128

Is there an easy way in Python to check whether the value of an optional parameter comes from its default value, or because the user has set it explicitly at the function call?

8
  • 12
    Because I want to check it in that function of course :) Commented Feb 7, 2013 at 10:54
  • 4
    Just use None as the default and check for that. If you really could set up this test, you'd also exclude any possibility for the user to explicitly pass the value that invokes the default behavior. Commented Feb 7, 2013 at 11:05
  • 3
    That can be done in a much more reusable and beautiful way than in answer you accepted, at least for CPython. See my answer below. Commented Feb 7, 2013 at 11:25
  • 2
    @Volatility: it matters if you have two sets of defaults. Consider a recursive class: Class My(): def __init__(self, _p=None, a=True, b=True, c=False) User calls it with x=My(b=False). A class method could call itself with x=My(_p=self, c=True) if functions could detect that b is not explicitly set and that unset variables are to be passed down from the top level. But if they can't, the recursive calls have to pass every variable explicitly: x=My(a=self.a, b=self.b, c=True, d=self.d, ...). Commented Mar 8, 2016 at 13:19
  • @Dave but is that what the question is about? In my understanding, the question is asking how to differentiate x=My() and x=My(a=True). Your scenario involves assigning optional parameters a value other than their default value. Commented Mar 9, 2016 at 11:04

10 Answers 10

70

Not really. The standard way is to use a default value that the user would not be expected to pass, e.g. an object instance:

DEFAULT = object()
def foo(param=DEFAULT):
    if param is DEFAULT:
        ...

Usually you can just use None as the default value, if it doesn't make sense as a value the user would want to pass.

The alternative is to use kwargs:

def foo(**kwargs):
    if 'param' in kwargs:
        param = kwargs['param']
    else:
        ...

However this is overly verbose and makes your function more difficult to use as its documentation will not automatically include the param parameter.

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5 Comments

I've also seen several people use the Ellipsis builtin for places where this is needed and None is considered valid input. This is essentially the same as the first example.
If you want to implement special behaviour if None was passed, but still need a way to test if the argument was given by the user, you can use the Ellipsis singleton as a default, which was explicitly designed to be used as a skip this value. ... is an alias for Ellipsis, so users who want to use positional arguments can just call your_function(p1, ..., p3) which makes it obvious and nice to read.
However this is overly verbose and makes your function more difficult to use as its documentation will not automatically include the param parameter. This is actually untrue, as you can set the description of a function and of its parameters using the inspect module. It depends on your IDE whether it'll work or not.
This and similar tests don't work when I send a Pandas Series as parameter. Then the comparison of the series with anything produces the error "The truth value of a {type(self).__name__} is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()." But of course the suggested test functions fail when I use something other than a Series as parameter. The only way around which I found this unwieldy line: if not isinstance(param, pd.Series) and param==DEFAULT:
@EmilAlbert use is, not ==.
36

Lot of answers have little pieces of the full info, so I'd like to bring it all together with my favourite pattern(s).

default value is a mutable type

If the default value is a mutable object, you are lucky: you can exploit the fact that Python’s default arguments are evaluated once when the function is defined (some more about this at the end of the answer in the last section)

This means you can easily compare a default mutable value using is to see if it was passed as an argument or left by default, as in the following examples as function or method:

def f(value={}):
    if value is f.__defaults__[0]:
        print('default')
    else:
        print('passed in the call')

and

class A:
    def f(self, value={}):
        if value is self.f.__defaults__[0]:
            print('default')
        else:
            print('passed in the call')

Immutable default arguments

Now, it's a bit less elegant if your default is expected to be an immutable value (and remember that even strings are immutable!) because you can't exploit the trick as it is, but there is still something you can do, still exploiting mutable type; basically you put a mutable "fake" default in the function signature, and the desired "real" default value in the function body.

def f(value={}):
    """
    my function
    :param value: value for my function; default is 1
    """
    if value is f.__defaults__[0]:
        print('default')
        value = 1
    else:
        print('passed in the call')
    # whatever I want to do with the value
    print(value)

It feels particularly funny if you real default is None, but None is immutable so... you still need to explicitly use a mutable as the function default parameter, and switch to None in the code.

Using a Default class for immutable defaults

or, similar to @c-z suggestion, if python docs are not enough :-) , you can add an object in between to make the API more explicit (without reading the docs); the used_proxy_ Default class instance is mutable, and will contain the real default value you want to use.

class Default:
    def __repr__(self):
        return "Default Value: {} ({})".format(self.value, type(self.value))

    def __init__(self, value):
        self.value = value

def f(default=Default(1)):
    if default is f.__defaults__[0]:
        print('default')
        print(default)
        default = default.value
    else:
        print('passed in the call')
    print("argument is: {}".format(default))

now:

>>> f()
default
Default Value: 1 (<class 'int'>)
argument is: 1

>>> f(2)
passed in the call
argument is: 2

The above works nicely also for Default(None).

