feat: macro series
This commit is contained in:
@@ -740,3 +740,63 @@ def eco_status() -> Dict[str, Any]:
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}
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finally:
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conn.close()
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# ── Macro Series Log ──────────────────────────────────────────────────────────
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@router.get("/series-log")
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def get_series_log(
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series_id: str = Query(...),
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from_date: str = Query("2020-01-01"),
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limit: int = Query(500, le=2000),
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) -> List[Dict[str, Any]]:
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"""Return logged actual/forecast snapshots for a given series (change events only)."""
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from services.database import get_conn
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conn = get_conn()
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try:
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rows = conn.execute(
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"""SELECT series_id, event_name, event_date, actual_value, forecast_value,
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previous_value, currency, impact, logged_at, source, changed
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FROM macro_series_log
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WHERE series_id = ? AND event_date >= ?
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ORDER BY event_date ASC, logged_at ASC
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LIMIT ?""",
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(series_id, from_date, limit)
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).fetchall()
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return [dict(r) for r in rows]
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finally:
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conn.close()
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@router.get("/series-log/distinct-series")
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def list_logged_series() -> List[Dict[str, Any]]:
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"""Return all series_id that have entries in macro_series_log."""
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from services.database import get_conn
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conn = get_conn()
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try:
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rows = conn.execute(
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"""SELECT series_id, event_name,
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COUNT(*) as log_count,
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MIN(event_date) as first_date,
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MAX(event_date) as last_date,
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MAX(logged_at) as last_logged
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FROM macro_series_log
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GROUP BY series_id
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ORDER BY last_date DESC"""
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).fetchall()
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return [dict(r) for r in rows]
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finally:
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conn.close()
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@router.post("/series-log/backfill")
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def backfill_series_log() -> Dict[str, Any]:
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"""Seed macro_series_log from existing ff_calendar rows (one-time historical import)."""
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from services.database import get_conn
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from services.macro_series_log import backfill_from_ff_calendar
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conn = get_conn()
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try:
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result = backfill_from_ff_calendar(conn)
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return result
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finally:
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conn.close()
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@@ -47,6 +47,17 @@ def calendar_sync(weeks_ahead: int = 8) -> Dict[str, Any]:
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result = {"error": str(e)}
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source = "error"
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# After calendar upsert, log any forecast/actual changes to macro_series_log
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try:
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from services.database import get_conn
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from services.macro_series_log import scan_and_log_all
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_conn = get_conn()
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log_result = scan_and_log_all(_conn, source=source)
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_conn.close()
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result["_log"] = log_result
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except Exception as e:
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logger.warning(f"[calendar_sync] macro_series_log scan failed: {e}")
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_sync_status["running"] = False
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_sync_status["last_result"] = result
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_sync_status["source"] = source
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@@ -715,6 +715,29 @@ def init_db():
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except Exception:
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pass # Column already exists
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# ── Macro Series Log ───────────────────────────────────────────────────────
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# One row per change: actual or forecast changed vs previous snapshot.
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# Allows tracking forecast revisions over time + actual vs consensus history.
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c.execute("""CREATE TABLE IF NOT EXISTS macro_series_log (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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series_id TEXT NOT NULL,
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event_name TEXT NOT NULL DEFAULT '',
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event_date TEXT NOT NULL,
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actual_value REAL,
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forecast_value REAL,
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previous_value REAL,
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currency TEXT DEFAULT '',
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impact TEXT DEFAULT '',
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logged_at TEXT NOT NULL DEFAULT (datetime('now')),
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source TEXT DEFAULT 'calendar_sync',
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changed TEXT DEFAULT 'new'
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)""")
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try:
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c.execute("CREATE INDEX IF NOT EXISTS idx_msl_series ON macro_series_log(series_id, event_date)")
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c.execute("CREATE INDEX IF NOT EXISTS idx_msl_logged ON macro_series_log(logged_at DESC)")
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except Exception:
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pass
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# ── Specialist Desks ───────────────────────────────────────────────────────
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c.execute("""CREATE TABLE IF NOT EXISTS specialist_reports (
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id TEXT PRIMARY KEY,
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159
backend/services/macro_series_log.py
Normal file
159
backend/services/macro_series_log.py
Normal file
@@ -0,0 +1,159 @@
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"""
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Macro series log — tracks changes to actual_value and forecast_value over time.
