Chris Amow
bb84b6e73f
Two things kept the chart quieter than the feed. Higher timeframes only moved once a minute. Tick bars are 1m and the socket filters bar events by the subscriber's timeframe, so on the hourly chart every tick was discarded and only a closed minute passing through the aggregator showed up. They cannot simply be fed to the aggregator — it accumulates with current.v += incoming.v, so the same forming minute re-sent on each tick would add its volume to every higher timeframe again and again. provisional_higher combines the aggregator's committed state with the live minute instead, without mutating it; the next closed minute goes through normally and replaces the result, because the store keys on the bucket timestamp. A test pins the behaviour: five ticks in one minute leave the hour's volume at closed plus live, counted exactly once. Trades known only by their volume were skipped. Level 1 resends only changed fields, so some trades carry a trade stamp and a moved TOTAL_VOLUME with neither LAST_PRICE nor LAST_SIZE. Those now count, with size left at zero rather than guessed from the volume delta — CHART_FUTURES replaces the minute's volume with the exchange's own figure moments later, and two ways of counting the same trades is how double counting starts. Measured: 66 to 74 updates per 90s. The tick throttle drops to 0.25s, which no longer binds. Measured in regular hours the gaps between updates are whole multiples of 1.005s — 2.01, 3.02, 4.03 — which is Schwab conflating LEVEL_ONE_FUTURES to one update per second per symbol. One per second is the source's ceiling, not ours; the longer gaps are seconds in which their feed carried no trade. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
86 lines
3.4 KiB
Python
86 lines
3.4 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.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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daily_anchor_et: str = "18:00"
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manual_lines_path: Path = Path("./data/manual_lines.json")
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# Schwab. Empty until the app's keys are issued; nothing reads them while
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# live_source is yahoo. The token lives under data/ so it lands on the
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# Coolify persistent volume — a rebuild would otherwise log you out, and
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# re-authenticating is an interactive browser flow.
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schwab_api_key: str = ""
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schwab_app_secret: str = ""
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schwab_callback_url: str = "https://chart.amow.com/api/qt"
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schwab_token_path: Path = Path("./data/.schwab_token.json")
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schwab_symbol: str = "/ES"
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# Seconds between forming-bar emissions built from LEVEL_ONE_FUTURES ticks.
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# Set negative to drop the Level 1 subscription and take closed minute bars
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# only. Measured in regular hours, /ES supplies a price-changing trade far
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# faster than this, so the value is the update rate: at 1.0 the throttle was
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# the limiter and the chart felt sluggish.
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schwab_tick_seconds: float = 0.25
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confluence_min_score: float = 28
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# Four hours, chosen from the sweep in scripts/calibrate_alerts.py. Suppression is
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# per price zone, so an unrelated zone still alerts immediately; this only
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# governs how often the *same* area repeats itself.
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alert_cooldown_seconds: int = 14400
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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 live_symbol(self) -> str:
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"""What the live source calls the instrument.
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Yahoo wants ES=F, Schwab wants /ES. Seeding always uses the Yahoo
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symbol, because Yahoo is always the source of history.
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"""
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return self.schwab_symbol if self.live_source == "schwab" else self.yahoo_symbol
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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 = {Timeframe.D1: self.ma_sets__1d}
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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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