Refactor calendar (month and year view), switching to vertical slice arch. Also in progress of refactoring of stats so they are retreived after inital page load for performance sake
This commit is contained in:
Peter Stockings
141
features/calendar.py
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141
features/calendar.py
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from datetime import datetime, timedelta
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from dateutil.relativedelta import relativedelta
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import pandas as pd
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class Calendar:
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def __init__(self, db_connection_method):
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self.execute = db_connection_method
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def fetch_workouts_for_person(self, person_id, date, view):
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prev_date, next_date = None, None
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if view == 'month':
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first_day_of_month = date.replace(day=1)
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days_to_subtract = (first_day_of_month.weekday() + 1) % 7
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start_date = first_day_of_month - timedelta(days=days_to_subtract)
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end_date = start_date + timedelta(days=6 * 7 - 1)
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prev_date = first_day_of_month - relativedelta(months=1)
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next_date = first_day_of_month + relativedelta(months=1)
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elif view == 'year':
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start_date = date.replace(month=1, day=1)
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end_date = date.replace(year=date.year + 1, month=1, day=1) - timedelta(days=1)
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prev_date = date - relativedelta(years=1)
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next_date = date + relativedelta(years=1)
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else:
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raise ValueError('Invalid view')
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query = """
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SELECT
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w.workout_id,
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w.start_date,
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t.topset_id,
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t.repetitions,
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t.weight,
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e.name AS exercise_name,
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p.name AS person_name
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FROM
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person p
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LEFT JOIN workout w ON p.person_id = w.person_id AND w.start_date BETWEEN %s AND %s
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LEFT JOIN topset t ON w.workout_id = t.workout_id
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LEFT JOIN exercise e ON t.exercise_id = e.exercise_id
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WHERE
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p.person_id = %s
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ORDER BY
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w.start_date,
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t.topset_id;
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"""
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workouts_data = self.execute(query, [start_date, end_date, person_id])
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# Assuming person_name is the same for all rows as we filter by person_id
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person_name = workouts_data[0]['person_name'] if workouts_data else 'Unknown'
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calendar_view = {'prev_date': prev_date, 'next_date': next_date, 'person_id': person_id, 'person_name': person_name, 'view': view, 'date': date}
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if view == 'month':
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calendar_view['days'] = []
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workouts_by_date = {}
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for row in workouts_data:
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if row['workout_id'] is None:
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continue # Skip rows that don't have workout data
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workout_date_str = row['start_date'].strftime("%Y-%m-%d")
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workout_id = row['workout_id']
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if workout_date_str not in workouts_by_date:
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workouts_by_date[workout_date_str] = {}
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if workout_id not in workouts_by_date[workout_date_str]:
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workouts_by_date[workout_date_str][workout_id] = {
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'workout_id': workout_id,
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'start_date': row['start_date'],
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'sets': []
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}
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workouts_by_date[workout_date_str][workout_id]['sets'].append({
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'repetitions': row['repetitions'],
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'weight': row['weight'],
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'exercise_name': row['exercise_name']
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})
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for current_date in pd.date_range(start_date, end_date, freq='D'):
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date_str = current_date.strftime("%Y-%m-%d")
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day_workouts = workouts_by_date.get(date_str, {})
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today = datetime.today().date()
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calendar_view['days'].append({
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'day': current_date.day,
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'is_today': current_date == today,
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'is_in_current_month': current_date.month == date.month, # Ensure it compares with the selected month
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'has_workouts': len(day_workouts) > 0,
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'workouts': list(day_workouts.values())
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})
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elif view == 'year':
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calendar_view['months'] = []
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workouts_by_date = {}
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for row in workouts_data:
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if row['start_date'] is None:
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continue # Skip rows that don't have workout data
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workout_date_str = row['start_date'].strftime("%Y-%m-%d")
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if workout_date_str not in workouts_by_date:
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workouts_by_date[workout_date_str] = []
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workouts_by_date[workout_date_str].append({
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'workout_id': row['workout_id'],
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'start_date': row['start_date'],
