A simple, easy-to-use, unofficial Python wrapper for the ThetaData REST API.
The original thetadata-python library is deprecated and it's preferred to use the REST API directly.
Their documentation provides Python examples for the REST API that are useful and comprehensive and you'll find these on every endpoint page (example). This library is a simple wrapper on those examples into neat classes and functions that anyone can download and use. It provides 2 additional conveniences:
- Integration with pandas, so data is returned to your program directly in a DataFrame.
- A CLI (command-line-interface) wrapper for downloading data directly without writing any code yourself
Make sure ThetaTerminal is running - nothing will work without it!
This library currently provides 3 classes for core operations:
ThetaDataStocksHistoricalThetaDataStocksSnapshotThetaDataOptions
Here's an example of using the snapshot object to get current market quotes:
stocks_snapshot = ThetaDataStocksSnapshot(log_level="INFO", output_dir="./output")
quotes_df = stocks_snapshot.get_quotes("AAPL")
print(quotes_df.head())
Several code examples are available here.
There's also a command line interface available in cli. You can use it as follows:
(pft) ➜ cli git:(main) python thetadata_cli.py
Usage: thetadata_cli.py [OPTIONS] COMMAND [ARGS]...
╭─ Options ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --install-completion Install completion for the current shell. │
│ --show-completion Show completion for the current shell, to copy it or customize the installation. │
│ --help Show this message and exit. │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Commands ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ options │
│ stocks │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Subcommands nest downwards naturally. For example, let's say you want to get historical OHLC data for a stock:
(pft) ➜ cli git:(main) python thetadata_cli.py stocks historical ohlc AAPL 20240101 20240201
⠸ Loading data...Data retrieved successfully
This will save the data as a local CSV named ohlc_AAPL_20240101_20240201.csv. Many examples of CLI usage can be found here.
If you want to learn more about working with market data in Python, here are some resources for you:
- Free Algo Trading Academy
- Free Tutorial Videos
- Course: Financial Data Mastery
- Learn to acquire, augment, analyze, and automate the way you work with financial data.
- Project: Securities Master Database and ETL Pipeline:
- Build a securities database and data pipeline that you can apply and adopt for your own market data needs right away.