from datetime import date, datetime from enum import Enum from typing import Any, Dict, List, Optional, Union from pydantic import BaseModel from freqtrade.constants import DATETIME_PRINT_FORMAT class Ping(BaseModel): status: str class AccessToken(BaseModel): access_token: str class AccessAndRefreshToken(AccessToken): refresh_token: str class Version(BaseModel): version: str class StatusMsg(BaseModel): status: str class ResultMsg(BaseModel): result: str class Balance(BaseModel): currency: str free: float balance: float used: float est_stake: float stake: str class Balances(BaseModel): currencies: List[Balance] total: float symbol: str value: float stake: str note: str starting_capital: float starting_capital_ratio: float starting_capital_pct: float starting_capital_fiat: float starting_capital_fiat_ratio: float starting_capital_fiat_pct: float class Count(BaseModel): current: int max: int total_stake: float class PerformanceEntry(BaseModel): pair: str profit: float profit_ratio: float profit_pct: float profit_abs: float count: int class Profit(BaseModel): profit_closed_coin: float profit_closed_percent_mean: float profit_closed_ratio_mean: float profit_closed_percent_sum: float profit_closed_ratio_sum: float profit_closed_percent: float profit_closed_ratio: float profit_closed_fiat: float profit_all_coin: float profit_all_percent_mean: float profit_all_ratio_mean: float profit_all_percent_sum: float profit_all_ratio_sum: float profit_all_percent: float profit_all_ratio: float profit_all_fiat: float trade_count: int closed_trade_count: int first_trade_date: str first_trade_timestamp: int latest_trade_date: str latest_trade_timestamp: int avg_duration: str best_pair: str best_rate: float best_pair_profit_ratio: float winning_trades: int losing_trades: int class SellReason(BaseModel): wins: int losses: int draws: int class Stats(BaseModel): sell_reasons: Dict[str, SellReason] durations: Dict[str, Union[str, float]] class DailyRecord(BaseModel): date: date abs_profit: float fiat_value: float trade_count: int class Daily(BaseModel): data: List[DailyRecord] fiat_display_currency: str stake_currency: str class UnfilledTimeout(BaseModel): buy: Optional[int] sell: Optional[int] unit: Optional[str] exit_timeout_count: Optional[int] class OrderTypeValues(str, Enum): limit = 'limit' market = 'market' class OrderTypes(BaseModel): buy: OrderTypeValues sell: OrderTypeValues emergencysell: Optional[OrderTypeValues] forcesell: Optional[OrderTypeValues] forcebuy: Optional[OrderTypeValues] stoploss: OrderTypeValues stoploss_on_exchange: bool stoploss_on_exchange_interval: Optional[int] class ShowConfig(BaseModel): version: str api_version: float dry_run: bool stake_currency: str stake_amount: Union[float, str] available_capital: Optional[float] stake_currency_decimals: int max_open_trades: int minimal_roi: Dict[str, Any] stoploss: Optional[float] trailing_stop: Optional[bool] trailing_stop_positive: Optional[float] trailing_stop_positive_offset: Optional[float] trailing_only_offset_is_reached: Optional[bool] unfilledtimeout: UnfilledTimeout order_types: OrderTypes use_custom_stoploss: Optional[bool] timeframe: Optional[str] timeframe_ms: int timeframe_min: int exchange: str strategy: Optional[str] forcebuy_enabled: bool ask_strategy: Dict[str, Any] bid_strategy: Dict[str, Any] bot_name: str state: str runmode: str class TradeSchema(BaseModel): trade_id: int pair: str is_open: bool exchange: str amount: float amount_requested: float stake_amount: float strategy: str buy_tag: Optional[str] timeframe: int fee_open: Optional[float] fee_open_cost: Optional[float] fee_open_currency: Optional[str] fee_close: Optional[float] fee_close_cost: