Remove unused duplicated stats logic for dashboard

db.py

@@ -13,7 +13,7 @@ from features.person_overview import PersonOverview
 from features.stats import Stats
 from features.workout import Workout
 from features.sql_explorer import SQLExplorer
-from utils import count_prs_over_time, get_all_exercises_from_topsets, get_exercise_graph_model, get_stats_from_topsets, get_topsets_for_person, get_weekly_pr_graph_model, get_workout_counts, get_workouts
+from utils import count_prs_over_time, get_all_exercises_from_topsets, get_exercise_graph_model, get_topsets_for_person, get_weekly_pr_graph_model, get_workout_counts, get_workouts
 
 
 class DataBase():
@@ -214,7 +214,6 @@ class DataBase():
         return {
             'PersonId': next((t['PersonId'] for t in topsets), -1),
             'PersonName': next((t['PersonName'] for t in topsets), 'Unknown'),
-            'Stats': get_stats_from_topsets(topsets),
             'Exercises': get_all_exercises_from_topsets(topsets),
             'Workouts': get_workouts(topsets),
             'ExerciseProgressGraphs': get_topsets_for_person(topsets),

utils.py

@@ -115,56 +115,7 @@ def get_people_and_exercise_rep_maxes(topsets, selected_person_ids, selected_exe
             'Exercises': get_topsets_for_person(person_topsets)
         })
 
-    return {"People": people, "Stats": get_stats_from_topsets(topsets)}
+    return {"People": people}
-
-
-
-def get_stats_from_topsets(topsets):
-    workout_count = len(set([t['WorkoutId']
-                             for t in topsets if t['WorkoutId'] is not None]))
-    people_count = len(set([t['PersonId']
-                            for t in topsets if t['PersonId'] is not None]))
-    exercise_count = len(set([t['ExerciseId']
-                            for t in topsets if t['ExerciseId'] is not None]))
-    workout_start_dates = [t['StartDate']
-                           for t in topsets if t['StartDate'] is not None]
-
-    stats = [{"Text": "Total Workouts", "Value": workout_count},
-             {"Text": "Total Sets", "Value": len(topsets)},
-             {"Text": "Total Exercises", "Value": exercise_count}]
-    if people_count > 1:
-        stats.append({"Text": "People tracked", "Value": people_count})
-    if workout_count > 0:
-        first_workout_date = min(workout_start_dates)
-        last_workout_date = max(workout_start_dates)
-
-        stats.append({"Text": "Days Since First Workout", "Value": (
-            date.today() - first_workout_date).days})
-        if workout_count >= 2:
-            stats.append({"Text": "Days Since Last Workout",
-                          "Value": (
-                              date.today() - last_workout_date).days})
-            average_number_sets_per_workout = round(
-                len(topsets) / workout_count, 1)
-            stats.append({"Text": "Average sets per workout",
-                         "Value": average_number_sets_per_workout})
-            
-            # Average exercises per workout
-            average_exercises_per_workout = round(exercise_count / workout_count, 1)
-            stats.append({"Text": "Average Exercises Per Workout", "Value": average_exercises_per_workout})
-
-            training_duration = last_workout_date - first_workout_date
-            if training_duration > timedelta(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})
-            
-            # Average sets per exercise
-            average_sets_per_exercise = round(len(topsets) / exercise_count, 1) if exercise_count > 0 else 0
-            stats.append({"Text": "Average Sets Per Exercise", "Value": average_sets_per_exercise})
-
-    return stats
 
 
 def convert_str_to_date(date_str, format='%Y-%m-%d'):