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Use JayDeBeApi to access REST Data in Python


Use standard Python scripting and the development environment of your choice to access live REST data.

Access REST data with Python scripts and standard SQL on any machine where Python and Java can be installed. You can use the CData JDBC Driver for REST and the JayDeBeApi module to work with remote REST data in Python. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular Python language. This article shows how to use the driver to execute SQL queries to REST and visualize REST data with standard Python.

Use the JayDeBeApi module

JayDeBeApi is a Python library that serves as a JDBC (Java Database Connectivity) bridge, allowing Python programs to interact with Java databases, including CData JDBC Drivers. Use the pip install command to install the module:

pip install JayDeBeApi

Create the JDBC URL

Once you have JayDeBeApi installed, you are ready to work with REST data in Python using SQL.

See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models REST APIs as bidirectional database tables and XML/JSON files as read-only views (local files, files stored on popular cloud services, and FTP servers). The major authentication schemes are supported, including HTTP Basic, Digest, NTLM, OAuth, and FTP. See the Getting Started chapter in the data provider documentation for authentication guides.

After setting the URI and providing any authentication values, set Format to "XML" or "JSON" and set DataModel to more closely match the data representation to the structure of your data.

The DataModel property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

  • Document (default): Model a top-level, document view of your REST data. The data provider returns nested elements as aggregates of data.
  • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
  • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

See the Modeling REST Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the REST JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.rest.jar

Fill in the connection properties and copy the connection string to the clipboard.

Below is a sample variable assignment, including a typical JDBC connection string:

jdbc_url = "jdbc:rest:DataModel=Relational;URI=C:/people.xml;Format=XML;"

Access REST data in Python

With the JDBC URL configured, you only need the absolute path to the JDBC driver JAR file, which is in the "lib" folder in the installation directory ("C:\Program Files\CData[product_name] 20XX\lib\cdata.jdbc.rest.jar" on Windows).

NOTE: If you haven't already, set the JAVA_HOME environment variable to the Java installation directory.

Use code similar to the follow to read and print data from REST:

import jaydebeapi #The JDBC connection string jdbc_url = "jdbc:rest:DataModel=Relational;URI=C:/people.xml;Format=XML;" username = "****" password = "****" #The absolute Path to the JDBC driver JAR file, typically: jdbc_driver_jar = "C:\Program Files\CData[product_name] 20XX\lib\cdata.jdbc.rest.jar" conn = jaydebeapi.connect( "cdata.jdbc.rest.jar", jdbc_url, [username, password], jdbc_driver_jar, ) cursor = conn.cursor() cursor.execute("SELECT * FROM people;") results = cursor.fetchall() for row in results: print(row) cursor.close() conn.close()

Free trial & more information

Download a free, 30-day trial of the CData JDBC Driver for REST and start working with your live REST data in Python. Reach out to our Support Team if you have any questions.