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Called after each calendar sync to detect and persist revisions.
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"""
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import logging
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from datetime import datetime, timezone
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from typing import Optional
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logger = logging.getLogger(__name__)
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def _parse_num(v) -> Optional[float]:
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"""Convert FF text value (e.g. '178K', '0.3%', '-92K') to float or None."""
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if v is None:
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return None
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s = str(v).strip().replace('%', '').replace('K', 'e3').replace('M', 'e6').replace('B', 'e9')
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try:
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return float(s)
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except Exception:
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return None
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def log_if_changed(conn, series_id: str, event_name: str, event_date: str,
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actual_value, forecast_value, previous_value,
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currency: str = '', impact: str = '',
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source: str = 'calendar_sync') -> bool:
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"""
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Compare (actual, forecast) against the last log entry for this series+date.
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Insert a new row only if something changed or it's the first time we see it.
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Returns True if a row was inserted.
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"""
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actual_num = _parse_num(actual_value)
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forecast_num = _parse_num(forecast_value)
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previous_num = _parse_num(previous_value)
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# Nothing to log if both actual and forecast are None
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if actual_num is None and forecast_num is None:
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return False
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last = conn.execute(
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"""SELECT actual_value, forecast_value FROM macro_series_log
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WHERE series_id=? AND event_date=?
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ORDER BY logged_at DESC LIMIT 1""",
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(series_id, event_date)
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).fetchone()
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if last is None:
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changed = 'new'
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else:
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prev_actual = last['actual_value']
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prev_forecast = last['forecast_value']
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actual_changed = actual_num != prev_actual and actual_num is not None
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forecast_changed = forecast_num != prev_forecast and forecast_num is not None
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if not actual_changed and not forecast_changed:
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return False
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if actual_changed and forecast_changed:
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changed = 'both'
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elif actual_changed:
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changed = 'actual'
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else:
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changed = 'forecast'
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conn.execute(
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"""INSERT INTO macro_series_log
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(series_id, event_name, event_date, actual_value, forecast_value,
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previous_value, currency, impact, logged_at, source, changed)
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VALUES (?,?,?,?,?,?,?,?,?,?,?)""",
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(series_id, event_name or '', event_date,
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actual_num, forecast_num, previous_num,
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currency or '', impact or '',
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datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S'),
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source, changed)
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)
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conn.commit()
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return True
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def backfill_from_ff_calendar(conn) -> dict:
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"""
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Seed macro_series_log from existing ff_calendar rows (historical).
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Only inserts rows that don't already exist (idempotent).
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Skips events without series_id.
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"""
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rows = conn.execute(
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"""SELECT series_id, event_name, event_date, actual_value, forecast_value,
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previous_value, currency, impact, fetched_at
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FROM ff_calendar
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WHERE series_id IS NOT NULL AND series_id != ''
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AND (actual_value IS NOT NULL OR forecast_value IS NOT NULL)
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ORDER BY event_date ASC"""
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).fetchall()
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inserted = 0
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for r in rows:
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already = conn.execute(
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"SELECT 1 FROM macro_series_log WHERE series_id=? AND event_date=? AND source='backfill' LIMIT 1",
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(r['series_id'], r['event_date'])
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).fetchone()
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if already:
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continue
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actual_num = _parse_num(r['actual_value'])
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forecast_num = _parse_num(r['forecast_value'])
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previous_num = _parse_num(r['previous_value'])
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if actual_num is None and forecast_num is None:
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continue
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logged_at = r['fetched_at'] or r['event_date']
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changed = 'actual' if actual_num is not None else 'forecast'
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conn.execute(
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"""INSERT OR IGNORE INTO macro_series_log
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(series_id, event_name, event_date, actual_value, forecast_value,
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previous_value, currency, impact, logged_at, source, changed)
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VALUES (?,?,?,?,?,?,?,?,?,?,?)""",
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(r['series_id'], r['event_name'] or '', r['event_date'],
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actual_num, forecast_num, previous_num,
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r['currency'] or '', r['impact'] or '',
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logged_at, 'backfill', changed)
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)
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inserted += 1
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conn.commit()
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logger.info(f"[macro_series_log] backfill: {inserted} rows inserted from ff_calendar")
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return {"inserted": inserted, "scanned": len(rows)}
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def scan_and_log_all(conn, source: str = 'calendar_sync') -> dict:
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"""
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After a calendar sync, scan all ff_calendar rows with series_id and log any changes.
