Faster Python, beyond semantic interposition

#501 has a useful suggestion for speeding up Python by ~20%. After that's done, it's actually possible to do better.

Host is Fedora 33. All tests were run with Python 3.9.

On host:

• Fedora's Python gives 200K pystone/sec.
• Conda-Forge Python gives 240K pystone/sec.

Running inside Docker 20.04 (cgroups v2 enabled):

• fedora:33 gives 173K pystone/sec.
• python:3.9-slim-buster, I get 169K pystone/sec.
• ubuntu:20.04 (no shared library): 183K pystone/sec.
• continuumio/miniconda3 with Python from Conda-Forge: 189K/sec

I am mystified why things are so much slower inside Docker. Some of this is clearly not because of the image, but the runtime. But notice the Ubuntu image is definitely faster.

With podman:

• python:3.9-slim-buster: 204K/sec
• continuumio/miniconda3 with Python from Conda-Forge: 230K/sec

Note that the Anaconda (default Conda) Python 3.9 does not appear faster, it's specifically whatever Conda-Forge does. I am trying to figure that out.

Comienza reproduciendo los resultados de pystone informados con Docker y Podman en las imágenes de Fedora, Ubuntu, Debian slim y Conda-Forge enumeradas en el issue. Compara el runtime de Python y las condiciones de las imágenes que difieren entre esas ejecuciones. Se considerará terminado cuando se haya identificado una causa específica y reproducible de la diferencia de rendimiento y se haya documentado una mejora aplicable.