Other patterns

Obviously the above patterns looks uglier than they should because of all the print which are there only for showing how they work. Otherwise I find them terse and repeatable enough.

You could write a decorator to add the __call__ pattern suggested by @dmg in a more streamlined way, but this will still oblige to use weird tricks in the function definition itself - you would need to split out value and value_default if your code need to distinguish them, so I don't see much advantage and I won't write the example :-)

Mutable types as default values in Python

A bit more about #1 python gotcha!, abused for your own pleasure above. You can see what happens due to the evaluation at definition by doing:

def testme(default=[]):
    print(id(default))

You can run testme() as many time as you want, you will always see a reference to the same default instance (so basically your default is immutable :-) ).

Remember that in Python there are only 3 mutable built-in types: set, list, dict; everything else - even strings! - is immutable.

10 Comments

The example you have in "Immutable default arguments" does not actually have an immutable default argument. If it did, it wouldn't work.
@Karol, care to elaborate? The default value in that example is 1, which should be immutable...
I see the signature of the function as def f(value={}).
Ha, I get it now, thanks. It's not easy to follow unless someone reads your text very carefully which might not happen that often on SO. Consider rewording.
In "if default is f.__defaults__[0]:", you have to hard-code which default parameter number to use, which may be fragile if the function signature changes. An alternative is "if default in f.__defaults__:". Assuming you use a different Default instance for each arg, "in" should work just as well as "is".
|
16

The following function decorator, explicit_checker, makes a set of parameter names of all the parameters given explicitly. It adds the result as an extra parameter (explicit_params) to the function. Just do 'a' in explicit_params to check if parameter a is given explicitly.

def explicit_checker(f):
    varnames = f.func_code.co_varnames
    def wrapper(*a, **kw):
        kw['explicit_params'] = set(list(varnames[:len(a)]) + kw.keys())
        return f(*a, **kw)
    return wrapper

@explicit_checker
def my_function(a, b=0, c=1, explicit_params=None):
    print a, b, c, explicit_params
    if 'b' in explicit_params:
        pass # Do whatever you want


my_function(1)
my_function(1, 0)
my_function(1, c=1)

3 Comments

This code works only in python2. For python 3, see my answer below: stackoverflow.com/questions/14749328/…
This is pretty cool, but better to avoid the problem with better design in the first place, if possible.
@Karol, I agree. In most cases one should not need that if the design is reasonable.
5

I sometimes use a universally unique string (like a UUID).

import uuid
DEFAULT = uuid.uuid4()
def foo(arg=DEFAULT):
  if arg is DEFAULT:
    # it was not passed in
  else:
    # it was passed in

This way, no user could even guess the default if they tried so I can be very confident that when I see that value for arg, it was not passed in.

1 Comment

Python objects are references, you can just use object() instead of uuid4() - it's still a unique instance, which is what is checks
5

I've seen this pattern a few times (e.g. library unittest, py-flags, jinja):

class Default:
    def __repr__( self ):
        return "DEFAULT"

DEFAULT = Default()

...or the equivalent one-liner...:

DEFAULT = type( 'Default', (), { '__repr__': lambda x: 'DEFAULT' } )()

Unlike DEFAULT = object(), this assists type-checking and provides information when errors occur -- frequently either the string representation ("DEFAULT") or the class name ("Default") are used in error messages.

Comments

5

@Ellioh's answer works in python 2. In python 3, the following code should work:

import inspect
from functools import wraps

def explicit_checker(f):
    varnames = inspect.getfullargspec(f)[0]
    @wraps(f)
    def wrapper(*a, **kw):
        kw['explicit_params'] = set(list(varnames[:len(a)]) + list(kw.keys()))
        return f(*a, **kw)
    return wrapper

@explicit_checker
def my_function(a, b=0, c=1, explicit_params=None):
    print(a, b, c, explicit_params)
    if 'b' in explicit_params:
        pass # Do whatever you want

This method can keep the argument names and default values (instead of **kwargs) with better readability.

