Files
ForexBot2/providers/oanda.py
T
Harwinder Sekhon d2e679cd20 providers: keep real news bars (snap-back bad-print rule), Oanda retry ladder, scan_kind=failed
2026-09-07 signal-log inspection follow-up — three fixes that do not depend on sample size.

- providers/base.py: the signal-side 10σ outlier filter is now a bad-print filter. A >10σ
  close-to-close bar is dropped only when the NEXT close snaps back ≥80% of the way
  (OUTLIER_SIGMA / OUTLIER_REVERT_FRACTION); persisting moves and the newest bar are kept.
  The unconditional rule deleted ~36 real M5 news bars/yr in the backtester (whole-frame σ)
  and a different ~24/yr live (fetch-window σ) — e.g. the 2026-09-04 12:30 UTC NFP bar
  vanished from M5+M15 and the 12:35 scan was a byte-identical repeat of 12:30. 3-yr Oanda
  drops are now M5 2 / M15 1 / H1 0.
- providers/oanda.py: transient 401/5xx/network faults retry along RETRY_DELAYS_S=(2,5,10)s
  under RETRY_BUDGET_S=45s. 11 boundary scans in two days had lost their primary frame at
  xx:00:22–:26 UTC; one 2 s retry could not outlast the top-of-hour blip.
- signal_aggregator/_log_signal: a scan whose primary fetch failed logs scan_kind='failed'
  (price 0, no signal); analyze_signal_log.parity_report skips it like 'blocked'.
- test_all.py: 466 tests (+6): retry ladder walks all delays, 5xx blip recovers on the third
  attempt, retry budget stops the ladder, persisting/newest/partially-retraced 10σ bars kept,
  failed-scan row kind, parity skip.
- CLAUDE.md: cleaning rule, retry ladder, failed scan kind, dated current-state note.

Book impact at $0.65 (rule 1 still passes everywhere, both halves positive):
  12mo  M5 557/+112.21/PF1.56 → 560/+108.81/1.54   M15 397/+73.93/1.53 → 398/+74.61/1.53   H1 identical
  3yr   M5 857/+161.3/1.53 → 870/+153.6/1.50   M15 1086/+148.7/1.37 → 1092/+151.9/1.38
        H1 255/+70.5/1.98 → 253/+70.0/1.98   H4 113/+22.7/1.63 → 114/+21.7/1.59
Only trades on the previously-deleted event bars move; the pinned M5/M15 CSVs are no longer
byte-reproducible and should be regenerated at the next re-pin.

Claude-Session: https://claude.ai/code/session_01NDnBxJ2y8GRUM6ZNFJs1hZ
2026-09-07 11:07:29 -04:00

