Before ParamSpec
(PEP612) was released in Python3.10 and typing_extensions
,
there was a big problem in typing decorators that change a function’s signature.
Let’s start with a basic example. How one can type a decorator function that does not change anything?
from typing import Callable, TypeVar
C = TypeVar('C', bound=Callable)
def logger(function: C) -> C:
def decorator(*args, **kwargs):
print('Function called!')
return function(*args, **kwargs)
return decorator
Notice the most important part here: C = TypeVar('C', bound=Callable)
What does it mean? It means that we take any callable in and return the exact same callable.
This allows you to decorate any function and preserve its signature:
@logger
def example(arg: int, other: str) -> tuple[int, str]:
return arg, other
reveal_type(example) # (arg: int, other: str) -> tuple[int, str]
But, there’s a problem when a function does want to change something.
Imagine, that some decorator might also add None
as a return value in some cases:
def catch_exception(function):
def decorator(*args, **kwargs):
try:
return function(*args, **kwargs)
except Exception:
return None
return decorator
This is a perfectly valid Python code.
But how can we type it? Note that we cannot use TypeVar('C', bound=Callable)
anymore, since we are changing the return type now.
Initially, I’ve tried something like:
def catch_exception(function: Callable[..., T]) -> Callable[..., Optional[T]]:
...
But, this means a different thing: it turns all function’s arguments into *args: Any, **kwargs: Any
, but, the return type will be correct. Generally, this is not what we need when it comes to type-safety.
The second way to do that in a type-safe way is adding a custom Mypy plugin.
Here’s our example from dry-python/returns
to support decorators that were changing return types. But, plugins are quite hard to write (you need to learn a bit of Mypy’s API), they are not universal (for example, Pyright does not understand Mypy plugins), and they require to be explicitly installed by the end user.
That’s why ParamSpec
was added. Here’s how it can be used in this case:
from typing import Callable, TypeVar, Optional
from typing_extensions import ParamSpec # or `typing` for `python>=3.10`
T = TypeVar('T')
P = ParamSpec('P')
def catch_exception(function: Callable[P, T]) -> Callable[P, Optional[T]]:
def decorator(*args: P.args, **kwargs: P.kwargs) -> Optional[T]:
try:
return function(*args, **kwargs)
except Exception:
return None
return decorator
Now, all decorated functions will preserve their argument types and change their return type to include None
:
@catch_exception
def div(arg: int) -> float:
return arg / arg
reveal_type(div) # (arg: int) -> Optional[float]
@catch_exception
def plus(arg: int, other: int) -> int:
return arg + other
reveal_type(plus) # (arg: int, other: int) -> Optional[int]:
The recent release of Mypy 0.930 with ParamSpec
support allowed us to remove our custom Mypy plugin and use a well-defined primitive. Here’s a commit to show how easy our transition was. It was even released today in [email protected]
, check it out!
What’s next? Concatenate
But, that’s not all! Because some decorators modify argument types, PEP612 also adds the Concatenate
type that allows prepending, appending, transforming, or removing function arguments.
Unfortunately, Mypy does not support Concatenate
just yet, but I can show you some examples from PEP itself. Here’s how it is going to work.
Let’s start with some basic definitions:
from typing_extensions import ParamSpec, Concatenate # or `typing` for `python>=3.10`
P = ParamSpec('P')
def bar(x: int, *args: bool) -> int: ...
We are going to change the type of bar
function with the help of P
parameter specification. First, let’s prepend an str
argument to this function:
def add(x: Callable[P, int]) -> Callable[Concatenate[str, P], int]: ...
add(bar) # (str, /, x: int, *args: bool) -> int
Notice that a positional-only str
argument is added to the return type of add(bar)
.
Now, let’s try removing an argument:
def remove(x: Callable[Concatenate[int, P], int]) -> Callable[P, int]: ...
remove(bar) # (*args: bool) -> int
Because we use P
and Concatenate
in the argument type, the return type will not have an int
argument anymore.
And finally, let’s change an argument type from int
to str
and return type from int
to bool
:
def transform(
x: Callable[Concatenate[int, P], int]
) -> Callable[Concatenate[str, P], bool]: ...
transform(bar) # (str, /, *args: bool) -> bool
Looking forward to new Mypy release with Concatenate
support. I totally know some places where it will be useful.
Conclusion
PEP612 adds two very powerful abstractions that allow us to better type our functions and decorators, which play a very important role in Python’s world.
Complex projects (like Django) or simple type-safe scripts can highly benefit from this new typing feature. And I hope you will!
Happy New Year!