashes are often system or namespace-reserved and may not be appropriate for general access.

CData Python Connector for SAP ERP

Destination

The name of a destination, defined in a local saprfc.ini or sapnwrfc.ini file. When this connection property is set, the connection details embedded in this destination are used to connect.

Data Type

string

Default Value

""

Remarks

As an alternative to describing your connection details to the connector via connection properties, setting this connection property to the name of a destination (the value of the "DEST" parameter from a local saprfc.ini or sapnwrfc.ini file) causes the connector to instead use the configuration found in that .ini file to connect.

Take the following .ini file for example (the contents of the .ini file vary depending on your specific connection configuration):

DEST=MYSAPDEST
TYPE=A
CLIENT=001
LANG=EN
ASHOST=10.0.1.123
SYSNR=00

To use this .ini's configuration to connect, you would set this connection property to "MYSAPDEST".

Note: This connection property is not supported when ConnectionType is set to Soap.

The name and the location of the .ini file varies depending on the ConnectionType specified:

  • For the CLASSIC type, the file is named saprfc.ini and the file path can be found in the RFC_INI environment variable.
  • For the Netweaver type, the file is named sapnwrfc.ini. Place this file in the current execution directory. For example, if you are creating an application that incorporates the connector, place sapnwrfc.ini next to that project's executable file.
Note that values absent from the .ini (such as User and Password) still need to be set using connection properties.

See the SAP RFC SDK for more information about using .ini files with the RFC library.

CData Python Connector for SAP ERP

EndianType

The endian type of your SAP server.

Possible Values

Auto, Big, Little

Data Type

string

Default Value

"Auto"

Remarks

The endian type of your SAP server determines whether it orders bytes from the most significant to least significant bytes (big-endian) or from the least significant to most significant byte (little-endian).

The connector needs to know the endian type of your SAP server in order to retrieve SAP data.

If you do not know the endian type for the SAP server, set this value to Auto. The connector attempts to automatically detect the endian type.

However, if the connector returns an error indicated that your SAP server does not have the RFC needed to automatically determine its endian type, use this connection property to set the Endian type manually. If you need to set this manually and you do not know the value that you should set, ask your SAP administrator for assistance.

CData Python Connector for SAP ERP

GatewayHost

The gateway host you want to connect to.

Data Type

string

Default Value

""

Remarks

Set this connection property if you want to connect to your SAP installation via a specific SAP Gateway server.

If not specified, the connector attempts to connect to the SAP system specified by the Host connection property.

CData Python Connector for SAP ERP

GatewayService

The port used to connect to the SAP Gateway server specified in the GatewayHost connection property.

Data Type

string

Default Value

""

Remarks

If no value is specified in this connection property, the connector uses the value "sapgw##", where the "##" is the value specified in the SystemNumber connection property, to connect.

CData Python Connector for SAP ERP

GenerateSchemaFiles

Determines how and when schema files are generated.

Possible Values

Never, OnUse, OnStart

Data Type

string

Default Value

"Never"

Remarks

The connector can generate schema files corresponding to views returned by the connector. Editing these generated schema files gives you granular control over the metadata (such as columns) returned by the connector when the corresponding views are queried.

For example, removing a column (<attr> element) from a generated schema file causes that column not to be reported.

Schema files generated by the connector are output to the folder specified in the Location connection property.

When this connection property is set to OnUse, upon making a metadata request for a view, the connector generates a schema file for that view.

When this connection property is set to OnStart, the connector generates schema files for all the views that are discovered when the connection begins.

Schema files are not overwritten if they already exist in the Location folder. To update a specific schema file with updated metadata, first delete that schema file from this folder, then trigger the schema file creation again.

CData Python Connector for SAP ERP

IncludeMetadataDescription

Controls whether the provider retrieves descriptions for tables, columns, or both from SAP metadata.

Possible Values

NONE, Columns, Tables, TablesAndColumns

Data Type

string

Default Value

"Columns"

Remarks

The SAP data dictionary provides descriptions for tables and columns that can be useful for schema exploration, documentation, and reporting tools. By default, only column descriptions are retrieved. You can set this property to one of the following values:

  1. Set to Columns (default) to retrieve descriptions for all columns in the schema.
  2. Set to Tables to retrieve descriptions for all tables but not columns.
  3. Set to TablesAndColumns to retrieve descriptions for both tables and their respective columns.
  4. Set to NONE to disable retrieval of all metadata descriptions.

