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gh-96130: Rephrase use of "typecheck" verb for clarity (GH-98144)

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I'm sympathetic to the issue report, especially in case this helps
clarify to new users that Python itself does not do type checking at runtime
(cherry picked from commit ed6344eed0)

Co-authored-by: Shantanu <12621235+hauntsaninja@users.noreply.github.com>
This commit is contained in:
Miss Islington (bot) 2022-10-11 19:45:44 -07:00 • committed by Pablo Galindo
parent 37d165904d
commit 7b1be2ac81
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1 changed files with 10 additions and 10 deletions
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18
Doc/library/typing.rst
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@ -100,7 +100,7 @@ A type alias is defined by assigning the type to the alias. In this example,
def scale(scalar: float, vector: Vector) -> Vector:
return [scalar * num for num in vector]
# typechecks; a list of floats qualifies as a Vector.
# passes type checking; a list of floats qualifies as a Vector.
new_vector = scale(2.0, [1.0, -4.2, 5.4])
Type aliases are useful for simplifying complex type signatures. For example::
@ -142,10 +142,10 @@ of the original type. This is useful in helping catch logical errors::
def get_user_name(user_id: UserId) -> str:
...
# typechecks
# passes type checking
user_a = get_user_name(UserId(42351))
# does not typecheck; an int is not a UserId
# fails type checking; an int is not a UserId
user_b = get_user_name(-1)
You may still perform all ``int`` operations on a variable of type ``UserId``,
@ -171,7 +171,7 @@ It is invalid to create a subtype of ``Derived``::
UserId = NewType('UserId', int)
# Fails at runtime and does not typecheck
# Fails at runtime and does not pass type checking
class AdminUserId(UserId): pass
However, it is possible to create a :class:`NewType` based on a 'derived' ``NewType``::
@ -458,7 +458,7 @@ value of type :data:`Any` and assign it to any variable::
s = a # OK
def foo(item: Any) -> int:
# Typechecks; 'item' could be any type,
# Passes type checking; 'item' could be any type,
# and that type might have a 'bar' method
item.bar()
...
@ -495,20 +495,20 @@ reject almost all operations on it, and assigning it to a variable (or using
it as a return value) of a more specialized type is a type error. For example::
def hash_a(item: object) -> int:
# Fails; an object does not have a 'magic' method.
# Fails type checking; an object does not have a 'magic' method.
item.magic()
...
def hash_b(item: Any) -> int:
# Typechecks
# Passes type checking
item.magic()
...
# Typechecks, since ints and strs are subclasses of object
# Passes type checking, since ints and strs are subclasses of object
hash_a(42)
hash_a("foo")
# Typechecks, since Any is compatible with all types
# Passes type checking, since Any is compatible with all types
hash_b(42)
hash_b("foo")