Analyze your Whoop workouts with Python

This code can be used to extract all workouts using the Whoop API.

Credits: The whoop.py file with the Whoop API Client implementation was simply copied from https://github.com/hedgertronic/whoop/.

Example Output

Number of workouts in 2023: 279
Total kcal: 100562.94 kcal
Average kcal: 360.44 kcal
Total duration: 169h 42m 2s (7 days, 1:42:02)
Average duration: 0:36:29
Top 3 activities:
Running: 164
Functional Fitness: 58
Yoga: 42

Step 1: Installation

pip install -r requirements.txt

The only dependencies listed in there are Authlib and requests.

Step 2: Get Workouts

Set the following variables in get_workouts.py:

• username: Your Whoop email/username
• password: Your Whoop password
• start_date: The day until it should collect the workouts

Then run

python get_workouts.py

This will collect the workouts from today until the specified start date and dumps it to a file called workouts.json.

Step 3: Analyze Workouts

Run

python analyze_workouts.py

This loads the JSON file and prints the stats for 2023.

Note: The current logic filters for 2023 workouts and ignores activities categorized as Unknown, MISC, and Walking. If you want to modify this logic, change the code in the filter_workouts() function.

How to identify the activity from the Whoop sport_id

Whoop specifies a sport_id for each workout. I compared these numbers with my workouts to identify the corresponding activity.

So far I've converted the following sport_id values to workout names:

SPORT_ID_TO_NAME = {
    0: "Running",
    1: "Bicycle",
    33: "Swimming",
    96: "HIIT",
    71: "MISC",
    43: "Pilates",
    44: "Yoga",
    48: "Functional Fitness",
    52: "Hiking",
    -1: "Unknown Activity",
    63: "Walking",
}