"""Synthetic user events data generator."""

import uuid
import random
from datetime import datetime, timedelta, date

import numpy as np
import pandas as pd
from faker import Faker

from .schema import (
    EVENT_TYPES, DEVICE_TYPES, OS_VALUES, BROWSER_VALUES,
    COUNTRY_CODES, DEVICE_OS_COMPAT, OS_BROWSER_COMPAT,
)

fake = Faker()


def generate(n_rows: int, seed: int = 42) -> pd.DataFrame:
    """Generate n_rows of clean synthetic user events."""
    rng = np.random.default_rng(seed)
    random.seed(seed)
    Faker.seed(seed)

    # Pre-generate a pool of users and sessions
    n_users = max(100, n_rows // 50)
    n_sessions = max(500, n_rows // 10)

    user_ids = [str(uuid.uuid4()) for _ in range(n_users)]
    session_ids = [str(uuid.uuid4()) for _ in range(n_sessions)]
    session_user = {s: random.choice(user_ids) for s in session_ids}

    # Base timestamp range: last 30 days
    now = datetime(2024, 3, 1, 12, 0, 0)
    start = now - timedelta(days=30)

    rows = []
    for _ in range(n_rows):
        session_id = random.choice(session_ids)
        user_id = session_user[session_id]
        device_type = random.choice(DEVICE_TYPES)
        os = random.choice(DEVICE_OS_COMPAT[device_type])
        browser = random.choice(OS_BROWSER_COMPAT[os])
        country_code = random.choice(COUNTRY_CODES)
        event_type = random.choice(EVENT_TYPES)
        ts = start + timedelta(seconds=int(rng.integers(0, int((now - start).total_seconds()))))
        is_purchase = event_type == "purchase"
        is_search = event_type == "search"
        is_cart = event_type in ("add_to_cart", "purchase", "checkout")

        row = {
            "event_id": str(uuid.uuid4()),
            "user_id": user_id,
            "session_id": session_id,
            "event_type": event_type,
            "timestamp": ts,
            "page_url": fake.url() + fake.uri_path(),
            "referrer_url": fake.url() if random.random() > 0.3 else None,
            "ip_address": fake.ipv4_public(),
            "device_type": device_type,
            "os": os,
            "browser": browser,
            "country_code": country_code,
            "city": fake.city(),
            "duration_seconds": int(rng.integers(1, 3600)),
            "revenue": round(float(rng.uniform(0.99, 999.99)), 2) if is_purchase else 0.0,
            "product_id": str(uuid.uuid4()) if is_cart else None,
            "quantity": int(rng.integers(1, 10)) if is_purchase else 0,
            "search_query": fake.sentence(nb_words=3) if is_search else None,
            "user_agent": fake.user_agent(),
            "is_authenticated": bool(random.random() > 0.2),
            "user_age": int(rng.integers(18, 80)),
            "email": fake.email(),
            "user_registration_date": (ts - timedelta(days=int(rng.integers(1, 1000)))).date(),
        }
        rows.append(row)

    return pd.DataFrame(rows)