How it works

This project uses a fork of python-bridge (opens in a new tab) to spawn a Python interpreter as a subprocess and communicates back and forth via standard Unix pipes. The IPC pipes don't interfere with stdout/stderr/stdin, so your Node.js code and the underlying Python code can print things normally.

The TS library is auto-generated from the Python scikit-learn API docs (opens in a new tab). By using the official Python docs as a source of truth, we can guarantee a certain level of compatibility and upgradeability.

For each scikit-learn HTML page that belongs to an exported Python class or function, we first parse it's metadata, params, methods, attributes, etc using cheerio, then we convert the Python types into equivalent TypeScript types. We then generate a corresponding TypeScript file which wraps an instance of that Python declaration via a PythonBridge.

For each TypeScript wrapper class of function, we take special care to handle serializing values back and forth between Node.js and Python as JSON, including converting between primitive arrays and numpy arrays where necessary. All numpy array conversions should be handled automatically for you since we only support serializing primitive JSON types over the PythonBridge. There may be some edge cases where the automatic numpy inference fails, but we have a regression test suite for parsing these cases, so as long as the official Python docs are correct for a given type, then our implicit numpy conversion logic should "just work".