Performance Considerations

Enabling table descriptions requires an additional RFC call to retrieve data from the DD02T table, which may impact performance, especially in environments with large schemas. Consider using only when needed to avoid excessive API requests.

Note: The language of the descriptions comes from the value of the Language connection property. Unlike UseLabels, this property does not rename tables or columns; it only controls whether descriptions are populated.

CData Python Connector for SAP ERP

InitialValueMode

Controls whether empty column values are displayed as NULL or an initial (non-NULL) value.

Possible Values

Null, InitialValue

Data Type

string

Default Value

"Null"

Remarks

Some fields in SAP tables are configured to have an initial value.

This means that, when a record is inserted into the SAP table without including a value for those fields, instead of being considered NULL, the fields are initialized with a set generic value that represents an empty value without technically being NULL.

For example, a field may be set to initialize with the value 0, or "" (empty string) instead of being NULL.

When this connection property is set to Null, records in fields with the InitialValue indicator enabled in SAP, and whose value matches the initial value for their data type (0, "", etc.), are returned as NULL in query results.

When this connection property is set to InitialValue, records in fields with the InitialValue indicator enabled in SAP, and whose value matches the initial value for their data type (0, "", etc.), are returned as-is in query results.

CData Python Connector for SAP ERP

Language

The ISO 639-1 language code used by your SAP system.

Data Type

string

Default Value

"EN"

Remarks

Set this connection property to the language value you specify when you log into SAP.

By default, "EN" (English) is used. Other codes include "DE" for German and "JA" for Japanese.

This connection property's value informs the column names returned when querying SAP tables. See the UseLabels connection property for more details.

CData Python Connector for SAP ERP

Location

The path where generated schema files are placed.

Data Type

string

Default Value

""

Remarks

Through the use of schema files, you can customize the metadata returned by views and stored procedures. Any view with a corresponding schema file in the path set in this connection property are always persisted in the list of queryable views, regardless of the current value of TableMode.

Schema files can be generated manually by executing stored procedures such as CreateSchema, or generated automatically when the conditions specified in the GenerateSchemaFiles connection property are met.

Schema files generated by the connector are output to the directory specified in this connection property.

The value of this connection property can be an absolute path or a relative path from the location of the connector executable.

CData Python Connector for SAP ERP

MapNUMCToVarchar

Specifies whether to map SAP table fields of NUMC and ACCP types to Varchar type.

Data Type

bool

Default Value

true

Remarks

The SAP NUMC type is a long character field that only allows numeric entries. The length of this field is limited to a maximum of 255 characters.

The SAP ACCP type represents a posting period. This field is 6 characters long, with the format YYYYMM.

If this connection property is set to False, NUMC and ACCP type fields are returned with a numeric type.

If this connection property is set to True, NUMC and ACCP fields are returned as Varchar type.

CData Python Connector for SAP ERP

MapRAWToVarchar

Specifies whether to map the SAP RAW and LRAW types to Varchar type.

Data Type

bool

Default Value

false

Remarks

If this connection property is set to True, the connector maps the SAP RAW and LRAW types to Varchar type.

If this connection property is set to False, the connector maps RAW and LRAW types to Binary type.

CData Python Connector for SAP ERP

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 SAP ERP

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 SAP ERP

Pagesize

The maximum number of records per page the provider returns when requesting data from SAP ERP. Only used for SAP tables.

Data Type

string

Default Value

""

Remarks

When processing a query, instead of requesting all of the queried data at once from SAP ERP, 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.

The RFC_READ_TABLE function module uses the rowcount and rowskips parameters for paging. This can cause unusual behavior if you are paging through data while it is being interacted with.

For instance, if a new row is inserted to a table while you are paging through data, you may see a duplicate entry show up.

Also, if a row is deleted from a table, the results you get back may be missing a row.

This can be avoided by increasing the page size to such a degree that the connector only needs one page to return all data requested in the problematic query.

Note that, while setting large page sizes can resolve this issue and may improve overall query execution time, doing so also causes the connector to use more memory when executing queries and risks triggering a timeout.

CData Python Connector for SAP ERP

PaginationScheme

Determines how to handle the pagination query.

