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Optopsy is a Python-based, nimble backtesting and statistics library focused on evaluating options trading strategies like calls, puts, straddles, spreads, and more, using pandas-driven analysis. The csv_data() function is a convenience function. Under the hood it uses Panda's read_csv() function to do the import. There are other parameters that can help with loading the csv data, consult the code/future documentation to see how to use them. Optopsy is a small simple library that offloads the heavy work of backtesting option strategies, the API is designed to be simple and easy to implement into your regular Panda's data analysis workflow. As such, we just need to call the long_calls() function to have Optopsy generate all combinations of a simple long call strategy for the specified time period and return a DataFrame. Here we also use Panda's round() function afterwards to return statistics within two decimal places.
Features
- Supports strategies including calls/puts, straddles, strangles, and vertical spreads
- Enables evaluation of performance statistics (e.g., percent change, profit potential) for strategies like SPX straddles
- Accepts data from any source via pandas DataFrames—compatible with flexible inputs
- Provides filters and composable backtest parameters (entry/exit rules like DTE, delta, stop‑loss, profit target)
- Integrates seamlessly into pandas workflows via DataFrame extensions
- Licensed under GPL-3.0, with easy installation via pip install optopsy
Project Samples
