Mise à jour de la version applicative dans VERSION.txt.
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d20302be0e
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3 changed files with 65 additions and 85 deletions
103
home/views.py
103
home/views.py
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@ -11,6 +11,49 @@ from progression.models import Progression
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import json
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from django.http import JsonResponse
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# --------------------
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# Helpers Stats Module
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# --------------------
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def _parse_period(request, default=30, options=None):
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"""Parse period parameter 'p' from request and compute date range.
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Returns (p, now_dt, start_dt, start_date, end_date)
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- now_dt is timezone-aware now
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- start_dt is datetime at start of range (inclusive)
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- start_date/end_date are date objects for convenient filtering
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"""
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if options is None:
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options = [7, 30, 90, 180]
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try:
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p = int(request.GET.get('p', default))
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except (TypeError, ValueError):
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p = default
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if p not in options:
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p = default
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now_dt = timezone.now()
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start_dt = now_dt - timezone.timedelta(days=p - 1)
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return p, now_dt, start_dt, start_dt.date(), now_dt.date()
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def _build_series_for_range(start_date, end_date, qs, date_key='day', count_key='c'):
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"""Build a continuous daily series from an aggregated queryset.
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qs must yield dicts with date_key (date as string or date) and count_key.
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Returns (labels_days, values_counts)
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"""
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counts = {str(item[date_key]): item[count_key] for item in qs}
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days = []
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values = []
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d = start_date
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while d <= end_date:
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key = str(d)
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days.append(key)
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values.append(counts.get(key, 0))
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d += timezone.timedelta(days=1)
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return days, values
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def home(request):
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courses = Course.objects.order_by('-created_at')[:6]
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return render(request, 'home.html', {'courses': courses})
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@ -30,19 +73,13 @@ def stats_dashboard(request):
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# Période
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period_options = [7, 30, 90, 180]
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try:
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p = int(request.GET.get('p', 30))
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except ValueError:
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p = 30
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if p not in period_options:
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p = 30
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now = timezone.now()
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start_dt = now - timezone.timedelta(days=p-1) # inclut aujourd'hui
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p, now, start_dt, period_start_date, period_end_date = _parse_period(
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request, default=30, options=period_options
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)
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# Utilisateurs
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total_users = User.objects.count()
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new_users_qs = User.objects.filter(date_joined__date__gte=start_dt.date(), date_joined__date__lte=now.date())
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new_users_qs = User.objects.filter(date_joined__date__gte=period_start_date, date_joined__date__lte=period_end_date)
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# Séries quotidiennes nouveaux utilisateurs
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new_users_by_day = (
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new_users_qs
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@ -53,7 +90,7 @@ def stats_dashboard(request):
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# Activité approximée via Progression mise à jour
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active_users_qs = (
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Progression.objects.filter(updated_at__date__gte=start_dt.date(), updated_at__date__lte=now.date())
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Progression.objects.filter(updated_at__date__gte=period_start_date, updated_at__date__lte=period_end_date)
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.values('user').distinct()
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)
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active_users_count = active_users_qs.count()
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@ -62,7 +99,7 @@ def stats_dashboard(request):
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total_courses = Course.objects.count()
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total_courses_enabled = Course.objects.filter(enable=True).count()
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new_courses_by_day = (
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Course.objects.filter(created_at__date__gte=start_dt.date(), created_at__date__lte=now.date())
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Course.objects.filter(created_at__date__gte=period_start_date, created_at__date__lte=period_end_date)
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.extra(select={'day': "date(created_at)"})
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.values('day').annotate(c=Count('id'))
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)
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@ -83,7 +120,7 @@ def stats_dashboard(request):
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# Si la table M2M n'a pas de timestamps, on utilisera updated_at de Progression pour l'activité par jour
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# donc on refait une série quotidienne d'activité progression
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progress_activity_by_day = (
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Progression.objects.filter(updated_at__date__gte=start_dt.date(), updated_at__date__lte=now.date())
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Progression.objects.filter(updated_at__date__gte=period_start_date, updated_at__date__lte=period_end_date)
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.extra(select={'day': "date(updated_at)"})
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.values('day').annotate(c=Count('id'))
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)
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@ -91,7 +128,7 @@ def stats_dashboard(request):
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# Blog
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total_posts = Post.objects.count()
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new_posts_by_day = (
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Post.objects.filter(created_at__date__gte=start_dt.date(), created_at__date__lte=now.date())
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Post.objects.filter(created_at__date__gte=period_start_date, created_at__date__lte=period_end_date)
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.extra(select={'day': "date(created_at)"})
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.values('day').annotate(c=Count('id'))
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)
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@ -101,8 +138,6 @@ def stats_dashboard(request):
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technique_disponible = False
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# Visites / Trafic
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period_start_date = start_dt.date()
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period_end_date = now.date()
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period_visits = Visit.objects.filter(date__gte=period_start_date, date__lte=period_end_date)
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unique_visitors = period_visits.values('visitor_id').distinct().count()
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@ -135,16 +170,8 @@ def stats_dashboard(request):
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# Helper pour avoir toutes les dates de la période et remplir les trous
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def build_series_dict(qs, date_key='day', count_key='c'):
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counts = {str(item[date_key]): item[count_key] for item in qs}
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days = []
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values = []
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d = start_dt.date()
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while d <= now.date():
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key = str(d)
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days.append(key)
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values.append(counts.get(key, 0))
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d += timezone.timedelta(days=1)
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return days, values
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# Wrapper conservant l'API locale mais utilisant le helper commun
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return _build_series_for_range(period_start_date, period_end_date, qs, date_key=date_key, count_key=count_key)
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days_users, values_new_users = build_series_dict(new_users_by_day)
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days_courses, values_new_courses = build_series_dict(new_courses_by_day)
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@ -158,8 +185,8 @@ def stats_dashboard(request):
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context = {
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'period_options': period_options,
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'p': p,
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'start_date': start_dt.date(),
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'end_date': now.date(),
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'start_date': period_start_date,
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'end_date': period_end_date,
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# KPI
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'kpi': {
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@ -206,19 +233,11 @@ def stats_dashboard(request):
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@cache_page(60 * 15)
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def stats_charts(request):
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"""Page dédiée aux graphiques (réservée superadmins)."""
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# Période
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# Période (utilise les mêmes helpers que le dashboard pour harmonisation)
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period_options = [7, 30, 90, 180]
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try:
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p = int(request.GET.get('p', 30))
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except ValueError:
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p = 30
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if p not in period_options:
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p = 30
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now = timezone.now()
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start_dt = now - timezone.timedelta(days=p-1)
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period_start_date = start_dt.date()
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period_end_date = now.date()
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p, _now, _start_dt, period_start_date, period_end_date = _parse_period(
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request, default=30, options=period_options
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)
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# Trafic par jour (visiteurs uniques)
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visits_qs = (
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@ -255,8 +274,8 @@ def stats_charts(request):
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d += timezone.timedelta(days=1)
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return days, values
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labels, visitors_series = build_series_dict(visits_qs, date_key='date')
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_, conversions_series = build_series_dict(conversions_qs, date_key='day')
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labels, visitors_series = _build_series_for_range(period_start_date, period_end_date, visits_qs, date_key='date')
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_, conversions_series = _build_series_for_range(period_start_date, period_end_date, conversions_qs, date_key='day')
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# Sources & Pays (sur la période)
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period_visits = Visit.objects.filter(date__gte=period_start_date, date__lte=period_end_date)
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