PyPy has been working for me for several years now

Original Article ↗ Hacker News Discussion ↗

Naming confusion and Python culture

  • Multiple commenters confuse PyPy (interpreter) with PyPI (package index); several needed rereads to realize the article wasn’t about packaging.
  • Some blame poor naming within the same ecosystem; others note historical ambiguity over which name came first, and that PyPI was long nicknamed “the Cheese Shop.”
  • “Wheel” terminology confuses some; others explain it as a “wheel of cheese,” i.e., a standard cheese form, not a Monty Python reference.
  • There’s a split between liking playful, punny names and preferring descriptive, low‑cognitive‑load names.

Perception of PyPy’s achievements

  • Many see PyPy as an under‑celebrated, long‑running “heroic” effort that has quietly delivered performance benefits for years.
  • Some recall very responsive maintainers and good real‑world speedups on heavier problems.
  • Others compare its ambition to projects like GraalVM or other visionary “high‑magic” runtimes.

Why PyPy didn’t take over

  • Key blockers cited:
    • Historically lagging behind CPython feature releases.
    • Incomplete or fragile support for C extensions and Cython, especially widely used libraries like NumPy and PostgreSQL drivers.
    • Larger memory footprint and delayed garbage collection behavior.
  • There is debate on how well it keeps up with CPython today; some say “pretty well,” others point to small contributor base and inevitable drift.
  • Some used PyPy successfully “for years” but hit hard limits once they needed C/Fortran‑backed scientific or DB libraries.

JIT, performance, and CPython relationship

  • One side argues CPython historically treated performance as a non‑goal, in contrast to PyPy, and only moved toward JITs under pressure from other languages and big vendors.
  • Another side emphasizes compatibility constraints and public, scheduled CPython development; they see JIT work as inherently hard rather than neglected.
  • There’s disagreement on whether JIT was PyPy’s primary goal from the start; project history is cited in both directions.
  • Some argue Python doesn’t need to compete as a JITted language at all; others counter that users will keep trying to use Python for everything regardless.

Other tools and ecosystems

  • Alternative or related efforts mentioned include Shedskin, Nuitka, and CPython enhancements like “Faster CPython” and no‑GIL work.
  • pipx is praised as a “silent hero” for managing Python CLIs cleanly, contrasted with the alphabet soup of pip/PyPI/pipenv/pyenv/PyPy.