[KRAKRISMOTT]

If you want people to take your framework seriously, I suggest adding integrations with some of the bigger data vendors on this list:

https://quantpedia.com/links-tools/?category=historical-data

If you want to remain beginner friendly, consider perhaps DataBento for data and interactive brokers for trade execution. You are doing your users no favors by pushing them towards Alpaca and Yahoo finance. Quant finance is not a poor man's game and if you want to do any significant research into market microstructure you need good data. Alpaca is for shilling trades for consumer fintech. At the professional level you should consider something like Interactive Brokers at the very minimum, you want a broker that offers greater control over order routing and trade execution.

Use IB-insync for the integration.

[pyfreak182]

Thank you for your feedback. The Alpaca and Yahoo Finance APIs are provided as examples for convenience to help users get started with PyBroker, as they offer free data. However, PyBroker is data source agnostic, and it is possible to load data from any provider into a Pandas DataFrame and use it with PyBroker. See this notebook on creating custom data sources: https://www.pybroker.com/en/latest/notebooks/7.%20Creating%2...

WRT trade execution, PyBroker is currently only designed for backtesting and analysis right now.