Backend:
- ff_calendar: add series_id column (migration) + FF_TO_FRED mapping dict
(NFP→PAYEMS, CPI→CPIAUCSL, Jobless Claims→ICSA, GDP→GDPC1, FEDFUNDS, PCE)
- import_csv + sync_live now populate series_id on each FF event
- New GET /api/eco/series/{id}/history: FRED time series + linked FF events
(surprises, forecast, actual) merged by date — enables context queries
Frontend:
- New MacroSeriesPage.tsx: sidebar with 11 FRED series grouped by category,
recharts ComposedChart with area + z-score surprise reference lines (|z|≥1.5),
KPI cards (latest/prev/min/max), FF events table (actual vs forecast coloring),
z-score bar chart for recent surprises, range selector (1Y/2Y/5Y/10Y/All)
- Route /macro-series + Sidebar entry "Macro Series"
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
346 lines
12 KiB
Python
346 lines
12 KiB
Python
"""
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Forex Factory calendar service.
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- CSV bulk import from forex_factory_cache.csv (2007-2025)
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- Live sync from nfs.faireconomy.media JSON endpoint (this week / next week)
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"""
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import csv
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import json
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import logging
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from datetime import datetime, timezone, timedelta
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from typing import Any, Dict, List, Optional
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import httpx
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logger = logging.getLogger(__name__)
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_FF_THIS_WEEK_URL = "https://nfs.faireconomy.media/ff_calendar_thisweek.json"
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_FF_NEXT_WEEK_URL = "https://nfs.faireconomy.media/ff_calendar_nextweek.json"
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# Map FF impact strings → normalized
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_IMPACT_MAP = {
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"High Impact Expected": "high",
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"High": "high",
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"Medium Impact Expected": "medium",
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"Medium": "medium",
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"Low Impact Expected": "low",
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"Low": "low",
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"Non-Economic": "non-economic",
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"Holiday": "non-economic",
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}
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# Currencies we care about (drop 'All' pseudo-currency)
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SUPPORTED_CURRENCIES = {"USD", "EUR", "GBP", "JPY", "AUD", "CAD", "NZD", "CHF", "CNY"}
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# ── FF event name → FRED series_id mapping ────────────────────────────────────
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# Exact FF event names → our FRED series catalog
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FF_TO_FRED: dict[str, str] = {
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# Employment
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"Non-Farm Employment Change": "PAYEMS",
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"ADP Non-Farm Employment Change": "PAYEMS",
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"Unemployment Rate": "UNRATE",
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"Unemployment Claims": "ICSA",
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# Inflation — CPI
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"CPI m/m": "CPIAUCSL",
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"CPI y/y": "CPIAUCSL",
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"Core CPI m/m": "CPILFESL",
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"Core CPI y/y": "CPILFESL",
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# Inflation — PCE
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"Core PCE Price Index m/m": "PCEPILFE",
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"Core PCE Price Index y/y": "PCEPILFE",
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# Monetary policy
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"Federal Funds Rate": "FEDFUNDS",
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"FOMC Statement": "FEDFUNDS",
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# Growth — GDP
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"Advance GDP q/q": "GDPC1",
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"Prelim GDP q/q": "GDPC1",
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"Final GDP q/q": "GDPC1",
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"GDP q/q": "GDPC1",
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}
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def _parse_ff_datetime(dt_str: str) -> tuple[str, str]:
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"""
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Parse an ISO datetime with offset (e.g. '2007-01-05T17:00:00+03:30')
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into (event_date YYYY-MM-DD UTC, event_time HH:MM UTC).
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"""
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try:
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dt = datetime.fromisoformat(dt_str)
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dt_utc = dt.astimezone(timezone.utc)
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return dt_utc.strftime("%Y-%m-%d"), dt_utc.strftime("%H:%M")
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except Exception:
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# Fallback: take the date/time literally
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parts = dt_str[:16].split("T")
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return parts[0], parts[1] if len(parts) > 1 else "00:00"
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def import_csv(csv_path: str, progress_cb=None) -> Dict[str, Any]:
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"""
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Bulk-import forex_factory_cache.csv into ff_calendar table.
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Skips non-economic events and unsupported currencies.
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Returns {inserted, skipped, total}.
