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import requests |
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from fastapi import FastAPI, HTTPException, status |
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from pydantic import BaseModel |
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from typing import List, Dict, Optional, Any |
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from data_ingestion.api_loader import get_daily_adjusted_prices, DataIngestionError |
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import logging |
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logging.basicConfig( |
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level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s" |
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) |
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logger = logging.getLogger(__name__) |
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app = FastAPI(title="API Agent") |
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class MarketDataRequest(BaseModel): |
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tickers: List[str] |
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start_date: Optional[str] = None |
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end_date: Optional[str] = None |
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data_type: Optional[str] = "adjClose" |
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@app.post("/get_market_data") |
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def get_market_data(request: MarketDataRequest): |
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""" |
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Fetches daily adjusted market data by calling the data_ingestion layer (FMP). |
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Returns adjusted close prices per ticker per date. |
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""" |
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result: Dict[str, Dict[str, float]] = {} |
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errors: Dict[str, str] = {} |
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warnings: Dict[str, str] = {} |
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key = ( |
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request.data_type |
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if request.data_type in ["open", "high", "low", "close", "adjClose", "volume"] |
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else "adjClose" |
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) |
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for ticker in request.tickers: |
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try: |
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raw = get_daily_adjusted_prices(ticker) |
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time_series: Dict[str, Any] = {} |
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if isinstance(raw, dict): |
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time_series = raw |
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elif isinstance(raw, list): |
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logger.warning( |
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f"Loader returned list for {ticker}; filtering dict entries." |
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) |
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for rec in raw: |
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if isinstance(rec, dict) and "date" in rec: |
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date_val = rec["date"] |
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time_series[date_val] = rec |
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else: |
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logger.warning( |
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f"Skipping non-dict or missing-date entry for {ticker}: {rec}" |
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) |
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else: |
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raise DataIngestionError( |
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f"Unexpected format from loader for {ticker}: {type(raw)}" |
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) |
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ticker_prices: Dict[str, float] = {} |
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for date_str, values in time_series.items(): |
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if not isinstance(values, dict): |
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warnings.setdefault(ticker, "") |
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warnings[ticker] += f" Non-dict for {date_str}; skipped." |
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continue |
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if key not in values: |
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warnings.setdefault(ticker, "") |
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warnings[ticker] += f" Missing '{key}' on {date_str}." |
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continue |
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try: |
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ticker_prices[date_str] = float(values[key]) |
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except (TypeError, ValueError): |
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warnings.setdefault(ticker, "") |
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warnings[ticker] += f" Invalid '{key}' value on {date_str}." |
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if ticker_prices: |
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result[ticker] = ticker_prices |
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logger.info(f"Fetched {len(ticker_prices)} points for {ticker}.") |
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else: |
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warnings.setdefault(ticker, "") |
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warnings[ticker] += " No valid data points found." |
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except (requests.RequestException, DataIngestionError) as err: |
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errors[ticker] = str(err) |
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logger.error(f"Error fetching {ticker}: {err}") |
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except Exception as err: |
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errors[ticker] = f"Unexpected error for {ticker}: {err}" |
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logger.error(errors[ticker]) |
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if not result and errors: |
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raise HTTPException( |
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, |
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detail="Failed to fetch market data for all tickers.", |
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) |
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return {"result": result, "errors": errors, "warnings": warnings} |
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