63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
from pathlib import Path
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from pydantic_settings import BaseSettings, SettingsConfigDict
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from app.bars.models import Timeframe
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TIMEFRAME_WEIGHT = {
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Timeframe.M1: 1,
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Timeframe.M2: 1,
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Timeframe.M5: 1,
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Timeframe.M15: 2,
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Timeframe.M30: 3,
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Timeframe.H1: 4,
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Timeframe.H4: 8,
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Timeframe.D1: 16,
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}
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MA_WEIGHT_FACTOR = 0.75
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class Settings(BaseSettings):
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model_config = SettingsConfigDict(env_file=".env", extra="ignore")
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live_source: str = "yahoo"
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seed_source: str = "yahoo"
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yahoo_symbol: str = "ES=F"
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yahoo_poll_seconds: float = 20
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seed_1h_range: str = "730d"
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seed_1m_range: str = "8d"
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timeframes: str = "1m,5m,15m,30m,1h,1d"
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base_timeframes: str = "1m,30m,1d"
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max_bars_per_tf: int = 5000
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ma_sets__1d: str = "sma10,sma20,sma50,sma100,sma200"
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ma_sets__1h: str = ""
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daily_anchor_et: str = "18:00"
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manual_lines_path: Path = Path("./data/manual_lines.json")
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confluence_min_score: float = 28
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alert_cooldown_seconds: int = 900
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ntfy_topic: str = ""
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ntfy_server: str = "https://ntfy.sh"
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chart_auth_token: str = ""
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replay_file: Path | None = None
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@property
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def enabled_timeframes(self) -> list[Timeframe]:
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return [Timeframe(value.strip()) for value in self.timeframes.split(",") if value.strip()]
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@property
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def ma_sets(self) -> dict[Timeframe, list[tuple[str, int]]]:
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configured = {
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Timeframe.D1: self.ma_sets__1d,
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Timeframe.H1: self.ma_sets__1h,
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}
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result: dict[Timeframe, list[tuple[str, int]]] = {}
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for tf, value in configured.items():
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definitions = []
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for item in filter(None, (part.strip().lower() for part in value.split(","))):
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kind = "sma" if item.startswith("sma") else "ema" if item.startswith("ema") else ""
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if not kind or not item[len(kind) :].isdigit():
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raise ValueError(f"Invalid MA definition: {item}")
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definitions.append((kind, int(item[len(kind) :])))
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result[tf] = definitions
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return result
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