318 lines
13 KiB
Python
318 lines
13 KiB
Python
from sqlmodel import Session, create_engine, select
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from uuid import uuid4, UUID
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from datetime import datetime, timedelta, date
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import os
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import json
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import glob
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from database import engine, init_db
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import models
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import bcrypt
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DEFAULT_SEED_HASH = bcrypt.hashpw("Password123!".encode('utf-8'), bcrypt.gensalt()).decode('utf-8')
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def seed_local_database():
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# Ensure tables are created
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init_db()
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has_data = False
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with Session(engine) as session:
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# Prevent double seeding in local testing environment
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if session.exec(select(models.Question)).first() is not None:
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has_data = True
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if has_data:
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print("Local environment database already contains data components. Dropping all and reseeding...")
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import sqlmodel
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sqlmodel.SQLModel.metadata.drop_all(engine)
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init_db()
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print("Seeding baseline content entities...")
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with Session(engine) as session:
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# 1. Super Admin User
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admin_id = UUID("aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa")
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admin_user = models.User(
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id=admin_id,
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phone="9999999998",
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email="admin@pragativeer.com",
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password_hash=bcrypt.hashpw("admin123".encode('utf-8'), bcrypt.gensalt()).decode('utf-8'),
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name="Super Admin",
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student_class=models.ClassEnum.TWELFTH,
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medium=models.MediumEnum.ENGLISH,
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target_exam=models.ExamEnum.JEE_MAIN,
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city="New Delhi",
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state="Delhi",
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tier=models.TierEnum.AI_COACH,
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streak_count=0,
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last_active=datetime.utcnow()
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)
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session.add(admin_user)
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# 2. AI Coach Demo Student User
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student_id = UUID("b0e17378-864d-439e-8806-708dc48a891b")
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student_user = models.User(
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id=student_id,
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phone="9999999999",
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email="demo@pragativeer.com",
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password_hash=bcrypt.hashpw("Pv9#kL2$mQ8!vX4@".encode('utf-8'), bcrypt.gensalt()).decode('utf-8'),
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name="Rahul Sharma (Demo AI Coach)",
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student_class=models.ClassEnum.TWELFTH,
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medium=models.MediumEnum.ENGLISH,
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target_exam=models.ExamEnum.JEE_MAIN,
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school="Delhi Public School, R.K. Puram",
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city="New Delhi",
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state="Delhi",
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tier=models.TierEnum.AI_COACH,
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trial_end=None,
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subscription_end=datetime.utcnow() + timedelta(days=345),
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streak_count=6,
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longest_streak=6,
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last_active=datetime.utcnow()
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)
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session.add(student_user)
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# 3. Neha Verma (AI Coach demo student)
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neha_id = UUID("33333333-3333-3333-3333-333333333333")
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neha_user = models.User(
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id=neha_id,
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phone="9999999997",
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email="neha.demo@pragativeer.com",
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password_hash=bcrypt.hashpw("Pv9#kL2$mQ8!vX4@".encode('utf-8'), bcrypt.gensalt()).decode('utf-8'),
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name="Neha Verma",
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student_class=models.ClassEnum.TWELFTH,
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medium=models.MediumEnum.ENGLISH,
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target_exam=models.ExamEnum.JEE_MAIN,
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school="Modern School, Barakhamba Road",
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city="New Delhi",
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state="Delhi",
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tier=models.TierEnum.AI_COACH,
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trial_end=None,
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subscription_end=datetime.utcnow() + timedelta(days=345),
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streak_count=15,
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longest_streak=25,
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last_active=datetime.utcnow()
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)
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session.add(neha_user)
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# 4. Priya Singh (Pro Tier demo student)
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priya_id = UUID("22222222-2222-2222-2222-222222222222")
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priya_user = models.User(
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id=priya_id,
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phone="9999999996",
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email="priya.demo@pragativeer.com",
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password_hash=bcrypt.hashpw("Pv9#kL2$mQ8!vX4@".encode('utf-8'), bcrypt.gensalt()).decode('utf-8'),
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name="Priya Singh",
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student_class=models.ClassEnum.TWELFTH,
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medium=models.MediumEnum.ENGLISH,
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target_exam=models.ExamEnum.NEET,
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school="City Montessori School",
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city="Lucknow",
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state="Uttar Pradesh",
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tier=models.TierEnum.PRO,
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trial_end=None,
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subscription_end=datetime.utcnow() + timedelta(days=345),
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streak_count=42,
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longest_streak=42,
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last_active=datetime.utcnow()
