"""Interactive Brokers provider adapter.

This is a stub implementation that demonstrates the structure for IBKR integration.
The actual IBKR API calls need to be wired using your existing IB client.

TODO:
- Wire up IB connection (client_id/host/port/paper)
- Implement _fetch_chunk using historicalData/reqHistoricalData
- Add proper token-bucket rate limiting
- Handle IBKR-specific error codes
- Map interval strings to IBKR bar sizes
- Respect calendar and trading hours
"""

import time
from collections.abc import Iterable
from datetime import datetime

from ..configs.model import Dataset, Job
from ..configs.model import IBKRProvider as IBKRConfig
from ..runtime.provider_protocol import Bar, Provider


class IBKRAdapter(Provider):
    """Interactive Brokers data provider adapter.

    This adapter handles:
    - Connection management (client_id, host, port, paper)
    - Rate limiting (pacing budget)
    - Retry logic with exponential backoff
    - Chunked backfills to respect IBKR limits
    - Bar size translation (5min → "5 mins", 1d → "1 day")

    Status: STUB - Requires IBKR client integration

    Example:
        ```python
        from market_data_core.configs.model import IBKRProvider
        from market_data_core.providers import IBKRAdapter

        cfg = IBKRProvider(
            type="ibkr",
            host="127.0.0.1",
            port=7497,
            client_id="1",
            paper=True
        )

        adapter = IBKRAdapter("ibkr_primary", cfg)

        # TODO: Implement fetch methods
        # bars = adapter.backfill(dataset, job)
        ```

    Integration Notes:
        To complete this adapter:
        1. Import your IB client: `from market_data_core.services.ib_client import ...`
        2. Initialize connection in __init__
        3. Implement _fetch_chunk using reqHistoricalData
        4. Map interval strings: "5min" → "5 mins", "1d" → "1 day"
        5. Handle pacing with proper token bucket
        6. Add error handling for IBKR-specific codes
    """

    def __init__(self, name: str, cfg: IBKRConfig):
        """Initialize IBKR adapter.

        Args:
            name: Provider instance name (from config)
            cfg: IBKR provider configuration

        TODO:
            - Initialize IB connection
            - Setup pacing/rate limiter
            - Configure retry policy
        """
        self.name = name
        self.cfg = cfg

        # TODO: Initialize IB connection
        # Example:
        # from market_data_core.services.ib_client import IBClient
        # self._client = IBClient(
        #     host=cfg.host,
        #     port=cfg.port,
        #     client_id=int(cfg.client_id or "1"),
        # )
        # if cfg.paper:
        #     self._client.connect_paper()
        # else:
        #     self._client.connect_live()

    def _respect_budget(self) -> None:
        """Rate limiting to respect IBKR pacing budget.

        TODO:
            Replace with proper token-bucket algorithm.
            Current implementation is a simple sleep.

        Implementation notes:
            - IBKR allows ~60 requests per 10 minutes
            - Use burst capability for initial requests
            - Back off during cooldown period
            - Track request timestamps
        """
        # Simple sleep for now - replace with token bucket
        time.sleep(max(0, self.cfg.pacing.cooldown_seconds / 10))

    def _fetch_chunk(
        self,
        _symbol: str,
        _start: datetime,
        _end: datetime,
        _interval: str,
    ) -> Iterable[Bar]:
        """Fetch a single chunk of historical data from IBKR.

        Args:
            symbol: Symbol to fetch (e.g., "SPY")
            start: Start datetime (UTC)
            end: End datetime (UTC)
            interval: Interval string (e.g., "5min", "1d")

        Yields:
            Bar: OHLCV bars for the requested period

        TODO:
            Implement using IBKR API:
            ```python
            # Map interval to IBKR bar size
            bar_size = self._map_interval(interval)  # "5min" → "5 mins"

            # Call IBKR historicalData
            ib_bars = self._client.req_historical_data(
                symbol=symbol,
                end_datetime=end,
                duration=str(end - start),
                bar_size=bar_size,
                what_to_show=self.cfg.what_to_show_default,
                use_rth=True,  # Regular trading hours
            )

            # Convert to Bar format
            for ib_bar in ib_bars:
                yield Bar(
                    provider=self.name,
                    symbol=symbol,
                    interval=interval,
                    ts=ib_bar.date,
                    open=ib_bar.open,
                    high=ib_bar.high,
                    low=ib_bar.low,
                    close=ib_bar.close,
                    volume=ib_bar.volume,
                )
            ```
        """
        # Stub: yield nothing for now
        self._respect_budget()
        yield from ()

    def backfill(self, _dataset: Dataset, job: Job) -> Iterable[Bar]:
        """Fetch historical data according to backfill specification.

