GymRun to Hevy

Purpose

This project provides Python scripts to convert workout data exported from the GymRun app (in CSV format) into the format used by the Strong app. This is primarily useful for users who want to import their historical GymRun data into the Hevy app, as Hevy currently supports importing data directly from Strong's CSV format but not from GymRun's.

By converting your gymrun.csv export to a Strong-compatible format, you can then use Hevy's import feature to bring your workout history across.

Files

• convert.py:

  • This is the main script for performing the conversion.
  • It reads the gymrun.csv file.
  • It reads an example strong.csv file to fetch the required headers and format.
  • It processes the GymRun data:
    • Parses dates and times, converting them from the local timezone (assumed Europe/Oslo in the script, adjust if needed) to UTC.
    • Groups exercises into workouts based on date.
    • Calculates the start time, end time, and total duration for each workout.
    • Assigns a sequential workout number.
    • Maps GymRun column names (e.g., Routine, Set, Weight) to Strong column names (e.g., Workout Name, Set Order, Weight (kg)).
    • Handles cardio/timed exercises by mapping GymRun's Duration (assumed minutes) to Strong's Seconds column and GymRun's Distance (assumed km) to Strong's Distance (meters) column.
    • Uses the exercise_mappings dictionary from mappings.py to rename exercises to match Hevy naming conventions to limit how many custom exercises are created when imported into Hevy.
    • Ensures all necessary Strong columns are present and have correct data types.
  • Outputs the converted data to a new CSV file (converted.csv) in the Strong format, ready for import into Hevy.

• mappings.py:

  • This file contains the exercise_mappings Python dictionary.
  • Crucial: You need to edit this file to define how exercise names from your GymRun export should be translated to the names used in Hevy.
  • The keys of the dictionary should be the exact exercise names from your gymrun.csv.
  • The values should be the corresponding exercise names you want in the final output (matching Hevy's exercise names is recommended to prevent custom exercises from being created).

• exercises.py:

  • This is a helper script.
  • It reads your gymrun.csv and your mappings.py.
  • It identifies which exercises listed in gymrun.csv are not yet included as keys in your exercise_mappings dictionary in mappings.py.
  • It outputs a new CSV file (unmapped.csv) containing only the rows with unmapped exercises.
  • This helps you easily see which exercises you still need to add to your mappings.py file.

• gymrun.csv:

  • An example CSV file exported from the GymRun app. Place your own export here and rename it or update the script accordingly.

• strong.csv:

  • An example CSV file showing the target format required when importing to Hevy. The convert.py script uses this file to get the correct header names and order.

• converted.csv (Generated):

  • The output file created by convert.py. This file should be suitable for importing into the Hevy app.

• unmapped.csv (Generated):

  • The output file created by exercises.py, listing exercises you still need to map.

How to Use

1. Export Data: Export your workout history from the GymRun app as a CSV file. Save it in this project directory as gymrun.csv (or update the filename in the scripts).
2. Install Libraries: Make sure you have Python 3 installed and install all required libraries:

   pip install -r requirements.txt

3. Map Exercises:
   • Run the helper script to find unmapped exercises:

     python exercises.py

   • Open the generated unmapped.csv to see which exercises need mapping.
   • Edit the mappings.py file. Add entries to the exercise_mappings dictionary for each exercise listed in the unmapped file. The key is the GymRun name, and the value is the desired Hevy name.
   • Repeat this step until exercises.py reports 0 unique unmapped exercises or you have mapped all exercises you care about.
4. Run Conversion: Execute the main conversion script:

   python convert.py

5. Import to Hevy: The script will create converted.csv. Use the import function within the Hevy app and select this generated file.

Note: Verify the timezone (Europe/Oslo) in convert.py matches your local timezone where the GymRun data was recorded. Adjust if necessary. Also, double-check the assumptions about units (minutes for Duration, km for Distance) match your GymRun export. Also double-check assumptions made about some of the exercise mappings in mappings.py.