Getting Started with the CData Connect AI Python SDK for Cvent

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

Prerequisites

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

Connect to Cvent 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 "Cvent" from the Add Connection panel

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

   Before you can authenticate to Cvent, you must create a workspace and an OAuth application.

   Creating a Workspace

   To create a workspace:

   1. Sign into Cvent and navigate to App Switcher (the blue button in the upper right corner of the page) >> Admin.
   2. In the Admin menu, navigate to Integrations >> REST API.
   3. A new tab launches for Developer Management. Click on Manage API Access in the new tab.
   4. Create a Workspace and name it. Select the scopes you would like your developers to have access to. Scopes control what data domains the developer can access.
      • Choose All to allow developers to choose any scope, and any future scopes added to the REST API.
      • Choose Custom to limit the scopes developers can choose for their OAuth apps to selected scopes. To access all tables exposed by the driver, you need to set the following scopes:

        event/attendees:read	event/attendees:write	event/contacts:read
        event/contacts:write	event/custom-fields:read	event/custom-fields:write
        event/events:read	event/events:write	event/sessions:delete
        event/sessions:read	event/sessions:write	event/speakers:delete
        event/speakers:read	event/speakers:write	budget/budget-items:read
        budget/budget-items:write	exhibitor/exhibitors:read	exhibitor/exhibitors:write
        survey/surveys:read	survey/surveys:write

   Creating an OAuth Application

   After you have set up a Workspace and invited them, developers can sign up and create a custom OAuth app. See the Creating a Custom OAuth Application section in the Help documentation for more information.

   Connecting to Cvent

   After creating an OAuth application, set the following connection properties to connect to Cvent:

   • InitiateOAuth: GETANDREFRESH. Used to automatically get and refresh the OAuthAccessToken.
   • OAuthClientId: The Client ID associated with the OAuth application. You can find this on the Applications page in the Cvent Developer Portal.
   • OAuthClientSecret: The Client secret associated with the OAuth application. You can find this on the Applications page in the Cvent Developer Portal.
   
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, Cvent1).

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, Title "
    "FROM [Cvent1].[Cvent].[Events] "
    "LIMIT 10"
)

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

Write Back to Cvent

When the data source and your connection permissions allow it, the same cursor runs INSERT, UPDATE, and DELETE statements. Bind values with pyformat (%(name)s) parameters, exactly as you would for a filtered read, and check cursor.rowcount for the number of affected rows.

# Insert a new record
cur.execute(
    "INSERT INTO [Cvent1].[Cvent].[Events] (Id) "
    "VALUES (%(newvalue)s)",
    {"newvalue": "Example value"},
)
print(f"Rows inserted: {cur.rowcount}")

# Update existing records
cur.execute(
    "UPDATE [Cvent1].[Cvent].[Events] "
    "SET Title = %(newvalue)s "
    "WHERE Virtual = 'true'",
    {"newvalue": "Updated value"},
)
print(f"Rows updated: {cur.rowcount}")

conn.close()

Note: Even for writable sources, a read-only PAT or connection permission will reject write operations. The same parameterized pattern also covers DELETE statements and stored procedures through cursor.callproc().

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