"""Trading-related Pydantic schemas for Redis Streams messages and API payloads."""

from datetime import datetime
from enum import Enum
from typing import Any
from uuid import UUID, uuid4

from pydantic import BaseModel, Field


class OrderType(str, Enum):
    MARKET = "market"
    LIMIT = "limit"
    STOP = "stop"


class OrderSide(str, Enum):
    BUY = "BUY"
    SELL = "SELL"


class OrderStatus(str, Enum):
    PENDING = "PENDING"
    FILLED = "FILLED"
    CANCELLED = "CANCELLED"
    REJECTED = "REJECTED"


class SignalDirection(str, Enum):
    LONG = "LONG"
    SHORT = "SHORT"
    NEUTRAL = "NEUTRAL"


# ---------------------------------------------------------------------------
# API request / response schemas
# ---------------------------------------------------------------------------


class OrderRequest(BaseModel):
    """Submitted by the trade executor or the API to place an order."""

    ticker: str
    side: OrderSide
    qty: float = Field(gt=0)
    order_type: OrderType = OrderType.MARKET
    limit_price: float | None = None
    stop_price: float | None = None

    model_config = {"from_attributes": True}


class OrderResult(BaseModel):
    """Returned after order submission or status query."""

    order_id: str
    ticker: str
    side: OrderSide
    qty: float
    filled_price: float | None = None
    status: OrderStatus
    timestamp: datetime

    model_config = {"from_attributes": True}


class PositionInfo(BaseModel):
    """Current position state — used in API responses and portfolio views."""

    ticker: str
    qty: float
    avg_entry: float
    current_price: float
    unrealized_pnl: float
    market_value: float

    model_config = {"from_attributes": True}


class AccountInfo(BaseModel):
    """Account-level summary from the brokerage."""

    equity: float
    cash: float
    buying_power: float
    portfolio_value: float

    model_config = {"from_attributes": True}


# ---------------------------------------------------------------------------
# Redis Stream message schemas
# ---------------------------------------------------------------------------


class TradeSignal(BaseModel):
    """Published to ``signals:generated`` by the signal generator."""

    signal_id: UUID = Field(default_factory=uuid4)
    ticker: str
    direction: SignalDirection
    strength: float = Field(ge=0.0, le=1.0)
    strategy_sources: list[str]
    sentiment_context: dict[str, Any] | None = None
    timestamp: datetime

    model_config = {"from_attributes": True}


class TradeExecution(BaseModel):
    """Published to ``trades:executed`` by the trade executor."""

    trade_id: UUID
    ticker: str
    side: OrderSide
    qty: float
    price: float
    status: OrderStatus
    signal_id: UUID | None = None
    strategy_id: UUID | None = None
    timestamp: datetime

    model_config = {"from_attributes": True}


class OHLCVBar(BaseModel):
    """Single OHLCV bar."""

    timestamp: datetime
    open: float
    high: float
    low: float
    close: float
    volume: float


class MarketSnapshot(BaseModel):
    """Snapshot of market data for a single ticker — used by strategies."""

    ticker: str
    current_price: float
    open: float
    high: float
    low: float
    close: float
    volume: float
    sma_20: float | None = None
    sma_50: float | None = None
    rsi: float | None = None
    bars: list[dict[str, Any]] = Field(default_factory=list)

    model_config = {"from_attributes": True}


class SentimentContext(BaseModel):
    """Aggregated sentiment for a ticker — passed to strategies."""

    ticker: str
    avg_score: float = Field(ge=-1.0, le=1.0)
    article_count: int = Field(ge=0)
    recent_scores: list[float] = Field(default_factory=list)
    avg_confidence: float = Field(ge=0.0, le=1.0)

    model_config = {"from_attributes": True}