"""Step 10 – News collection. Collects two categories of news data: Part A: Per-ticker news & press releases via YFinance (FREE, recent only). Part B: Per-scenario event-specific news via Firecrawl (date-targeted) with Tavily fallback. Output ------ data/news/tickers/{TICKER}.json -- per-ticker yfinance news + press data/news/scenarios/{scenario_id}.json -- per-scenario Firecrawl/Tavily Resume: skips if output file already exists. """ from __future__ import annotations import asyncio import json import logging import os import time from concurrent.futures import ThreadPoolExecutor from pathlib import Path import pandas as pd from dotenv import load_dotenv from projects.agent_builder.scripts.whatif_bench import config load_dotenv() logger = logging.getLogger(__name__) # --------------------------------------------------------------------------- # Helpers # --------------------------------------------------------------------------- def _ensure_dirs() -> tuple[Path, Path]: """Create news output directories and return (tickers_dir, scenarios_dir).""" tickers_dir = config.NEWS_DIR / "tickers" scenarios_dir = config.NEWS_DIR / "scenarios" tickers_dir.mkdir(parents=True, exist_ok=True) scenarios_dir.mkdir(parents=True, exist_ok=True) return tickers_dir, scenarios_dir # --------------------------------------------------------------------------- # Part A – Per-ticker news + press releases (yfinance, FREE) # --------------------------------------------------------------------------- def _collect_single_ticker_news(ticker: str, tickers_dir: Path, client) -> int: """Fetch news + press releases for a single ticker. Returns article count.""" out_path = tickers_dir / f"{ticker}.json" if out_path.exists(): return 0 # resume: already collected articles: list[dict] = [] any_success = False for tab in ("news", "press releases"): for attempt in range(3): try: result = client.fetch_news_from_single_ticker( ticker, tab=tab, count=config.NEWS_PER_TICKER_COUNT, ) articles.extend([item.model_dump(mode="json") for item in result.root]) any_success = True break except Exception: if attempt == 2: logger.warning("Failed to fetch %s tab=%s after 3 attempts", ticker, tab) else: time.sleep(2 ** attempt) # Fallback: if yfinance returned nothing, try Tavily for per-ticker news. # Tavily is a paid API but handles obscure small-caps better than yfinance. if not articles: tavily_key = os.environ.get("TAVILY_API_KEY", "") if tavily_key: try: from tavily import TavilyClient tv = TavilyClient(api_key=tavily_key) tv_results = tv.search( query=f"{ticker} stock news financial", search_depth="basic", max_results=config.NEWS_PER_TICKER_COUNT, topic="news", ) for item in tv_results.get("results", []): articles.append({ "source": "tavily", "title": item.get("title", ""), "url": item.get("url", ""), "snippet": item.get("content", ""), "date": item.get("published_date", ""), }) if articles: any_success = True logger.info("Tavily fallback for %s: %d articles", ticker, len(articles)) except Exception as exc: logger.debug("Tavily fallback failed for %s: %s", ticker, exc) # Only write the file if at least one tab succeeded. # If ALL tabs failed, do NOT write — leave the file missing so it's retried next run. if any_success: tmp_path = out_path.with_suffix(".json.tmp") tmp_path.write_text(json.dumps(articles, default=str), encoding="utf-8") tmp_path.replace(out_path) # atomic rename else: logger.warning("All tabs failed for %s — NOT writing file (will retry next run)", ticker) return len(articles) # Shared lock to enforce actual rate limiting across threads import threading _rate_lock = threading.Lock() _last_request_time = 0.0 def _rate_limited_worker(ticker: str, tickers_dir: Path, client) -> int: """Worker that enforces sequential rate limiting via a shared lock.""" global _last_request_time with _rate_lock: elapsed = time.time() - _last_request_time if elapsed < config.NEWS_RATE_LIMIT_SEC: time.sleep(config.NEWS_RATE_LIMIT_SEC - elapsed) _last_request_time = time.time() return _collect_single_ticker_news(ticker, tickers_dir, client) def _run_part_a(tickers: list[str], tickers_dir: Path) -> None: """Parallel per-ticker news collection with proper rate limiting.""" logger.info("Part A: collecting per-ticker news for %d tickers …", len(tickers)) from concurrent.futures import as_completed from projects.tools.finance.yahoo import YFinanceClient # Single shared client for connection reuse client = YFinanceClient() total_articles = 0 done = 0 with ThreadPoolExecutor(max_workers=config.NEWS_WORKERS) as pool: futures = {pool.submit(_rate_limited_worker, t, tickers_dir, client): t for t in tickers} for future in as_completed(futures): ticker = futures[future] try: n = future.result() total_articles += n except Exception: logger.exception("Error collecting news for %s", ticker) done += 1 if done % 200 == 0: logger.info(" Part A progress: %d / %d