Thursday, 13th February 2025
URL-addressable Pyodide Python environments
This evening I spotted an obscure bug in Datasette, using Datasette Lite. I figure it’s a good opportunity to highlight how useful it is to have a URL-addressable Python environment, powered by Pyodide and WebAssembly.
[... 1,905 words]python-build-standalone now has Python 3.14.0a5. Exciting news from Charlie Marsh:
We just shipped the latest Python 3.14 alpha (3.14.0a5) to uv and python-build-standalone. This is the first release that includes the tail-calling interpreter.
Our initial benchmarks show a ~20-30% performance improvement across CPython.
This is an optimization that was first discussed in faster-cpython in January 2024, then landed earlier this month by Ken Jin and included in the 3.14a05 release. The alpha release notes say:
A new type of interpreter based on tail calls has been added to CPython. For certain newer compilers, this interpreter provides significantly better performance. Preliminary numbers on our machines suggest anywhere from -3% to 30% faster Python code, and a geometric mean of 9-15% faster on pyperformance depending on platform and architecture. The baseline is Python 3.14 built with Clang 19 without this new interpreter.
This interpreter currently only works with Clang 19 and newer on x86-64 and AArch64 architectures. However, we expect that a future release of GCC will support this as well.
Including this in python-build-standalone means it's now trivial to try out via uv. I upgraded to the latest uv
like this:
pip install -U uv
Then ran uv python list
to see the available versions:
cpython-3.14.0a5+freethreaded-macos-aarch64-none <download available>
cpython-3.14.0a5-macos-aarch64-none <download available>
cpython-3.13.2+freethreaded-macos-aarch64-none <download available>
cpython-3.13.2-macos-aarch64-none <download available>
cpython-3.13.1-macos-aarch64-none /opt/homebrew/opt/python@3.13/bin/python3.13 -> ../Frameworks/Python.framework/Versions/3.13/bin/python3.13
I downloaded the new alpha like this:
uv python install cpython-3.14.0a5
And tried it out like so:
uv run --python 3.14.0a5 python
The Astral team have been using Ken's bm_pystones.py benchmarks script. I grabbed a copy like this:
wget 'https://gist.githubusercontent.com/Fidget-Spinner/e7bf204bf605680b0fc1540fe3777acf/raw/fa85c0f3464021a683245f075505860db5e8ba6b/bm_pystones.py'
And ran it with uv
:
uv run --python 3.14.0a5 bm_pystones.py
Giving:
Pystone(1.1) time for 50000 passes = 0.0511138
This machine benchmarks at 978209 pystones/second
Inspired by Charlie's example I decided to try the hyperfine benchmarking tool, which can run multiple commands to statistically compare their performance. I came up with this recipe:
brew install hyperfine
hyperfine \
"uv run --python 3.14.0a5 bm_pystones.py" \
"uv run --python 3.13 bm_pystones.py" \
-n tail-calling \
-n baseline \
--warmup 10
So 3.14.0a5 scored 1.12 times faster than 3.13 on the benchmark (on my extremely overloaded M2 MacBook Pro).