How to use Python decorators to check function arguments?

I would like to define some generic decorators to check arguments before calling some functions.

Something like:

@checkArguments(types = ['int', 'float'])
def myFunction(thisVarIsAnInt, thisVarIsAFloat)
    ''' Here my code '''
    pass

Side notes:

1. Type checking is just here to show an example
2. I'm using Python 2.7 but Python 3.0 whould be interesting too

EDIT 2021: funny that type checking did not go antipythonic in the long run with type hinting and mypy.

Solution 1:

From the Decorators for Functions and Methods:

Python 2

def accepts(*types):
    def check_accepts(f):
        assert len(types) == f.func_code.co_argcount
        def new_f(*args, **kwds):
            for (a, t) in zip(args, types):
                assert isinstance(a, t), \
                       "arg %r does not match %s" % (a,t)
            return f(*args, **kwds)
        new_f.func_name = f.func_name
        return new_f
    return check_accepts

Python 3

In Python 3 func_code has changed to __code__ and func_name has changed to __name__.

def accepts(*types):
    def check_accepts(f):
        assert len(types) == f.__code__.co_argcount
        def new_f(*args, **kwds):
            for (a, t) in zip(args, types):
                assert isinstance(a, t), \
                       "arg %r does not match %s" % (a,t)
            return f(*args, **kwds)
        new_f.__name__ = f.__name__
        return new_f
    return check_accepts

Usage:

@accepts(int, (int,float))
def func(arg1, arg2):
    return arg1 * arg2

func(3, 2) # -> 6
func('3', 2) # -> AssertionError: arg '3' does not match <type 'int'>

arg2 can be either int or float

Solution 2:

On Python 3.3, you can use function annotations and inspect:

import inspect

def validate(f):
    def wrapper(*args):
        fname = f.__name__
        fsig = inspect.signature(f)
        vars = ', '.join('{}={}'.format(*pair) for pair in zip(fsig.parameters, args))
        params={k:v for k,v in zip(fsig.parameters, args)}
        print('wrapped call to {}({})'.format(fname, params))
        for k, v in fsig.parameters.items():
            p=params[k]
            msg='call to {}({}): {} failed {})'.format(fname, vars, k, v.annotation.__name__)
            assert v.annotation(params[k]), msg
        ret = f(*args)
        print('  returning {} with annotation: "{}"'.format(ret, fsig.return_annotation))
        return ret
    return wrapper

@validate
def xXy(x: lambda _x: 10<_x<100, y: lambda _y: isinstance(_y,float)) -> ('x times y','in X and Y units'):
    return x*y

xy = xXy(10,3)
print(xy)

If there is a validation error, prints:

AssertionError: call to xXy(x=12, y=3): y failed <lambda>)

If there is not a validation error, prints:

wrapped call to xXy({'y': 3.0, 'x': 12})
  returning 36.0 with annotation: "('x times y', 'in X and Y units')"

You can use a function rather than a lambda to get a name in the assertion failure.

Solution 3:

As you certainly know, it's not pythonic to reject an argument only based on its type.
Pythonic approach is rather "try to deal with it first"
That's why I would rather do a decorator to convert the arguments

def enforce(*types):
    def decorator(f):
        def new_f(*args, **kwds):
            #we need to convert args into something mutable   
            newargs = []        
            for (a, t) in zip(args, types):
               newargs.append( t(a)) #feel free to have more elaborated convertion
            return f(*newargs, **kwds)
        return new_f
    return decorator

This way, your function is fed with the type you expect But if the parameter can quack like a float, it is accepted

@enforce(int, float)
def func(arg1, arg2):
    return arg1 * arg2

print (func(3, 2)) # -> 6.0
print (func('3', 2)) # -> 6.0
print (func('three', 2)) # -> ValueError: invalid literal for int() with base 10: 'three'

I use this trick (with proper conversion method) to deal with vectors.
Many methods I write expect MyVector class as it has plenty of functionalities; but sometime you just want to write

transpose ((2,4))