partirdezero/home/views.py

356 lines
13 KiB
Python

from django.shortcuts import render, get_object_or_404
from django.contrib.auth.decorators import user_passes_test
from django.utils import timezone
from django.db.models import Count
from core.models import Visit
from django.views.decorators.cache import cache_page
from django.contrib.auth.models import User
from courses.models import Course, Lesson
from blog.models import Post
from progression.models import Progression
import json
from django.http import JsonResponse
# --------------------
# Helpers Stats Module
# --------------------
def _parse_period(request, default=30, options=None):
"""Parse period parameter 'p' from request and compute date range.
Returns (p, now_dt, start_dt, start_date, end_date)
- now_dt is timezone-aware now
- start_dt is datetime at start of range (inclusive)
- start_date/end_date are date objects for convenient filtering
"""
if options is None:
options = [7, 30, 90, 180]
try:
p = int(request.GET.get('p', default))
except (TypeError, ValueError):
p = default
if p not in options:
p = default
now_dt = timezone.now()
start_dt = now_dt - timezone.timedelta(days=p - 1)
return p, now_dt, start_dt, start_dt.date(), now_dt.date()
def _build_series_for_range(start_date, end_date, qs, date_key='day', count_key='c'):
"""Build a continuous daily series from an aggregated queryset.
qs must yield dicts with date_key (date as string or date) and count_key.
Returns (labels_days, values_counts)
"""
counts = {str(item[date_key]): item[count_key] for item in qs}
days = []
values = []
d = start_date
while d <= end_date:
key = str(d)
days.append(key)
values.append(counts.get(key, 0))
d += timezone.timedelta(days=1)
return days, values
def home(request):
courses = Course.objects.order_by('-created_at')[:6]
return render(request, 'home.html', {'courses': courses})
def premium(request, course_id):
"""Landing page présentant les avantages du Premium."""
course = get_object_or_404(Course, pk=course_id)
return render(request, 'premium.html', {'course': course})
# 15 minutes de cache sur la page complète (sauf si décochée plus tard pour des blocs en direct)
@user_passes_test(lambda u: u.is_superuser)
@cache_page(60 * 15)
def stats_dashboard(request):
""" Tableau de bord statistiques réservé aux superadministrateurs.
Périodes supportées: 7, 30, 90, 180 jours (GET param 'p'). """
# Période
period_options = [7, 30, 90, 180]
p, now, start_dt, period_start_date, period_end_date = _parse_period(
request, default=30, options=period_options
)
# Utilisateurs
total_users = User.objects.count()
new_users_qs = User.objects.filter(date_joined__date__gte=period_start_date, date_joined__date__lte=period_end_date)
# Séries quotidiennes nouveaux utilisateurs
new_users_by_day = (
new_users_qs
.extra(select={'day': "date(date_joined)"})
.values('day')
.annotate(c=Count('id'))
)
# Activité approximée via Progression mise à jour
active_users_qs = (
Progression.objects.filter(updated_at__date__gte=period_start_date, updated_at__date__lte=period_end_date)
.values('user').distinct()
)
active_users_count = active_users_qs.count()
# Cours
total_courses = Course.objects.count()
total_courses_enabled = Course.objects.filter(enable=True).count()
new_courses_by_day = (
Course.objects.filter(created_at__date__gte=period_start_date, created_at__date__lte=period_end_date)
.extra(select={'day': "date(created_at)"})
.values('day').annotate(c=Count('id'))
)
# Leçons
total_lessons = Lesson.objects.count()
# Achèvements de leçons (via table de liaison M2M)
through = Progression.completed_lessons.through
lesson_completions_by_day = (
through.objects.filter(
progression__updated_at__date__gte=start_dt.date(),
progression__updated_at__date__lte=now.date(),
)
.extra(select={'day': "date(progression_updated_at)"}) if 'progression_updated_at' in [f.name for f in through._meta.fields]
else through.objects.extra(select={'day': "date(created_at)"}) # fallback si champs créé n'existe pas