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)
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session.add(priya_user)
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# 5. Amit Kumar (Free Tier demo student)
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amit_id = UUID("11111111-1111-1111-1111-111111111111")
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amit_user = models.User(
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id=amit_id,
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phone="9999999995",
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email="amit.demo@pragativeer.com",
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password_hash=bcrypt.hashpw("Pv9#kL2$mQ8!vX4@".encode('utf-8'), bcrypt.gensalt()).decode('utf-8'),
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name="Amit Kumar",
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student_class=models.ClassEnum.ELEVENTH,
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medium=models.MediumEnum.ENGLISH,
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target_exam=models.ExamEnum.JEE_MAIN,
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school="Loyola High School",
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city="Patna",
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state="Bihar",
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tier=models.TierEnum.FREE,
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trial_end=None,
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streak_count=38,
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longest_streak=38,
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last_active=datetime.utcnow()
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)
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session.add(amit_user)
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# Flush users first so FK constraints for subscription/transaction are satisfied
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session.flush()
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# Seed Demo Student Subscription records
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for uid, tier in [(student_id, models.TierEnum.AI_COACH), (neha_id, models.TierEnum.AI_COACH), (priya_id, models.TierEnum.PRO)]:
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demo_subscription = models.Subscription(
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id=uuid4(),
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user_id=uid,
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tier=tier,
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billing_cycle="Annual",
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start_date=datetime.utcnow() - timedelta(days=20),
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end_date=datetime.utcnow() + timedelta(days=345),
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amount=1199900,
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payment_id=f"PAY_DEMO_{str(uid)[:6]}",
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status="Active",
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auto_renew=True,
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)
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session.add(demo_subscription)
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# Seed Demo Student Transaction record
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demo_txn = models.Transaction(
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id=uuid4(),
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user_id=student_id,
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amount=11999.0,
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tier="Al_Coach",
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status="Success",
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created_at=datetime.utcnow() - timedelta(days=20),
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)
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session.add(demo_txn)
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# admin_id is already defined above as the fixed UUID for the admin user
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jee_test_id = UUID("b6faa295-3bf5-4de2-a587-d72b889629c4")
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neet_test_id = UUID("e7c80521-825b-4c07-889a-ee646c05d762")
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# --- MOCK TESTS from admin_uploads JSON files ---
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print("Seeding Mock tests from admin_uploads...")
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_script_dir = os.path.dirname(os.path.abspath(__file__))
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_docker_path = os.path.join(_script_dir, "admin_uploads")
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_local_path = os.path.join(_script_dir, "..", "admin_uploads")
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mock_json_dir = _docker_path if os.path.isdir(_docker_path) else _local_path
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mock_json_files = sorted(glob.glob(os.path.join(mock_json_dir, "mock_*.json")))
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for json_path in mock_json_files:
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with open(json_path, "r", encoding="utf-8") as f:
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raw_questions = json.load(f)
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is_neet = "neet" in json_path.lower()
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pattern = models.ExamEnum.NEET if is_neet else models.ExamEnum.JEE_MAIN
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title = "NEET UG Full Mock Test (2025)" if is_neet else "JEE Advanced Paper 1 (2025)"
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sections = {}
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for raw_q in raw_questions:
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subject = raw_q.get("subject", "General")
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if subject not in sections:
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sections[subject] = {"name": subject, "questions": [], "time_limit": 45 if is_neet else 60}
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q = models.Question(
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id=uuid4(),
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subject=subject,
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topic=raw_q.get("topic", "Mixed"),
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subtopic=raw_q.get("subtopic", "Mixed"),
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difficulty=raw_q.get("difficulty", "Medium"),
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type=models.QuestionTypeEnum(raw_q.get("type", "MCQ_Single")),
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question_text=raw_q.get("question_text", ""),
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options=raw_q.get("options"),
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correct_answer=raw_q.get("correct_answer"),
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solution_text=raw_q.get("solution_text", ""),
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language=models.MediumEnum.ENGLISH,
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exam=pattern,
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created_by=admin_id
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)
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session.add(q)
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sections[subject]["questions"].append(str(q.id))
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mock_test = models.Test(
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id=neet_test_id if is_neet else jee_test_id,
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title=title,
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type="Mock",
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exam_pattern=pattern,
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sections=sections,
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total_time=180,
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difficulty="Mixed",
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scheduled_date=datetime.utcnow(),
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is_active=True,
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created_by=admin_id
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)
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session.add(mock_test)
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session.commit()
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# --- DPS (Daily Practice Sheets) from admin_uploads JSON files ---
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print("Seeding DPS tests from admin_uploads...")
