Getting Started with the CData Connect AI Python SDK for Adobe Analytics

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

Prerequisites

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

Connect to Adobe Analytics 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 "Adobe Analytics" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Adobe Analytics.

   Adobe Analytics uses the OAuth authentication standard. To authenticate using OAuth, create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the "Getting Started" section of the help documentation for a guide.

   Retrieving GlobalCompanyId

   GlobalCompanyId is a required connection property. If you do not know your Global Company ID, you can find it in the request URL for the users/me endpoint on the Swagger UI. After logging into the Swagger UI Url, expand the users endpoint and then click the GET users/me button. Click the Try it out and Execute buttons. Note your Global Company ID shown in the Request URL immediately preceding the users/me endpoint.

   Retrieving Report Suite Id

   Report Suite ID (RSID) is also a required connection property. In the Adobe Analytics UI, navigate to Admin -> Report Suites and you will get a list of your report suites along with their identifiers next to the name.

   After setting the GlobalCompanyId, RSID and OAuth connection properties, you are ready to connect to Adobe Analytics.

   
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, AdobeAnalytics1).

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 Page, PageViews "
    "FROM [AdobeAnalytics1].[AdobeAnalytics].[AdsReport] "
    "LIMIT 10"
)

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

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