decorator-validation 2.0.1

Fast Argument validation for functions using decorators

Validation Decorators

Simple and fast type-checking and parameter validation.

Do you want to remove visual clutter in your python function? Do you want to check types fast without a lot of boilerplate?

Then this package is right for you.

Not convinced? Check out the following:

# classic
def foo(bar: int, message: str, some_additional_info: dict):
    if not isinstance(bar, int):
        raise TypeError(...)
    if not isinstance(message, str):
        raise TypeError(...)
    if not isinstance(some_additional_info, dict):
        raise TypeError(...)
    # now begin to code...

# now
@validate_types(bar=(int,), message=(str,), some_additional_info=(dict,))
def foo(bar: int, message: str, , some_additional_info: dict):
    # begin to code

If of course also supports multiple types:

from pathlib import Path

@validate_types(path=(str, Path), message=(str,))
def foo(path: str | Path, message: str):
    # begin to code

Do you want to convert your input-types fast and without clutter?

def from_dict(dict_: dict):
    return (dict_.get('bar'), dict_.get('message'), dict_.get('some_additional_info')), {}

@convert_with(from_dict)
def foo(bar: int, message:str, some_additional_info: dict):
    ...

Skip Type-checks by providing the SkipTypecheck class as a type, this is very usefull for methods.

from decorator_validation.decorators import validate_types
from decorator_validation.types import SkipTypeCheck

class FileReader:

    @validate_types((SkipTypeCheck,), file_path=(str,))
    def __init__(self, file_path: str):
        ...

Of course, sometimes you want to have custom error messages. Then, just use the following code:

from decorator_validation.decorators import validate_with
from pathlib import Path

def my_validation_func(obj, file_path:str) -> True:

    if not isinstance(file_path, str):
        raise TypeError(...)
    if not Path(file_path).resolve().is_file():
        raise ValueError(...)
    return True

class FileReader:

    @validate_with(my_validation_func)
    def __init__(self, file_path: str):
        ...

Map Multiple functions for subtypes

You can also directly map different validation functions to your arguments.

from decorator_validation.decorators import validate_map
from decorator_validation.std_validators import is_file

class FileReader:

    @validate_map(None, file_path=is_file)
    def __init__(self, file_path: str):
        ...

Validate Arbitrary Arguments

Starting with version 2.0.0, the package allows for a single use decorator called validate.

Depending on the argument, it will either check the type or use a function to validate. If a tuple is used, the standard typecheck will be applied, if not it expectes a Callable that returns a boolean value. All of the examples above can be directly copied and just the name of the decorator has to be changed.

An example.

from decorator_validation.decorators import validate
from decorator_validation.std_validators import is_file

class Logger:

    @validate(file_path=is_file, message:str)
    def log(file_path: str, message:str):
        ...