yfinance-extended

yfinance Package with Wide-Form Data Support and Data Export

yfinance-extended extends yfinance package by Ran Aroussi and make it easier to:

1. Retrieve multiple-ticker intraday price data in a wide-form pandas dataframe;
2. Read options data for all available expiration dates;
3. Retrieve top-of-the-book bid-ask prices and sizes; and,
4. Store data in the parquet format with the following structure:

./saved_data
├── AAPL
│   ├── AAPL-2023-04-24.parquet
│   ├── AAPL-2023-04-25.parquet
│   ├── AAPL-2023-04-26.parquet
│   ├── AAPL-2023-04-27.parquet
│   └── AAPL-2023-04-28.parquet
└── TSM
    └── TSM-2023-04-24.parquet
    └── TSM-2023-04-25.parquet
    └── TSM-2023-04-26.parquet
    └── TSM-2023-04-27.parquet
    └── TSM-2023-04-28.parquet

Sample Usage

Get Historical Data

Getting past five days of minute-by-minute prices of Apple, Inc., including pre-/post-market data.

import yfinance-extended as yfe

loader = yfe.YahooBatchLoader()

price_df = get_historical_prices("AAPL", period="5d", interval="1m", prepost=True)
prices_df = get_historical_prices(["AAPL", "GOOGL"], period="5d", interval="1m", prepost=True)

Read all Available Options Information

options_df = loader.options_data("AAPL")

Get Top-of-the-Book Data

live_prices_df = loader.get_prices("AAPL")
live_prices_df = loader.get_prices(["AAPL", "GOOGL"])

Save to and Read Data from Parquet Files

Save files:

prices_df = get_historical_prices(["AAPL", "GOOGL"], period="5d", interval="1m", prepost=True)
yfe.to_parquet(prices_df, root_dir="./data")

Read files:

prices_df = yfe.read_parquet(root_dir="./data")

Alternatively, if you wish to save all data into one file:

# Write to one file
yfe.to_parquet(prices_df, filepath="./data/datafile.parquet")

# Read from the file
prices_df = yfe.read_parquet(filepath="./data/datafile.parquet")