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YFinance client for fetching SPY/SPX option chain data.
This is a backup data source when OpenBB is unavailable.
"""
from typing import Optional, List, Tuple
from datetime import datetime, timedelta
import pandas as pd
import numpy as np
import yfinance as yf
class YFinanceClient:
"""Client for fetching option data from Yahoo Finance."""
def __init__(self):
"""Initialize YFinance client."""
pass
def get_spy_options(
self,
ticker: str = "SPY",
min_expiry_days: int = 7,
max_expiry_days: int = 90
) -> pd.DataFrame:
"""
Fetch SPY option chain data from Yahoo Finance.
Args:
ticker: Ticker symbol (SPY or ^SPX)
min_expiry_days: Minimum days to expiration
max_expiry_days: Maximum days to expiration
Returns:
DataFrame with columns:
- strike: Strike price
- expiration: Expiration date
- optionType: 'call' or 'put'
- bid: Bid price
- ask: Ask price
- lastPrice: Last traded price
- volume: Volume
- openInterest: Open interest
- impliedVolatility: Implied volatility
"""
try:
# Create ticker object
stock = yf.Ticker(ticker)
# Get all expiration dates
expirations = stock.options
if not expirations:
raise ValueError(f"No option data available for {ticker}")
# Filter expirations by date range
today = datetime.now()
valid_expirations = []
for exp_str in expirations:
exp_date = datetime.strptime(exp_str, '%Y-%m-%d')
days_to_exp = (exp_date - today).days
if min_expiry_days <= days_to_exp <= max_expiry_days:
valid_expirations.append(exp_str)
if not valid_expirations:
raise ValueError(
f"No expirations found between {min_expiry_days} and {max_expiry_days} days"
)
# Fetch option chains for valid expirations
all_options = []
for exp_date in valid_expirations:
try:
# Get option chain
opt_chain = stock.option_chain(exp_date)
# Process calls
calls = opt_chain.calls.copy()
calls['optionType'] = 'call'
calls['expiration'] = exp_date
# Process puts
puts = opt_chain.puts.copy()
puts['optionType'] = 'put'
puts['expiration'] = exp_date
# Combine
all_options.extend([calls, puts])
except Exception as e:
print(f"Warning: Failed to fetch options for {exp_date}: {str(e)}")
continue
if not all_options:
raise ValueError("Failed to fetch any option data")
# Concatenate all data
df = pd.concat(all_options, ignore_index=True)
# Standardize column names
df = self._standardize_columns(df)
# Calculate days to expiry
df['days_to_expiry'] = df['expiration'].apply(
lambda x: (datetime.strptime(x, '%Y-%m-%d') - today).days
)
# Clean data
df = self._clean_option_data(df)
return df
except Exception as e:
raise RuntimeError(f"Failed to fetch option data from YFinance: {str(e)}")
def get_spot_price(self, ticker: str = "SPY") -> float:
"""
Get current spot price for the underlying.
Args:
ticker: Ticker symbol
Returns:
Current price
"""
try:
stock = yf.Ticker(ticker)
info = stock.info
return float(info.get('currentPrice', info.get('regularMarketPrice', 0)))
except Exception as e:
# Fallback: get from recent history
try:
stock = yf.Ticker(ticker)
hist = stock.history(period='1d')
return float(hist['Close'].iloc[-1])
except:
raise RuntimeError(f"Failed to fetch spot price: {str(e)}")
def get_option_expirations(self, ticker: str = "SPY") -> List[str]:
"""
Get available option expiration dates.
Args:
ticker: Ticker symbol
Returns:
List of expiration dates (YYYY-MM-DD format)
"""
try:
stock = yf.Ticker(ticker)
return list(stock.options)
except Exception as e:
raise RuntimeError(f"Failed to fetch expirations: {str(e)}")
def get_options_by_expiration(
self,
expiration_date: str,
ticker: str = "SPY"
) -> Tuple[pd.DataFrame, pd.DataFrame]:
"""
Get calls and puts for a specific expiration date.
Args:
expiration_date: Expiration date (YYYY-MM-DD)
ticker: Ticker symbol
Returns:
Tuple of (calls_df, puts_df)
"""
try:
stock = yf.Ticker(ticker)
opt_chain = stock.option_chain(expiration_date)
calls = opt_chain.calls.copy()
calls = self._standardize_columns(calls)
calls['expiration'] = expiration_date
calls['optionType'] = 'call'
puts = opt_chain.puts.copy()
puts = self._standardize_columns(puts)
puts['expiration'] = expiration_date
puts['optionType'] = 'put'
return calls, puts
except Exception as e:
raise RuntimeError(f"Failed to fetch options for {expiration_date}: {str(e)}")
def _standardize_columns(self, df: pd.DataFrame) -> pd.DataFrame:
"""
Standardize column names to match OpenBB format.
Args:
df: Raw yfinance DataFrame
Returns:
DataFrame with standardized columns
"""
# YFinance uses different column names
column_mapping = {
'strike': 'strike',
'lastPrice': 'lastPrice',
'bid': 'bid',
'ask': 'ask',
'volume': 'volume',
'openInterest': 'openInterest',
'impliedVolatility': 'impliedVolatility'
}
# Rename columns if they exist
df = df.rename(columns=column_mapping)
return df
def _clean_option_data(self, df: pd.DataFrame) -> pd.DataFrame:
"""
Clean and validate option data.
Args:
df: Raw option DataFrame
Returns:
Cleaned DataFrame
"""
# Remove rows with missing critical data
df = df.dropna(subset=['strike', 'lastPrice', 'impliedVolatility'])
# Remove zero or negative prices
df = df[df['lastPrice'] > 0]
# Remove zero or negative IV
df = df[df['impliedVolatility'] > 0]
# Calculate mid price from bid-ask if available
if 'bid' in df.columns and 'ask' in df.columns:
df['midPrice'] = (df['bid'] + df['ask']) / 2
# Use mid price if available and reasonable
df['price'] = df.apply(
lambda row: row['midPrice']
if pd.notna(row['midPrice']) and row['midPrice'] > 0
else row['lastPrice'],
axis=1
)
else:
df['price'] = df['lastPrice']
# Sort by strike
df = df.sort_values(['expiration', 'strike'])
return df
def get_spy_options(*args, **kwargs) -> pd.DataFrame:
"""Convenience function to fetch SPY options."""
client = YFinanceClient()
return client.get_spy_options(*args, **kwargs)
def get_spot_price(ticker: str = "SPY") -> float:
"""Convenience function to get spot price."""
client = YFinanceClient()
return client.get_spot_price(ticker)
if __name__ == "__main__":
# Test the client
print("Testing YFinance client...")
try:
client = YFinanceClient()
# Get spot price
spot = client.get_spot_price("SPY")
print(f"SPY spot price: ${spot:.2f}")
# Get available expirations
expirations = client.get_option_expirations("SPY")
print(f"\nAvailable expirations: {expirations[:5]}")
# Get option chain
options = client.get_spy_options("SPY", min_expiry_days=20, max_expiry_days=40)
print(f"\nFetched {len(options)} option contracts")
print(f"Expirations: {options['expiration'].unique()}")
print(f"Strike range: ${options['strike'].min():.2f} - ${options['strike'].max():.2f}")
# Show sample data
print("\nSample data:")
print(options[['strike', 'expiration', 'optionType', 'lastPrice', 'impliedVolatility']].head())
print("\n✅ YFinance client test passed!")
except Exception as e:
print(f"\n❌ YFinance client test failed: {str(e)}")
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