117 lines
5.0 KiB
Python
117 lines
5.0 KiB
Python
from datetime import datetime
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import json
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def get_workouts(topsets):
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# Get all unique workout_ids (No duplicates)
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workout_ids = set([t['WorkoutId']
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for t in topsets if t['WorkoutId'] is not None])
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# Group topsets into workouts
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workouts = []
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for workout_id in workout_ids:
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topsets_in_workout = [
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t for t in topsets if t['WorkoutId'] == workout_id]
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workouts.append({
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'WorkoutId': workout_id,
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'StartDate': datetime.strptime(topsets_in_workout[0]['StartDate'], "%Y-%m-%d").strftime("%b %d %Y"),
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'TopSets': [{"TopSetId": t['TopSetId'], "ExerciseId": t['ExerciseId'], "ExerciseName": t['ExerciseName'], "Weight": t['Weight'], "Repetitions": t['Repetitions']} for t in topsets_in_workout]
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})
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return workouts
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def get_all_exercises_from_topsets(topsets):
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exercise_ids = set([t['ExerciseId']
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for t in topsets if t['ExerciseId'] is not None])
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exercises = []
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for exercise_id in exercise_ids:
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exercises.append({
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'ExerciseId': exercise_id,
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'ExerciseName': next((t['ExerciseName'] for t in topsets if t['ExerciseId'] == exercise_id), 'Unknown')
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})
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return exercises
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def get_rep_maxes_for_person(person_topsets):
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person_exercises = get_all_exercises_from_topsets(person_topsets)
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rep_maxes_in_exercises = []
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for e in person_exercises:
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exercise_topsets = [
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t for t in person_topsets if t['ExerciseId'] == e['ExerciseId']]
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set_reps = set([t['Repetitions'] for t in exercise_topsets])
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topsets_for_exercise = []
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for rep in set_reps:
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reps = [t for t in exercise_topsets if t['Repetitions'] == rep]
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max_weight = max([t['Weight'] for t in reps])
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max_topset_for_rep = [t for t in reps if t['Weight'] == max_weight]
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topsets_for_exercise.append({
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'StartDate': datetime.strptime(max_topset_for_rep[0]['StartDate'], "%Y-%m-%d").strftime("%b %d %Y"),
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'Repetitions': rep,
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'Weight': max_weight,
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'Estimated1RM': max_topset_for_rep[0]['Estimated1RM'],
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})
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# datetime.strptime(x['StartDate'], "%Y-%m-%d")
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topsets_for_exercise.sort(
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key=lambda x: x['Repetitions'], reverse=True)
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rep_maxes_in_exercises.append({
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'ExerciseId': e['ExerciseId'],
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'ExerciseName': e['ExerciseName'],
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'RepMaxes': topsets_for_exercise,
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'EstimatedOneRepMaxProgressions': {
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'StartDates': json.dumps([t['StartDate'] for t in exercise_topsets]),
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'TopSets': json.dumps([f"{t['Repetitions']} x {t['Weight']}kg" for t in exercise_topsets]),
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'Estimated1RMs': json.dumps([t['Estimated1RM'] for t in exercise_topsets]),
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}
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})
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return rep_maxes_in_exercises
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def get_people_and_exercise_rep_maxes(topsets):
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# Get all unique workout_ids (No duplicates)
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people_ids = set([t['PersonId'] for t in topsets])
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# Group topsets into workouts
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people = []
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for person_id in people_ids:
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workouts_for_person = [
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t for t in topsets if t['PersonId'] == person_id]
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people.append({
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'PersonId': person_id,
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'PersonName': workouts_for_person[0]['PersonName'],
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'NumberOfWorkouts': len(list(set([t['WorkoutId'] for t in workouts_for_person if t['WorkoutId'] is not None]))),
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'Exercises': get_rep_maxes_for_person(workouts_for_person)
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})
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return {"People": people, "Stats": get_stats_from_topsets(topsets)}
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def get_stats_from_topsets(topsets):
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workout_count = len(set([t['WorkoutId']
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for t in topsets if t['WorkoutId'] is not None]))
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people_count = len(set([t['PersonId']
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for t in topsets if t['PersonId'] is not None]))
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workout_start_dates = [datetime.strptime(
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t['StartDate'], '%Y-%m-%d') for t in topsets if t['StartDate'] is not None]
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stats = [{"Text": "Total Workouts", "Value": workout_count}]
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if people_count > 1:
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stats.append({"Text": "People tracked", "Value": people_count})
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if workout_count > 0:
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first_workout_date = min(workout_start_dates)
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last_workout_date = max(workout_start_dates)
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training_duration = last_workout_date - first_workout_date
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average_workouts_per_week = round(
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workout_count / (training_duration.days / 7), 2)
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stats.append({"Text": "Days Since First Workout", "Value": (
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datetime.now() - first_workout_date).days})
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stats.append({"Text": "Days Since Last Workout",
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"Value": (
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datetime.now() - last_workout_date).days})
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stats.append({"Text": "Average Workouts Per Week",
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"Value": average_workouts_per_week})
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return stats
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