"""KPI / analytics query functions.

All functions return plain dicts or lists of dicts.
Uses text() for raw SQL to avoid ORM lazy-loading surprises.
Every function accepts date_from / date_to ISO-date strings to scope metrics.
"""
from datetime import date as _date
from sqlalchemy import text
from sqlalchemy.ext.asyncio import AsyncSession


def _parse_date(s: str) -> _date:
    """Convert ISO date string to datetime.date for asyncpg compatibility."""
    return _date.fromisoformat(s)


async def order_throughput_by_week(
    db: AsyncSession, date_from: str, date_to: str,
) -> list[dict]:
    """Weekly order creation + completion counts within the date range."""
    sql = text(
        """
        SELECT
            TO_CHAR(DATE_TRUNC('week', created_at), 'IYYY-"W"IW') AS week,
            COUNT(*) AS count,
            COUNT(*) FILTER (WHERE status = 'completed') AS completed
        FROM orders
        WHERE created_at >= CAST(:date_from AS date)
          AND created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        GROUP BY DATE_TRUNC('week', created_at)
        ORDER BY DATE_TRUNC('week', created_at)
        """
    )
    result = await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})
    rows = result.fetchall()
    return [{"week": r[0], "count": r[1], "completed": r[2]} for r in rows]


async def processing_time_stats(
    db: AsyncSession, date_from: str, date_to: str,
) -> dict:
    """Average and percentile processing times for completed orders in range."""
    sql = text(
        """
        SELECT
            EXTRACT(EPOCH FROM AVG(completed_at - submitted_at))::FLOAT
                AS avg_submit_to_complete_s,
            EXTRACT(EPOCH FROM AVG(processing_started_at - submitted_at))::FLOAT
                AS avg_submit_to_processing_s,
            EXTRACT(EPOCH FROM PERCENTILE_CONT(0.5) WITHIN GROUP (
                ORDER BY completed_at - submitted_at
            ))::FLOAT AS p50_s,
            EXTRACT(EPOCH FROM PERCENTILE_CONT(0.95) WITHIN GROUP (
                ORDER BY completed_at - submitted_at
            ))::FLOAT AS p95_s
        FROM orders
        WHERE status = 'completed'
          AND submitted_at IS NOT NULL
          AND completed_at IS NOT NULL
          AND submitted_at >= CAST(:date_from AS date)
          AND submitted_at < CAST(:date_to AS date) + INTERVAL '1 day'
        """
    )
    result = await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})
    row = result.fetchone()
    if row is None:
        return {
            "avg_submit_to_complete_s": None,
            "avg_submit_to_processing_s": None,
            "p50_s": None,
            "p95_s": None,
        }
    return {
        "avg_submit_to_complete_s": row[0],
        "avg_submit_to_processing_s": row[1],
        "p50_s": row[2],
        "p95_s": row[3],
    }


async def revenue_overview(
    db: AsyncSession, date_from: str, date_to: str,
) -> list[dict]:
    """Monthly revenue (sum of estimated_price for completed orders) in range."""
    sql = text(
        """
        SELECT
            TO_CHAR(DATE_TRUNC('month', completed_at), 'YYYY-MM') AS month,
            COALESCE(SUM(estimated_price), 0)::FLOAT AS revenue,
            COUNT(*) AS order_count
        FROM orders
        WHERE status = 'completed'
          AND completed_at >= CAST(:date_from AS date)
          AND completed_at < CAST(:date_to AS date) + INTERVAL '1 day'
        GROUP BY DATE_TRUNC('month', completed_at)
        ORDER BY DATE_TRUNC('month', completed_at)
        """
    )
    result = await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})
    rows = result.fetchall()
    return [{"month": r[0], "revenue": r[1], "order_count": r[2]} for r in rows]


async def item_status_breakdown(
    db: AsyncSession, date_from: str, date_to: str,
) -> dict:
    """Count of order lines grouped by item_status, scoped to orders in range."""
    sql = text(
        """
        SELECT ol.item_status, COUNT(*) AS cnt
        FROM order_lines ol
        JOIN orders o ON o.id = ol.order_id
        WHERE o.created_at >= CAST(:date_from AS date)
          AND o.created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        GROUP BY ol.item_status
        """
    )
    result = await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})
    rows = result.fetchall()
    out: dict = {"pending": 0, "approved": 0, "rejected": 0}
    for row in rows:
        key = str(row[0])
        out[key] = int(row[1])
    return out


async def render_time_breakdown(
    db: AsyncSession, date_from: str, date_to: str,
) -> dict:
    """Average render duration from completed order lines, scoped to date range.

