matitos
8b6cf8130c
Adds MultiStrategyManager: it runs several strategies concurrently, each with its own TradingEngine seeded with starting_balance * allocation, so one strategy's losses cannot eat into another's capital. Weights are normalised across the run ([1,3] -> 25%/75%). Risk limits stay per strategy (each engine owns a RiskManager). New API: POST /api/bot/start-many and GET /api/bot/status. The existing single-strategy endpoints delegate to the manager, so their behaviour is unchanged. Adds manager tests (allocation, isolation, duplicate keys) and API tests.
286 lines
6.3 KiB
Python
286 lines
6.3 KiB
Python
from __future__ import annotations
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from datetime import datetime
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from typing import Any, Literal
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from pydantic import BaseModel, ConfigDict, Field
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class Candle(BaseModel):
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ts: int
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open: float
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high: float
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low: float
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close: float
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volume: float
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class ParamSpec(BaseModel):
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name: str
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type: Literal["int", "float", "bool", "str"]
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default: Any
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description: str = ""
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min: float | None = None
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max: float | None = None
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class StrategyOut(BaseModel):
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key: str
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name: str
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description: str
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params: list[ParamSpec]
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class PositionOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: int
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strategy_key: str
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symbol: str
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side: str
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qty: float
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entry_price: float
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status: str
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stop_loss: float | None = None
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take_profit: float | None = None
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exit_price: float | None = None
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realized_pnl: float | None = None
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unrealized_pnl: float | None = None
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opened_at: datetime
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closed_at: datetime | None = None
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class OrderOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: int
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position_id: int | None
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strategy_key: str
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symbol: str
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side: str
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qty: float
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price: float
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fee: float
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reason: str
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created_at: datetime
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class EventOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: int
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level: str
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message: str
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strategy_key: str | None
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created_at: datetime
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class EquityPointOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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equity: float
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cash: float
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price: float
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created_at: datetime
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class StatusOut(BaseModel):
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running: bool
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mode: str
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exchange: str
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symbol: str
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timeframe: str
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strategy_key: str | None
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strategy_name: str | None
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params: dict[str, Any] = Field(default_factory=dict)
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price: float | None
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cash: float
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equity: float
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starting_balance: float
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realized_pnl: float
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unrealized_pnl: float
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total_pnl: float
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open_positions: int
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last_tick: datetime | None
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error: str | None = None
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halted: bool = False
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halt_reason: str | None = None
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trades_today: int = 0
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day_pnl: float = 0.0
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drawdown_pct: float = 0.0
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class KillRequest(BaseModel):
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reason: str = "manual kill switch"
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class StrategyConfigIn(BaseModel):
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name: str = Field(default="", max_length=80)
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strategy_key: str
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symbol: str
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timeframe: str
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params: dict[str, Any] = Field(default_factory=dict)
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class StrategyConfigOut(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: int
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name: str
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strategy_key: str
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symbol: str
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timeframe: str
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params: dict[str, Any]
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created_at: datetime
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class StrategySpec(BaseModel):
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"""One strategy in a multi-strategy run."""
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strategy_key: str
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params: dict[str, Any] = Field(default_factory=dict)
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symbol: str | None = None
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timeframe: str | None = None
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# Fraction of the account allocated to this strategy (relative weights are
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# normalised across the run, so [1, 3] gives 25% / 75%).
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weight: float = Field(default=1.0, gt=0)
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class StartRequest(BaseModel):
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strategy_key: str
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symbol: str | None = None
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timeframe: str | None = None
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params: dict[str, Any] = Field(default_factory=dict)
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starting_balance: float | None = None
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class StartManyRequest(BaseModel):
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strategies: list[StrategySpec] = Field(min_length=1)
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starting_balance: float | None = None
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class StrategyStatusOut(BaseModel):
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"""Per-strategy status inside a multi-strategy run."""
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strategy_key: str
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strategy_name: str | None
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params: dict[str, Any] = Field(default_factory=dict)
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symbol: str
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timeframe: str
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allocation: float
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cash: float
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equity: float
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realized_pnl: float
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unrealized_pnl: float
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total_pnl: float
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open_positions: int
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halted: bool = False
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halt_reason: str | None = None
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trades_today: int = 0
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error: str | None = None
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class MultiStatusOut(BaseModel):
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running: bool
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mode: str
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exchange: str
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price: float | None = None
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starting_balance: float
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equity: float
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total_pnl: float
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strategies: list[StrategyStatusOut] = Field(default_factory=list)
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last_tick: datetime | None = None
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class ManualOrderRequest(BaseModel):
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side: Literal["buy", "sell"]
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qty: float | None = None
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quote_amount: float | None = None
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reason: str = "manual"
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class ClosePositionRequest(BaseModel):
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reason: str = "manual"
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class BacktestRequest(BaseModel):
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strategy_key: str
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params: dict[str, Any] = Field(default_factory=dict)
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symbol: str | None = None
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timeframe: str | None = None
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limit: int = Field(default=500, ge=20, le=1000)
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starting_balance: float | None = None
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class BacktestTradeOut(BaseModel):
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side: str
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entry_ts: int
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exit_ts: int
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entry_price: float
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exit_price: float
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qty: float
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pnl: float
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return_pct: float
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reason: str
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class BacktestPointOut(BaseModel):
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ts: int
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equity: float
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buy_hold: float
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price: float
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class BacktestMetricsOut(BaseModel):
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initial_equity: float
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final_equity: float
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total_return_pct: float
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buy_hold_return_pct: float
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max_drawdown_pct: float
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num_trades: int
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win_rate_pct: float
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profit_factor: float | None
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avg_trade_pct: float
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best_trade_pct: float
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worst_trade_pct: float
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sharpe: float | None
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class BacktestResult(BaseModel):
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strategy_key: str
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strategy_name: str
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symbol: str
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timeframe: str
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starting_balance: float
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metrics: BacktestMetricsOut
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equity_curve: list[BacktestPointOut]
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trades: list[BacktestTradeOut]
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error: str | None = None
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class SweepRequest(BaseModel):
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strategy_key: str
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base_params: dict[str, Any] = Field(default_factory=dict)
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# param name -> list of candidate values (cartesian product)
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grid: dict[str, list[Any]] = Field(default_factory=dict)
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symbol: str | None = None
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timeframe: str | None = None
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limit: int = Field(default=500, ge=20, le=1000)
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starting_balance: float | None = None
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top_n: int = Field(default=20, ge=1, le=100)
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class SweepRowOut(BaseModel):
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params: dict[str, Any]
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metrics: BacktestMetricsOut
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class SweepResult(BaseModel):
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strategy_key: str
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strategy_name: str
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symbol: str
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timeframe: str
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combinations: int
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rows: list[SweepRowOut]
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error: str | None = None
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