        Args:
            dataset: Dataset configuration (symbols, interval, etc.)
            job: Job configuration with backfill spec

        Yields:
            Bar: OHLCV bars for all symbols in the backfill period

        TODO:
            Implement chunking logic:
            1. Parse relative times: "now-3y" → datetime
            2. Split period into chunks (e.g., 180d each)
            3. For each symbol, for each chunk:
               - Call _fetch_chunk
               - Respect pacing budget
               - Handle retries
            4. Yield bars incrementally (don't buffer)

        Example implementation:
            ```python
            bf = job.backfill
            assert bf, "Backfill job requires backfill spec"

            # Parse dates
            end = self._parse_time(bf.to)  # "now" → datetime.utcnow()
            start = self._parse_time(bf.from_)  # "now-3y" → 3 years ago
            chunk_size = self._parse_duration(bf.chunk)  # "180d" → timedelta

            # Get symbols
            symbols = self._resolve_symbols(dataset.symbols)

            # Chunk and fetch
            for symbol in symbols:
                current = start
                while current < end:
                    chunk_end = min(current + chunk_size, end)
                    yield from self._fetch_chunk(
                        symbol, current, chunk_end, dataset.interval
                    )
                    current = chunk_end
            ```
        """
        bf = job.backfill
        assert bf, "Backfill job requires backfill spec"

        # TODO: Implement chunking and fetching
        # For now, yield nothing
        yield from ()

    def fetch_live(self, _dataset: Dataset, _job: Job) -> Iterable[Bar]:
        """Fetch live/recent data for the dataset.

        Args:
            dataset: Dataset configuration (symbols, interval, etc.)
            job: Job configuration (execution policy, etc.)

        Yields:
            Bar: OHLCV bars for the most recent window

        TODO:
            Implement live fetching:
            1. Calculate window: [now - interval, now]
            2. Map interval to IBKR bar size
            3. For each symbol:
               - Call _fetch_chunk with recent window
               - Respect pacing budget
            4. Yield bars as they arrive

        Example implementation:
            ```python
            # Calculate recent window
            now = datetime.utcnow()
            window = self._parse_duration(dataset.interval)  # "5min" → timedelta
            start = now - window

            # Get symbols
            symbols = self._resolve_symbols(dataset.symbols)

            # Fetch
            for symbol in symbols:
                yield from self._fetch_chunk(symbol, start, now, dataset.interval)
            ```
        """
        # TODO: Implement live fetching
        # For now, yield nothing
        yield from ()

    # Helper methods to implement:
    #
    # def _map_interval(self, interval: str) -> str:
    #     """Map interval string to IBKR bar size."""
    #     mapping = {
    #         "1min": "1 min", "5min": "5 mins", "15min": "15 mins",
    #         "30min": "30 mins", "1h": "1 hour", "1d": "1 day",
    #     }
    #     return mapping.get(interval, interval)
    #
    # def _parse_time(self, time_str: str) -> datetime:
    #     """Parse relative time string to datetime."""
    #     if time_str == "now":
    #         return datetime.utcnow()
    #     # Parse "now-3y", "now-30d", etc.
    #     ...
    #
    # def _parse_duration(self, duration_str: str) -> timedelta:
    #     """Parse duration string to timedelta."""
    #     # Parse "180d", "1y", "5min", etc.
    #     ...
    #
    # def _resolve_symbols(self, symbols) -> list[str]:
    #     """Resolve symbol references to actual list."""
    #     if isinstance(symbols, list):
    #         return symbols
    #     # Handle "@watchlists.name" references
    #     ...
