Deploying scikit-learn models in Pyodide Use pickle?
24
Classifier decision boundary example
25
Packaging Scipy and Fortran
26
Function Pointer Cast Handling
27
Getting http.client to work (WIP)
28
Asyncio in the browser
29
Download sizes for packages
30
Make Python package sizes web friendly
31
Roadmap
32
Acknowledgement
Description:
Explore Pyodide, a Python distribution for the browser and Node.js based on WebAssembly, in this PyCon US talk. Discover how to run Python applications in the browser, learn about porting existing Python packages, and understand the criteria for determining project suitability. Delve into Pyodide's components, including CPython 3.9 ported to WebAssembly/Emscripten, and its robust Javascript ⟺ Python foreign function interface. Examine examples of Python utils from JavaScript, random sampling, and using the fetch API from Python. Investigate the Emscripten host environment, client-only architecture, and the growing ecosystem of notebook environments and educational applications. Learn about deploying machine learning models, including scikit-learn models in Pyodide, and explore challenges such as function pointer cast handling and making Python package sizes web-friendly. Gain insights into Pyodide's roadmap and its potential impact on serverless Python apps for the web.