Optional[float] fee_close_currency: Optional[str] open_date: str open_timestamp: int open_rate: float open_rate_requested: Optional[float] open_trade_value: float close_date: Optional[str] close_timestamp: Optional[int] close_rate: Optional[float] close_rate_requested: Optional[float] close_profit: Optional[float] close_profit_pct: Optional[float] close_profit_abs: Optional[float] profit_ratio: Optional[float] profit_pct: Optional[float] profit_abs: Optional[float] profit_fiat: Optional[float] sell_reason: Optional[str] sell_order_status: Optional[str] stop_loss_abs: Optional[float] stop_loss_ratio: Optional[float] stop_loss_pct: Optional[float] stoploss_order_id: Optional[str] stoploss_last_update: Optional[str] stoploss_last_update_timestamp: Optional[int] initial_stop_loss_abs: Optional[float] initial_stop_loss_ratio: Optional[float] initial_stop_loss_pct: Optional[float] min_rate: Optional[float] max_rate: Optional[float] open_order_id: Optional[str] class OpenTradeSchema(TradeSchema): stoploss_current_dist: Optional[float] stoploss_current_dist_pct: Optional[float] stoploss_current_dist_ratio: Optional[float] stoploss_entry_dist: Optional[float] stoploss_entry_dist_ratio: Optional[float] current_profit: float current_profit_abs: float current_profit_pct: float current_rate: float open_order: Optional[str] class TradeResponse(BaseModel): trades: List[TradeSchema] trades_count: int total_trades: int class ForceBuyResponse(BaseModel): __root__: Union[TradeSchema, StatusMsg] class LockModel(BaseModel): id: int active: bool lock_end_time: str lock_end_timestamp: int lock_time: str lock_timestamp: int pair: str reason: str class Locks(BaseModel): lock_count: int locks: List[LockModel] class DeleteLockRequest(BaseModel): pair: Optional[str] lockid: Optional[int] class Logs(BaseModel): log_count: int logs: List[List] class ForceBuyPayload(BaseModel): pair: str price: Optional[float] ordertype: Optional[OrderTypeValues] class ForceSellPayload(BaseModel): tradeid: str ordertype: Optional[OrderTypeValues] class BlacklistPayload(BaseModel): blacklist: List[str] class BlacklistResponse(BaseModel): blacklist: List[str] blacklist_expanded: List[str] errors: Dict length: int method: List[str] class WhitelistResponse(BaseModel): whitelist: List[str] length: int method: List[str] class DeleteTrade(BaseModel): cancel_order_count: int result: str result_msg: str trade_id: int class PlotConfig_(BaseModel): main_plot: Dict[str, Any] subplots: Dict[str, Any] class PlotConfig(BaseModel): __root__: Union[PlotConfig_, Dict] class StrategyListResponse(BaseModel): strategies: List[str] class StrategyResponse(BaseModel): strategy: str code: str class AvailablePairs(BaseModel): length: int pairs: List[str] pair_interval: List[List[str]] class PairHistory(BaseModel): strategy: str pair: str timeframe: str timeframe_ms: int columns: List[str] data: List[Any] length: int buy_signals: int sell_signals: int last_analyzed: datetime last_analyzed_ts: int data_start_ts: int data_start: str data_stop: str data_stop_ts: int class Config: json_encoders = { datetime: lambda v: v.strftime(DATETIME_PRINT_FORMAT), } class BacktestRequest(BaseModel): strategy: str timeframe: Optional[str] timeframe_detail: Optional[str] timerange: Optional[str] max_open_trades: Optional[int] stake_amount: Optional[Union[float, str]] enable_protections: bool dry_run_wallet: Optional[float] class BacktestResponse(BaseModel): status: str running: bool status_msg: str step: str progress: float trade_count: Optional[float] # TODO: Properly type backtestresult... backtest_result: Optional[Dict[str, Any]] class SysInfo(BaseModel): cpu_pct: List[float] ram_pct: float