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

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

Connecting to Drift Data

Connecting to Drift 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.

Start by setting the Profile connection property to the location of the Drift Profile on disk (e.g. C:\profiles\Drift.apip). Next, set the ProfileSettings connection property to the connection string for Drift (see below).

Drift API Profile Settings

Drift uses OAuth-based authentication.

You must first register an application here: https://dev.drift.com. Your app will be assigned a client ID and a client secret. Set these in your connection string via the OAuthClientId and OAuthClientSecret properties. More information on setting up an OAuth application can be found at https://devdocs.drift.com/docs/.

After setting the following options in the ProfileSettings connection property, you are ready to connect:

• AuthScheme: Set this to OAuth.
• OAuthClientId: Set this to the Client Id that is specified in your app settings.
• OAuthClientSecret: Set this to Client Secret that is specified in your app settings.
• CallbackURL: Set this to the Redirect URI you specified in your app settings.
• InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.

After installing the CData Drift Connector, follow the procedure below to install the other required modules and start accessing Drift 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 Drift 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 Drift Connector to create a connection for working with Drift data.

cnxn = mod.connect("Profile=C:\profiles\Drift.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query Drift

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

sql = "SELECT Id, DisplayName FROM Contacts WHERE LastName = 'Stark'"

Extract, Transform, and Load the Drift Data

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

Loading Drift Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData API Driver for Python, you can work with Drift 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 Drift data. Reach out to our Support Team if you have any questions.

Full Source Code

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

cnxn = mod.connect("Profile=C:\profiles\Drift.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT Id, DisplayName FROM Contacts WHERE LastName = 'Stark'"

table1 = etl.fromdb(cnxn,sql)

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

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