from collections import defaultdict from datetime import date class Stats: def __init__(self, db_connection_method): self.execute = db_connection_method def get_stats_from_topsets(self, topsets): if not topsets: return [] # Extract necessary fields workout_ids = [t["WorkoutId"] for t in topsets if t["WorkoutId"]] person_ids = [t["PersonId"] for t in topsets if t["PersonId"]] start_dates = [t["StartDate"] for t in topsets if t["StartDate"]] exercise_ids = [t["ExerciseId"] for t in topsets if t["ExerciseId"]] workout_count = len(set(workout_ids)) people_count = len(set(person_ids)) total_sets = len(topsets) exercise_count = len(set(exercise_ids)) # Group sets by workout and exercise sets_per_exercise_per_workout = defaultdict(lambda: defaultdict(int)) for t in topsets: if t["WorkoutId"] and t["ExerciseId"]: sets_per_exercise_per_workout[t["WorkoutId"]][t["ExerciseId"]] += 1 # Calculate the average sets per exercise across all workouts total_sets_per_exercise = [] for workout_exercises in sets_per_exercise_per_workout.values(): total_sets_per_exercise.extend(workout_exercises.values()) average_sets_per_exercise = round(sum(total_sets_per_exercise) / len(total_sets_per_exercise), 1) if total_sets_per_exercise else 0 # Group exercises by workout exercises_by_workout = defaultdict(set) for t in topsets: if t["WorkoutId"] and t["ExerciseId"]: exercises_by_workout[t["WorkoutId"]].add(t["ExerciseId"]) # Calculate average exercises per workout average_exercises_per_workout = round( sum(len(exercises) for exercises in exercises_by_workout.values()) / workout_count, 1 ) if workout_count > 0 else 0 # Stats stats = [ {"Text": "Total Workouts", "Value": workout_count}, {"Text": "Total Sets", "Value": total_sets}, {"Text": "Total Exercises", "Value": exercise_count}, {"Text": "Average Sets Per Exercise", "Value": average_sets_per_exercise}, {"Text": "Average Exercises Per Workout", "Value": average_exercises_per_workout}, ] if people_count > 1: stats.append({"Text": "People Tracked", "Value": people_count}) if workout_count > 0: first_workout_date = min(start_dates) last_workout_date = max(start_dates) current_date = date.today() stats.append({"Text": "Days Since First Workout", "Value": (current_date - first_workout_date).days}) if workout_count >= 2: stats.append({"Text": "Days Since Last Workout", "Value": (current_date - last_workout_date).days}) average_sets_per_workout = round(total_sets / workout_count, 1) stats.append({"Text": "Average Sets Per Workout", "Value": average_sets_per_workout}) training_duration = last_workout_date - first_workout_date if training_duration.days > 0: average_workouts_per_week = round( workout_count / (training_duration.days / 7), 1) stats.append({"Text": "Average Workouts Per Week", "Value": average_workouts_per_week}) return stats def fetch_stats_for_person(self, person_id): query = """ SELECT t.workout_id AS "WorkoutId", w.person_id AS "PersonId", w.start_date AS "StartDate", e.exercise_id AS "ExerciseId" FROM topset t JOIN workout w ON t.workout_id = w.workout_id JOIN person p ON w.person_id = p.person_id JOIN exercise e ON t.exercise_id = e.exercise_id WHERE p.person_id = %s """ workouts_data = self.execute(query, [person_id]) person_stats = self.get_stats_from_topsets(workouts_data) return person_stats def fetch_all_stats(self): query = """ SELECT t.workout_id AS "WorkoutId", w.person_id AS "PersonId", w.start_date AS "StartDate", e.exercise_id AS "ExerciseId" FROM topset t JOIN workout w ON t.workout_id = w.workout_id JOIN person p ON w.person_id = p.person_id JOIN exercise e ON t.exercise_id = e.exercise_id """ workouts_data = self.execute(query, []) person_stats = self.get_stats_from_topsets(workouts_data) return person_stats