tickers", done, len(tickers)) logger.info("Part A complete: %d articles across %d tickers", total_articles, len(tickers)) # --------------------------------------------------------------------------- # Part B – Scenario-event news (Firecrawl + Tavily fallback) # --------------------------------------------------------------------------- async def _collect_single_scenario_news( scenario: dict, scenarios_dir: Path, firecrawl_client, tavily_client, ) -> int: """Fetch news for a single scenario event. Returns article count.""" sc_id = scenario["scenario_id"] out_path = scenarios_dir / f"{sc_id}.json" if out_path.exists(): return 0 event_date = pd.Timestamp(scenario["event_date"]) # Wider window (±30 days) — narrow windows return empty from news APIs start = (event_date - pd.Timedelta(days=30)).strftime("%-m/%-d/%Y") end = (event_date + pd.Timedelta(days=30)).strftime("%-m/%-d/%Y") tbs = f"cdr:1,cd_min:{start},cd_max:{end}" # Simplify query: use event_type keywords + date, not full description event_type = scenario.get("event_type", "").replace("_", " ") year_month = event_date.strftime("%B %Y") query = f"{event_type} {year_month} financial markets impact" articles: list[dict] = [] # Try Firecrawl first try: fc_results = await firecrawl_client._search( query=query, limit=config.NEWS_SCENARIO_LIMIT, sources=["news"], categories=[], tbs=tbs, ) if fc_results and hasattr(fc_results, "news") and fc_results.news: for item in fc_results.news: articles.append({ "source": "firecrawl", "title": getattr(item, "title", ""), "url": getattr(item, "url", ""), "snippet": getattr(item, "snippet", getattr(item, "description", "")), "date": getattr(item, "date", ""), }) except Exception: logger.warning("Firecrawl failed for scenario %s, trying Tavily", sc_id) # Tavily fallback if Firecrawl returned nothing if not articles and tavily_client is not None: try: tv_results = await tavily_client._search( query=query, search_depth="advanced", include_raw_content=True, max_results=config.NEWS_SCENARIO_LIMIT, ) for item in tv_results.get("results", []): articles.append({ "source": "tavily", "title": item.get("title", ""), "url": item.get("url", ""), "snippet": item.get("content", ""), "date": item.get("published_date", ""), "raw_content": item.get("raw_content", ""), }) except Exception: logger.warning("Tavily also failed for scenario %s", sc_id) out_path.write_text(json.dumps(articles, default=str), encoding="utf-8") return len(articles) async def _run_part_b(scenarios_dir: Path) -> None: """Async per-scenario news collection.""" # Load scenarios benchmark_dir = config.get_benchmark_dir() scenarios_path = benchmark_dir / "scenarios.parquet" if not scenarios_path.exists(): logger.warning("scenarios.parquet not found at %s — skipping Part B", scenarios_path) return scenarios_df = pd.read_parquet(scenarios_path) scenarios = scenarios_df.to_dict("records") logger.info("Part B: collecting scenario news for %d events …", len(scenarios)) # Init clients firecrawl_api_key = os.environ.get("FIRECRAWL_API_KEY", "") tavily_api_key = os.environ.get("TAVILY_API_KEY", "") from projects.tools.web.firecrawl_search import FirecrawlClient from projects.tools.web.tavily_search import TavilyClient fc_client = FirecrawlClient(api_key=firecrawl_api_key) if firecrawl_api_key else None tv_client = TavilyClient(api_key=tavily_api_key) if tavily_api_key else None if fc_client is None and tv_client is None: logger.error("Neither FIRECRAWL_API_KEY nor TAVILY_API_KEY set — skipping Part B") return total = 0 for i, sc in enumerate(scenarios): if fc_client is not None: n = await _collect_single_scenario_news(sc, scenarios_dir, fc_client, tv_client) elif tv_client is not None: n = await _collect_single_scenario_news(sc, scenarios_dir, None, tv_client) else: n = 0 total += n await asyncio.sleep(config.NEWS_RATE_LIMIT_SEC) if (i + 1) % 10 == 0: logger.info(" Part B progress: %d / %d scenarios", i + 1, len(scenarios)) logger.info("Part B complete: %d articles across %d scenarios", total, len(scenarios)) # --------------------------------------------------------------------------- # Public entry points # --------------------------------------------------------------------------- async def run_async(tickers: list[str] | None = None) -> None: """Run both Part A and Part B news collection. Parameters ---------- tickers : list[str] | None Ticker symbols for Part A. If None, reads from universe CSV. """ tickers_dir, scenarios_dir = _ensure_dirs() # Resolve tickers if tickers is None: universe_path = config.UNIVERSE_DIR / "benchmark_universe.csv" if universe_path.exists(): tickers = pd.read_csv(universe_path)["ticker"].tolist() else: logger.error("No tickers provided and universe CSV not found") return # Part A: synchronous (uses ThreadPoolExecutor internally) _run_part_a(tickers, tickers_dir) # Part B: async await _run_part_b(scenarios_dir) logger.info("News collection complete.")