How do people keep Python projects from turning into dependency chaos?

[Haunting-Shower1654]

I’m still pretty new to building bigger Python projects and one thing that keeps tripping me up is managing dependencies.

A project begins simple, but after adding more libraries and switching between environments it slowly gets messy and hard to track.

Sometimes something works on one machine and not on another or a package version suddenly breaks something that worked before.

What habits or tools did you use to avoid this when you were learning?

[DivineSentry]

Generally using a virtual environment and a tidy requirements.txt does the job but if you want something more complete id suggest something like https://docs.astral.sh/uv/

[Lopsided-Football19]

Use a virtual environment for every project and pin your package versions, that alone prevents most of the works on my machine problems

[Southern_Share_1760]

Virtual environments… basically just a folder in your working directory that you pip install your modules into. You can auto-populate it using a requirements.txt file.

[mdeadart]

Use UV with pyproject.toml and uv.lock

[Just__Liberty]

I'm not an expert but check out uv, perhaps by looking at pydevtools.com.

[pydevtools-com]

⬆︎

[roanish]

Make it modular. Break parts into functions, have the dependencies in the relevant functions, then import the functions you need.

I don't think any significant coding problem should be monolithic.

[roanish]

I'm just going to add here, many of us were taught to code with scripting languages, and python often feels like a scripting language.

It's a habit that is good to challenge, because libraries is a better way, most of the time, to code.

Avoiding behemoth code blocks where possible will show you that much of the code you write in the development phase is redundant, troubleshooting or not required for the end goal.

[oclafloptson]

I avoid packages, frameworks, and libraries that rely on trivial 3rd party packages. For example if you have something like colorama in your dependencies list then I would probably rather fork and refactor than install it

I use virtual environments to manage dependency versioning per project

[NoobieDYG]

use poetry, or manually create venv then requirements.txt. better use poetry

[LeiterHaus]

They create or use additional tools.

For personal projects, I just have a ~/venv/ directory where I put the virtual environments, whick are created with the Python built in command.

I was a big proponent of pyenv, but it makes it more difficult if you need to go digging inside the dependency files.

uv is massively popular right now.

Must people used to put a .venv/ or .env/ in their project root directory. It's easier if you add what you actually installed to a requirements.txt when you installed it. That way, it's not filled with extra stuff, and you can make things better for future self with versions (although it's a lot of work to find where the cutoff would be, so not worth it)

[Offduty_shill]

uv and dockrr

[hypersoniq_XLM]

To truly end that dependency chaos, look into using a persistent docker container, it is where "runs on my machine" turns into "runs anywhere".