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Typically called at end of each 6h sync cycle.
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"""
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rows = conn.execute(
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"""SELECT series_id, event_name, event_date, actual_value, forecast_value,
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previous_value, currency, impact
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FROM ff_calendar
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WHERE series_id IS NOT NULL AND series_id != ''
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AND (actual_value IS NOT NULL OR forecast_value IS NOT NULL)"""
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).fetchall()
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logged = 0
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for r in rows:
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did_log = log_if_changed(
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conn,
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series_id=r['series_id'],
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event_name=r['event_name'] or '',
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event_date=r['event_date'],
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actual_value=r['actual_value'],
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forecast_value=r['forecast_value'],
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previous_value=r['previous_value'],
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currency=r['currency'] or '',
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impact=r['impact'] or '',
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source=source,
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)
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if did_log:
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logged += 1
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logger.info(f"[macro_series_log] scan_and_log_all: {logged} changes logged out of {len(rows)} rows")
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return {"logged": logged, "scanned": len(rows)}
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@@ -1,9 +1,9 @@
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import { useState, useEffect, useCallback } from 'react'
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import clsx from 'clsx'
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import { RefreshCw, TrendingUp, TrendingDown, Minus } from 'lucide-react'
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import { RefreshCw, TrendingUp, TrendingDown, Minus, Database } from 'lucide-react'
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import {
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ComposedChart, Line, XAxis, YAxis, CartesianGrid, Tooltip,
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ResponsiveContainer, ReferenceLine, Area,
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ComposedChart, Line, Bar, XAxis, YAxis, CartesianGrid, Tooltip,
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ResponsiveContainer, ReferenceLine, Area, Legend,
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} from 'recharts'
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const API = ''
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@@ -46,6 +46,17 @@ interface SeriesHistory {
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events: FFEvent[]
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}
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interface LogEntry {
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series_id: string
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event_name: string
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event_date: string
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actual_value: number | null
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forecast_value: number | null
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previous_value: number | null
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logged_at: string
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changed: string // 'new' | 'actual' | 'forecast' | 'both' | 'backfill'
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}
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// ── Constants ─────────────────────────────────────────────────────────────────
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const CATEGORY_COLORS: Record<string, string> = {
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@@ -254,9 +265,11 @@ export default function MacroSeriesPage() {
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const [selectedId, setSelectedId] = useState<string>('PAYEMS')
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const [range, setRange] = useState('5y')
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const [history, setHistory] = useState<SeriesHistory | null>(null)
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const [logEntries, setLogEntries] = useState<LogEntry[]>([])
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const [loading, setLoading] = useState(false)
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const [backfilling, setBackfilling] = useState(false)
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const [tab, setTab] = useState<'chart' | 'log'>('chart')
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// Load series catalog
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useEffect(() => {
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fetch(`${API}/api/eco/series`).then(r => r.json()).then(setSeriesList).catch(() => {})
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}, [])