    Uses render_started_at / render_completed_at on order_lines (added in migration 015).
    avg_stl_s is not tracked at order-line level, so only avg_render_s and sample_count
    are meaningful here; avg_stl_s is left None for UI compatibility.
    """
    sql = text(
        """
        SELECT
            AVG(EXTRACT(EPOCH FROM (render_completed_at - render_started_at)))  AS avg_render_s,
            COUNT(*)                                                              AS sample_count
        FROM order_lines
        WHERE render_status = 'completed'
          AND render_started_at IS NOT NULL
          AND render_completed_at IS NOT NULL
          AND render_completed_at >= CAST(:date_from AS date)
          AND render_completed_at < CAST(:date_to AS date) + INTERVAL '1 day'
        """
    )
    result = await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})
    row = result.fetchone()
    if row is None or row[1] == 0:
        return {"avg_stl_s": None, "avg_render_s": None, "avg_total_s": None, "sample_count": 0}
    return {
        "avg_stl_s": None,
        "avg_render_s": float(row[0]) if row[0] is not None else None,
        "avg_total_s": float(row[0]) if row[0] is not None else None,
        "sample_count": int(row[1]),
    }


async def render_time_by_output_type(
    db: AsyncSession, date_from: str, date_to: str,
) -> list[dict]:
    """Render time statistics per output type for completed order lines."""
    sql = text(
        """
        SELECT
            COALESCE(ot.name, 'Unknown')                                             AS output_type,
            COUNT(*)                                                                  AS job_count,
            AVG(EXTRACT(EPOCH FROM (ol.render_completed_at - ol.render_started_at))) AS avg_render_s,
            MIN(EXTRACT(EPOCH FROM (ol.render_completed_at - ol.render_started_at))) AS min_render_s,
            MAX(EXTRACT(EPOCH FROM (ol.render_completed_at - ol.render_started_at))) AS max_render_s,
            PERCENTILE_CONT(0.5) WITHIN GROUP (
                ORDER BY EXTRACT(EPOCH FROM (ol.render_completed_at - ol.render_started_at))
            )                                                                         AS p50_render_s
        FROM order_lines ol
        LEFT JOIN output_types ot ON ot.id = ol.output_type_id
        WHERE ol.render_status = 'completed'
          AND ol.render_started_at IS NOT NULL
          AND ol.render_completed_at IS NOT NULL
          AND ol.render_completed_at >= CAST(:date_from AS date)
          AND ol.render_completed_at < CAST(:date_to AS date) + INTERVAL '1 day'
        GROUP BY ot.id, ot.name
        ORDER BY avg_render_s DESC NULLS LAST
        """
    )
    result = await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})
    return [
        {
            "output_type": r[0],
            "job_count": int(r[1]),
            "avg_render_s": float(r[2]) if r[2] is not None else None,
            "min_render_s": float(r[3]) if r[3] is not None else None,
            "max_render_s": float(r[4]) if r[4] is not None else None,
            "p50_render_s": float(r[5]) if r[5] is not None else None,
        }
        for r in result.fetchall()
    ]


async def top_level_summary(
    db: AsyncSession, date_from: str, date_to: str,
) -> dict:
    """High-level summary counts and totals within the date range."""
    sql = text(
        """
        SELECT
            COUNT(*)                                              AS total_orders,
            COUNT(*) FILTER (WHERE status = 'completed')         AS completed_orders,
            COALESCE(SUM(estimated_price) FILTER (WHERE status = 'completed'), 0)::FLOAT
                                                                  AS total_revenue
        FROM orders
        WHERE created_at >= CAST(:date_from AS date)
          AND created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        """
    )
    result = await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})
    row = result.fetchone()

    items_sql = text(
        """
        SELECT COUNT(*)
        FROM order_lines ol
        JOIN orders o ON o.id = ol.order_id
        WHERE ol.output_type_id IS NOT NULL
          AND o.created_at >= CAST(:date_from AS date)
          AND o.created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        """
    )
    items_result = await db.execute(items_sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})
    items_count = items_result.scalar() or 0

