StravaDataAnalysis

This repository extracts data from the Strava API, stores it locally (encrypted), and generates visualizations.

If other people start using this, I'll try and streamline this process as much as I can.

Generated Content

📅 Stats last updated on: 2025-05-21 04:19:20

🏃‍♂️ Most recent run: 0 years, 0 months, 1 days, 8 hours and 49 minutes

Instructions

As I'm sure is obvious, I'm teaching myself python as I go so the code quality is not likely to be great. Do with it as you wish.

1. To use, create an Application on Strava. This can be done here: https://www.strava.com/settings/api

Give it a name, a website and an 'Authorization Callback Domain'. The 'Authorization Callback Domain' should be 'local host'.

2. Copy and paste the following link into your browser, replacing {CLIENTIDHERE} with your numeric Client ID found on your Strava application settings page.

http://www.strava.com/oauth/authorize?client_id={CLIENTIDHERE}&response_type=code&redirect_uri=http://localhost/exchange_token&approval_prompt=force&scope=profile:read_all,activity:read_all

Click authorise when you visit the above link

3. You will go to a 404 not found page with a link that looks like this: -

http://localhost/exchange_token?state=&code={LONGCODEHERE}&scope=read,activity:read_all,profile:read_all

Copy the code after '&code=' to save for step 4. You will also need your client ID and client secret found on your Strava application settings page.

4. Run 'get_tokens.py'. This will create the initial tokens required for the script.

Once this has been completed, you can run 'main.py' which uses the tokens to get the data points. If the access_token has expired, it will refresh its tokens automatically during run time.