Harwinder
b1687582ec
Multi-indicator signal engine with RSI, MACD, Bollinger Bands, EMA trend filter, ADX strength gate, Stochastic, ATR, and higher-timeframe trend confirmation. Twelve Data API client with in-memory cache and rate limiting. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
103 lines
3.0 KiB
Python
103 lines
3.0 KiB
Python
"""Twelve Data API client with in-memory cache and simple rate limiting."""
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from __future__ import annotations
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import asyncio
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import logging
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import time
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from typing import Any
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import httpx
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import pandas as pd
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from config import SUPPORTED_PAIRS, SUPPORTED_TIMEFRAMES, TWELVE_DATA_API_KEY
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logger = logging.getLogger(__name__)
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_API_URL = "https://api.twelvedata.com/time_series"
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_TTL_SECONDS: dict[str, int] = {
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"15min": 800,
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"1h": 3500,
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"4h": 14000,
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"1day": 43000,
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}
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_cache: dict[tuple[str, str], tuple[float, pd.DataFrame]] = {}
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_call_times: list[float] = []
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_lock = asyncio.Lock()
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_MAX_CALLS_PER_MIN = 8
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_WINDOW = 60.0
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def _to_api_symbol(pair: str) -> str:
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"""Convert 'EURUSD' to 'EUR/USD'."""
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return f"{pair[:3]}/{pair[3:]}"
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async def _respect_rate_limit() -> None:
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now = time.monotonic()
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cutoff = now - _WINDOW
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while _call_times and _call_times[0] < cutoff:
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_call_times.pop(0)
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if len(_call_times) >= _MAX_CALLS_PER_MIN:
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sleep_for = _WINDOW - (now - _call_times[0]) + 0.1
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logger.info("Rate limit hit, sleeping %.2fs", sleep_for)
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await asyncio.sleep(sleep_for)
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_call_times.append(time.monotonic())
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async def fetch_ohlc(pair: str, timeframe: str, size: int = 200) -> pd.DataFrame:
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"""Fetch OHLC candles for a forex pair from Twelve Data.
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Returns a DataFrame indexed by datetime (ascending) with columns
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[open, high, low, close]. Cached per (pair, timeframe) with timeframe-aware TTL.
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"""
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pair = pair.upper()
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if pair not in SUPPORTED_PAIRS:
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raise ValueError(f"Unsupported pair: {pair}")
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if timeframe not in SUPPORTED_TIMEFRAMES:
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raise ValueError(f"Unsupported timeframe: {timeframe}")
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key = (pair, timeframe)
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ttl = _TTL_SECONDS[timeframe]
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now = time.time()
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async with _lock:
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cached = _cache.get(key)
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if cached and (now - cached[0]) < ttl:
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return cached[1]
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await _respect_rate_limit()
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params: dict[str, Any] = {
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"symbol": _to_api_symbol(pair),
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"interval": timeframe,
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"outputsize": size,
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"apikey": TWELVE_DATA_API_KEY,
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"format": "JSON",
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}
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try:
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async with httpx.AsyncClient(timeout=15.0) as client:
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resp = await client.get(_API_URL, params=params)
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resp.raise_for_status()
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data = resp.json()
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except httpx.HTTPError as e:
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logger.error("Twelve Data HTTP error: %s", e)
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raise
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if data.get("status") == "error" or "values" not in data:
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msg = data.get("message", "Unknown API error")
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logger.error("Twelve Data API error: %s", msg)
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raise ValueError(f"API error: {msg}")
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df = pd.DataFrame(data["values"])
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df["datetime"] = pd.to_datetime(df["datetime"])
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for col in ("open", "high", "low", "close"):
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df[col] = df[col].astype(float)
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df = df.set_index("datetime")[["open", "high", "low", "close"]].sort_index()
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_cache[key] = (now, df)
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return df
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