    return {
        "total_orders": int(row[0]) if row else 0,
        "completed_orders": int(row[1]) if row else 0,
        "total_revenue": float(row[2]) if row else 0.0,
        "total_rendering_items": int(items_count),
    }


async def product_and_category_stats(
    db: AsyncSession, date_from: str, date_to: str,
) -> dict:
    """Product-level stats: unique rendered, total products, CAD coverage, by category."""
    params = {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)}

    rendered_sql = text(
        """
        SELECT COUNT(DISTINCT ol.product_id)
        FROM order_lines ol
        JOIN orders o ON o.id = ol.order_id
        WHERE ol.render_status = 'completed'
          AND o.created_at >= CAST(:date_from AS date)
          AND o.created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        """
    )
    rendered = (await db.execute(rendered_sql, params)).scalar() or 0

    totals_sql = text(
        """
        SELECT COUNT(*) AS total, COUNT(cad_file_id) AS with_cad
        FROM products
        """
    )
    totals_row = (await db.execute(totals_sql)).fetchone()
    total_products = int(totals_row[0]) if totals_row else 0
    products_with_cad = int(totals_row[1]) if totals_row else 0

    cat_sql = text(
        """
        SELECT COALESCE(category_key, 'unknown') AS category, COUNT(*) AS cnt
        FROM products
        GROUP BY category_key
        ORDER BY cnt DESC
        """
    )
    cat_rows = (await db.execute(cat_sql)).fetchall()

    return {
        "unique_products_rendered": int(rendered),
        "total_products": total_products,
        "products_with_cad": products_with_cad,
        "products_by_category": [
            {"category": r[0], "count": int(r[1])} for r in cat_rows
        ],
    }


async def output_type_usage(
    db: AsyncSession, date_from: str, date_to: str,
) -> list[dict]:
    """Order lines grouped by output type name."""
    sql = text(
        """
        SELECT ot.name AS output_type, COUNT(*) AS cnt
        FROM order_lines ol
        JOIN output_types ot ON ot.id = ol.output_type_id
        JOIN orders o ON o.id = ol.order_id
        WHERE o.created_at >= CAST(:date_from AS date)
          AND o.created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        GROUP BY ot.name
        ORDER BY cnt DESC
        """
    )
    rows = (await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})).fetchall()
    return [{"output_type": r[0], "count": int(r[1])} for r in rows]


async def render_status_distribution(
    db: AsyncSession, date_from: str, date_to: str,
) -> tuple[dict, list[dict]]:
    """(a) order_lines by render_status, (b) cad_files by renderer from render_log."""
    params = {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)}

    status_sql = text(
        """
        SELECT ol.render_status, COUNT(*) AS cnt
        FROM order_lines ol
        JOIN orders o ON o.id = ol.order_id
        WHERE o.created_at >= CAST(:date_from AS date)
          AND o.created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        GROUP BY ol.render_status
        """
    )
    status_rows = (await db.execute(status_sql, params)).fetchall()
    status_map: dict = {"pending": 0, "processing": 0, "completed": 0, "failed": 0}
    for row in status_rows:
        key = str(row[0])
        status_map[key] = int(row[1])

    renderer_sql = text(
        """
        SELECT render_log->>'renderer' AS renderer, COUNT(*) AS cnt
        FROM cad_files
        WHERE render_log IS NOT NULL
          AND render_log->>'renderer' IS NOT NULL
          AND created_at >= CAST(:date_from AS date)
          AND created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        GROUP BY render_log->>'renderer'
        ORDER BY cnt DESC
        """
    )
    renderer_rows = (await db.execute(renderer_sql, params)).fetchall()
    renderer_usage = [{"renderer": r[0], "count": int(r[1])} for r in renderer_rows]

