Dovodi_Backend/apps/api/views/professor_dashboard.py

from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.permissions import IsAuthenticated
from rest_framework.authentication import TokenAuthentication
from django.utils import timezone
from datetime import timedelta
from django.db.models import Count, Q
from django.db.models.functions import TruncDate

from apps.account.models import User
from apps.course.models import Course, Participant
from apps.course.models.course import extract_text_from_json
from apps.quiz.models import Quiz, QuizParticipant
from apps.chat.models import ChatMessage, RoomMessage
from apps.api.permissions import IsProfessorUser


class ProfessorDashboardStatsView(APIView):
    authentication_classes = [TokenAuthentication]
    permission_classes = [IsAuthenticated, IsProfessorUser]

    def get(self, request):
        now = timezone.now()
        thirty_days_ago = now - timedelta(days=30)

        # ---------------------------------------------------------
        # 1. CARDS & BASIC STATS
        # ---------------------------------------------------------
        # Total courses taught by this professor
        courses_count = Course.objects.filter(professor=request.user).count()

        # Total unique active students enrolled in this professor's courses
        students_count = Participant.objects.filter(
            course__professor=request.user,
            is_active=True
        ).values('student').distinct().count()

        # Total quizzes created in this professor's courses
        quizzes_count = Quiz.objects.filter(course__professor=request.user).count()

        # Chat rooms count (group rooms for professor's courses + private chats with professor)
        chat_rooms_count = RoomMessage.objects.filter(
            Q(course__professor=request.user) |
            (Q(room_type=RoomMessage.RoomTypeChoices.PRIVATE) & (Q(initiator=request.user) | Q(recipient=request.user)))
        ).distinct().count()

        # ---------------------------------------------------------
        # 2. CHARTS DATA
        # ---------------------------------------------------------
        # Chat Volume Trend (30 days)
        professor_rooms = RoomMessage.objects.filter(
            Q(course__professor=request.user) |
            (Q(room_type=RoomMessage.RoomTypeChoices.PRIVATE) & (Q(initiator=request.user) | Q(recipient=request.user)))
        )
        chat_volume = ChatMessage.objects.filter(
            room__in=professor_rooms,
            sent_at__gte=thirty_days_ago
        ).annotate(
            date=TruncDate('sent_at')
        ).values('date').annotate(count=Count('id')).order_by('date')
        
        chat_chart = [{"date": item['date'].strftime('%Y-%m-%d'), "messages": item['count']} for item in chat_volume]

        # Course Efficacy: Completed vs Enrolled (Bar Chart for Top 5 Courses)
        top_courses_qs = Course.objects.filter(professor=request.user).annotate(
            participant_count=Count('participants')
        ).order_by('-participant_count')[:5]

        course_efficacy = []
        for course in top_courses_qs:
            enrolled = course.participant_count
            completed = Participant.objects.filter(
                course=course,
                student__lesson_completions__course_lesson__course=course
            ).distinct().count()
            title_text = extract_text_from_json(course.title)
            course_efficacy.append({
                "title": title_text[:20] + "..." if len(title_text) > 20 else title_text,
                "enrolled": enrolled,
                "completed": completed
            })

        # Quiz Participation statistics (all quizzes of the professor)
        quizzes = Quiz.objects.filter(course__professor=request.user)
        quizzes_stats = []
        for quiz in quizzes:
            course = quiz.course
            if not course:
                continue
            total_enrolled = Participant.objects.filter(course=course, is_active=True).count()
            participated = QuizParticipant.objects.filter(quiz=quiz).values('user').distinct().count()
            not_participated = max(0, total_enrolled - participated)
            quizzes_stats.append({
                "id": quiz.id,
                "title": quiz.title,
                "course_title": extract_text_from_json(course.title),
                "participated": participated,
                "not_participated": not_participated,
            })

        # ---------------------------------------------------------
        # 3. LISTS & LEADERBOARDS
        # ---------------------------------------------------------
        # Top Courses List
        top_courses_list = [
            {
                "id": c.id,
                "title": extract_text_from_json(c.title),
                "participants": c.participant_count
            } for c in top_courses_qs
        ]

        # Leaderboard (Top 5 Performing Students in professor's quizzes)
        top_students = QuizParticipant.objects.filter(
            quiz__course__professor=request.user
        ).select_related('user').order_by('-total_score', 'total_timing')[:5]
        
        leaderboard = [
            {"id": s.user.id, "name": s.user.fullname, "score": s.total_score, "time": s.total_timing}
            for s in top_students
        ]

        return Response({
            "cards": {
                "courses_count": courses_count,
                "students_count": students_count,
                "quizzes_count": quizzes_count,
                "chat_rooms_count": chat_rooms_count,
            },
            "charts": {
                "chat_volume": chat_chart,
                "course_efficacy": course_efficacy,
                "quizzes_stats": quizzes_stats
            },
            "lists": {
                "top_courses": top_courses_list,
                "leaderboard": leaderboard
            }
        })