)
# Si la table M2M n'a pas de timestamps, on utilisera updated_at de Progression pour l'activité par jour
# donc on refait une série quotidienne d'activité progression
progress_activity_by_day = (
Progression.objects.filter(updated_at__date__gte=period_start_date, updated_at__date__lte=period_end_date)
.extra(select={'day': "date(updated_at)"})
.values('day').annotate(c=Count('id'))
)
# Blog
total_posts = Post.objects.count()
new_posts_by_day = (
Post.objects.filter(created_at__date__gte=period_start_date, created_at__date__lte=period_end_date)
.extra(select={'day': "date(created_at)"})
.values('day').annotate(c=Count('id'))
)
# Revenus/Paiements & Technique (placeholders faute de sources)
revenus_disponibles = False
technique_disponible = False
# Visites / Trafic
period_visits = Visit.objects.filter(date__gte=period_start_date, date__lte=period_end_date)
unique_visitors = period_visits.values('visitor_id').distinct().count()
earlier_visitors_qs = Visit.objects.filter(date__lt=period_start_date).values('visitor_id').distinct()
returning_visitors = period_visits.filter(visitor_id__in=earlier_visitors_qs).values('visitor_id').distinct().count()
converted_visitors = (
period_visits
.filter(became_user_at__isnull=False, became_user_at__date__gte=period_start_date, became_user_at__date__lte=period_end_date)
.values('visitor_id').distinct().count()
)
top_sources_qs = (
period_visits
.values('source')
.annotate(c=Count('visitor_id', distinct=True))
.order_by('-c')
)
top_countries_qs = (
period_visits
.exclude(country='')
.values('country')
.annotate(c=Count('visitor_id', distinct=True))
.order_by('-c')
)
top_sources_table = [(row['source'] or 'Direct/Unknown', row['c']) for row in top_sources_qs[:10]]
top_countries_table = [(row['country'], row['c']) for row in top_countries_qs[:10]]
# Helper pour avoir toutes les dates de la période et remplir les trous
def build_series_dict(qs, date_key='day', count_key='c'):
# Wrapper conservant l'API locale mais utilisant le helper commun
return _build_series_for_range(period_start_date, period_end_date, qs, date_key=date_key, count_key=count_key)
days_users, values_new_users = build_series_dict(new_users_by_day)
days_courses, values_new_courses = build_series_dict(new_courses_by_day)
days_posts, values_new_posts = build_series_dict(new_posts_by_day)
days_activity, values_activity = build_series_dict(progress_activity_by_day)
# Tables simples (jour, valeur)
new_users_table = list(zip(days_users, values_new_users))
new_courses_table = list(zip(days_courses, values_new_courses))
context = {
'period_options': period_options,
'p': p,
'start_date': period_start_date,
'end_date': period_end_date,
# KPI
'kpi': {
'total_users': total_users,
'new_users_period': sum(values_new_users),
'active_users_period': active_users_count,
'unique_visitors': unique_visitors,
'returning_visitors': returning_visitors,
'converted_visitors': converted_visitors,
'total_courses': total_courses,
'courses_enabled': total_courses_enabled,
'total_lessons': total_lessons,
'total_posts': total_posts,
},
# Séries pour graphiques
'series': {
'days': days_users, # mêmes intervalles pour tous
'new_users': values_new_users,
'new_courses': values_new_courses,
'new_posts': values_new_posts,
'activity_progress': values_activity,
},
# Disponibilité des sections
'revenus_disponibles': revenus_disponibles,
'technique_disponible': technique_disponible,
# Tables
'new_users_table': new_users_table,
'new_courses_table': new_courses_table,
'top_sources_table': top_sources_table,
'top_countries_table': top_countries_table,
}
# Sérialisation JSON pour Chart.js
context['series_json'] = json.dumps(context['series'])
context['labels_json'] = json.dumps(context['series']['days'])
return render(request, 'home/stats_dashboard.html', context)
@user_passes_test(lambda u: u.is_superuser)
@cache_page(60 * 15)
def stats_charts(request):
"""Page dédiée aux graphiques (réservée superadmins)."""
