"""Async SQL Server access layer used by the warehouse application.

The module centralizes DSN creation and exposes :class:`AsyncMSSQLClient`,
which lazily binds a SQLAlchemy async engine to the running event loop. The
implementation intentionally avoids pooling because the GUI schedules work on a
single shared background loop and pooled connections were a source of
cross-loop errors.
"""

from __future__ import annotations

import asyncio
import logging
import time
import urllib.parse
from typing import Any, Dict, Optional

from sqlalchemy import text
from sqlalchemy.ext.asyncio import create_async_engine
from sqlalchemy.pool import NullPool

try:
    import orjson as _json

    def _dumps(obj: Any) -> str:
        """Serialize an object to JSON using the fastest available backend."""
        return _json.dumps(obj, default=str).decode("utf-8")
except Exception:
    import json as _json

    def _dumps(obj: Any) -> str:
        """Serialize an object to JSON using the standard library fallback."""
        return _json.dumps(obj, default=str)


def make_mssql_dsn(
    *,
    server: str,
    database: str,
    user: Optional[str] = None,
    password: Optional[str] = None,
    driver: str = "ODBC Driver 17 for SQL Server",
    trust_server_certificate: bool = True,
    encrypt: Optional[str] = None,
    extra_odbc_kv: Optional[Dict[str, str]] = None,
) -> str:
    """Build a SQLAlchemy ``mssql+aioodbc`` DSN from SQL Server parameters."""
    kv = {
        "DRIVER": driver,
        "SERVER": server,
        "DATABASE": database,
        "TrustServerCertificate": "Yes" if trust_server_certificate else "No",
    }
    if user:
        kv["UID"] = user
    if password:
        kv["PWD"] = password
    if encrypt:
        kv["Encrypt"] = encrypt
    if extra_odbc_kv:
        kv.update(extra_odbc_kv)
    odbc = ";".join(f"{k}={v}" for k, v in kv.items()) + ";"
    return f"mssql+aioodbc:///?odbc_connect={urllib.parse.quote_plus(odbc)}"


class AsyncMSSQLClient:
    """Thin async query client for SQL Server.

    The engine is created lazily on the currently running event loop and uses
    :class:`sqlalchemy.pool.NullPool` to avoid recycling connections across
    loops or threads.
    """

    def __init__(self, dsn: str, *, echo: bool = False, log: bool = True):
        """Initialize the client without opening any connection immediately."""
        self._dsn = dsn
        self._echo = echo
        self._engine = None
        self._engine_loop: Optional[asyncio.AbstractEventLoop] = None
        self._logger = logging.getLogger("AsyncMSSQLClient")
        if log and not self._logger.handlers:
            handler = logging.StreamHandler()
            handler.setFormatter(logging.Formatter("[%(levelname)s] %(message)s"))
            self._logger.addHandler(handler)
        self._enable_log = log

    async def _ensure_engine(self):
        """Create the async engine on first use for the current running loop."""
        if self._engine is not None:
            return
        loop = asyncio.get_running_loop()
        self._engine = create_async_engine(
            self._dsn,
            echo=self._echo,
            # NullPool avoids reusing connections bound to a different event loop.
            poolclass=NullPool,
            # aioodbc must explicitly receive the loop to bind to.
            connect_args={"loop": loop},
        )
        self._engine_loop = loop
        if self._enable_log:
            self._logger.info("Engine created on loop %s", id(loop))

    async def dispose(self):
        """Dispose the engine on the loop where it was created."""
        if self._engine is None:
            return
        if asyncio.get_running_loop() is self._engine_loop:
            await self._engine.dispose()
        else:
            fut = asyncio.run_coroutine_threadsafe(self._engine.dispose(), self._engine_loop)
            fut.result(timeout=2)
        self._engine = None
        if self._enable_log:
            self._logger.info("Engine disposed")

    async def query_json(
        self,
        sql: str,
        params: Optional[Dict[str, Any]] = None,
        *,
        as_dict_rows: bool = False,
    ) -> Dict[str, Any]:
        """Execute a query and return a JSON-friendly payload.

        Args:
            sql: SQL statement to execute.
            params: Optional named parameters bound to the statement.
            as_dict_rows: When ``True`` returns rows as dictionaries keyed by
                column name; otherwise rows are returned as lists.

        Returns:
            A dictionary containing column names, rows and elapsed execution
            time in milliseconds.
        """
        await self._ensure_engine()
        t0 = time.perf_counter()
        async with self._engine.connect() as conn:
            res = await conn.execute(text(sql), params or {})
            rows = res.fetchall()
            cols = list(res.keys())
        if as_dict_rows:
            rows_out = [dict(zip(cols, row)) for row in rows]
        else:
            rows_out = [list(row) for row in rows]
        return {
            "columns": cols,
            "rows": rows_out,
            "elapsed_ms": round((time.perf_counter() - t0) * 1000, 3),
        }

    async def exec(self, sql: str, params: Optional[Dict[str, Any]] = None, *, commit: bool = False) -> int:
        """Execute a DML statement and return its row count."""
        await self._ensure_engine()
        async with (self._engine.begin() if commit else self._engine.connect()) as conn:
            res = await conn.execute(text(sql), params or {})
            return res.rowcount or 0