chart/app/config.py
Chris Amow d526001742 Add the Schwab live source: real-time /ES minute bars
Verified against a live account before and after writing it. CHART_FUTURES
delivers one true-OHLCV minute bar per symbol per minute, LEVEL_ONE_FUTURES
reports delayed: false, and consecutive bars arrived sixty seconds apart through
the production code path.

Yahoo stays. Schwab serves no futures history whatever, so seed_source resolves
to Yahoo even when SEED_SOURCE=schwab is asked for — the pairing is the intended
configuration rather than a fallback. The symbols differ, ES=F against /ES, so
Settings.live_symbol picks the live one while seeding always uses Yahoo's.

Three findings worth keeping, each of which cost a round trip:

- get_quote() singular returns the wrong instrument entirely. It puts the symbol
  in the URL path, where the leading slash is normalised away, so /ES resolves to
  Eversource Energy at $72 and returns HTTP 200 with a populated body. Only
  get_quotes() plural, which passes symbols as a query parameter, returns the
  future. A 200 is not evidence; assetMainType is.
- Streaming requires the Accounts and Trading product. StreamClient.login() reads
  /trader/v1/userPreference for its socket URL, and that path does not exist in
  Market Data Production.
- /ES resolves to the active contract on Schwab's side, so the contract roll
  handling the plan left open needs no code.

The stream drops the oldest queued message rather than stalling the socket, and
surfaces a dead pump task instead of waiting forever on a queue nothing fills.
schwab-py moves into requirements.txt, imported only when LIVE_SOURCE=schwab.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-10 05:23:20 -05:00

80 lines
3 KiB
Python

from pathlib import Path
from pydantic_settings import BaseSettings, SettingsConfigDict
from app.bars.models import Timeframe
TIMEFRAME_WEIGHT = {
Timeframe.M1: 1,
Timeframe.M2: 1,
Timeframe.M5: 1,
Timeframe.M15: 2,
Timeframe.M30: 3,
Timeframe.H1: 4,
Timeframe.D1: 16,
}
MA_WEIGHT_FACTOR = 0.75
class Settings(BaseSettings):
model_config = SettingsConfigDict(env_file=".env", extra="ignore")
live_source: str = "yahoo"
seed_source: str = "yahoo"
yahoo_symbol: str = "ES=F"
yahoo_poll_seconds: float = 20
seed_1h_range: str = "730d"
seed_1m_range: str = "8d"
timeframes: str = "1m,5m,15m,30m,1h,1d"
base_timeframes: str = "1m,30m,1d"
max_bars_per_tf: int = 5000
ma_sets__1d: str = "sma10,sma20,sma50,sma100,sma200"
daily_anchor_et: str = "18:00"
manual_lines_path: Path = Path("./data/manual_lines.json")
# Schwab. Empty until the app's keys are issued; nothing reads them while
# live_source is yahoo. The token lives under data/ so it lands on the
# Coolify persistent volume — a rebuild would otherwise log you out, and
# re-authenticating is an interactive browser flow.
schwab_api_key: str = ""
schwab_app_secret: str = ""
schwab_callback_url: str = "https://chart.amow.com/api/qt"
schwab_token_path: Path = Path("./data/.schwab_token.json")
schwab_symbol: str = "/ES"
confluence_min_score: float = 28
# Four hours, chosen from the sweep in scripts/calibrate_alerts.py. Suppression is
# per price zone, so an unrelated zone still alerts immediately; this only
# governs how often the *same* area repeats itself.
alert_cooldown_seconds: int = 14400
ntfy_topic: str = ""
ntfy_server: str = "https://ntfy.sh"
chart_auth_token: str = ""
replay_file: Path | None = None
@property
def live_symbol(self) -> str:
"""What the live source calls the instrument.
Yahoo wants ES=F, Schwab wants /ES. Seeding always uses the Yahoo
symbol, because Yahoo is always the source of history.
"""
return self.schwab_symbol if self.live_source == "schwab" else self.yahoo_symbol
@property
def enabled_timeframes(self) -> list[Timeframe]:
return [Timeframe(value.strip()) for value in self.timeframes.split(",") if value.strip()]
@property
def ma_sets(self) -> dict[Timeframe, list[tuple[str, int]]]:
configured = {Timeframe.D1: self.ma_sets__1d}
result: dict[Timeframe, list[tuple[str, int]]] = {}
for tf, value in configured.items():
definitions = []
for item in filter(None, (part.strip().lower() for part in value.split(","))):
kind = "sma" if item.startswith("sma") else "ema" if item.startswith("ema") else ""
if not kind or not item[len(kind) :].isdigit():
raise ValueError(f"Invalid MA definition: {item}")
definitions.append((kind, int(item[len(kind) :])))
result[tf] = definitions
return result