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@@ -267,35 +280,57 @@ export default function MacroSeriesPage() {
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try {
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const months = RANGE_OPTIONS.find(r => r.key === range)?.months ?? 60
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const from = fromDateForRange(months)
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const r: SeriesHistory = await fetch(
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`${API}/api/eco/series/${selectedId}/history?from_date=${from}`
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).then(x => x.json())
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setHistory(r)
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const [hist, log] = await Promise.all([
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fetch(`${API}/api/eco/series/${selectedId}/history?from_date=${from}`).then(x => x.json()),
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fetch(`${API}/api/eco/series-log?series_id=${selectedId}&from_date=${from}&limit=1000`).then(x => x.json()),
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])
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setHistory(hist)
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setLogEntries(Array.isArray(log) ? log : [])
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} catch {}
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finally { setLoading(false) }
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}, [selectedId, range])
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useEffect(() => { loadHistory() }, [loadHistory])
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// Build chart data — merge FRED time series + FF events by date
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const handleBackfill = async () => {
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setBackfilling(true)
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try {
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await fetch(`${API}/api/eco/series-log/backfill`, { method: 'POST' })
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await loadHistory()
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} catch {}
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finally { setBackfilling(false) }
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}
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// Build chart data — merge FRED time series + log entries by event_date
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// For each release date: actual from log (last entry with actual) + last forecast before actual
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const chartData = (() => {
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if (!history) return []
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const ffByDate = new Map<string, FFEvent>()
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for (const ev of history.events) ffByDate.set(ev.event_date, ev)
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// Group log entries by event_date, pick last forecast before actual and first actual
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const logByDate = new Map<string, { actual: number | null; lastForecast: number | null }>()
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for (const e of logEntries) {
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const existing = logByDate.get(e.event_date) ?? { actual: null, lastForecast: null }
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if (e.actual_value != null) existing.actual = e.actual_value
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if (e.forecast_value != null && e.actual_value == null) existing.lastForecast = e.forecast_value
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logByDate.set(e.event_date, existing)
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}
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return history.timeseries.map(pt => {
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const ff = ffByDate.get(pt.event_date)
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const logged = logByDate.get(pt.event_date)
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return {
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event_date: pt.event_date,
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label: fmtDate(pt.event_date),
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value: pt.actual_value,
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zscore: pt.surprise_zscore,
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direction: pt.surprise_direction,
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ff_event: ff?.event_name ?? null,
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ff_actual: ff?.actual_value ?? null,
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ff_forecast:ff?.forecast_value ?? null,
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// For reference lines — mark surprise events
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is_surprise: pt.surprise_zscore !== null && Math.abs(pt.surprise_zscore) >= 1.5,
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event_date: pt.event_date,
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label: fmtDate(pt.event_date),
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value: pt.actual_value,
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forecast: logged?.lastForecast ?? (ff?.forecast_value ? parseFloat(ff.forecast_value) || null : null),
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zscore: pt.surprise_zscore,
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direction: pt.surprise_direction,
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ff_event: ff?.event_name ?? null,
