Add more stats

features/stats.py

@@ -1,29 +1,61 @@
-from collections import Counter
+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 []
 
-        # Extracting 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']]
+        # 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 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})
+            stats.append({"Text": "People Tracked", "Value": people_count})
 
         if workout_count > 0:
             first_workout_date = min(start_dates)
@@ -31,53 +63,56 @@ class Stats:
             current_date = date.today()
 
             stats.append({"Text": "Days Since First Workout",
-                        "Value": (current_date - first_workout_date).days})
+                          "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})
+                              "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})
+                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})
+                                  "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"
+            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"
+            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 person p ON w.person_id = p.person_id
+            JOIN exercise e ON t.exercise_id = e.exercise_id
         """
         workouts_data = self.execute(query, [])