Pythonic way to have a choice of 2-3 options as an argument to a function

Question

I have a Python function which requires a number of parameters, one of which is the type of simulation to perform. For example, the options could be "solar", "view" or "both.

What is a Pythonic way to allow the user to set these?

I can see various options:

Use a string variable and check it - so it would be func(a, b, c, type='solar')
Set some constants in the class and use func(a, b, c, type=classname.SOLAR)
If there are only two options (as there are for some of my functions) force it into a True/False argument, by using something like func(a, b, c, do_solar=False) to get it to use the 'view' option.

Any preferences (or other ideas) for Pythonic ways of doing this?

You shouldn't use `type` as your argument name, since that's a built-in... — Steven T. Snyder, Mar 01 '12 at 19:53
you can also use ENUMS, as shown here: https://stackoverflow.com/questions/36932/how-can-i-represent-an-enum-in-python — Alon Gouldman, Feb 27 '19 at 13:08

score 20 · Answer 1 · edited May 23 '17 at 10:30

20

If the point Niklas' makes in his answer doesn't hold, I would use a string argument. There are Python modules in the standard library that use similar arguments. For example csv.reader().

sim_func(a, b, c, sim_type='solar')

Remember to give a reasonable error inside the function, that helps people out if they type in the wrong thing.

def sim_func(a, b, c, sim_type='solar'):
    sim_types = ['solar', 'view', 'both']
    if sim_type not in sim_types:
        raise ValueError("Invalid sim type. Expected one of: %s" % sim_types)
    ...

edited May 23 '17 at 10:30

Community

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answered Mar 01 '12 at 19:57

Steven T. Snyder

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1

Simple, stupid, clean - I love it! :D – user2678074 Dec 10 '21 at 10:35

score 9 · Answer 2 · answered Mar 01 '12 at 19:49

I don't like any of those options.

I'd define two different functions, perform_solar(a, b, c) and perform_view(a, b, c) and let the caller decide which ones he wants to use, in which order and with which arguments.

If the reason why you thought you'd have to pack these into one single function is that they share state, you should share that state in an object and define the functions as methods.

score 5 · Answer 3 · answered Oct 09 '18 at 17:54

5

You can use the assert statement like this:

assert sim_types in ['solar', 'view', 'both'], 'sim type parameter must be solar, view or both'

If sim_types is not in the list, python will raise an Assertion Error

answered Oct 09 '18 at 17:54

MathLal

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score 3 · Answer 4 · answered Mar 01 '12 at 19:51

3

You can use optional (keyword) arguments like this

def func(a, b, c, **kw):
    if kw.get('do_solar'):
        # Do Solar
    if kw.get('do_view'):
        # Do view

answered Mar 01 '12 at 19:51

John La Rooy

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Silas Ray · Answer 5 · 2012-03-01T20:10:46.183

3

Since functions are objects in python, you could actually process *args as a list of methods and pass the types of simulations as arbitratry args at the end. This would have the benefit of allowing you to define new simulations in the future without having to refactor this code.

def func(a, b, c, *args):
    for arg in args:
        arg(a, b, c)

def foosim(a, b, c):
    print 'foosim %d' % (a + b + c)

def barsim(a, b, c):
    print 'barsim %d' % (a * b * c)

Use:

func(2, 2, 3, foosim)
func(2, 2, 3, barsim)
func(2, 2, 3, foosim, barsim)

Output:

foosim 7
barsim 12
foosim 7
barsim 12

edited Mar 01 '12 at 20:10

answered Mar 01 '12 at 20:01

Silas Ray

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I'm no language lawyer but I've seen this approach in good code. It requires your simulations to be separate functions, which is a good idea anyway: Good conventions encourage good programming. – alexis Mar 02 '12 at 17:08

mo-han · Answer 6 · 2020-08-06T03:23:22.720

Just have written a decorator factory for this, based on your option #1, which is "Use a string variable and check it".

def limited_argument_choices(choices: Dict[int or str, Iterable] = None) -> Callable:
    """decorator factory: force arguments of a func limited in the given choices

    :param choices: a dict which describes the choices for the value-limited arguments.
            the key of the dict must be either the index of args or the key_str of kwargs,
            while the value of the dict must be an iterable."""
    err_fmt = "value of '{}' is not a valid choice: '{}'"

    def decorator(func):
        if not choices:
            return func

        @wraps(func)
        def decorated_func(*args, **kwargs):
            for i in range(len(args)):
                if i in choices and args[i] not in choices[i]:
                    param_name = func.__code__.co_varnames[i]
                    valid_choices = list(choices[i])
                    raise ValueError(err_fmt.format(param_name, valid_choices))
            for k in kwargs:
                if k in choices and kwargs[k] not in choices[k]:
                    raise ValueError(err_fmt.format(k, list(choices[k])))

            return func(*args, **kwargs)

        return decorated_func

    return decorator

So now we could make new functions like this:

@limited_argument_choices({1: (0, 1, 2), 'y': ('hi', 'hello')})
def test(a, b, c, y=1):
    print(a, b, c, y)

And test it:

test(0, 1, 2, y='hello')
test(0, 3, 2, y='hello')
test(0, 1, 2, y='world')

Output:

0 1 2 hello
ValueError: value of 'b' is not a valid choice: '[0, 1, 2]'
ValueError: value of 'y' is not a valid choice: '['hi', 'hello']'

This decorator still needs improvements, but it's already usable now.

An improved revision here:

def decorator_factory_args_choices(choices: Dict[int or str, Iterable]) -> Decorator:
    """decorator factory: force arguments of a func limited inside the given choices

    :param choices: a dict which describes the choices of arguments
        the key of the dict must be either the index of args or the key(str) of kwargs
        the value of the dict must be an iterable."""
    err_fmt = "value of '{}' is not a valid choice in {}"

    def decorator(func):
        @wraps(func)
        def decorated_func(*args, **kwargs):
            for arg_index in range(len(args)):
                param_name = func.__code__.co_varnames[arg_index]
                if arg_index in choices and args[arg_index] not in choices[arg_index]:
                    raise ValueError(err_fmt.format(param_name, choices[arg_index]))
                elif param_name in choices and args[arg_index] not in choices[param_name]:
                    raise ValueError(err_fmt.format(param_name, choices[param_name]))
            for param_name in kwargs:
                if param_name in choices and kwargs[param_name] not in choices[param_name]:
                    raise ValueError(err_fmt.format(param_name, choices[param_name]))

            return func(*args, **kwargs)

        return decorated_func

    return decorator

score 1 · Answer 7 · answered Feb 23 '22 at 08:17

I really like dictionaries (the pythonic switch-case replacement) for that because it is performant, easy to read, and easy to maintain/extend:

def example_function(a, b, c, op='add'):
    return {'add': a+b+c, 'multiply': a*b*c}[op]


example_function(0, 1, 2, 'add') # returns 3
example_function(0, 1, 2, 'multiply') # returns 0

And it fails nicely for wrong/not implemented type-parameters:

example_function(0, 1, 2, 'divide') # returns a key error for 'divide'

Pythonic way to have a choice of 2-3 options as an argument to a function

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