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Reposted by The PyPy Project

Tobias @krono.toot.berlin.ap.brid.gy · 25/03/2026

Do I see this right that pypy is immortalized in the python3 Docs? :D

a screenshot from the pyhon3 documentation, argparse. Left: table of contents, right:
```
:et’s show the sort of functionality that we are going to explore in this introductory tutorial by making use of the ls command:

ls
cpython devguide prog.py pypy rm-unused-function.patch
ls pypy
ctypes_configure demo dotviewer include lib_pypy lib-python ...
ls -l
total 20
drwxr-xr-x 19 wena wena 4096 Feb 18 18:51 cpython
drwxr-xr-x 4 wena wena 4096 Feb 8 12:04 devguide
-rwxr-xr-x 1 wena wena 535 Feb 19 00:05 prog.py
drwxr-xr-x 14 wena wena 4096 Feb 7 00:59 pypy
-rw-r--r-- 1 wena wena 741 Feb 18 01:01 rm-unused-function.patch
ls --help
Usage: ls [OPTION]... [FILE]...
List information about the FILEs (the current directory by default).
Sort entries alphabetically if none of -cftuvSUX nor --sort is specified.
...

```

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Reposted by The PyPy Project

Laurence Tratt @ltratt.bsky.social · 15/04/2026

C interpreters underlie many of our most widely used language implementations -- but they're slow. Wouldn't it be great if we could turn them into JIT compiling VMs? This video shows what happens when we do just that to the normal Lua VM (first) and "yklua" (Lua w/JIT, second).

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Reposted by The PyPy Project

oberstet.bsky.social @oberstet.bsky.social · 07/11/2025

#Autobahn v25.10.2 Released: #WebSocket & #WAMP for Python with Critical Fixes and Enhanced CI/CD, #PyPy Support, Binary Wheels, and native NVX (SIMD vector acceleration) - **📋 Full Announcement:** github.com/crossbario/a... - **🌐 WAMP Protocol:** wamp-proto.org

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Reposted by The PyPy Project

Stefan Marr @stefan-marr.de · 09/06/2025

This year's DLS Most Notable Paper award goes to Compiling for Multi-language Task Migration by Marc Feeley The paper is motivated by the challenges of implementing continuations for an uncooperative environment, and worth a read! Congratulations to the author! www.iro.umontreal.ca/~feeley/pape...

The award with the following citation:

Recent years have seen a resurgent interest in the use and implementation of first-class control, especially in the form of delimited continuations via effect handlers. This paper is motivated by the challenges of implementing continuations for an uncooperative environment and the opportunities for code migration that the implementation affords. The paper recaps the design of the Gambit Virtual Machine for efficient continuations, and it provides evidence for the ongoing effectiveness of the design.

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Reposted by The PyPy Project

CF Bolz-Tereick @cfbolz.bsky.social · 12/06/2025

"How slow is the tracing interpreter of PyPy's meta-tracing JIT?" cfbolz.de/posts/speed-... Spoiler: for the microbenchmark I tried, the slowdown of the meta-tracing interpreter is about 900x

cfbolz.de

How slow is the tracing interpreter of PyPy's meta-tracing JIT?

I wanted to investigate the warmup behavior of the PyPy interpreter, so I wrote a somewhat arbitrary microbenchmark: all_results = set() num = int(sys.argv[1]) class A(object): pass def main():

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The PyPy Project @pypyproject.bsky.social · 21/05/2025

Adding heap operations to Z3 didn't actually find any bugs in the JIT optimizer for heap operations. Maybe that's not entirely surprising, because miscompilations in that area tend to lead to crashes pretty quickly. In any case, it's good to have that infrastructure for the future.

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The PyPy Project @pypyproject.bsky.social · 21/05/2025

We also added limited support for generating random heap operations to our JIT optimizer fuzzer. This extends previous work, which supported only int operations in Z3: pypy.org/posts/2022/1...

pypy.org

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The PyPy Project @pypyproject.bsky.social · 21/05/2025

Christoph Jung, another student @cfbolz.bsky.social, added a memory model to our Z3 based translation validation. Now our CI checks whether our optimizer unit tests contain invalid optimizations using Z3.

pypy.org

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The PyPy Project @pypyproject.bsky.social · 21/05/2025

Micro-benchmarks for both optimizations look great, but both are hard to see in the performance of bigger programs.