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"""
ForexBot2 — Oanda v20 data provider
====================================
OHLCV candles from the Oanda v20 REST API. All shared behavior (cache,
validation, boundary guarantees, range pagination) lives in
`BaseDataProvider`; this module only maps symbols/granularities, parses
Oanda's candle JSON, and exposes the real bid/ask spread from MBA candles.
"""
import logging
import time
from datetime import datetime
from typing import Dict, Optional
import pandas as pd
import requests
from app_config import oanda_api_token, oanda_base_url
from config import PAIR_INFO, PlatformConfig, Timeframe, XAUUSD
from providers.base import BaseDataProvider, DataIntegrityError
logger = logging.getLogger(__name__)
class OandaDataError(DataIntegrityError):
"""Raised when an Oanda data fetch fails or returns invalid data."""
class OandaDataProvider(BaseDataProvider):
"""Oanda v20 REST candle provider."""
name = "oanda"
DATA_ERROR = OandaDataError
# Transient-fault retry ladder (see _fetch_oanda_candles): sleeps
# between attempts, plus a wall-clock cap on the whole sequence.
RETRY_DELAYS_S = (2.0, 5.0, 10.0)
RETRY_BUDGET_S = 45.0
RETRY_DELAY_S = RETRY_DELAYS_S[0] # first delay; kept for callers/tests
OANDA_GRANULARITY = {
Timeframe.M1: "M1",
Timeframe.M5: "M5",
Timeframe.M15: "M15",
Timeframe.M30: "M30",
Timeframe.H1: "H1",
Timeframe.H4: "H4",
Timeframe.D1: "D",
Timeframe.W1: "W",
}
OANDA_INSTRUMENT = {
"XAU/USD": "XAU_USD",
}
def __init__(
self,
config: PlatformConfig,
api_token: Optional[str] = None,
base_url: Optional[str] = None,
):
super().__init__(config)
# Credentials default to the config.json `oanda` block / env vars
# so the provider registry can build this class with config only.
if api_token is None:
api_token = oanda_api_token()
if base_url is None:
base_url = oanda_base_url()
self._base_url = base_url.rstrip("/")
self._session = requests.Session()
self._session.headers.update({
"Authorization": f"Bearer {api_token}",
"Accept-Datetime-Format": "RFC3339",
"Content-Type": "application/json",
})
self._spread_cache: Dict[str, float] = {}
# ── Public extras ──────────────────────────────────────────────
def get_spread(self, symbol: str = XAUUSD) -> float:
return self._spread_cache.get(
symbol, PAIR_INFO.get(symbol, PAIR_INFO[XAUUSD])["default_spread"])
# ── Raw fetch ──────────────────────────────────────────────────
def _fetch_raw(
self,
symbol: str,
timeframe: Timeframe,
outputsize: int,
start: Optional[datetime] = None,
end: Optional[datetime] = None,
) -> pd.DataFrame:
if start is not None or end is not None:
return self._fetch_oanda_candles(
symbol, timeframe, outputsize, start, end)
return self._fetch_oanda_candles(symbol, timeframe, outputsize)
def _to_oanda_instrument(self, symbol: str) -> str:
try:
return self.OANDA_INSTRUMENT[symbol]
except KeyError:
raise OandaDataError(
f"Unsupported symbol {symbol!r} for Oanda") from None
def _fetch_oanda_candles(
self,
symbol: str,
timeframe: Timeframe,
count: int,
start: Optional[datetime] = None,
end: Optional[datetime] = None,
) -> pd.DataFrame:
instrument = self._to_oanda_instrument(symbol)
granularity = self.OANDA_GRANULARITY.get(timeframe)
if granularity is None:
raise OandaDataError(
f"Unsupported timeframe {timeframe} for Oanda")
url = f"{self._base_url}/v3/instruments/{instrument}/candles"
params = {
"granularity": granularity,
"price": "MBA",
"dailyAlignment": 0,
"alignmentTimezone": "Etc/UTC",
}
# v20 rejects `count` combined with both `from` and `to`; a date
# window replaces it (used by fetch_range pagination).
if start is not None and end is not None:
params["from"] = pd.Timestamp(start).isoformat()
params["to"] = pd.Timestamp(end).isoformat()
else:
params["count"] = min(count, self.MAX_BARS_PER_REQUEST)
# Retry ladder for transient faults: Oanda's sporadic spurious
# 401s (~15-20/day on the practice API — the same token succeeds
# on adjacent requests), 5xx and network errors. Other 4xx (bad
# request, 429) are never retried; a real credential problem
# fails every attempt and raises as before. The 2026-09-07
# signal-log audit found 11 boundary scans in two days that lost
# their primary frame at xx:00:22-:26 UTC: a single 2 s retry
# could not outlast a 10-15 s provider blip at the top of the
# hour, and a scan without its primary frame logs a price-0
# NEUTRAL row. RETRY_BUDGET_S bounds the whole sequence so a scan
# (three fetches) still finishes well inside an M5 bar.
last_err: Optional[OandaDataError] = None
resp = None
attempts = 1 + len(self.RETRY_DELAYS_S)
started = time.monotonic()
for attempt in range(attempts):
if attempt:
delay = self.RETRY_DELAYS_S[attempt - 1]
if time.monotonic() - started + delay > self.RETRY_BUDGET_S:
logger.warning(
f"Oanda fetch for {instrument}: retry budget "
f"({self.RETRY_BUDGET_S:.0f}s) exhausted after "
f"{attempt} attempt(s) — giving up")
break
time.sleep(delay)
try:
resp = self._session.get(url, params=params, timeout=30)
except requests.RequestException as e:
last_err = OandaDataError(
f"Oanda candle fetch failed for {instrument}: {e}")
last_err.__cause__ = e
resp = None
logger.warning(
f"Oanda fetch for {instrument} attempt "
f"{attempt + 1}/{attempts} failed: {e}")
continue
if resp.status_code == 401 or resp.status_code >= 500:
last_err = OandaDataError(
f"Oanda candle fetch failed for {instrument}: "
f"HTTP {resp.status_code}: {resp.text[:300]}")
logger.warning(
f"Oanda fetch for {instrument} attempt "
f"{attempt + 1}/{attempts} got HTTP {resp.status_code}")
resp = None
continue
break
if resp is None:
raise last_err
if resp.status_code != 200:
raise OandaDataError(
f"Oanda candle fetch failed for {instrument}: "
f"HTTP {resp.status_code}: {resp.text[:300]}")
try:
data = resp.json()
except ValueError as e:
raise OandaDataError(
f"Oanda candle response for {instrument} is not valid "
f"JSON: {e}") from e
candles = data.get("candles", [])
if not candles:
raise OandaDataError(
f"Empty candle response from Oanda for {instrument}")
rows = []
last_bid_close = None
last_ask_close = None
skipped_malformed = 0
for c in candles:
if not c.get("complete", False):
continue
mid = c.get("mid", {})
bid = c.get("bid", {})
ask = c.get("ask", {})
# A candle missing any OHLC field must be SKIPPED, never
# defaulted to 0.0: a zero price flows through cleaning as a
# "legit" bar and poisons ATR/Keltner/SL math — and a
# mid-frame zero Close makes pct_change() emit inf, which
# NaNs the std and disarms the 10σ outlier filter for the
# whole frame (2026-08-04 audit, I45).
if any(mid.get(k) is None for k in ("o", "h", "l", "c")):
skipped_malformed += 1
continue
rows.append({
"Datetime": pd.Timestamp(c["time"]).tz_convert("UTC"),
"Open": float(mid["o"]),
"High": float(mid["h"]),
"Low": float(mid["l"]),
"Close": float(mid["c"]),
"Volume": int(c.get("volume", 0)),
})
if bid and ask:
last_bid_close = float(bid.get("c", 0))
last_ask_close = float(ask.get("c", 0))
if skipped_malformed:
logger.warning(
"Oanda returned %d malformed candle(s) for %s (missing "
"OHLC fields) — skipped", skipped_malformed, instrument)
if not rows:
raise OandaDataError(
f"No complete candles from Oanda for {instrument}")
if last_bid_close and last_ask_close:
self._spread_cache[symbol] = round(
last_ask_close - last_bid_close, 4)
df = pd.DataFrame(rows)
df = df.set_index("Datetime")
df = df.sort_index()
if df.index.tz is None:
df.index = df.index.tz_localize("UTC")
df.index.name = "Datetime"
for col in ("Open", "High", "Low", "Close"):
df[col] = pd.to_numeric(df[col], errors="coerce")
df["Volume"] = pd.to_numeric(df["Volume"], errors="coerce").fillna(0).astype(float)
logger.debug(
"Fetched %d bars for %s @ %s from Oanda",
len(df), instrument, granularity)
return df