How to Build an ETL App for Gong 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 API Driver for Python and the petl framework, you can build Gong-connected applications and pipelines for extracting, transforming, and loading Gong data. This article shows how to connect to Gong with the CData Python Connector and use petl and pandas to extract, transform, and load Gong data.

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

Connecting to Gong Data

Connecting to Gong 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.

To authenticate to Gong, you can use API Key authentication with your Gong API Key and API Secret.

Authentication

To authenticate to Gong, you must provide your Gong API Key and API Secret, along with your tenant Domain. These credentials are combined and Base64-encoded to form the Basic authentication header used for all API requests.

Using API Key Authentication

To authenticate using an API Key, you need to obtain your API Key and API Secret from your Gong account settings.

You can then connect by setting the AuthScheme to APIKey and providing your credentials:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Gong API Key.
• APISecret: Set this to your Gong API Secret.
• Domain: Set this to your Gong tenant domain (e.g., us-36533.api.gong.io).

Example connection string

Profile=C:\profiles\Gong.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;APISecret=your_api_secret;Domain=your-tenant.api.gong.io';

After installing the CData Gong Connector, follow the procedure below to install the other required modules and start accessing Gong 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 Gong 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.api as mod

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

cnxn = mod.connect("Profile=C:\profiles\Gong.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;APISecret=your_api_secret;Domain=your-tenant.api.gong.io';")

Create a SQL Statement to Query Gong

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

sql = "SELECT , FROM AnsweredScorecards WHERE = ''"

Extract, Transform, and Load the Gong Data

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

Loading Gong Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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

With the CData API Driver for Python, you can work with Gong 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 API Driver for Python to start building Python apps and scripts with connectivity to Gong 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.api as mod

cnxn = mod.connect("Profile=C:\profiles\Gong.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;APISecret=your_api_secret;Domain=your-tenant.api.gong.io';")

sql = "SELECT , FROM AnsweredScorecards WHERE = ''"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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