release date: end august (may be delayed early september waiting pytorch and numba)

wanted:

• technical debt removal:
  • no more NullSoft usage to create the launchers (only mkshim400.py + pywin32)
  • no more inno setup code
  • no more NullSoft installer code
• Fitness challenge:
  • a slim version < 650 Mo , so it can be checked on virustotal.com
  • standard version < 900 Mo
• easing Security Checking challenge:
  • releasing a .7z big distro seems now a better idea than .exe, as Windows now supports unpacking .7z
  • as interim, a slim build with .exe format will be provided
• numpy-2.0.1
• numpy-2+ may require torch-2.4.1 and numba-0.61 ?

focus:

• simplification of build and maintenance:
  • drop packages.ini, use only package provided summary
  • further simplification or removal of internal code
  • less packages... less updates to check
  • remove NSIS use for launchers from ALL launchers
  • remove redundant "WinPython Terminal" launcher
  • remove all Inno Setup code
  • Python needs for a build to get down to WinPythondot: flit + packaging + Pywin32
• simplification of end-user checkings:
  • slim version
  • no auto-executable archives the big version

postpone (no time):

• jupyterlite more: webnn may be a thing: https://webmachinelearning.github.io/webnn-intro/
• llm and generative AI: whisper.cpp
• replacing torch per jax[cpu] would shrink WinPython by 100Mo (or not increase per 200 More) ?
• WinPythondot being enough to build a WinPython...
• free-threading effort delayed to 3.14, and eco-system is a big mountain to climb:
  • essential-for-speed patches will only be in 3.14 cycle, 3.13t will have accepted leakages ... it's a Work-in-Process state
  • pyzmq doesn't support multi-threads
  • so... no cython, no jupyterlab (until pyzmq replaced), .... hummmm end-game is looking year 2026
• free-threading test:
  • scientific builds tests there https://github.com/Quansight-Labs/free-threaded-compatibility
• llm: AI agents and the 7b models, whispers made easy coming to town ?

Direction:

• Help to Python Sustainability improvement:
  • favorise latest=more efficient and maintained python
  • favorise speed = Free-threading (complex) revolution
  • favorise external data motors: dataframe interchange protocol, numpy-2, pandas-3, scikit-learn integrating polars,
  • favorise AI: onnx (for AI PC), llvm local small equivalent to ggerganov/whisper.cpp
• Help to Python Reachability:
  • in browser (and WebApp): Jupyterlite prototype (https://stonebig.github.io/my_demo_4/lab/index.html),
  • WASI: in VSCode
  • inside Excel 365: asks Operational Research packages
  • in Windows Store: a requirement file- remove need of build pieces: nsis, 7zip
• PEP-751:
  • WinPython ideal world is to shrink to a toml file specifying package/version/hash