Add calendar research infra: FF scraper + verified event store
Scrapes Forex Factory weekly pages (epoch datelines, actual/forecast/ impact/betterWorse) into backtest/cache/calendar.parquet (gitignored; rebuild with the scraper). Timestamps verified: NFP/CPI/ECB times exact across DST, and high-impact event bars average 3.5x ATR with the spike vanishing at +/-1h shifts. calendar_store provides precise_events and event_window_mask for screens and counterfactuals.
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"""Forex Factory calendar scraper -> backtest/cache/calendar.parquet.
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Fetches weekly calendar pages and parses the event JSON embedded in
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`window.calendarComponentStates` (the `days:` array). Event `dateline`
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is a unix epoch, so timestamps carry no timezone ambiguity — verified
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2026-07-11 against known release times (NFP 12:30/13:30 UTC across DST,
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ECB 12:15/13:15) and against EUR/USD M15 volatility: the bar containing
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a high-impact event averages 3.5x normal range, and shifting event
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times by ±1h destroys that alignment.
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Usage:
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python backtest/research/ff_calendar_scraper.py --start 2024-01-01 --end 2026-07-13
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python backtest/research/ff_calendar_scraper.py # refresh: last stored week -> today
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Merges into the existing parquet on event (id, dateline), so refreshing
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is idempotent and also picks up revised `actual` values for recent weeks.
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Be polite: ~1.6s between requests (a full year is ~52 requests).
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"""
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import argparse
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import json
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import time
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from datetime import date, timedelta
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from pathlib import Path
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from typing import List, Optional
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import pandas as pd
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import requests
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CACHE_DIR = Path(__file__).resolve().parent.parent / "cache"
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PARQUET = CACHE_DIR / "calendar.parquet"
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UA = ("Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 "
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"(KHTML, like Gecko) Chrome/126.0 Safari/537.36")
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FIELDS = ["id", "dateline", "name", "country", "currency", "impactName",
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"timeLabel", "timeMasked", "actual", "forecast", "previous",
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"revision", "actualBetterWorse"]
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def week_url(d: date) -> str:
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return (f"https://www.forexfactory.com/calendar?week="
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f"{d.strftime('%b').lower()}{d.day}.{d.year}")
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def extract_days(html: str) -> Optional[list]:
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"""Balanced-bracket extraction of the `days:` JSON array."""
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i = html.find("days:")
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if i < 0:
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return None
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j = html.find("[", i)
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depth, in_str, esc = 0, False, False
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for k in range(j, len(html)):
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ch = html[k]
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if in_str:
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if esc:
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esc = False
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elif ch == "\\":
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esc = True
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elif ch == '"':
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in_str = False
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else:
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if ch == '"':
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in_str = True
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elif ch == "[":
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depth += 1
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elif ch == "]":
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depth -= 1
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if depth == 0:
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return json.loads(html[j:k + 1])
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return None
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def fetch_week(sess: requests.Session, d: date, retries: int = 4) -> Optional[List[dict]]:
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for attempt in range(retries):
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try:
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r = sess.get(week_url(d), timeout=30)
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if r.status_code == 200:
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days = extract_days(r.text)
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if days is not None:
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return [{k: e.get(k) for k in FIELDS}
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for day in days for e in day.get("events", [])]
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except requests.RequestException:
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pass
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time.sleep(5 * (attempt + 1))
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return None
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def scrape(start: date, end: date) -> pd.DataFrame:
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sess = requests.Session()
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sess.headers["User-Agent"] = UA
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rows: List[dict] = []
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failed: List[date] = []
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d = start
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while d <= end:
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week_rows = fetch_week(sess, d)
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if week_rows is None:
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failed.append(d)
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print(f"FAILED week {d}")
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else:
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rows.extend(week_rows)
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d += timedelta(days=7)
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time.sleep(1.6)
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if failed:
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print(f"WARNING: {len(failed)} weeks failed: {failed}")
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return pd.DataFrame(rows)
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def merge_into_store(new: pd.DataFrame, path: Path = PARQUET) -> pd.DataFrame:
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if path.exists():
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old = pd.read_parquet(path)
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combined = pd.concat([old, new])
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else:
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combined = new
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# keep="last": a refresh overwrites stale rows (actuals fill in
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# after release, revisions land weeks later).
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combined = (combined.drop_duplicates(subset=["id", "dateline"], keep="last")
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.sort_values("dateline").reset_index(drop=True))
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combined.to_parquet(path, index=False)
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return combined
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def main() -> None:
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ap = argparse.ArgumentParser(description=__doc__.splitlines()[0])
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ap.add_argument("--start", type=date.fromisoformat, default=None)
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ap.add_argument("--end", type=date.fromisoformat, default=date.today())
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args = ap.parse_args()
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start = args.start
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if start is None:
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if PARQUET.exists():
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last = pd.read_parquet(PARQUET).dateline.max()
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start = pd.Timestamp(last, unit="s").date() - timedelta(days=7)
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else:
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start = date(2024, 1, 1)
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print(f"Scraping {start} -> {args.end}")
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new = scrape(start, args.end)
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combined = merge_into_store(new)
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print(f"Store: {len(combined)} events "
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f"({pd.Timestamp(combined.dateline.min(), unit='s')} -> "
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f"{pd.Timestamp(combined.dateline.max(), unit='s')}) -> {PARQUET}")
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if __name__ == "__main__":
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main()
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