docopt
rules_python
docopt | rules_python | |
---|---|---|
29 | 7 | |
7,892 | 498 | |
-0.0% | 1.0% | |
2.5 | 9.5 | |
about 1 month ago | 4 days ago | |
Python | Starlark | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
docopt
- Docopt: Command-line interface description language
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Building a Command Line Tool with PHP and Symfony Console
Symfony Console closely follows the well-established docopt conventions. Docopt, based on longstanding conventions from help messages and man pages, ensures a consistent and intuitive interface for describing a program's interface. Symfony Console's adherence to docopt conventions guarantees that your command line tools maintain a standardized and predictable user experience, simplifying development and user interaction.
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CLI user experience case study
You probably already know, but just in case you don't, you might read about http://docopt.org/ It seems to me a lot of your usage ideas could be refinements of / tooling around docopt-style interfaces.
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Gooey: Turn almost any Python command line program into a full GUI application
http://docopt.org/
Not quite what you asked for, but close: type example invocations to generate the CLI, and just pull the arguments from a dictionary at runtime.
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Things I've learned about building CLI tools in Python
I've been using docopt to handle CLI arguments for years now.
http://docopt.org/
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What's up, Python? The GIL removed, a new compiler, optparse deprecated
If you aren't averse to using a third party package, on my personal projects I always found https://github.com/docopt/docopt to be nice.
You can kill 2 birds with one stone by documenting your scripts while also providing the argument structure / parsing.
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adaszko/complgen: Generate {bash,fish,zsh} completions from a single EBNF-like grammar
As for the implementation differences, complgen uses a trivial DSL that’s everybody is already familiar with more or less because it’s a slightly more rigorous version of what tools usually spit out when you do command --help (projects like docopt even use that for command line arguments parsing). Those happen to be regular languages and therefore can be represented as a Deterministic Finite Automata. complgen compiles the grammars to DFAs, minimizes the DFA and spits out shell-specific shell completions scripts that simply walk the DFA to match and complete the current input.
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[Media] shrs: a shell that is configurable and extensible in rust
The current completion system has a list of rules of which completions to use at which time. It's purposely simple to make it as flexible as possible. The current things I'm planning is a derive macro like what clap has to generate these rules. I'm also considering introducing a plugin that let's you write rules in the format of docopt
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Docopt.sh – Command-Line Argument Parser for Bash 3.2, 4, and 5
For anyone unfamiliar, docopt is an established standard for specifying arguments in a script’s doc string. I use it for Python and it’s lovely. You’re going to write a docstring with examples anyway, why not make them functional?
http://docopt.org/
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I am sick of writing argparse boilerplate code, so I made "duckargs" to do it for me
I like http://docopt.org/ a lot. You seem like someone who might have opinions on that.
rules_python
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Things I've learned about building CLI tools in Python
What's SV?
I honestly don't know why anyone would use that... as in what does Bazel do better than virtually anything else that can provide this functionality. But, I used to be an ops engineer in a big company which wanted everything to be Maven, regardless of whether it does it well or not. So we built and deployed with Maven a lot of weird and unrelated stuff.
Not impossible, but not anything I'd advise anyone to do on their free time.
Specifically wrt' the link you posted, if you look here: https://github.com/bazelbuild/rules_python/blob/main/python/... it says that only pure Python wheels are supported, but that's also a lie, they don't support half of the functionality of pure Python wheels.
So, definitely not worth using, since lots of functionality is simply not there.
- Python coverage in Bazel has been broken for nearly 6 years
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Build faster with Buck2: Our open source build system
Regarding bazel, the rules_python has a py_wheel rule that helps you creating wheels that you can upload to pypi (https://github.com/bazelbuild/rules_python/blob/52e14b78307a...).
If you want to see an approach of bazel to pypi taken a bit to the extreme you can have a look at tensorflow on GitHub to see how they do it. They don't use the above-mentioned building rule because I think their build step is quite complicated (C/C++ stuff, Vida/ROCm support, python bindings, and multiOS support all in one before you can publish to pypi).
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Incremental Builds for Haskell with Bazel
Python support in Bazel now looks more promising with `rules_python`: https://github.com/bazelbuild/rules_python
`rules_go` to my understanding is great too.
Over years, Bazel is not as opinionated as before, mostly because adoptions in different orgs force it to be so.
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Advantages of Monorepos
I have personally run converted build systems to Bazel, and use it for personal projects as well.
Bazel 1.0 was released in October 2019. If you were using it "a few years ago", I'm guessing you were using a pre-1.0 version. There's not some cutoff where Bazel magically got easy to use, and I still wouldn't describe it as "easy", but the problem it solves is hard to solve well, and the community support for Bazel has gotten a lot better over the past years.
https://github.com/bazelbuild/rules_python
The difficulty and complexity of using Bazel is highly variable. I've seen some projects where using Bazel is just super simple and easy, and some projects where using Bazel required a massive effort (custom toolchains and the like).
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Experimentations on Bazel: Python & FastAPI (1)
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive") #------------------------------------------------------------------------------ # Python #------------------------------------------------------------------------------ # enable python rules http_archive( name = "rules_python", url = "https://github.com/bazelbuild/rules_python/releases/download/0.2.0/rules_python-0.2.0.tar.gz", sha256 = "778197e26c5fbeb07ac2a2c5ae405b30f6cb7ad1f5510ea6fdac03bded96cc6f", )
What are some alternatives?
click - Python composable command line interface toolkit
uwsgi-nginx-flask-docker - Docker image with uWSGI and Nginx for Flask applications in Python running in a single container.
Python Fire - Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
pip-upgrade - Upgrade your pip packages with one line. A fast, reliable and easy tool for upgrading all of your packages while not breaking any dependencies
typer - Typer, build great CLIs. Easy to code. Based on Python type hints.
black - The uncompromising Python code formatter
Gooey - Turn (almost) any Python command line program into a full GUI application with one line
python-streams - A Library to support Writing concise functional code in python
cement - Application Framework for Python
bazel-coverage-report-renderer - Haskell rules for Bazel.
Argh - An argparse wrapper that doesn't make you say "argh" each time you deal with it.
TypeRig - Proxy API and Font Development Toolkit for FontLab