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The PyPy Project @pypyproject.bsky.social · 21/05/2025

An unrelated optimization we also merged was to make store-to-load and load-to-load forwarding work for array reads and writes where the index is a variable. This already worked for constant indexes before.

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The PyPy Project @pypyproject.bsky.social · 21/05/2025

We've already had type based alias analysis before, but only taking the RPython level types into account. Unfortunately instances of different Python classes get represented as instances of the same RPython type, making the old JIT logic useless for distinguishing them, which is now fixed.

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The PyPy Project @pypyproject.bsky.social · 21/05/2025

We just merged an improvement to the PyPy JIT heap optimizations: type based alias analysis for Python instances. Work was done by @cfbolz.bsky.social and their student Nico Rittinghaus.

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Reposted by The PyPy Project

Ned Batchelder @nedbat.com · 09/03/2025

nedbatchelder.com/blog/202503/... After nearly two years, I think this is finally ready: coverage․py can use sys.monitoring to more efficiently measure branch coverage.

nedbatchelder.com

Faster branch coverage measurement

After nearly two years, I think this is finally ready: coverage.py can use <a rel="external noopener" href="https://docs.python.org/3/library/sys.monitoring.html">sys.monitoring</a> to more efficientl...

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Reposted by The PyPy Project

matti-p.bsky.social @matti-p.bsky.social · 26/02/2025

Fast on the heels of the last release, I have published a PyPy v7.3.19 bug-fix release with PyPy2.7, PyPY3.10 and a beta-quality PyPy3.11. Please try it out! The complete release note is at doc.pypy.org/en/latest/re...

doc.pypy.org

PyPy v7.3.19: release of python 2.7, 3.10 and 3.11 beta, released 2025-02-26 — PyPy documentation

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Reposted by The PyPy Project

CF Bolz-Tereick @cfbolz.bsky.social · 25/02/2025

New blog post by my excellent master student Christoph Jung: "Low Overhead Allocation Sampling with VMProf in PyPy's GC" pypy.org/posts/2025/0... Hopefully the first in a series about his work on a sampling allocation profiler for PyPy

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CF Bolz-Tereick @cfbolz.bsky.social · 13/02/2025

Since I was now wondering, here's PyPy VS CPython 3.x binary sizes

Plot of CPython and PyPy binary sizes over time. CPython 3.7 is 35 MiB, shrinks to 22.5 MiB in 3.8, then slowly grows again until 3.11 at 25.2 MiB. Cpython 3.12 is much bigger, at 37.3 MiB. CPy 3.13 shrinks a bit again to 36.1 MiB.

PyPy tracks the ups and downs in roughly the same shape but is generally much bigger. 3.7 is at 60.5, 3.8 at 56.2, then it slowly increases to 58.8 at PyPy 3.11

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The PyPy Project @pypyproject.bsky.social · 13/02/2025

Interestingly enough PyPy 3.x is mostly smaller than 2.7. E.g. PyPy 3.11 is 58.8 MiB, despite having a bunch more features. I never quite figure out why. Just for comparison, CPython 3.11 is 25.2 MiB.

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The PyPy Project @pypyproject.bsky.social · 13/02/2025

This is the size of PyPy 2.7, btw. It doesn't make sense to use the 3.x variant for this, because the size of that changes due to newer Python versions being implemented over time.

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The PyPy Project @pypyproject.bsky.social · 13/02/2025

We don't do this regularly or anything, but every couple of years @cfbolz.bsky.social looks at how the PyPy binary sizes have developed. Looks like an ok balance between occasionally cleaning something up and thereby shrinking the binary; and then slow growth or explicit time/binary-size-tradeoffs.

plot showing how the PyPy binary went from 68 MiB in early 2020 to 61 MiB today, with a few ups and downs in between. various points in time are annotated with reasons for growth and shrinkage. the biggest shrinkage is: 2022-05-10 compact jitcode liveness info

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The PyPy Project @pypyproject.bsky.social · 09/02/2025

As a response to these benchmarks, @cfbolz.bsky.social optimized `itertools.islice` for the common case where no step is given, and also for converting large but not very large integers to strings (basically any int that doesn't fit into 64 bits, but is also not really huge, maybe a few words).

