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Running
on
Zero
File size: 3,565 Bytes
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from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
import yfinance as yf
import pandas as pd
from datetime import datetime, timedelta
import logging
from typing import Optional
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
app = FastAPI()
# Configure CORS
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # Allows all origins
allow_credentials=True,
allow_methods=["*"], # Allows all methods
allow_headers=["*"], # Allows all headers
)
def fetch_stock_data(symbol: str, period: str = "1y") -> pd.DataFrame:
"""
Fetch historical stock data for a given symbol using yfinance with authentication.
Args:
symbol (str): Stock symbol (e.g., 'AAPL')
period (str): Time period to fetch (default: '1y')
Returns:
pd.DataFrame: DataFrame containing historical stock data
"""
try:
# Create a Ticker object with authentication
ticker = yf.Ticker(symbol)
# Set authentication credentials
ticker._session.headers.update({
'User-Agent': 'Mozilla/5.0',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
'Accept-Language': 'en-US,en;q=0.5',
'Connection': 'keep-alive',
'Upgrade-Insecure-Requests': '1',
})
# Fetch historical data
df = ticker.history(period=period)
if df.empty:
logger.warning(f"No data found for symbol {symbol}")
return pd.DataFrame()
# Reset index to make Date a column
df = df.reset_index()
# Rename columns to match expected format
df = df.rename(columns={
'Date': 'date',
'Open': 'open',
'High': 'high',
'Low': 'low',
'Close': 'close',
'Volume': 'volume'
})
# Convert date to string format
df['date'] = df['date'].dt.strftime('%Y-%m-%d')
logger.info(f"Successfully fetched data for {symbol}")
return df
except Exception as e:
logger.error(f"Error fetching data for {symbol}: {str(e)}")
return pd.DataFrame()
@app.get("/")
async def root():
return {"message": "Stock Prediction API"}
@app.get("/api/stock/{symbol}")
async def get_stock_data(symbol: str, period: Optional[str] = "1y"):
"""
Get historical stock data for a given symbol.
Args:
symbol (str): Stock symbol (e.g., 'AAPL')
period (str, optional): Time period to fetch. Defaults to "1y".
Valid periods: 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max
Returns:
dict: Dictionary containing stock data and metadata
"""
try:
df = fetch_stock_data(symbol, period)
if df.empty:
raise HTTPException(status_code=404, detail=f"No data found for symbol {symbol}")
# Convert DataFrame to dictionary format
data = df.to_dict(orient='records')
return {
"symbol": symbol,
"period": period,
"data": data,
"count": len(data)
}
except Exception as e:
logger.error(f"Error processing request for {symbol}: {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000) |