pyflow VS black

Very cool! Of note, I made something along these lines a few years ago, although with a slightly broader scope to also include managing and installing python versions. I abandoned it due to lack of free time, and edge cases breaking things. The major challenge is that Python packages that aren't wheels can do surprising things due to setup.py running arbitrary code. (https://github.com/David-OConnor/pyflow)

Pyflow

Pyflow takes care of the use when you need pyenv to isolate different python versions, pipx to isolate some global python-based tools, and isolated, reproducible builds per project with on tool. I highly recommend people to give it go.

https://github.com/David-OConnor/pyflow#a-thoroughly-biased-...

Pyflow is a similar implementation of PEP582. NGL I wonder if it's better because of how good Rust stuff is. Probably a lot faster. Looks like you can install it via Pypi. I should've tested it before moving to PDM. Though it seems dev is a bit slow. Hmmm.

I’m personally complaining that pip is so much behind cargo. I have some hope with Pyflow though.

I literally stumbled into this issue again today. Has anyone leveraged Pyflow before? It looks pretty slick for keeping things organized. I don't do heavy dev work, just need something to keep things generally tidy. Was curious if anyone had used it and their opinion on it.

PDM is pretty new so it’s not entirely clear how it’ll play out but if you’re interested in PEP 582 then it’s really that or pyflow.

It's a good safeguard, and it's going in the direction of the other initiatives to make python package management default behavior saner.

PEP 852 is the another one to follow up: https://www.python.org/dev/peps/pep-0582/

It basically uses the concept of node_modules, making python interpreters local any local __pypackages__ directory. There are 2 differences though:

- unlike JS, python can only have one version of one lib

- but since having several versions of python often matters, you may have several __pypackages__/X.Y sub dirs to catter to each of them

It does also force you to use "-m" to use commands, which is the best practice anyway. I hope it will make jupyter fix "-m" on windows for them because that's a blocker for beginners.

If you are not already using "-m", start now. It solves a lot of different problems with running python cli programs.

E.G: instead of running "black" or "pylint", do "python -m black" or "python -m pylint". Or course you may want to chose a specific version of python, so "python3.8 -m black" for unix, or "py -3.8 -m black" on windows.

To test out __pypackages__, give a try to the pdm project: https://github.com/pdm-project/pdm

At last, some other tools that I wish people knew more about that solves packaging issues:

- pyflow (https://github.com/David-OConnor/pyflow): it's a package manager like poetry, but it also install whatever python you want like pyenv. Except it provides the binary, no need to compile anything. It's a young project, but I wish it succeeds because it's really a great concept.

- shiv (shiv.readthedocs.io/): it leverage the concept of zipapp, meaning the ability that python has to execute python inside a zip file. It's a successor to pex. Basically it lets you bundle your code + all deps from virtualenv inside a zip, like a Java .war file. You can then run the resulting zip, a .pyz file, like if it was a regular .py file. It will unzip on the first run automatically. It makes deployment almost as easy as with golang.

- nuitka (shiv.readthedocs.io/): take your code and all dependancies, turn them into C, and compiles it. Although it does require a bit of setup, since it needs headers and a compiler, it results reliably in a standalone compiled executable that will run on the same architecture with no need for anything else. Also it will speed up your Python program, up to 4 times.

$ git commit -m "add pre-commit configuration" [INFO] Initializing environment for https://github.com/psf/black. [INFO] Installing environment for https://github.com/psf/black. [INFO] Once installed this environment will be reused. [INFO] This may take a few minutes... black................................................(no files to check)Skipped [main 6e21eab] add pre-commit configuration 1 file changed, 7 insertions(+)

Black: Known as “The Uncompromising Code Formatter”, Black automatically formats your Python code to conform to the PEP 8 style guide. It takes away the hassle of having to manually adjust your code style.

black @ git+https://github.com/psf/black

In the realm of Python development, there is a multitude of code formatters that adhere to PEP 8 guidelines. Today, we will briefly discuss how to install and utilize black.

Perfect, that worked, thank you!

I thought this could be solved by changing the directory to src/ and then executing that command, but this didn't work.

This also seems to be an issue with the web app, e.g. the repository for the formatter black is only one white dot https://dep-tree-explorer.vercel.app/api?repo=https://github...

Ruff is not only much faster, but it is also very convenient to have an all-in-one solution that replaces multiple other widely used tools: Flake8 (linter), isort (imports sorting), Black (code formatter), autoflake, many Flake8 plugins and more. And it has drop-in parity with these tools, so it is really straightforward to migrate from them to Ruff.

What I am looking for is something like Black for Python, which is opinionated, with reasonable defaults, and auto-fixes most/all issues.

1. LICENSE: This file contains information about the rights and permissions granted to users regarding the use, modification, distribution, and sharing of the software. I already had an MIT License in my project. 2. pyproject.toml: It is a configuration file typically used for specifying build requirements and backend build systems for Python projects. I was already using this file for Black code formatter configuration. 3. README.md: Used as a documentation file for your project, typically includes project overview, installation instructions and optionally, contribution instructions. 4. example_package_YOUR_USERNAME_HERE: One big change I had to face was restructuring my project, essentially packaging all files in this directory. The name of this directory should be what you want to name your package and shoud not conflict with any of the existing packages. Of course, since its a Python Package, it needs to have an __init__.py. 5. tests/: This is where you put all your unit and integration tests, I think its optional as not all projects will have tests. The rest of the project remains as is.

using pylint and black ("the uncompromising code formatter")