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ff_actual: ff?.actual_value ?? null,
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ff_forecast: ff?.forecast_value ?? null,
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is_surprise: pt.surprise_zscore !== null && Math.abs(pt.surprise_zscore) >= 1.5,
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}
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})
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})()
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@@ -346,26 +381,33 @@ export default function MacroSeriesPage() {
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</div>
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<div className="flex items-center gap-2">
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{/* Tab selector */}
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<div className="flex gap-1 bg-slate-800 rounded p-0.5">
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{(['chart', 'log'] as const).map(t => (
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<button key={t} onClick={() => setTab(t)}
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className={clsx('px-2.5 py-1 rounded text-xs font-medium transition-colors',
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tab === t ? 'bg-slate-600 text-white' : 'text-slate-400 hover:text-slate-200')}>
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{t === 'chart' ? 'Chart' : `Log (${logEntries.length})`}
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</button>
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))}
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</div>
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{/* Range selector */}
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<div className="flex gap-1 bg-slate-800 rounded p-0.5">
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{RANGE_OPTIONS.map(r => (
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<button
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key={r.key}
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onClick={() => setRange(r.key)}
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className={clsx(
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'px-2.5 py-1 rounded text-xs font-medium transition-colors',
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range === r.key ? 'bg-slate-600 text-white' : 'text-slate-400 hover:text-slate-200'
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)}
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>
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<button key={r.key} onClick={() => setRange(r.key)}
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className={clsx('px-2.5 py-1 rounded text-xs font-medium transition-colors',
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range === r.key ? 'bg-slate-600 text-white' : 'text-slate-400 hover:text-slate-200')}>
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{r.label}
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</button>
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))}
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</div>
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<button
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onClick={loadHistory}
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disabled={loading}
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className="p-1.5 rounded bg-slate-700 hover:bg-slate-600 disabled:opacity-50"
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>
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<button onClick={handleBackfill} disabled={backfilling}
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title="Importer l'historique ff_calendar → macro_series_log"
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className="p-1.5 rounded bg-slate-700 hover:bg-slate-600 disabled:opacity-50">
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<Database size={13} className={clsx(backfilling && 'animate-pulse')} />
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</button>
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<button onClick={loadHistory} disabled={loading}
|
||||
className="p-1.5 rounded bg-slate-700 hover:bg-slate-600 disabled:opacity-50">
|
||||
<RefreshCw size={13} className={clsx(loading && 'animate-spin')} />
|
||||
</button>
|
||||
</div>
|
||||
@@ -397,107 +439,138 @@ export default function MacroSeriesPage() {
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Chart */}
|
||||
{tab === 'chart' && (
|
||||
<div className="bg-slate-800 rounded-lg border border-slate-700 p-4">
|
||||
<div className="flex items-center justify-between mb-3">
|
||||
<span className="text-sm font-medium text-slate-300">
|
||||
Time Series
|
||||
{history && <span className="text-slate-500 text-xs ml-2">({chartData.length} data points)</span>}
|
||||
Actual vs Consensus
|
||||
{history && <span className="text-slate-500 text-xs ml-2">({chartData.length} releases)</span>}
|
||||
</span>
|
||||
{bigSurprises.length > 0 && (
|
||||
<span className="text-xs text-slate-500">
|
||||
{bigSurprises.length} big surprises (|z| ≥ 1.5)
|
||||
</span>
|
||||
<span className="text-xs text-slate-500">{bigSurprises.length} surprises (|z|≥1.5)</span>
|
||||
)}
|
||||
</div>
|
||||
|
||||
{loading && (
|
||||
<div className="h-64 flex items-center justify-center text-slate-600 text-sm">
|
||||
Loading…
|
||||
</div>
|
||||
)}
|
||||
|
||||
{loading && <div className="h-64 flex items-center justify-center text-slate-600 text-sm">Chargement…</div>}
|
||||
{!loading && chartData.length === 0 && (
|
||||
<div className="h-64 flex items-center justify-center text-slate-600 text-sm">
|
||||
No data — run FRED bootstrap first in the Calendar page.
|
||||
Pas de données — lancez le bootstrap FRED depuis Calendar.
