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Use python to extract and model your whoop data; you might just unlock a new level

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How to

Credentials

You must store credentials (username and password) in a .env file which should always be added to your .gitignore Within your .env please define credentials in the following format

USERNAME=my_email@gmail.com PASSWORD=my_password

All necessary modules have been defined in the requirements.txt file. Which can be installed via pip install -r requirements.txt

Functions

There are two types of function in this repo:

  • Data extraction
  • Data transformation & processing

Extraction is done via paginated requests made via the requests module. Currently this functions as a full load/extraction and has not been implemented in an incremental manner. Even for long term users this is a small dataset so there are no serious performance considerations here

Transformation is done via the pandas module, by default all times are measured in milliseconds and are parsed to hours or minutes depending on the context.

Whoop-Data Summary

Physiological Cycles

  • Activity is referenced in the context of a Physiological Cycle (Cycle for short).
  • Current Cycle: Only has a Start Time. Past Cycles have both start and end times.
  • A physiological day on WHOOP begins when you fall asleep one night and ends when you fall asleep the following night.

Recovery

  • Daily measure of body preparedness to perform.
  • Recovery score: Percentage between 0 - 100% calculated in the morning.
  • Calculated using previous day's data including RHR, HRV, respiratory rate, sleep quality, etc.
  • GREEN (67-100%): Well recovered and primed to perform.
  • YELLOW (34-66%): Maintaining and ready for moderate strain.
  • RED (0-33%): Indicates the need for rest.

Sleep Tracking

  • Tracks sleep duration and stages: Light, REM, and Deep sleep.
  • Calculates sleep need based on Sleep Debt and previous day's activity.

Strain

Workout Tracking

  • WHOOP tracks workouts and measures accumulated Strain over each workout.

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Use python to extract and model your whoop data; you might just unlock a new level

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