GoKawiilPython 3.15a7, which is now just a uv python install 3.15 away on all major platforms, has lazy imports! This exciting feature, proposed in PEP 810, promises to make CLI applications faster (especially when using flags like --help ), and could make a lot of large code with lots of imports that don’t always get used faster too. Unlike the earlier, failed attempt, this requires libraries to put in some work. I’ve developed a helper tool to make it easy; I’d like to cover what lazy imports are and how to use my tool. Since this is the first library that I used AI heavily in developing, the second half of the post will cover how my experience with AI for a task like this went.
TL;DR: run uvx flake8-lazy --apply=list to make your code magically faster on Python 3.15!
What is a lazy import?
Imagine you have a file like this, with a standard Python argparse CLI:
import argparse import numpy def main (): parser = argparse . ArgumentParser () parser . add_argument ( "--foo" , action = "store_true" ) args = parser . parse_args () if args . foo : print ( numpy . array ([ 1 , 2 , 3 ]))
What happens if you run this with --help ? The numpy library will be imported, even though it is never used. If you are using modern uv tooling, this can be even worse, since uv doesn’t pre-compile bytecode unless you ask it to; that makes the install faster, but imports are slower the first time.
The above is just one example; this can also happen when you have this common pattern:
# __init__.py from . import a from . import b __all__ = [ "a" , "b" ]
The idea behind this is that a user can just use lib.a.stuff with just import lib , rather than import lib.a , but you pay the cost of import even if they never use all the imports. Some libraries, like rich , are careful to avoid this and ask users to import explicitly, but many older libraries did this.
And there are also libraries that can do multiple things (like CLI libraries with subcommands), but you don’t need the dependencies for every subcommand.
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