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# Resolve path: works inside Docker (/app/admin_uploads) and locally (../../admin_uploads)
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_script_dir = os.path.dirname(os.path.abspath(__file__))
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_docker_path = os.path.join(_script_dir, "admin_uploads")
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_local_path = os.path.join(_script_dir, "..", "admin_uploads")
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dps_json_dir = _docker_path if os.path.isdir(_docker_path) else _local_path
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dps_json_files = sorted(glob.glob(os.path.join(dps_json_dir, "dps_*.json")))
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with Session(engine) as dps_session:
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for i, json_path in enumerate(dps_json_files):
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with open(json_path, "r", encoding="utf-8") as f:
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raw_questions = json.load(f)
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subject = raw_questions[0].get("subject", "General") if raw_questions else "General"
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topic = raw_questions[0].get("topic", "Chapter 4") if raw_questions else "Chapter 4"
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sheet_title = f"{subject} DPS"
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sheet_date = date.today() - timedelta(days=i)
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is_neet = any(s in subject.lower() for s in ["botany", "zoology", "bio", "biology"])
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dps_pattern = models.ExamEnum.NEET if is_neet else models.ExamEnum.JEE_MAIN
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# Create Question records from the JSON
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q_ids = []
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for raw_q in raw_questions:
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q = models.Question(
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id=uuid4(),
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subject=raw_q.get("subject", subject),
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topic=raw_q.get("topic", topic),
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subtopic=raw_q.get("subtopic", "Mixed"),
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difficulty=raw_q.get("difficulty", "Medium"),
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type=models.QuestionTypeEnum(raw_q.get("type", "MCQ_Single")),
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question_text=raw_q.get("question_text", "Sample question"),
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options=raw_q.get("options"),
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correct_answer=raw_q.get("correct_answer", {"value": "A"}),
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solution_text=raw_q.get("solution_text", "Refer to standard solution."),
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language=models.MediumEnum.ENGLISH,
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exam=dps_pattern,
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created_by=admin_id,
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)
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dps_session.add(q)
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q_ids.append(str(q.id))
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dps_id = uuid4()
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dps = models.DPS(
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id=dps_id,
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date=sheet_date,
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title=sheet_title,
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questions=q_ids,
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difficulty="Medium",
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time_limit=30,
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is_active=True,
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created_by=admin_id,
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)
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dps_session.add(dps)
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# Also create as Test(type='DPS') so /api/tests?type=DPS and CBT engine can run it
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dps_test = models.Test(
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id=dps_id,
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title=sheet_title,
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type="DPS",
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exam_pattern=dps_pattern,
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sections={"Practice": {"questions": q_ids, "time_limit": 30}},
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total_time=30,
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difficulty="Medium",
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scheduled_date=datetime.combine(sheet_date, datetime.min.time()),
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is_active=True,
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created_by=admin_id,
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)
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dps_session.add(dps_test)
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print(f" ✓ DPS & CBT Test seeded: {sheet_title} ({len(q_ids)} questions)")
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dps_session.commit()
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print("\n=== LOCAL SEED COMPLETED SUCCESSFULLY ===")
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print(f"JEE Test ID: {jee_test_id}")
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print(f"NEET Test ID: {neet_test_id}")
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print("DPS Sheets: seeded from admin_uploads/\n")
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if __name__ == "__main__":
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seed_local_database()
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