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

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

Connecting to Strava Data

Connecting to Strava 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 Strava, and connect to your own data or to allow other users to connect to their data, you can use the OAuth standard.

Using OAuth Authentication

You must create a custom OAuth application to connect to Strava. To create a custom OAuth application:

1. Log into the Strava API Settings page
2. Create a new application or select an existing application
3. Set the "Authorization Callback Domain" to your callback URL domain (e.g. localhost)
4. Note down the Client ID and Client Secret

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to OAuth.
• InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
• OAuthClientId: Set this to the Client ID from your Strava API application.
• OAuthClientSecret: Set this to the Client Secret from your Strava API application.
• CallbackURL: Set this to the redirect URI matching your application's callback domain.

Example connection string:

Profile=C:\profiles\Strava.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackURL=http://localhost:33333;

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

cnxn = mod.connect("Profile=C:\profiles\Strava.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackURL=http://localhost:33333;")

Create a SQL Statement to Query Strava

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

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

Extract, Transform, and Load the Strava Data

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

Loading Strava Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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

With the CData API Driver for Python, you can work with Strava 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 Strava 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\Strava.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackURL=http://localhost:33333;")

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

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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