87260f4b10
Prerequisite refactor: - Consolidate duplicate _to_dicts into shared obb_utils.to_list - Add fetch_historical and first_or_empty helpers to obb_utils Phase 1 - Local computation (no provider risk): - Group I: 12 technical indicators (ATR, ADX, Stoch, OBV, Ichimoku, Donchian, Aroon, CCI, Keltner, Fibonacci, A/D, Volatility Cones) - Group J: Sortino, Omega ratios + rolling stats (variance, stdev, mean, skew, kurtosis, quantile via generic endpoint) - Group H: ECB currency reference rates Phase 2 - FRED/Federal Reserve providers: - Group C: 10 fixed income endpoints (treasury rates, yield curve, auctions, TIPS, EFFR, SOFR, HQM, commercial paper, spot rates, spreads) - Group D: 11 economy endpoints (CPI, GDP, unemployment, PCE, money measures, CLI, HPI, FRED search, balance of payments, Fed holdings, FOMC documents) - Group E: 5 survey endpoints (Michigan, SLOOS, NFP, Empire State, BLS search) Phase 3 - SEC/stockgrid/FINRA providers: - Group B: 4 equity fundamental endpoints (management, dividends, SEC filings, company search) - Group A: 4 shorts/dark pool endpoints (short volume, FTD, short interest, OTC dark pool) - Group F: 3 index/ETF enhanced (S&P 500 multiples, index constituents, ETF N-PORT) Phase 4 - Regulators: - Group G: 5 regulatory endpoints (COT report, COT search, SEC litigation, institution search, CIK mapping) Security hardening: - Service-layer allowlists for all getattr dynamic dispatch - Regex validation on date, country, security_type, form_type params - Exception handling in fetch_historical - Callable guard on rolling stat dispatch Total: 32 existing + 67 new = 99 endpoints, all free providers.
84 lines
2.3 KiB
Python
84 lines
2.3 KiB
Python
"""Macro economic data via OpenBB FRED provider."""
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import asyncio
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import logging
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from typing import Any
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from openbb import obb
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from obb_utils import to_list
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logger = logging.getLogger(__name__)
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PROVIDER = "fred"
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# Key FRED series IDs
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SERIES = {
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"fed_funds_rate": "FEDFUNDS",
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"us_10y_treasury": "DGS10",
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"us_2y_treasury": "DGS2",
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"cpi_yoy": "CPIAUCSL",
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"unemployment_rate": "UNRATE",
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"gdp_growth": "A191RL1Q225SBEA",
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"sp500": "SP500",
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"vix": "VIXCLS",
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}
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async def get_series(
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series_id: str, limit: int = 10, latest: bool = False,
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) -> list[dict[str, Any]]:
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"""Get a FRED time series by ID."""
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try:
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fetch_limit = limit if not latest else None
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kwargs: dict[str, Any] = {
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"symbol": series_id,
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"provider": PROVIDER,
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}
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if fetch_limit is not None:
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kwargs["limit"] = fetch_limit
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result = await asyncio.to_thread(
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obb.economy.fred_series,
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**kwargs,
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)
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items = to_list(result)
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items = [
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{**item, "date": str(item["date"])}
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if "date" in item and not isinstance(item["date"], str)
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else item
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for item in items
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]
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if latest:
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items = items[-limit:]
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return items
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except Exception:
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logger.warning("Failed to fetch FRED series %s", series_id, exc_info=True)
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return []
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async def get_macro_overview() -> dict[str, Any]:
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"""Get a summary of key macro indicators."""
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tasks = {
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name: get_series(series_id, limit=1, latest=True)
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for name, series_id in SERIES.items()
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}
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results = await asyncio.gather(*tasks.values(), return_exceptions=True)
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overview: dict[str, Any] = {}
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for (name, series_id), result in zip(SERIES.items(), results):
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if isinstance(result, BaseException):
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logger.warning("Failed to fetch %s: %s", name, result)
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overview[name] = None
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elif result and len(result) > 0:
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entry = result[-1]
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# FRED returns values keyed by series ID, not "value"
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value = entry.get(series_id) or entry.get("value")
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overview[name] = {
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"value": value,
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"date": str(entry.get("date", "")),
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}
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else:
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overview[name] = None
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return overview
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