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)):
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Note that now with fancy things like mypy sitting around, this answer is maybe a little outdated.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:
...
You could just check:
def fun(indict=dict(apple=None, pear=None)):
if "apple" not in indict and "pear" not in indict:
raise ValueError("'indict' must contain...")
However, you shouldn't really use a dictionary (or other mutable) default argument in Python; instead, prefer:
def fun(indict=None):
if indict is None:
indict = {"apple": None, "pear": None}
elif "apple" not in indict...
Or you could use update
to ensure both keys are always present, rather than forcing the caller to provide them:
def fun(indict=None):
defdict = {"apple": None, "pear": None}
if indict is not None:
defdict.update(indict)
indict = defdict
I see quite a few complicated answers for something that is really trivial:
def yourfunc(apple, pear, **kw):
your_code_here
then at call time pass indict
using the **kw
syntax, ie:
indie = dict(pear=1, apple=2, whatever=42)
yourfunc(**indie)
No need to check anything, Python will do it by itself and raise the appropriate exception.
If you cannot change the call syntax, just wrap yourfunc
with this simple decorator:
def kw2dict(func):
def wrap(**kw):
return func(kw)
return wrap
(nb : should use functools to correctly wrap the decorator)
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