Getting Started with the CData Connect AI Python SDK for Anaplan

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 Anaplan data with standard Python database code. Because Connect AI provides the connectivity: you install one package, authenticate with a Personal Access Token, and query Anaplan (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 Anaplan in Connect AI, generating a Personal Access Token, installing the SDK, and reading (and, where supported, writing) live Anaplan data.

Prerequisites

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

Connect to Anaplan 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 "Anaplan" from the Add Connection panel

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

   Authenticating to Anaplan

   The driver supports authenticating with Basic, Certificate, or OAuth. In every case, set Region to the region where your Anaplan account data is hosted (e.g., US1, which is the default).

   Using Basic Authentication

   Set AuthScheme to Basic, then supply your Anaplan User and Password. If your workspace uses single sign-on (SSO), you must be assigned as an Exception User to use Basic authentication.

   Using Certificate Authentication

   Set AuthScheme to Certificate, then supply the Certificate, CertificateType, and PrivateKey properties (and the matching CertificatePassword / PrivateKeyPassword if either is encrypted). The certificate must be a CA-issued X.509 certificate registered with your Anaplan tenant administrator.

   Using OAuth Authentication

   Register a custom OAuth application in Anaplan, then set the following properties:

   • OAuthClientId: The client Id assigned when you registered your custom OAuth application.
   • OAuthClientSecret: The client secret assigned when you registered your custom OAuth application.
   • CallbackURL: The redirect URI defined when you registered your application.
   • InitiateOAuth: Set to GETANDREFRESH to have the driver manage the OAuth token exchange and refresh automatically.

   See the Getting Started chapter of the help documentation for a guide to creating a custom OAuth app and using OAuth.

   
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, Anaplan1).

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 Region, Product "
    "FROM [Anaplan1].[Anaplan].[Sales] "
    "LIMIT 10"
)

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

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