Possible Values

Default, Key, MaxRows

Data Type

string

Default Value

"Default"

Remarks

Allowed values are:

  • Default: Performs LIMIT and OFFSET clauses to retrieve each page via the Remote Function Call (RFC) function.
  • Key: Paginates the query by the primary key and LIMIT (page size). If the table does not support a server-side ORDER BY clause or lacks a primary key, the driver automatically falls back to Default.
  • MaxRows: Retrieves the entire table in a single request rather than using pagination. While full ACID guarantees are not provided, this approach reduces the likelihood of inconsistent results caused by concurrent writes when querying small tables.

Note: When PaginationScheme is set to Default or Key, the driver orders results by the table's primary key(s) only when the table class supports a server-side ORDER BY clause. This behavior prevents duplicate records across paginated result sets.

If a table does not support server-side ORDER BY, the driver does not apply primary-key ordering by default. In this case, if an ORDER BY clause is explicitly specified in the query, it is not sent to SAP; instead, the driver applies the ordering client-side.

CData Python Connector for SAP ERP

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 SAP ERP

QueryMode

Determines which SAP Queries are displayed as views, if any.

Possible Values

None, Global, Local, All

Data Type

string

Default Value

"None"

Remarks

Like SAP tables, SAP Queries can also be displayed as views.

If this connection property is set to None, SAP Queries are not included in the data model of the connector. This is the default behavior.

You can expose some or all of your SAP Queries as views:

  • Set this connection property to Global to expose cross-client Query objects accessible to your user account as views.
  • Set this connection property to Local to expose Query objects specific to your user account as views.
  • Set this connection property to All to expose both user-specific and cross-client Query objects as views.

CData Python Connector for SAP ERP

ReadTableDelimiter

The delimiter used by the read table function specified in the ReadTableFunction connection property.

Data Type

string

Default Value

""

Remarks

If your SAP installation includes SAP Note 2246160, the connector uses "~" as the default delimiter for the RFC_READ_TABLE function module. If your data contains the "~" character in any records, change the delimiter to a character that does not appear in any of your records. If your SAP installation does not include SAP Note 2246160, the connector does not use a delimiter by default.

CData Python Connector for SAP ERP

ReadTableFunction

The function to use for reading table data.

Data Type

string

Default Value

"RFC_READ_TABLE"

Remarks

The connector can use various read table functions when retrieving SAP ERP data, including custom function that remove limitations on the buffer size.

See Using a Custom Read Table Function for more information.

CData Python Connector for SAP ERP

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 SAP ERP

StoredProcedureFilter

A filter controlling which function modules are reported as stored procedures.

Data Type

string

Default Value

"BAPI*"

Remarks

The connector can execute remote enabled function modules, and makes them available for query in the form of stored procedures.

Due to the large number of function modules available in your SAP installation, you may find it useful to hide a portion of these stored procedures in the reported metadata of the connector.

Use wildcards (*) to select the procedures you want to include based on a name pattern.

For example, the default value for this connection property, "BAPI*" matches all remote enabled function modules that start with "BAPI", and function modules whose names do not start with "BAPI" are not displayed.

Note that not all function modules in SAP are remote enabled. If there is a function module you are interested in using that does not display, check the TFDIR system table to verify its FMODE column is set to 'R'. If TFDIR is not visible in your metadata listing, set TableMode to TransparentSystem to make it available for querying.

CData Python Connector for SAP ERP

SupportServerSideCount

Enables server-side execution of the COUNT function in supported SAP installations.

Data Type

bool

Default Value

false

Remarks

The feature enabled by this connection property is only supported in SAP installations that include SAP Note 3390051.

CData Python Connector for SAP ERP

TableMode

Specifies which SAP ERP tables are displayed as views.

Possible Values

TransparentApplication, TransparentCustomer, TransparentSystem, Pooled, Cluster, InternalTable, View, AppendTable, All, None, Custom

Data Type

string

Default Value

"TransparentApplication"

Remarks

The connector lists SAP ERP tables as read-only views. If you need to write to SAP ERP tables, you can use BAPIs.

Most SAP ERP installations contain a very large number of tables, and while the connector can list all tables in your installation as available views, the more tables you have access to, the longer the process of displaying this list takes.

This property allows you to only list the tables that are important to you. This both avoids the need to scroll through a massive list of tables and allows the connector to display the now-filtered list of tables more quickly.

