Using the CData ODBC Driver for Bitbucket in PyCharm

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 Bitbucket 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 Bitbucket 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 Bitbucket

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.

For most queries, you must set the Workspace. The only exception to this is the Workspaces table, which does not require this property to be set, as querying it provides a list of workspace slugs that can be used to set Workspace. To query this table, you must set Schema to 'Information' and execute the query SELECT * FROM Workspaces>.

Setting Schema to 'Information' displays general information. To connect to Bitbucket, set these parameters:

• Schema: To show general information about a workspace, such as its users, repositories, and projects, set this to Information. Otherwise, set this to the schema of the repository or project you are querying. To get a full set of available schemas, query the sys_schemas table.
• Workspace: Required if you are not querying the Workspaces table. This property is not required for querying the Workspaces table, as that query only returns a list of workspace slugs that can be used to set Workspace.

Authenticating to Bitbucket

Bitbucket supports OAuth authentication only. To enable this authentication from all OAuth flows, you must create a custom OAuth application, and set AuthScheme to OAuth.

Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

Creating a custom OAuth application

From your Bitbucket account:

1. Go to Settings (the gear icon) and select Workspace Settings.
2. In the Apps and Features section, select OAuth Consumers.
3. Click Add Consumer.
4. Enter a name and description for your custom application.
5. Set the callback URL:
   • For desktop applications and headless machines, use http://localhost:33333 or another port number of your choice. The URI you set here becomes the CallbackURL property.
   • For web applications, set the callback URL to a trusted redirect URL. This URL is the web location the user returns to with the token that verifies that your application has been granted access.
6. If you plan to use client credentials to authenticate, you must select This is a private consumer. In the driver, you must set AuthScheme to client.
7. Select which permissions to give your OAuth application. These determine what data you can read and write with it.
8. To save the new custom application, click Save.
9. After the application has been saved, you can select it to view its settings. The application's Key and Secret are displayed. Record these for future use. You will use the Key to set the OAuthClientId and the Secret to set the OAuthClientSecret.

Below is the syntax for a DSN:

[CData Bitbucket Source]
Driver = CData ODBC Driver for Bitbucket
Description = My Description
Workspace = myworkspaceslug
Schema = Information
InitiateOAuth = GETANDREFRESH

Execute SQL to Bitbucket

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 Bitbucket};Workspace = myworkspaceslug;Schema = Information;InitiateOAuth = GETANDREFRESH;')
cursor = cnxn.cursor()
cursor.execute("SELECT Title, ContentRaw FROM Issues WHERE Id = '1'")
rows = cursor.fetchall()
for row in rows:
 print(row.Title, row.ContentRaw)

After connecting to Bitbucket in PyCharm using the CData ODBC Driver, you will be able to build Python apps with access to Bitbucket 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].