How to Build an ETL App for Cvent Data in Python with CData

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Cvent and the petl framework, you can build Cvent-connected applications and pipelines for extracting, transforming, and loading Cvent data. This article shows how to connect to Cvent with the CData Python Connector and use petl and pandas to extract, transform, and load Cvent data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Cvent data in Python. When you issue complex SQL queries from Cvent, the driver pushes supported SQL operations, like filters and aggregations, directly to Cvent and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Cvent Data

Connecting to Cvent data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

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.

After installing the CData Cvent Connector, follow the procedure below to install the other required modules and start accessing Cvent through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for Cvent Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import petl as etl
import pandas as pd
import cdata.cvent as mod

You can now connect with a connection string. Use the connect function for the CData Cvent Connector to create a connection for working with Cvent data.

cnxn = mod.connect("OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;InitiateOAuth=GETANDREFRESH;")

Create a SQL Statement to Query Cvent

Use SQL to create a statement for querying Cvent. In this article, we read data from the Events entity.

sql = "SELECT Id, Title FROM Events WHERE Virtual = 'true'"

Extract, Transform, and Load the Cvent Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the Cvent data. In this example, we extract Cvent data, sort the data by the Title column, and load the data into a CSV file.

Loading Cvent Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Title')

etl.tocsv(table2,'events_data.csv')

In the following example, we add new rows to the Events table.

Adding New Rows to Cvent

table1 = [ ['Id','Title'], ['NewId1','NewTitle1'], ['NewId2','NewTitle2'], ['NewId3','NewTitle3'] ]

etl.appenddb(table1, cnxn, 'Events')

With the CData Python Connector for Cvent, you can work with Cvent data just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Cvent to start building Python apps and scripts with connectivity to Cvent data. Reach out to our Support Team if you have any questions.

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Full Source Code

import petl as etl
import pandas as pd
import cdata.cvent as mod

cnxn = mod.connect("OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;InitiateOAuth=GETANDREFRESH;")

sql = "SELECT Id, Title FROM Events WHERE Virtual = 'true'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Title')

etl.tocsv(table2,'events_data.csv')

table3 = [ ['Id','Title'], ['NewId1','NewTitle1'], ['NewId2','NewTitle2'], ['NewId3','NewTitle3'] ]

etl.appenddb(table3, cnxn, 'Events')