Comments

4

I agree with Volatility's comment. But you could check in the following manner:

def function(arg1,...,**optional):
    if 'optional_arg' in optional:
        # user has set 'optional_arg'
    else:
        # user has not set 'optional_arg'
        optional['optional_arg'] = optional_arg_default_value # set default

3 Comments

I believe an optional parameter is something like def func(optional=value) not **kwargs
That's something which is somewhat open to interpretation. What's the actual difference between an argument with a default value and a keyword argument? They are both expressed using the same syntax "keyword=value".
I disagree, because the purpose of the optional parameters and **kwargs is a bit different. P.S. no problem's about -1 :) And my -1 for you was accidental :)
4

You can check it from foo.__defaults__ and foo.__kwdefaults__

see a simple example bellow

def foo(a, b, c=123, d=456, *, e=789, f=100):
    print(foo.__defaults__)
    # (123, 456) 
    print(foo.__kwdefaults__)
    # {'e': 789, 'f': 100}
    print(a, b, c, d, e, f)

#and these variables are also accessible out of function body
print(foo.__defaults__)    
# (123, 456)  
print(foo.__kwdefaults__)  
# {'e': 789, 'f': 100}

foo.__kwdefaults__['e'] = 100500

foo(1, 2) 
#(123, 456)
#{'f': 100, 'e': 100500}
#1 2 123 456 100500 100

then by using operator = and is you can compare them

and for some cases code bellow is enough

For example, you need to avoid changing default value then you can check on equality and then copy if so

    def update_and_show(data=Example):
        if data is Example:
            data = copy.deepcopy(data)
        update_inplace(data) #some operation
        print(data)

Also, it is quite convenient to use getcallargs from inspect as it returns real arguments with which function will be invoked. You pass a function and args and kwargs to it (inspect.getcallargs(func, /, *args, **kwds)), it will return real method's arguments used for invocation, taking into consideration default values and other stuff. Have a look at an example below.

from inspect import getcallargs

# we have a function with such signature
def show_params(first, second, third=3):
    pass

# if you wanted to invoke it with such params (you could get them from a decorator as example)
args = [1, 2, 5]
kwargs = {}
print(getcallargs(show_params, *args, **kwargs))
#{'first': 1, 'second': 2, 'third': 5}

# here we didn't specify value for d
args = [1, 2, 3, 4]
kwargs = {}

# ----------------------------------------------------------
# but d has default value =7
def show_params1(first, *second, d = 7):
    pass


print(getcallargs(show_params1, *args, **kwargs))
# it will consider b to be equal to default value 7 as it is in real method invocation
# {'first': 1, 'second': (2, 3, 4), 'd': 7}

# ----------------------------------------------------------
args = [1]
kwargs = {"d": 4}

def show_params2(first, d=3):
    pass


print(getcallargs(show_params2, *args, **kwargs))
#{'first': 1, 'd': 4}

https://docs.python.org/3/library/inspect.html

Comments

3

This is a variation on stefano's answer, but i find a little more readable:

not_specified = {}

def foo(x=not_specified):
    if x is not_specified:
            print("not specified")
    else:
            print("specified")

5 Comments

I downvoted because while this works at runtime, it creates an issue with typing (as most other answers).
Can you please elaborate bfontaine?
@KristjanJonasson mypy sees this function as foo(x: dict = not_specified) -> None. The dummy value used as a default gives its type to the argument. If your function has a parameterized type it doesn’t work: foo(x: T = not_specified); "Incompatible default for argument "x" (default has type "Dict[Any, Any]", argument has type "T")". You can use Union[T, dict] but that complicates the code.
It really seems that adopting some version of Fortran's present function would improve Python...
Note that mypy is a package, it is not Python. Note also that type hinting is an optional feature of the language. If you work for, or desire your own code to use and comply with mypy, then it matters if this causes an issue with typing. If not, then it does not matter.
1

A little freakish approach would be:

class CheckerFunction(object):
    def __init__(self, function, **defaults):
        self.function = function
        self.defaults = defaults

    def __call__(self, **kwargs):
        for key in self.defaults:
            if(key in kwargs):
                if(kwargs[key] == self.defaults[key]):
                    print 'passed default'
                else:
                    print 'passed different'
            else:
                print 'not passed'
                kwargs[key] = self.defaults[key]

        return self.function(**kwargs)

def f(a):
    print a

check_f = CheckerFunction(f, a='z')
check_f(a='z')
check_f(a='b')
check_f()

Which outputs:

passed default
z
passed different
b
not passed
z

Now this, as I mentioned, is quite freakish, but it does the job. However this is quite unreadable and similarly to ecatmur's suggestion won't be automatically documented.

2 Comments

You might want to include the behavior of check_f('z'), which is also, as you say, freakish.
@MichaelJ.Barber Good point. You'll have to do some "magic" with *args as well. However, my point was that it is possible, but needing to now whether the default value is passed or not is a bad design.

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