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Using the CData ODBC Driver for LinkedIn in PyCharm


Connect to LinkedIn as an ODBC data source in PyCharm using the CData ODBC Driver for LinkedIn.

The CData ODBC Drivers can be used in any environment that supports loading an ODBC Driver. In this tutorial we will explore using the CData ODBC Driver for LinkedIn from within PyCharm. Included are steps for adding the CData ODBC Driver as a data source, as well as basic PyCharm code to query the data source and display results.

To begin, this tutorial will assume that you have already installed the CData ODBC Driver for LinkedIn as well as PyCharm.

Add Pyodbc to the Project

Follow the steps below to add the pyodbc module to your project.

  1. Click File -> Settings to open the project settings window.
  2. Click Project Interpreter from the Project: YourProjectName menu.
  3. To add pyodbc, click the + button and enter pyodbc.
  4. Click Install Package to install pyodbc.

Connect to LinkedIn

You can now connect with an ODBC connection string or a DSN. See the Getting Started section in the CData driver documentation for a guide to creating a DSN on your OS.

LinkedIn uses the OAuth 2 authentication standard. You will need to obtain the OAuthClientId and OAuthClientSecret by registering an app with LinkedIn. For more information refer to our authentication guide.

Below is the syntax for a DSN:

[CData LinkedIn Source] Driver = CData ODBC Driver for LinkedIn Description = My Description OAuthClientId = MyOAuthClientId OAuthClientSecret = MyOAuthClientSecret CallbackURL = http://localhost:portNumber CompanyId = XXXXXXX

Execute SQL to LinkedIn

Instantiate a Cursor and use the execute method of the Cursor class to execute any SQL statement.

import pyodbc cnxn = pyodbc.connect('DRIVER={CData ODBC Driver for LinkedIn};OAuthClientId = MyOAuthClientId;OAuthClientSecret = MyOAuthClientSecret;CallbackURL = http://localhost:portNumber;CompanyId = XXXXXXX') cursor = cnxn.cursor() cursor.execute("SELECT VisibilityCode, Comment FROM CompanyStatusUpdates WHERE EntityId = '238'") rows = cursor.fetchall() for row in rows: print(row.VisibilityCode, row.Comment)

After connecting to LinkedIn in PyCharm using the CData ODBC Driver, you will be able to build Python apps with access to LinkedIn data as if it were a standard database. If you have any questions, comments, or feedback regarding this tutorial, please contact us at [email protected].

Ready to get started?

Download a free trial of the LinkedIn ODBC Driver to get started:

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LinkedIn Icon LinkedIn ODBC Driver

The LinkedIn ODBC Driver is a powerful tool that allows you to connect with live data from LinkedIn, directly from any applications that support ODBC connectivity.

With the LinkedIn ODBC Driver accessing live People, Profiles, Companies, Groups, Jobs, etc. is as easy as querying a database.

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