# Période (utilise les mêmes helpers que le dashboard pour harmonisation)
period_options = [7, 30, 90, 180]
p, _now, _start_dt, period_start_date, period_end_date = _parse_period(
request, default=30, options=period_options
)
# Trafic par jour (visiteurs uniques)
visits_qs = (
Visit.objects
.filter(date__gte=period_start_date, date__lte=period_end_date)
.values('date')
.annotate(c=Count('visitor_id', distinct=True))
.order_by('date')
)
# Conversions par jour (visiteurs devenus utilisateurs)
conversions_qs = (
Visit.objects
.filter(
became_user_at__isnull=False,
became_user_at__date__gte=period_start_date,
became_user_at__date__lte=period_end_date,
)
.extra(select={'day': "date(became_user_at)"})
.values('day')
.annotate(c=Count('visitor_id', distinct=True))
.order_by('day')
)
def build_series_dict(qs, date_key='date', count_key='c'):
counts = {str(item[date_key]): item[count_key] for item in qs}
days = []
values = []
d = period_start_date
while d <= period_end_date:
key = str(d)
days.append(key)
values.append(counts.get(key, 0))
d += timezone.timedelta(days=1)
return days, values
labels, visitors_series = _build_series_for_range(period_start_date, period_end_date, visits_qs, date_key='date')
_, conversions_series = _build_series_for_range(period_start_date, period_end_date, conversions_qs, date_key='day')
# Sources & Pays (sur la période)
period_visits = Visit.objects.filter(date__gte=period_start_date, date__lte=period_end_date)
top_sources_qs = (
period_visits
.values('source')
.annotate(c=Count('visitor_id', distinct=True))
.order_by('-c')[:10]
)
top_countries_qs = (
period_visits
.exclude(country='')
.values('country')
.annotate(c=Count('visitor_id', distinct=True))
.order_by('-c')[:10]
)
sources_labels = [(row['source'] or 'Direct/Unknown') for row in top_sources_qs]
sources_values = [row['c'] for row in top_sources_qs]
countries_labels = [row['country'] for row in top_countries_qs]
countries_values = [row['c'] for row in top_countries_qs]
context = {
'period_options': period_options,
'p': p,
'start_date': period_start_date,
'end_date': period_end_date,
'labels_json': json.dumps(labels),
'visitors_series_json': json.dumps(visitors_series),
'conversions_series_json': json.dumps(conversions_series),
'sources_labels_json': json.dumps(sources_labels),
'sources_values_json': json.dumps(sources_values),
'countries_labels_json': json.dumps(countries_labels),
'countries_values_json': json.dumps(countries_values),
}
return render(request, 'home/stats_charts.html', context)
@user_passes_test(lambda u: u.is_superuser)
def live_activity(request):
"""Retourne en JSON l'activité récente (5 dernières minutes):
visiteurs et utilisateurs et leur page actuelle.
"""
now = timezone.now()
since = now - timezone.timedelta(minutes=5)
qs = (
Visit.objects
.filter(last_seen__gte=since)
.order_by('-last_seen')
)
data = []
for v in qs[:200]:
username = None
is_user = False
if v.user_id:
is_user = True
# safe access if user deleted
try:
username = v.user.username
except Exception:
username = 'Utilisateur'
visitor_label = v.visitor_id[:8]
seconds_ago = int((now - v.last_seen).total_seconds())
data.append({
'visitor': visitor_label,
'is_user': is_user,
'username': username,
'path': v.path,
'last_seen': v.last_seen.isoformat(),
'seconds_ago': seconds_ago,
'date': str(v.date),
'country': v.country,
'source': v.source,
})
return JsonResponse({'now': now.isoformat(), 'items': data})