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The PyPy Project @pypyproject.bsky.social · 09/02/2025

Tim Peters benchmarking Python 3.13 vs PyPy on an OEIS sequence program he wrote: discuss.python.org/t/python-3-1... (the results are complicated, on one version Python 3.13 wins, but on others PyPy does).

discuss.python.org

Python 3.13.0 speed

This is a hearty “congratulations!” message. I often tackle a problem inspired by The On-Line Encyclopedia of Integer Sequences (OEIS). Here, sequence A378048: integers k such that k and k**2 together...

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The PyPy Project @pypyproject.bsky.social · 07/02/2025

So far this is a rather low-level mechanism, there's no convenient pdb integration yet. We plan to add something like that later, for now you can use a third-party package such as sdb to get an actual remote debugger going: github.com/ryanpetrello...

github.com

GitHub - ryanpetrello/sdb: a socket-based remote debugger for Python

a socket-based remote debugger for Python. Contribute to ryanpetrello/sdb development by creating an account on GitHub.

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The PyPy Project @pypyproject.bsky.social · 07/02/2025

The other new feature an implementation of the draft PEP 768, "Safe external debugger interface" (again, Linux only so far). PEP was written by @pablogsal.com et al. It allows you to remotely attach to a running PyPy process and inject Python code into it. doc.pypy.org/en/latest/re...

doc.pypy.org

Remote Debugging — PyPy documentation

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The PyPy Project @pypyproject.bsky.social · 07/02/2025

We have further features planned for VMProf, including a stochastic memory profiler hopefully coming out later this year.

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The PyPy Project @pypyproject.bsky.social · 07/02/2025

Here's a screenshot of the Firefox Profiler UI showing VMProf output. The blue functions are native functions, yellow is Python functions and orange jitted functions (no example of that is in the screenshot).

A screenshot of the Firefox profiler UI. It shows a hierarchically expandable view of stack traces together with counts of which stack traces were seen how often during sampling. The top layers of a stack trace are always yellow Python functions. the bottom layers show the native functions that these Python functions call in blue. One of the functions is selected, with extra information shown in a pane on the right.

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The PyPy Project @pypyproject.bsky.social · 07/02/2025

It works best by combining it with vmprof-firefox-profile, which converts vmprof output to a format the Firefox Profiler UI can read: github.com/Cskorpion/vm... (We're still working on a PyPI release of this tool.)

github.com

GitHub - Cskorpion/vmprof-firefox-converter: Firefox-Profiler as UI for VMProf

Firefox-Profiler as UI for VMProf. Contribute to Cskorpion/vmprof-firefox-converter development by creating an account on GitHub.

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The PyPy Project @pypyproject.bsky.social · 07/02/2025

VMProf on PyPy can now sample native functions and symbolify their names (Linux only at the moment). VMProf for CPython has had that feature for a while, we've now ported it to PyPy.

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The PyPy Project @pypyproject.bsky.social · 07/02/2025

Here's the blog post about the PyPY 7.3.18 release that came out yesterday. Thanks to @matti-p.bsky.social, our release manager! This the first version with 3.11 support (beta only so far). Two cool other features in the thread below. pypy.org/posts/2025/0...

pypy.org

PyPy v7.3.18 release

PyPy v7.3.18: release of python 2.7, 3.10 and 3.11 beta The PyPy team is proud to release version 7.3.18 of PyPy. This release includes a python 3.11 interpreter. We are labelling it "beta" because it

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matti-p.bsky.social @matti-p.bsky.social · 06/02/2025

PyPy 7.3.18, with Python3.11, 3.10, 2.7 is released. See the release note at doc.pypy.org/en/latest/re...

doc.pypy.org

PyPy v7.3.18: release of python 2.7, 3.10 and 3.11 beta, released 2025-02-06 — PyPy documentation

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