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'topset_id': row['topset_id'],
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'repetitions': row['repetitions'],
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'weight': row['weight'],
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'exercise_name': row['exercise_name']
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})
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for month in range(1, 13):
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first_day_of_month = date.replace(month=month, day=1)
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days_to_subtract = (first_day_of_month.weekday() + 1) % 7
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start_date = first_day_of_month - timedelta(days=days_to_subtract)
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end_date = start_date + timedelta(days=6 * 7 - 1)
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month_data = {'name': first_day_of_month.strftime('%B'), 'first_day_of_month': first_day_of_month, 'days': []}
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current_day = start_date
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while current_day <= end_date:
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day_workouts = workouts_by_date.get(current_day.strftime('%Y-%m-%d'), [])
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has_workouts = len(day_workouts) > 0
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first_workout_id = day_workouts[0]['workout_id'] if has_workouts else None
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day_data = {
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'day': current_day.day,
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'is_today': current_day == datetime.today().date(),
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'is_in_current_month': current_day.month == month,
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'workouts': day_workouts,
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'has_workouts': has_workouts,
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'first_workout_id': first_workout_id
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}
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month_data['days'].append(day_data)
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current_day += timedelta(days=1)
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calendar_view['months'].append(month_data)
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return calendar_view
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85
features/stats.py
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85
features/stats.py
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@@ -0,0 +1,85 @@
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from collections import Counter
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from datetime import date
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class Stats:
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def __init__(self, db_connection_method):
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self.execute = db_connection_method
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def get_stats_from_topsets(self, topsets):
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if not topsets:
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return []
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# Extracting necessary fields
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workout_ids = [t['WorkoutId'] for t in topsets if t['WorkoutId']]
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person_ids = [t['PersonId'] for t in topsets if t['PersonId']]
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start_dates = [t['StartDate'] for t in topsets if t['StartDate']]
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workout_count = len(set(workout_ids))
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people_count = len(set(person_ids))
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total_sets = len(topsets)
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stats = [
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{"Text": "Total Workouts", "Value": workout_count},
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{"Text": "Total Sets", "Value": total_sets}
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]
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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(start_dates)
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last_workout_date = max(start_dates)
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current_date = date.today()
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stats.append({"Text": "Days Since First Workout",
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"Value": (current_date - first_workout_date).days})
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if workout_count >= 2:
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stats.append({"Text": "Days Since Last Workout",
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"Value": (current_date - last_workout_date).days})
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average_sets_per_workout = round(total_sets / workout_count, 1)
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stats.append({"Text": "Average sets per workout",
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"Value": average_sets_per_workout})
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training_duration = last_workout_date - first_workout_date
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if training_duration.days > 0:
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average_workouts_per_week = round(
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workout_count / (training_duration.days / 7), 1)
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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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def fetch_stats_for_person(self, person_id):
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query = """
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SELECT
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t.workout_id AS "WorkoutId",
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w.person_id AS "PersonId",
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w.start_date AS "StartDate"
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FROM
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topset t
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JOIN workout w ON t.workout_id = w.workout_id
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JOIN person p ON w.person_id = p.person_id
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WHERE p.person_id = %s
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"""
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workouts_data = self.execute(query, [person_id])
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person_stats = self.get_stats_from_topsets(workouts_data)
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return person_stats
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def fetch_all_stats(self):
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query = """
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SELECT
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t.workout_id AS "WorkoutId",
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w.person_id AS "PersonId",
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w.start_date AS "StartDate"
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FROM
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topset t
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JOIN workout w ON t.workout_id = w.workout_id
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JOIN person p ON w.person_id = p.person_id;
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"""
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workouts_data = self.execute(query, [])
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person_stats = self.get_stats_from_topsets(workouts_data)
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return person_stats
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