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"""
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from services.database import get_conn
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conn = get_conn()
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inserted = 0
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skipped = 0
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total = 0
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try:
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with open(csv_path, encoding="utf-8", errors="replace") as f:
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reader = csv.DictReader(f)
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batch = []
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for row in reader:
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total += 1
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currency = (row.get("Currency") or "").strip()
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impact_raw = (row.get("Impact") or "").strip()
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impact = _IMPACT_MAP.get(impact_raw, "low")
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# Skip non-economic and unsupported currencies
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if currency not in SUPPORTED_CURRENCIES:
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skipped += 1
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continue
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if impact == "non-economic":
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skipped += 1
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continue
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event_name = (row.get("Event") or "").strip()
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if not event_name:
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skipped += 1
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continue
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dt_str = (row.get("DateTime") or "").strip()
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event_date, event_time = _parse_ff_datetime(dt_str)
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actual = (row.get("Actual") or "").strip() or None
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forecast = (row.get("Forecast") or "").strip() or None
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previous = (row.get("Previous") or "").strip() or None
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detail = (row.get("Detail") or "").strip() or None
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series_id = FF_TO_FRED.get(event_name)
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batch.append((
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event_date, event_time, currency, impact, event_name,
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actual, forecast, previous, series_id, detail, "ff_cache",
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))
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if len(batch) >= 500:
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_upsert_batch(conn, batch)
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inserted += len(batch)
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batch = []
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if progress_cb:
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progress_cb({"inserted": inserted, "total": total})
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if batch:
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_upsert_batch(conn, batch)
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inserted += len(batch)
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conn.commit()
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print(f"[FF import] Done: {inserted} inserted, {skipped} skipped, {total} total", flush=True)
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return {"inserted": inserted, "skipped": skipped, "total": total}
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except Exception as e:
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logger.error(f"[FF import] Failed: {e}")
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print(f"[FF import] ERROR: {e}", flush=True)
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return {"error": str(e)}
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finally:
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conn.close()
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def _upsert_batch(conn, batch: list):
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conn.executemany(
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"""INSERT INTO ff_calendar
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(event_date, event_time, currency, impact, event_name,
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actual_value, forecast_value, previous_value, series_id, detail, source)
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VALUES (?,?,?,?,?,?,?,?,?,?,?)
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ON CONFLICT(event_date, event_time, currency, event_name)
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DO UPDATE SET
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actual_value = COALESCE(excluded.actual_value, ff_calendar.actual_value),
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forecast_value = COALESCE(excluded.forecast_value, ff_calendar.forecast_value),
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previous_value = COALESCE(excluded.previous_value, ff_calendar.previous_value),
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series_id = COALESCE(excluded.series_id, ff_calendar.series_id),
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fetched_at = datetime('now')
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""",
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batch,
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)
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def sync_live() -> Dict[str, Any]:
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"""
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Fetch this week + next week from faireconomy.media and upsert into ff_calendar.
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Updates actual_value when it becomes available (real-time detection).
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"""
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from services.database import get_conn
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results = {}
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conn = get_conn()
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for label, url in [("thisweek", _FF_THIS_WEEK_URL), ("nextweek", _FF_NEXT_WEEK_URL)]:
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try:
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resp = httpx.get(url, timeout=15, follow_redirects=True)
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if resp.status_code == 404:
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results[label] = {"status": "not_available"}
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continue
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resp.raise_for_status()
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events = resp.json()
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batch = []
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for ev in events:
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currency = (ev.get("country") or "").strip().upper()
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if currency not in SUPPORTED_CURRENCIES:
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continue
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impact = _IMPACT_MAP.get(ev.get("impact") or "", "low")
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if impact == "non-economic":
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continue
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event_name = (ev.get("title") or "").strip()
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if not event_name:
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continue
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dt_str = ev.get("date") or ""
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event_date, event_time = _parse_ff_datetime(dt_str)
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actual = (ev.get("actual") or "").strip() or None
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forecast = (ev.get("forecast") or "").strip() or None
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previous = (ev.get("previous") or "").strip() or None
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series_id = FF_TO_FRED.get(event_name)
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batch.append((
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event_date, event_time, currency, impact, event_name,
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actual, forecast, previous, series_id, None, "ff_live",
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))
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if batch:
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_upsert_batch(conn, batch)
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conn.commit()
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results[label] = {"status": "ok", "events": len(batch)}
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print(f"[FF sync] {label}: {len(batch)} events upserted", flush=True)
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except Exception as e:
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logger.warning(f"[FF sync] {label} failed: {e}")
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results[label] = {"status": "error", "error": str(e)}
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conn.close()
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return results
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def get_calendar(
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period: str = "recent",
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currencies: Optional[List[str]] = None,
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impacts: Optional[List[str]] = None,
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limit: int = 300,
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offset: int = 0,
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) -> Dict[str, Any]:
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"""
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Query ff_calendar with period filter.
