Is it possible to type hint a lambda function?

Question

You can, sort of, in Python 3.6 and up using PEP 526 variable annotations. You can annotate the variable you assign the lambda result to with the typing.Callable generic:

from typing import Callable

func: Callable[[str, str], int] = lambda var1, var2: var1.index(var2)

This doesn't attach the type hinting information to the function object itself, only to the namespace you stored the object in, but this is usually all you need for type hinting purposes.

However, you may as well just use a function statement instead; the only advantage that a lambda offers is that you can put a function definition for a simple expression inside a larger expression. But the above lambda is not part of a larger expression, it is only ever part of an assignment statement, binding it to a name. That's exactly what a def func(var1: str, var2: str): return var1.index(var2) statement would achieve.

Note that you can't annotate *args or **kwargs arguments separately either, as the documentation for Callable states:

There is no syntax to indicate optional or keyword arguments; such function types are rarely used as callback types.

That limitation does not apply to a PEP 544 protocol with a __call__ method; use this if you need a expressive definition of what arguments should be accepted. You need Python 3.8 or install the typing-extensions project for a backport:

from typing_extensions import Protocol

class SomeCallableConvention(Protocol):
    def __call__(self, var1: str, var2: str, spam: str = "ham") -> int:
        ...

func: SomeCallableConvention = lambda var1, var2, spam="ham": var1.index(var2) * spam

For the lambda expression itself, you can't use any annotations (the syntax on which Python's type hinting is built). The syntax is only available for def function statements.

From PEP 3107 - Function Annotations:

lambda 's syntax does not support annotations. The syntax of lambda could be changed to support annotations, by requiring parentheses around the parameter list. However it was decided not to make this change because:

• It would be an incompatible change.
• Lambda's are neutered anyway.
• The lambda can always be changed to a function.

You can still attach the annotations directly to the object, the function.__annotations__ attribute is a writable dictionary:

>>> def func(var1: str, var2: str) -> int:
...     return var1.index(var2)
...
>>> func.__annotations__
{'var1': <class 'str'>, 'return': <class 'int'>, 'var2': <class 'str'>}
>>> lfunc = lambda var1, var2: var1.index(var2)
>>> lfunc.__annotations__
{}
>>> lfunc.__annotations__['var1'] = str
>>> lfunc.__annotations__['var2'] = str
>>> lfunc.__annotations__['return'] = int
>>> lfunc.__annotations__
{'var1': <class 'str'>, 'return': <class 'int'>, 'var2': <class 'str'>}

Not that dynamic annotations like these are going to help you when you wanted to run a static analyser over your type hints, of course.

Since Python 3.6, you can (see PEP 526):

from typing import Callable
is_even: Callable[[int], bool] = lambda x: (x % 2 == 0)

For those just looking for a swift access to intellisense when writing your code, an almost-hack is to type-annotate the parameter just before the lambda declaration, do your work and only then shadow it with the parameter.

    x: YourClass
    map(lambda _ :  x.somemethod ...) # x has access to methods defined on YourClass

Then, right after:

    x: YourClass # can remove or leave
    map(lambda x:  x.somemethod, ListOfYourObjects) # inner x now shadows the argument