    return status_map, renderer_usage


async def top_products(
    db: AsyncSession, date_from: str, date_to: str,
    limit: int = 10,
) -> list[dict]:
    """Top N most-ordered products by order line count."""
    sql = text(
        """
        SELECT p.pim_id, p.name AS product_name,
               COALESCE(p.category_key, 'unknown') AS category,
               COUNT(*) AS order_count
        FROM order_lines ol
        JOIN products p ON p.id = ol.product_id
        JOIN orders o ON o.id = ol.order_id
        WHERE o.created_at >= CAST(:date_from AS date)
          AND o.created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        GROUP BY p.id, p.pim_id, p.name, p.category_key
        ORDER BY order_count DESC
        LIMIT :lim
        """
    )
    rows = (await db.execute(sql, {
        "date_from": _parse_date(date_from),
        "date_to": _parse_date(date_to),
        "lim": limit,
    })).fetchall()
    return [
        {"pim_id": r[0], "product_name": r[1], "category": r[2], "order_count": int(r[3])}
        for r in rows
    ]


async def category_revenue(
    db: AsyncSession, date_from: str, date_to: str,
) -> list[dict]:
    """Proportional revenue by category: order price / line count, summed per category."""
    sql = text(
        """
        WITH order_share AS (
            SELECT o.id AS order_id,
                   COALESCE(o.estimated_price, 0) / GREATEST(COUNT(ol.id), 1) AS per_line_price,
                   COALESCE(p.category_key, 'unknown') AS category
            FROM orders o
            JOIN order_lines ol ON ol.order_id = o.id
            JOIN products p ON p.id = ol.product_id
            WHERE o.status = 'completed'
              AND o.completed_at >= CAST(:date_from AS date)
              AND o.completed_at < CAST(:date_to AS date) + INTERVAL '1 day'
            GROUP BY o.id, o.estimated_price, p.category_key
        )
        SELECT category,
               COUNT(DISTINCT order_id) AS order_count,
               COALESCE(SUM(per_line_price), 0)::FLOAT AS revenue
        FROM order_share
        GROUP BY category
        ORDER BY revenue DESC
        """
    )
    rows = (await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})).fetchall()
    return [{"category": r[0], "order_count": int(r[1]), "revenue": r[2]} for r in rows]


async def render_backend_stats(
    db: AsyncSession, date_from: str, date_to: str,
) -> list[dict]:
    """Render time + count by backend (celery vs flamenco)."""
    sql = text(
        """
        SELECT
            COALESCE(render_backend_used, 'unknown') AS backend,
            COUNT(*) AS total,
            COUNT(*) FILTER (WHERE render_status = 'completed') AS completed,
            COUNT(*) FILTER (WHERE render_status = 'failed') AS failed,
            EXTRACT(EPOCH FROM AVG(
                render_completed_at - render_started_at
            ) FILTER (WHERE render_status = 'completed'))::FLOAT AS avg_render_s,
            EXTRACT(EPOCH FROM PERCENTILE_CONT(0.5) WITHIN GROUP (
                ORDER BY render_completed_at - render_started_at
            ) FILTER (WHERE render_status = 'completed'))::FLOAT AS p50_render_s
        FROM order_lines ol
        JOIN orders o ON o.id = ol.order_id
        WHERE render_backend_used IS NOT NULL
          AND o.created_at >= CAST(:date_from AS date)
          AND o.created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        GROUP BY render_backend_used
        ORDER BY total DESC
        """
    )
    rows = (await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})).fetchall()
    return [
        {
            "backend": r[0],
            "total": int(r[1]),
            "completed": int(r[2]),
            "failed": int(r[3]),
            "avg_render_s": r[4],
            "p50_render_s": r[5],
        }
        for r in rows
    ]


async def orders_by_user(
    db: AsyncSession, date_from: str, date_to: str,
) -> list[dict]:
    """Orders grouped by user with counts and revenue."""
    sql = text(
        """
        SELECT u.full_name, u.email, u.role,
               COUNT(*) AS order_count,
               COALESCE(SUM(o.estimated_price) FILTER (WHERE o.status = 'completed'), 0)::FLOAT AS revenue
        FROM orders o
        JOIN users u ON u.id = o.created_by
        WHERE o.created_at >= CAST(:date_from AS date)
          AND o.created_at < CAST(:date_to AS date) + INTERVAL '1 day'
        GROUP BY u.id, u.full_name, u.email, u.role
        ORDER BY order_count DESC
        """
    )
    rows = (await db.execute(sql, {"date_from": _parse_date(date_from), "date_to": _parse_date(date_to)})).fetchall()
    return [
        {"full_name": r[0], "email": r[1], "role": r[2], "order_count": int(r[3]), "revenue": r[4]}
        for r in rows
    ]