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period options:
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recent | today | tomorrow | yesterday | this_week | next_week |
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previous_week | this_month | next_month | previous_month | custom
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"""
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from services.database import get_conn
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today = datetime.now(timezone.utc).date()
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monday = today - timedelta(days=today.weekday())
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sunday = monday + timedelta(days=6)
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date_from: Optional[str] = None
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date_to: Optional[str] = None
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if period == "today":
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date_from = date_to = str(today)
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elif period == "tomorrow":
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t = today + timedelta(days=1)
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date_from = date_to = str(t)
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elif period == "yesterday":
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t = today - timedelta(days=1)
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date_from = date_to = str(t)
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elif period == "this_week":
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date_from = str(monday)
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date_to = str(sunday)
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elif period == "next_week":
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nm = monday + timedelta(weeks=1)
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date_from = str(nm)
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date_to = str(nm + timedelta(days=6))
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elif period == "previous_week":
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pm = monday - timedelta(weeks=1)
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date_from = str(pm)
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date_to = str(pm + timedelta(days=6))
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elif period == "this_month":
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date_from = str(today.replace(day=1))
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# last day of month
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if today.month == 12:
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last = today.replace(year=today.year + 1, month=1, day=1) - timedelta(days=1)
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else:
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last = today.replace(month=today.month + 1, day=1) - timedelta(days=1)
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date_to = str(last)
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elif period == "next_month":
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if today.month == 12:
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first = today.replace(year=today.year + 1, month=1, day=1)
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else:
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first = today.replace(month=today.month + 1, day=1)
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if first.month == 12:
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last = first.replace(year=first.year + 1, month=1, day=1) - timedelta(days=1)
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else:
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last = first.replace(month=first.month + 1, day=1) - timedelta(days=1)
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date_from = str(first)
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date_to = str(last)
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elif period == "previous_month":
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if today.month == 1:
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first = today.replace(year=today.year - 1, month=12, day=1)
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else:
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first = today.replace(month=today.month - 1, day=1)
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last = today.replace(day=1) - timedelta(days=1)
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date_from = str(first)
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date_to = str(last)
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else: # recent: last 7 days + next 14 days
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date_from = str(today - timedelta(days=7))
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date_to = str(today + timedelta(days=14))
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conn = get_conn()
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where: List[str] = []
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params: List[Any] = []
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if date_from:
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where.append("event_date >= ?")
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params.append(date_from)
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if date_to:
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where.append("event_date <= ?")
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params.append(date_to)
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if currencies:
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ph = ",".join("?" * len(currencies))
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where.append(f"currency IN ({ph})")
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params.extend(currencies)
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if impacts:
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ph = ",".join("?" * len(impacts))
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where.append(f"impact IN ({ph})")
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params.extend(impacts)
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where_sql = ("WHERE " + " AND ".join(where)) if where else ""
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count_sql = f"SELECT COUNT(*) FROM ff_calendar {where_sql}"
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data_sql = (
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f"SELECT * FROM ff_calendar {where_sql} "
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f"ORDER BY event_date ASC, event_time ASC "
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f"LIMIT ? OFFSET ?"
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)
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try:
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total = conn.execute(count_sql, params).fetchone()[0]
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rows = conn.execute(data_sql, params + [limit, offset]).fetchall()
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events = [dict(r) for r in rows]
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return {
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"total": total,
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"offset": offset,
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"limit": limit,
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"period": period,
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"date_from": date_from,
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"date_to": date_to,
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"events": events,
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}
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finally:
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conn.close()
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