|
||||
</div>
|
||||
)}
|
||||
|
||||
{!loading && chartData.length > 0 && (
|
||||
<ResponsiveContainer width="100%" height={280}>
|
||||
<ResponsiveContainer width="100%" height={300}>
|
||||
<ComposedChart data={chartData} margin={{ top: 4, right: 16, bottom: 4, left: 0 }}>
|
||||
<defs>
|
||||
<linearGradient id={`grad-${selectedId}`} x1="0" y1="0" x2="0" y2="1">
|
||||
<stop offset="5%" stopColor={color} stopOpacity={0.25} />
|
||||
<stop offset="5%" stopColor={color} stopOpacity={0.3} />
|
||||
<stop offset="95%" stopColor={color} stopOpacity={0} />
|
||||
</linearGradient>
|
||||
</defs>
|
||||
<CartesianGrid strokeDasharray="3 3" stroke="#1e293b" />
|
||||
<XAxis
|
||||
dataKey="label"
|
||||
tick={{ fontSize: 10, fill: '#64748b' }}
|
||||
interval="preserveStartEnd"
|
||||
tickLine={false}
|
||||
/>
|
||||
<YAxis
|
||||
tick={{ fontSize: 10, fill: '#64748b' }}
|
||||
tickLine={false}
|
||||
axisLine={false}
|
||||
width={50}
|
||||
tickFormatter={v => `${v}${history?.unit === '%' || history?.unit === 'pp' ? '' : ''}`}
|
||||
/>
|
||||
<XAxis dataKey="label" tick={{ fontSize: 10, fill: '#64748b' }} interval="preserveStartEnd" tickLine={false} />
|
||||
<YAxis tick={{ fontSize: 10, fill: '#64748b' }} tickLine={false} axisLine={false} width={50} />
|
||||
<Tooltip content={<ChartTooltip unit={history?.unit ?? ''} />} />
|
||||
<Legend wrapperStyle={{ fontSize: 11, color: '#94a3b8' }} />
|
||||
|
||||
{/* Zero line if series crosses zero */}
|
||||
{minVal !== null && maxVal !== null && minVal < 0 && maxVal > 0 && (
|
||||
<ReferenceLine y={0} stroke="#475569" strokeDasharray="4 2" />
|
||||
)}
|
||||
|
||||
{/* Big surprise markers */}
|
||||
{bigSurprises.map(s => (
|
||||
<ReferenceLine
|
||||
key={s.event_date}
|
||||
x={fmtDate(s.event_date)}
|
||||
<ReferenceLine key={s.event_date} x={fmtDate(s.event_date)}
|
||||
stroke={s.direction === 'bullish' ? '#10b981' : s.direction === 'bearish' ? '#ef4444' : '#64748b'}
|
||||
strokeWidth={1}
|
||||
strokeDasharray="3 3"
|
||||
opacity={0.6}
|
||||
/>
|
||||
strokeWidth={1} strokeDasharray="3 3" opacity={0.5} />
|
||||
))}
|
||||
|
||||
<Area
|
||||
type="monotone"
|
||||
dataKey="value"
|
||||
stroke={color}
|
||||
strokeWidth={2}
|
||||
fill={`url(#grad-${selectedId})`}
|
||||
dot={false}
|
||||
activeDot={{ r: 4, fill: color }}
|
||||
/>
|
||||
{/* Actual — area + line */}
|
||||
<Area type="monotone" dataKey="value" name="Actual"
|
||||
stroke={color} strokeWidth={2} fill={`url(#grad-${selectedId})`}
|
||||
dot={false} activeDot={{ r: 4, fill: color }} />
|
||||
|
||||
{/* Forecast — dashed line */}
|
||||
<Line type="monotone" dataKey="forecast" name="Forecast (consensus)"
|
||||
stroke="#f59e0b" strokeWidth={1.5} strokeDasharray="4 3"
|
||||
dot={false} activeDot={{ r: 3 }} connectNulls />
|
||||
</ComposedChart>
|
||||
</ResponsiveContainer>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Legend for reference lines */}
|
||||
{bigSurprises.length > 0 && (
|
||||
<div className="flex items-center gap-4 mt-2 text-xs text-slate-500">
|
||||
<span className="flex items-center gap-1">
|
||||
<span className="w-4 border-t border-dashed border-emerald-500 inline-block" />
|
||||
Bullish surprise (|z|≥1.5)
|
||||
</span>
|
||||
<span className="flex items-center gap-1">
|
||||
<span className="w-4 border-t border-dashed border-red-500 inline-block" />
|
||||
Bearish surprise
|
||||
</span>
|
||||
{tab === 'log' && (
|
||||
<div className="bg-slate-800 rounded-lg border border-slate-700 p-4">
|
||||
<div className="flex items-center justify-between mb-3">
|
||||
<span className="text-sm font-medium text-slate-300">
|
||||
Journal des changements — {selectedId}
|
||||
<span className="text-slate-500 text-xs ml-2">({logEntries.length} entrées)</span>
|
||||
</span>
|
||||
{logEntries.length === 0 && (
|
||||
<button onClick={handleBackfill} disabled={backfilling}
|
||||
className="text-xs text-violet-400 hover:text-violet-200 bg-violet-900/20 border border-violet-800/40 rounded px-2 py-1 disabled:opacity-50">
|
||||
{backfilling ? 'Import…' : 'Importer historique ff_calendar'}
|
||||
</button>
|
||||
)}
|
||||
</div>
|
||||
{logEntries.length === 0 ? (
|
||||
<div className="text-slate-600 text-sm text-center py-8">
|
||||
Aucune entrée — cliquez "Importer historique" ou attendez le prochain sync (6h).