The connector retrieves the list of tables from the DD02L system table. Set this property either to the name of one of the filter presets below, or write a custom filter for DD02L directly in this connection property's value.

Internal Filtering Behavior

In addition to the selected filter, the connector applies internal filtering logic to avoid displaying system-reserved or special-use tables. For example, by default, the connector excludes tables that contain a forward slash in the name. This can cause tables such as /Customer/Orders/ to be omitted from the table list, even if they would otherwise match your selected filter.

Using CustomTableFilter to Override Default Filters

To override the default filtering behavior, you can set the TableMode to Custom and define your own filter using the CustomTableFilter property.

Available values:

SettingFilterDescription
TransparentApplication TABCLASS = 'TRANSP' AND CONTFLAG = 'A'Master and transaction data.
TransparentCustomer TABCLASS = 'TRANSP' AND ( CONTFLAG = 'C' OR CONTFLAG = 'G' )Data maintained by the customer only.
TransparentSystem TABCLASS = 'TRANSP' AND ( CONTFLAG = 'E' OR CONTFLAG = 'S' OR CONTFLAG = 'W' )Customer namespaces, program status changes, development environment tables, etc.
Pooled TABCLASS = 'POOL'All pooled tables.
Cluster TABCLASS = 'CLUSTER'All cluster tables such as BSEG and KONV.
InternalTable TABCLASS = 'INTTAB'All internal tables.
View TABCLASS = 'VIEW'All general view tables.
AppendTable TABCLASS = 'APPEND'All append tables.
AllAll tables regardless of type. Warning: This will cause a massive amount of tables to be retrieved and may result in a noticeable delay in table listing.
None No filter. No SAP tables are displayed. This may be useful if you intend to use schema files or SAP queries.
Custom User-defined filter. Please set this filter in the CustomTableFilter property.

CData Python Connector for SAP ERP

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 SAP ERP

TrimStrings

Specifies which, if any, leading and trailing whitespaces are omitted from varchar columns.

Possible Values

TrimLeft, TrimRight, TrimAll, None

Data Type

string

Default Value

"TrimAll"

Remarks

In SAP, the RFC_READ_TABLE function module pads Varchar columns with spaces.

Typically, trailing spaces are not deliberately added to SAP table records, so the connector defaults to removing any trailing spaces in query results.

If, however, you have deliberately added trailing spaces in your SAP table records, you may use this connection property to customize (or disable) this behavior.

Value of TrimStringsDescription
TrimLeftTrim the leading spaces of the string value.
TrimRightTrim the trailing spaces of the string value.
TrimAllTrim the leading and trailing spaces of the string value.
NoneDo not trim any spaces from the string value.

CData Python Connector for SAP ERP

UseInternalNames

Specifies whether to use the internal names of columns in query results rather than the display name.

Data Type

bool

Default Value

false

Remarks

When this connection property is set to False (the default), the connector displays columns by their display names (a more readable name for the column specific to your SAP client's language).

When this connection property is set to True, the connector displays columns by their internal names.

For example, the ADRC table has a column with the internal name "ADDRNUMBER".

If this connection property is set to False and you have your SAP client language set to "en", the connector uses the name "Address Number" for the column.

If this connection property is set to True, the connector uses the internal name ("ADDRNUMBER") as-is for the column name.

CData Python Connector for SAP ERP

UseLabels

Controls whether the human-readable names or internal names of tables and columns are displayed in query results.

Possible Values

NONE, Columns, Tables, TablesAndColumns

Data Type

string

Default Value

"NONE"

Remarks

You can set this connection property to one of the following values:

  • NONE - Tables and columns are displayed with the internal names used in SAP.
  • Columns - Columns are displayed with a more user-friendly name specific to the language set in your SAP client.
  • Tables - Tables are displayed with a more user-friendly name specific to the language set in your SAP client.
  • TablesAndColumns - Both tables and columns are displayed with a more user-friendly name specific to the language set in your SAP client.
Note: The language used comes from the value of the Language connection property.

If you have set this connection property to display human-readable names for tables/columns, and no human-readable name exists for a specific column or table, the connector displays its internal name instead.

CData Python Connector for SAP ERP

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 MARA 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 SAP ERP

UseSimpleNames

Specifies whether or not simple names should be used for tables and columns.

