The best Python CLI library, arguably.
arguably turns functions and docstrings into command line interfaces (CLIs). arguably has a tiny API and is
extremely easy to integrate. You can also use it directly through python3 -m arguably your_script.py, more on that
here.
To use arguably in a script, decorate any functions that should appear on the command line with @arguably.command,
then call arguably.run(). If multiple functions are decorated, they'll all appear as subcommands. You can even have
multiple levels of subcommands: def s3__ls() becomes s3 ls.
#!/usr/bin/env python3
import arguably
@arguably.command
def some_function(required, not_required=2, *others: int, option: float = 3.14):
"""
this function is on the command line!
Args:
required: a required argument
not_required: this one isn't required, since it has a default value
*others: all the other positional arguments go here
option: [-x] keyword-only args are options, short name is in brackets
"""
print(f"{required=}, {not_required=}, {others=}, {option=}")
if __name__ == "__main__":
arguably.run()
becomes
user@machine:~$ ./intro.py -h
usage: intro.py [-h] [-x OPTION] required [not-required] [others ...]
this function is on the command line!
positional arguments:
required a required argument (type: str)
not-required this one isn't required, since it has a default value (type: int, default: 2)
others all the other positional arguments go here (type: int)
options:
-h, --help show this help message and exit
-x, --option OPTION keyword-only args are options, short name is in brackets (type: float, default: 3.14)
Arguments to the CLI look just like calling the Python function.
>>> from intro import some_function
>>> some_function("asdf", 0, 7, 8, 9, option=2.71)
required='asdf', not_required=0, others=(7, 8, 9), option=2.71
user@machine:~$ ./intro.py asdf 0 7 8 9 --option 2.71
required='asdf', not_required=0, others=(7, 8, 9), option=2.71
arguably uses your docstrings to automatically generate help messages. It supports all major formats for docstrings:
reStructuredText, Google, Numpydoc, and Epydoc.
Type annotations are optional, but arguably can use them to automatically convert arguments. It has smart handling for
mapping built-in types to the command line, including tuple, list, enum.Enum, and enum.Flag.
There are also a few special behaviors you can attach to a parameter via Annotated[] and the arguably.arg.*
functions. Using arguably.arg.builder(), you can even build an object to pass in from the command line (using syntax
inspired by QEMU):
user@machine:~$ ./build.py --nic tap,model=e1000 --nic user,hostfwd=tcp::10022-:22
nic=[TapNic(model='e1000'), UserNic(hostfwd='tcp::10022-:22')]
Don't want to write any code? Simply pass any Python script to arguably to give it a command line interface.
user@machine:~$ python3 -m arguably party-trick.py -h
usage: party-trick [-h] [--version] command ...
this is the docstring for the whole script
positional arguments:
command
hello this is hello's docstring
goodbye any function from a script can be called
some-class so can any __init__ for objects defined in the script
some-class.func-static a @staticmethod on a class can be called
some-class.func-cls so can a @classmethod
options:
-h, --help show this help message and exit
--version show program's version number and exit
Install using pip install arguably. If you want to install using conda, please comment on
this issue.
All of arguably is built on top of argparse. It has one dependency:
docstring-parser for parsing function docstringsIdeas and help are very much appreciated! There's a guide for getting started with contributing to arguably that shows
you how to run tests and pre-commit hooks.
If you have any interest in these (either as a user or implementer), please leave a comment!
FAQs
The best Python CLI library, arguably.
We found that arguably demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Research
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
Research
Security News
Attackers used a malicious npm package typosquatting a popular ESLint plugin to steal sensitive data, execute commands, and exploit developer systems.
Security News
The Ultralytics' PyPI Package was compromised four times in one weekend through GitHub Actions cache poisoning and failure to rotate previously compromised API tokens.