Provider abstraction: providers/ package with BaseDataProvider template
One class per provider (TwelveData, Oanda, Tiingo), all subclassing BaseDataProvider which owns cache, validation/cleaning, freshness + boundary guarantees, fetch_range pagination, and streaming stubs — subclasses implement only _fetch_raw. config.json data_providers.active selects the live feed; data_provider.py / oanda_provider.py stay as back-compat shims. Module 16 provider-abstraction tests (253 total green). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Mc7XKYyPySVXiUpcN82QEK
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Harwinder Sekhon
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"""
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ForexBot2 — Oanda v20 data provider
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====================================
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OHLCV candles from the Oanda v20 REST API. All shared behavior (cache,
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validation, boundary guarantees, range pagination) lives in
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`BaseDataProvider`; this module only maps symbols/granularities, parses
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Oanda's candle JSON, and exposes the real bid/ask spread from MBA candles.
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"""
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import logging
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from datetime import datetime
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from typing import Dict, Optional
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import pandas as pd
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import requests
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from app_config import oanda_api_token, oanda_base_url
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from config import PAIR_INFO, PlatformConfig, Timeframe, XAUUSD
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from providers.base import BaseDataProvider, DataIntegrityError
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logger = logging.getLogger(__name__)
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class OandaDataError(DataIntegrityError):
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"""Raised when an Oanda data fetch fails or returns invalid data."""
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class OandaDataProvider(BaseDataProvider):
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"""Oanda v20 REST candle provider."""
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name = "oanda"
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DATA_ERROR = OandaDataError
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OANDA_GRANULARITY = {
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Timeframe.M1: "M1",
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Timeframe.M5: "M5",
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Timeframe.M15: "M15",
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Timeframe.M30: "M30",
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Timeframe.H1: "H1",
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Timeframe.H4: "H4",
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Timeframe.D1: "D",
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Timeframe.W1: "W",
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}
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OANDA_INSTRUMENT = {
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"XAU/USD": "XAU_USD",
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}
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def __init__(
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self,
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config: PlatformConfig,
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api_token: Optional[str] = None,
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base_url: Optional[str] = None,
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):
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super().__init__(config)
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# Credentials default to the config.json `oanda` block / env vars
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# so the provider registry can build this class with config only.
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if api_token is None:
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api_token = oanda_api_token()
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if base_url is None:
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base_url = oanda_base_url()
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self._base_url = base_url.rstrip("/")
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self._session = requests.Session()
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self._session.headers.update({
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"Authorization": f"Bearer {api_token}",
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"Accept-Datetime-Format": "RFC3339",
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"Content-Type": "application/json",
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})
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self._spread_cache: Dict[str, float] = {}
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# ── Public extras ──────────────────────────────────────────────
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def get_spread(self, symbol: str = XAUUSD) -> float:
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return self._spread_cache.get(
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symbol, PAIR_INFO.get(symbol, PAIR_INFO[XAUUSD])["default_spread"])
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# ── Raw fetch ──────────────────────────────────────────────────
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def _fetch_raw(
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self,
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symbol: str,
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timeframe: Timeframe,
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outputsize: int,
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start: Optional[datetime] = None,
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end: Optional[datetime] = None,
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) -> pd.DataFrame:
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if start is not None or end is not None:
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return self._fetch_oanda_candles(
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symbol, timeframe, outputsize, start, end)
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return self._fetch_oanda_candles(symbol, timeframe, outputsize)
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def _to_oanda_instrument(self, symbol: str) -> str:
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if symbol in self.OANDA_INSTRUMENT:
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return self.OANDA_INSTRUMENT[symbol]
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return symbol.replace("/", "_")
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def _fetch_oanda_candles(
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self,
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symbol: str,
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timeframe: Timeframe,
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count: int,
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start: Optional[datetime] = None,
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end: Optional[datetime] = None,
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) -> pd.DataFrame:
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instrument = self._to_oanda_instrument(symbol)
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granularity = self.OANDA_GRANULARITY.get(timeframe)
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if granularity is None:
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raise OandaDataError(
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f"Unsupported timeframe {timeframe} for Oanda")
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url = f"{self._base_url}/v3/instruments/{instrument}/candles"
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params = {
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"granularity": granularity,
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"price": "MBA",
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"dailyAlignment": 0,
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"alignmentTimezone": "Etc/UTC",
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}
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# v20 rejects `count` combined with both `from` and `to`; a date
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# window replaces it (used by fetch_range pagination).
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if start is not None and end is not None:
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params["from"] = pd.Timestamp(start).isoformat()
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params["to"] = pd.Timestamp(end).isoformat()
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else:
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params["count"] = min(count, self.MAX_BARS_PER_REQUEST)
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try:
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resp = self._session.get(url, params=params, timeout=30)
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except requests.RequestException as e:
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raise OandaDataError(
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f"Oanda candle fetch failed for {instrument}: {e}") from e
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if resp.status_code != 200:
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raise OandaDataError(
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f"Oanda candle fetch failed for {instrument}: "
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f"HTTP {resp.status_code}: {resp.text[:300]}")
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try:
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data = resp.json()
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except ValueError as e:
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raise OandaDataError(
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f"Oanda candle response for {instrument} is not valid "
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f"JSON: {e}") from e
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candles = data.get("candles", [])
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if not candles:
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raise OandaDataError(
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f"Empty candle response from Oanda for {instrument}")
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rows = []
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last_bid_close = None
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last_ask_close = None
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for c in candles:
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if not c.get("complete", False):
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continue
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mid = c.get("mid", {})
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bid = c.get("bid", {})
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ask = c.get("ask", {})
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rows.append({
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"Datetime": pd.Timestamp(c["time"]).tz_convert("UTC"),
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"Open": float(mid.get("o", 0)),
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"High": float(mid.get("h", 0)),
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"Low": float(mid.get("l", 0)),
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"Close": float(mid.get("c", 0)),
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"Volume": int(c.get("volume", 0)),
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})
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if bid and ask:
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last_bid_close = float(bid.get("c", 0))
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last_ask_close = float(ask.get("c", 0))
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if not rows:
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raise OandaDataError(
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f"No complete candles from Oanda for {instrument}")
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if last_bid_close and last_ask_close:
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self._spread_cache[symbol] = round(
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last_ask_close - last_bid_close, 4)
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df = pd.DataFrame(rows)
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df = df.set_index("Datetime")
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df = df.sort_index()
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if df.index.tz is None:
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df.index = df.index.tz_localize("UTC")
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df.index.name = "Datetime"
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for col in ("Open", "High", "Low", "Close"):
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df[col] = pd.to_numeric(df[col], errors="coerce")
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df["Volume"] = pd.to_numeric(df["Volume"], errors="coerce").fillna(0).astype(float)
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logger.debug(
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"Fetched %d bars for %s @ %s from Oanda",
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len(df), instrument, granularity)
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return df
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