python - Dictionary with some mandatory keys as function input

Question

I have a function that has a dictionary as an argument. I will pass various dictionaries to it that have more entries than the few used inside the function. Additionally, I would like to see in the function definition what keys are required. So I write

def fun(indict=dict(apple=None, pear=None)):

However, the function now accepts any input as indict. Is there a smart way for writing

any dictionary that has at least the keys 'apple' and 'pear' is accepted.

Something like

def fun(indict=dict(apple=NeedsToBeSpecified, pear=NeedsToBeSpecified)):

Answer 1

In python3.x, you can use function annotations:

>>> def foo(indict: dict(apple=None, pear=None)):
...     print(indict)
... 
>>> foo(dict())
{}

You can even go crazy with the now more widely accepted (by the interpreter) Ellipsis literal

>>> def foo(indict: dict(apple=None, pear=None, extra_items=...)) -> int:
...     if any(x not in indict for x in ('apple', 'pear')):
...         raise ValueError('message here...')
...     print(indict)
...     return 3
... 
>>> foo({})
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 3, in foo
ValueError: message here...
>>> foo({'apple':6, 'pear':4})
{'pear': 4, 'apple': 6}
3
>>> foo({'apple':6, 'pear':4, 'carrot':30000})
{'carrot': 30000, 'pear': 4, 'apple': 6}
3

As you can see from my first example, the annotation it doesn't enforce anything. You'd have to perform the validation in the function itself although I suppose you could introspect the required keys from the annotations¹ if you wanted to keep it DRY, but it's probably not worth the effort for just 2 keys...

In python2.x (and more traditionally), perhaps you'd just want to put the information in the docstring ;-) -- And I'd recommend you do that for python3.x as well since that's the traditional place to go looking for documentation ...

^{1keys = foo.__annotations__['indict'].keys() - {'extra_items'}}

UPDATE Note that now with fancy things like mypy sitting around, this answer is maybe a little outdated. You might consider annotating with a TypedDict from mypy_extensions. That should set expectations for your users and maybe even help catch some bugs if you use a type-checker like mypy.

from mypy_extensions import TypedDict

class Apple:
    """Represent an Apple."""

class Pear:
    """Represent a Pear."""

# "annotation-type" for a dictionary that has an apple and pear key whose values are Apple and Pear instances.
FruitBowl = TypedDict("FruitBowl": {"apple": Apple, "Pear": Pear})

def foo(indict: FruitBowl) -> int:
    ...