Some useful Python decorators for cleaner software development.
Project description
pedantic-python-decorators
These decorators will make you write cleaner and well-documented Python code.
Getting Started
This package requires Python 3.6.1 or later. There are multiple options for installing this package.
Option 1: Installing with pip from Pypi
Run pip install pedantic
.
Option 2: Installing with pip and git
- Install Git if you don't have it already.
- Run
pip install git+https://github.com/LostInDarkMath/pedantic-python-decorators.git@master
Option 3: Offline installation using wheel
- Download the latest release here by clicking on
pedantic-python-decorators-x.y.z-py-none-any.whl
. - Execute
pip install pedantic-python-decorators-x.y.z-py3-none-any.whl
.
Usage
Use from pedantic import pedantic, pedantic_class
to import the pedantic decorators for example. Of course you could import whatever decorator you want to use as well.
Don't forget to check out the documentation.
Happy coding!
Minimal example
from typing import Union, List
from pedantic import pedantic, pedantic_class
@pedantic
def get_sum_of(values: List[Union[int, float]]) -> Union[int, float]:
return sum(values)
@pedantic_class
class MyClass:
def __init__(self, x: float, y: int) -> None:
self.x = x
self.y = y
def print_sum(self) -> None:
print(get_sum_of(values=[self.x, self.y]))
m = MyClass(x=3.14, y=2)
m.print_sum()
The @pedantic decorator
The @pedantic
decorator does the following things:
- The decorated function can only be called by using keyword arguments. Positional arguments are not accepted.
- The decorated function must have Type annotations.
- Each time the decorated function is called, pedantic checks that the passed arguments and the return value of the function matches the given type annotations.
As a consequence, the arguments are also checked for
None
, becauseNone
is only a valid argument, if it is annotated viatyping.Optional
. - If the decorated function has a docstring which lists the arguments, the docstring is parsed and compared with the type annotations. In other words, pedantic ensures that the docstring is everytime up-to-date. Currently, only docstrings in the Google style are supported.
In a nutshell:
@pedantic
raises an PedanticException
if one of the following happened:
- The decorated function is called with positional arguments.
- The function has no type annotation for their return type or one or more parameters do not have type annotations.
- A type annotation is incorrect.
- A type annotation misses type arguments, e.g.
typing.List
instead oftyping.List[int]
. - The documented arguments do not match the argument list or their type annotations.
List of all decorators in this package
- @count_calls
- @deprecated
- @dirty
- @does_same_as_function
- @for_all_methods
- @needs_refactoring
- @overrides
- @pedantic
- @pedantic_class
- @pedantic_class_require_docstring
- @pedantic_require_docstring
- @require_kwargs
- @timer
- @timer_class
- @trace
- @trace_class
- @trace_if_returns
- @unimplemented
- @validate_args
Dependencies
Outside the Python standard library, the following dependencies are used:
Contributing
Feel free to contribute by submitting a pull request :)
Acknowledgments
Risks and side effects
The usage of decorators may affect the performance of your application.
For this reason, I would highly recommend you to disable the decorators if your code runs in a productive environment.
You can disable pedantic
by set an environment variable:
export ENABLE_PEDANTIC=0
You can also disable or enable the environment variables in your Python project by calling a method:
from pedantic import enable_pedantic, disable_pedantic
enable_pedantic()
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