Data Type

bool

Default Value

false

Remarks

SAP ERP tables can include special characters in their names that are typically not allowed in standard databases. This property makes the connector easier to use with traditional database tools.

Setting UseSimpleNames to True simplifies the names of the columns that are returned. It enforces a naming scheme where only alphanumeric characters and underscores are valid for displayed column names.

Notes:

  • Any non-alphanumeric characters are converted to underscores.
  • If the column or table names exceed 128 characters in length they are truncated to 128 characters to comply with SQL Server standards.

CData Python Connector for SAP ERP

UseUnicodeRFC

Specifies whether to use the RFC_GET_UNICODE_STRUCTURE function module to get structure information.

Data Type

bool

Default Value

true

Remarks

This connection property must be set to True (this is the default) when using SAP systems that are Unicode-enabled.

If you are connecting with a SOAP service (when the ConnectionType connection property is set to SOAP) and that SOAP service is not Unicode-enabled, set this connection property to False.

You can confirm whether your SAP system is Unicode-enabled by navigating in the SAP GUI to System > Status > SAP System data > Unicode System.

CData Python Connector for SAP ERP

WhitespaceToNull

Specifies whether to return string fields with an empty value as null.

Data Type

bool

Default Value

false

Remarks

When this connection property is set to True, empty column values (empty strings or strings that only contain whitespace characters) are returned as null.

This connection property only affects fields with the datatype "string".

CData Python Connector for SAP ERP

Third Party Copyrights

LZMA from 7Zip LZMA SDK

LZMA SDK is placed in the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or distribute the original LZMA SDK code, either in source code form or as a compiled binary, for any purpose, commercial or non-commercial, and by any means.

LZMA2 from XZ SDK

Version 1.9 and older are in the public domain.

Xamarin.Forms

Xamarin SDK

The MIT License (MIT)

Copyright (c) .NET Foundation Contributors

All rights reserved.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

NSIS 3.10

Copyright (C) 1999-2025 Contributors THE ACCOMPANYING PROGRAM IS PROVIDED UNDER THE TERMS OF THIS COMMON 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 code and documentation 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 additions to the Program which: (i) are separate modules of software distributed in conjunction with the Program under their own license agreement, and (ii) are not derivative works of the Program.

"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, including all Contributors.

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, in source code and object code form.

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 and object code 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.

3. REQUIREMENTS

A Contributor may choose to distribute the Program in object code form under its own license agreement, provided that:

a) it complies with the terms and conditions of this Agreement; and

b) its license agreement:

i) effectively disclaims on behalf of all 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 Contributors all liability for damages, including direct, indirect, special, incidental and consequential damages, such as lost profits;

iii) states that any provisions which differ from this Agreement are offered by that Contributor alone and not by any other party; and

iv) states that source code for the Program is available from such Contributor, and informs licensees how to obtain it in a reasonable manner on or through a medium customarily used for software exchange.

When the Program is made available in source code form:

a) it must be made available under this Agreement; and

b) a copy of this Agreement must be included with each copy of the Program.

Contributors may not remove or alter any copyright notices contained within the Program.

Each Contributor must identify itself as the originator of its Contribution, if any, in a manner that reasonably allows subsequent Recipients to identify the originator of the Contribution.

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, 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, 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 a Contributor with respect to a patent applicable to software (including a cross-claim or counterclaim in a lawsuit), then any patent licenses granted by that Contributor to such Recipient under this Agreement shall terminate as of the date such litigation is filed. In addition, 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. IBM is the initial Agreement Steward. IBM 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.

This Agreement is governed by the laws of the State of New York and the intellectual property laws of the United States of America. No party to this Agreement will bring a legal action under this Agreement more than one year after the cause of action arose. Each party waives its rights to a jury trial in any resulting litigation.

AdoptOpenJDK / Adoptium Temurin JRE 17.0.18_8

Copyright (c) Eclipse Foundation AISBL. All Rights Reserved.

Apache License, Version 2.0

TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document.

"Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License.

"Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity.

"You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License.

"Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files.

"Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types.

"Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below).

"Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof.

"Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution."

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2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form.

3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed.

4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions:

  1. You must give any other recipients of the Work or Derivative Works a copy of this License; and
  2. You must cause any modified files to carry prominent notices stating that You changed the files; and
  3. You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and
  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.

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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

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

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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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