You should look at the self-executing .pex file format (https://docs.pex-tool.org/whatispex.html). The whole python program exists as a single file. You can also unzip the .pex and inspect the dependency tree.

It's tooling agnostic and there are a couple ways to generate them, but the easiest it to just use pants build.

Pants also does dependency traversal (that's the main reason we started using it, deploying a microservices monorepo) so it only packages the necessary modules.

I haven't profiled it yet for cold starts, maybe I'll test that real quick.

https://www.pantsbuild.org/dev/docs/python/overview/pex

Edit: just ran it on a hello world with py3.14 on m3 macbook pro, about 100 +/-30 ms for `python -m hello` and 300-400 (but wild variance) for executing the pex with `./hello/binary.pex`.

I'm not sure if a pants expert could eke out more speed gains and I'm also not sure if this strategy would win out with a lot of dependencies. I'm guessing the time required to stat every imported file pales in comparison to the actual load time, and with pex, everything needs to be unzipped first.

Pex is honestly best when you want to build and distribute an application as a single file (there are flags to bundle the python interpreter too).

The other option is mypyc, though again that seems to mostly speed up runtime https://github.com/mypyc/mypyc

Now if I use `python -S` (disables `import site` on initialization), that gets down to ~15ms execution time for hello world. But that gain gets killed as soon as you start trying to import certain modules (there is a very limited set of modules you can work with and still keep speedup. So if you whole script is pure python with no imports, you could probably have a 20ms cold start).