Getting Started with the CData Connect AI Python SDK for Linear

The CData Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client that lets you fetch and act on live Linear data with standard Python database code. Because Connect AI provides the connectivity: you install one package, authenticate with a Personal Access Token, and query Linear (and every other source connected in Connect AI) using the same familiar connect() / cursor() / fetchall() pattern you already know from libraries like sqlite3 and psycopg2.

This guide walks through connecting Linear in Connect AI, generating a Personal Access Token, installing the SDK, and reading (and, where supported, writing) live Linear data.

Prerequisites

• An account in CData Connect AI
• Python 3.8 or higher
• An active Linear account with valid credentials

Connect to Linear in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Linear" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Linear.

   You can authenticate to Linear with a personal API key or with OAuth 2.0. The API key is the simplest option for connecting with your own Linear account.

   Authenticating with an API Key

   Set the following connection properties:

   • AuthScheme: Set this to APIKey.
   • APIKey: A Linear personal API key.

   To create a personal API key, log in to Linear, open Settings > Security & access > Personal API keys, select New API key, and create it. Copy the key immediately, because Linear shows it only once.

   Authenticating with OAuth

   OAuth requires a custom OAuth application registered in Linear (Settings > API > OAuth applications), which provides the OAuthClientId and OAuthClientSecret. Two flows are supported:

   • Authorization code: Set AuthScheme to OAuth, InitiateOAuth to GETANDREFRESH, and provide OAuthClientId, OAuthClientSecret, and the CallbackURL defined in your application (e.g., http://localhost:33333). The driver opens Linear in your browser so you can grant access.
   • Client credentials: Set AuthScheme to OAuthClient and provide OAuthClientId and OAuthClientSecret. This authenticates the application itself, with no browser interaction, and suits machine-to-machine integrations.

   By default, the driver requests the read,write scopes. The driver refreshes the access token automatically when it expires.

   
4. Click Save & Test
5. Navigate to the Permissions tab and update the user-based permissions.

Generate a Personal Access Token (PAT)

The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.

1. Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The PAT is only visible at creation, so copy it and store it securely.

Install the SDK

Install the SDK from PyPI with pip:

pip install cdata-connect-ai

Connect and Run Your First Query

Connect with your account email and PAT, then query sys_tables to discover every table available across your connected sources. Identifiers in Connect AI are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, Linear1).

import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)
cur = conn.cursor()

# Discover what's available across your connected sources
cur.execute("SELECT CatalogName, SchemaName, TableName FROM sys_tables LIMIT 25")

for row in cur.fetchall():
    print(row)

Pick any table from the results and query it directly:

cur.execute(
    "SELECT id, name "
    "FROM [Linear1].[Linear].[Team] "
    "LIMIT 10"
)

for row in cur.fetchall():
    print(row)

Linear is a read-only source in Connect AI, so the SDK supports queries but not INSERT, UPDATE, or DELETE. Close the connection when you are finished:

conn.close()

That is the entire workflow: one package, a PAT, and standard DB-API calls. Because the SDK returns a normal DB-API connection, it drops straight into the rest of the Python data ecosystem. From here you can load Linear data into pandas, build ETL pipelines with petl, or power a Dash web app, all using this same connection.

More Information and Free Trial

Now you can query live Linear data from Python through the CData Connect AI Python SDK. For more information on connecting to Linear (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start working with live Linear data in Python.