Strava Data Integration

Overview

This project demonstrates the process of integrating Strava API data into a Snowflake data warehouse using dbt (Data Build Tool) and Airflow.

By following this project, you can learn how to collect and analyze your Strava fitness data in a structured and automated way.

Here a example dashboard with this data

Prerequisites

For run this project you will need Docker Compose

Strava API Integration

Sign up for a Strava Developer Account (https://developers.strava.com/).

Create a new OAuth Application on the Strava Developer Dashboard and obtain your client_id and client_secret.

Create a strava refresh token

SnowFlake Warehouse

You will needs a snowflake project, with the following structure

SNOWFLAKE_SCHEMA = 'STRAVA'
SNOWFLAKE_WAREHOUSE = 'transforming'    
SNOWFLAKE_DATABASE = 'analytics'

In airflow create a connection called snowflake_default

Setup

Clone this repository to your local machine:

   git clone https://github.com/yourusername/strava-data-integration.git

Setup your strava keys, snowflake account and airflow local authentication on the .env file, like this:

#Airflow configuration setup

AIRFLOW_UID=1000
AIRFLOW_USER=admin
AIRFLOW_PASS=admin

#strava
STRAVA_CLIENT_ID=
STRAVA_CLIENT_SECRET=
STRAVA_REFRESH_TOKEN=

#Snowflake
SNOWFLAKE_ACCOUNT=


#Tags of images
REDIS_TAG=7.0.0
POSTGRES_TAG=13
MINIO_TAG=RELEASE.2021-10-23T03-28-24Z
MC_TAG=RELEASE.2021-11-05T10-05-06Z

Usage

Create the docker image running

 docker compose up

A docker instance will run on

localhost:8080

You will see two dags, when you run create_raw_tables, airflow will get data from your strava account, transform it and send to Snowflake.

The final snowflake table will be in:

analytics.strava."ACTIVITIES"

Contributing

Contributions are welcome! If you'd like to enhance this project, feel free to fork it and submit a pull request.