|
||||
</div>
|
||||
) : (
|
||||
<div className="overflow-x-auto">
|
||||
<table className="w-full text-xs">
|
||||
<thead>
|
||||
<tr className="text-slate-500 border-b border-slate-800">
|
||||
<th className="text-left py-1.5 pr-3">Release</th>
|
||||
<th className="text-left py-1.5 pr-3">Capturé à</th>
|
||||
<th className="text-right py-1.5 pr-3">Actual</th>
|
||||
<th className="text-right py-1.5 pr-3">Forecast</th>
|
||||
<th className="text-right py-1.5 pr-3">Previous</th>
|
||||
<th className="text-left py-1.5">Changement</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{[...logEntries].reverse().map((e, i) => {
|
||||
const isActual = e.actual_value != null
|
||||
const isForecastChange = e.changed === 'forecast' || e.changed === 'both'
|
||||
return (
|
||||
<tr key={i} className={clsx('border-b border-slate-800/50 hover:bg-slate-800/30',
|
||||
isActual ? 'bg-slate-800/20' : '')}>
|
||||
<td className="py-1.5 pr-3 text-slate-400 tabular-nums">{e.event_date}</td>
|
||||
<td className="py-1.5 pr-3 text-slate-600 tabular-nums">{e.logged_at.slice(0, 16)}</td>
|
||||
<td className={clsx('py-1.5 pr-3 text-right tabular-nums font-medium',
|
||||
isActual ? 'text-white' : 'text-slate-700')}>
|
||||
{e.actual_value != null ? e.actual_value.toFixed(2) : '—'}
|
||||
</td>
|
||||
<td className={clsx('py-1.5 pr-3 text-right tabular-nums',
|
||||
isForecastChange ? 'text-amber-400' : 'text-slate-400')}>
|
||||
{e.forecast_value != null ? e.forecast_value.toFixed(2) : '—'}
|
||||
</td>
|
||||
<td className="py-1.5 pr-3 text-right tabular-nums text-slate-600">
|
||||
{e.previous_value != null ? e.previous_value.toFixed(2) : '—'}
|
||||
</td>
|
||||
<td className="py-1.5">
|
||||
<span className={clsx('px-1.5 py-0.5 rounded text-[10px]',
|
||||
e.changed === 'actual' || e.changed === 'both' ? 'bg-emerald-900/40 text-emerald-400' :
|
||||
e.changed === 'forecast' ? 'bg-amber-900/40 text-amber-400' :
|
||||
'bg-slate-700/40 text-slate-500')}>
|
||||
{e.changed}
|
||||
</span>
|
||||
</td>
|
||||
</tr>
|
||||
)
|
||||
})}
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Events table */}
|
||||
<div className="bg-slate-800 rounded-lg border border-slate-700 p-4">
|
||||
<div className="text-sm font-medium text-slate-300 mb-3">
|
||||
FF Calendar Events
|
||||
{history && <span className="text-slate-500 text-xs ml-2">({history.events.length} linked)</span>}
|
||||
{history && <span className="text-slate-500 text-xs ml-2">({history.events.length} liés)</span>}
|
||||
</div>
|
||||
{history && <EventsTable events={history.events} unit={history.unit} />}
|
||||
</div>
|
||||
|
||||
Reference in New Issue
Block a user