Re:Show HN: I Wrote a Book on Java
by sodapopcan on Tuesday September 24, 2024 @12:36PM
(#41638324)
Awesome, thanks for the clarification.
class X(TypedDict):
x: str
class Y(TypedDict):
y: str
class XYZ(X, Y):
z: str
That should get you the class/superclass relationship that you want, no?That needs to be explicit for any interacting types. You must define separate classes and explicitly define their hierarchy. This is fine if you control all the types, but it breaks down quickly. The best example is having two TypedDicts with the same members; in Python, you cannot use one instead of the other.
from typing import TypedDict
class A(TypedDict):
a: int
b: str
class B(TypedDict):
a: int
b: str
def f(a: A) -> None: pass
b = B(a=1, b='b')
f(B) # mypy error: Argument 1 to "f" has incompatible type "type[B]"; expected "A" [arg-type]
On the other hand, this is legal in Typescript: interface A {
a: number;
b: string;
}
interface B {
a: number;
b: string;
}
function f(a: A) {}
const b: B = {a: 1, b: 'b'};
f(b);
This is most useful when A has a subset of B's attributes, like this (which also doesn't work in Python): interface A {
a: number;
}
interface B {
a: number;
b: string;
}
function f(a: A) {}
const b: B = {a: 1, b: 'b'};
f(b);That seems a lot like duck typing to me.
Yes, it is. Typed Python supports duck typing to some extent; see typing.Protocol and stuff like Sequence, Iterable, Mapping, etc.
In modern typed Python, you can instead use dataclasses, NamedTuples (both in the standard library), attrs or Pydantic (both third-party) to represent structs/records, the latter also providing validation. Still, TypedDicts are helpful when interfacing with older code that uses dicts for heterogeneous data.
My main gripe with them is that different TypedDicts are not compatible with each other. For example, it would be very helpful if a dict with x:str and y:str fields were considered superclasses of dicts with x:str, y:str and z:str like they are in TypeScript, but they aren't. They are considered different types, limiting their usability in some contexts.
When using homogenous dicts, you can still use dict[str, T], and T can be Any if you don't want to type the whole thing. You can use any hashable type instead of str for keys. I often do that when reading JSON from dynamically typed dict[str, Any] to dataclasses.