strongtyping 1.1.17

Decorator which checks whether the function is called with the correct type of parameters

Strong Typing

Decorator which checks at Runtime whether the function is called with the correct type of parameters.
And raises TypeMisMatch if the used parameters in a function call where invalid.

###The problem:

def multipler(a: int, b: int):
    return a * b


product = multipler(3, 4)
# >>> 12

# Some IDE's will/can highlight that one of the parameter doesn't match but you can run it
product_2 = multipler('Hello', 'World')
# >>> TypeError
# When we receiver an Exception then we are ‘safe’ and know what to do 
# but sometimes we will not run into an Exception

product_3 = multipler('Hello', 4)
# >>> 'HelloHelloHelloHello'
# No Exception but the result isn’t really what we expect

Now we can say that we will check the types in the function body to prevent this.

def multipler(a: int, b: int):
    if isinstance(a, int) and isinstance(b, int):
        return a * b
    ...

But when your function needs a lot of different parameters with different types you have to create a lot of noising code.

And why should we then use typing in our parameters??

###My solution:

I created a decorator called @match_typing which will check at runtime if the parameters you used when calling this function are from the same type as you wanted.

Here are some examples from my tests

@match_typing
def func_a(a: str, b: int, c: list):
    ...

func_a('1', 2, [i for i in range(5)])
# >>> True

func_a(1, 2, [i for i in range(5)])
# >>> will raise a TypeMismatch Exception

@match_typing
def func_e(a: List[Union[str, int]], b: List[Union[str, int, tuple]]):
    return f'{len(a)}-{len(b)}'

func_e([1, '2', 3, '4'], [5, ('a', 'b'), '10'])
# >>> '4-3'

func_e([5, ('a', 'b'), '10'], [1, '2', 3, datetime.date])
# >>> will raise a TypeMismatch Exception

I really love python and his freedom but with the new option of adding type hints I wanted to get rid of writing if isinstance(value, whatever) in my programs.

In a bigger project it happened that some developers used a really tiny IDE and others a more advanced one which highlighted typing issues. And there the trouble began, we had a bug and after a longer debugging session we found out that the issue was a wrong type of an argument, it doesn't crashed the program but the output was totally not what we expected.

And this is the reason why I created this package.

Getting Started

As normal decorator

@match_typing
def foo_bar(a: str, b: int, c: list):
    ...

as class method decorator

class Foo:
    ...
    @match_typing
    def foo_bar(self, a: int):
        ...

You can also use a mix of typed and untyped parameters but then only the typed parameters are checked on runtime

@match_typing
def foo_bar(with_type_a: str, without_type_a, with_type_b: list, without_type_b):
    ...

# no exception
foo_bar('hello', 'world', [1, 2, 3], ('a', 'b'))

# will raise an exception
foo_bar(123, 'world', [1, 2, 3], ('a', 'b'))

It is also possibile to add you own exception

@match_typing(excep_raise=SomeException)
def foo_bar(with_type_a: str, without_type_a, with_type_b: list, without_type_b):
    ...

And last but not least you can also enable internal cache with cache_size = 1

@match_typing(cache_size=1)
def foo_bar(a: tuple, b: MyClass):
    ...

At the current state it will work with

• builtin types like: str, int, tuple etc
• from typing:
  • List
  • Tuple
  • Union also nested ( Tuple[Union[str, int], Union[list, tuple]] )
  • Any
  • Dict
  • Set
  • Type
  • Iterator
  • Callable
• with string types representation like

class A:
    @match_typing
    def func_a(self, a: 'A'):

Tested for Versions

• 3.6, 3.7, 3.8

Prerequisites

• pytest

Installing

• pip install strongtyping
• pip install git+https://github.com/FelixTheC/strongtyping.git

Running the tests

• python test_typing.py

Versioning

• For the versions available, see the tags on this repository.

Authors

• Felix Eisenmenger - Initial work

License

• This project is licensed under the MIT License - see the LICENSE.md file for details

Special thanks

• Thanks to Ruud van der Ham for helping me improve my code
• And all how gave me Feedback in the Pythonista Cafe