Bump cherrypy from 18.6.1 to 18.8.0 (#1796)

* Bump cherrypy from 18.6.1 to 18.8.0

Bumps [cherrypy](https://github.com/cherrypy/cherrypy) from 18.6.1 to 18.8.0.
- [Release notes](https://github.com/cherrypy/cherrypy/releases)
- [Changelog](https://github.com/cherrypy/cherrypy/blob/main/CHANGES.rst)
- [Commits](https://github.com/cherrypy/cherrypy/compare/v18.6.1...v18.8.0)

---
updated-dependencies:
- dependency-name: cherrypy
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>

* Update cherrypy==18.8.0

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: JonnyWong16 <9099342+JonnyWong16@users.noreply.github.com>
This commit is contained in:
dependabot[bot] 2022-11-12 17:53:03 -08:00 committed by GitHub
commit 76cc56a215
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GPG key ID: 4AEE18F83AFDEB23
75 changed files with 19150 additions and 1339 deletions

View file

@ -72,7 +72,6 @@ class peekable(Generic[_T], Iterator[_T]):
@overload
def __getitem__(self, index: slice) -> List[_T]: ...
def collate(*iterables: Iterable[_T], **kwargs: Any) -> Iterable[_T]: ...
def consumer(func: _GenFn) -> _GenFn: ...
def ilen(iterable: Iterable[object]) -> int: ...
def iterate(func: Callable[[_T], _T], start: _T) -> Iterator[_T]: ...
@ -179,7 +178,7 @@ def padded(
iterable: Iterable[_T],
*,
n: Optional[int] = ...,
next_multiple: bool = ...
next_multiple: bool = ...,
) -> Iterator[Optional[_T]]: ...
@overload
def padded(
@ -225,7 +224,7 @@ def zip_equal(
__iter1: Iterable[_T],
__iter2: Iterable[_T],
__iter3: Iterable[_T],
*iterables: Iterable[_T]
*iterables: Iterable[_T],
) -> Iterator[Tuple[_T, ...]]: ...
@overload
def zip_offset(
@ -233,7 +232,7 @@ def zip_offset(
*,
offsets: _SizedIterable[int],
longest: bool = ...,
fillvalue: None = None
fillvalue: None = None,
) -> Iterator[Tuple[Optional[_T1]]]: ...
@overload
def zip_offset(
@ -242,7 +241,7 @@ def zip_offset(
*,
offsets: _SizedIterable[int],
longest: bool = ...,
fillvalue: None = None
fillvalue: None = None,
) -> Iterator[Tuple[Optional[_T1], Optional[_T2]]]: ...
@overload
def zip_offset(
@ -252,7 +251,7 @@ def zip_offset(
*iterables: Iterable[_T],
offsets: _SizedIterable[int],
longest: bool = ...,
fillvalue: None = None
fillvalue: None = None,
) -> Iterator[Tuple[Optional[_T], ...]]: ...
@overload
def zip_offset(
@ -420,7 +419,7 @@ def difference(
iterable: Iterable[_T],
func: Callable[[_T, _T], _U] = ...,
*,
initial: None = ...
initial: None = ...,
) -> Iterator[Union[_T, _U]]: ...
@overload
def difference(
@ -529,12 +528,12 @@ def distinct_combinations(
def filter_except(
validator: Callable[[Any], object],
iterable: Iterable[_T],
*exceptions: Type[BaseException]
*exceptions: Type[BaseException],
) -> Iterator[_T]: ...
def map_except(
function: Callable[[Any], _U],
iterable: Iterable[_T],
*exceptions: Type[BaseException]
*exceptions: Type[BaseException],
) -> Iterator[_U]: ...
def map_if(
iterable: Iterable[Any],
@ -610,7 +609,7 @@ def zip_broadcast(
scalar_types: Union[
type, Tuple[Union[type, Tuple[Any, ...]], ...], None
] = ...,
strict: bool = ...
strict: bool = ...,
) -> Iterable[Tuple[_T, ...]]: ...
def unique_in_window(
iterable: Iterable[_T], n: int, key: Optional[Callable[[_T], _U]] = ...
@ -640,7 +639,7 @@ def minmax(
iterable_or_value: Iterable[_SupportsLessThanT],
*,
key: None = None,
default: _U
default: _U,
) -> Union[_U, Tuple[_SupportsLessThanT, _SupportsLessThanT]]: ...
@overload
def minmax(
@ -653,12 +652,23 @@ def minmax(
def minmax(
iterable_or_value: _SupportsLessThanT,
__other: _SupportsLessThanT,
*others: _SupportsLessThanT
*others: _SupportsLessThanT,
) -> Tuple[_SupportsLessThanT, _SupportsLessThanT]: ...
@overload
def minmax(
iterable_or_value: _T,
__other: _T,
*others: _T,
key: Callable[[_T], _SupportsLessThan]
key: Callable[[_T], _SupportsLessThan],
) -> Tuple[_T, _T]: ...
def longest_common_prefix(
iterables: Iterable[Iterable[_T]],
) -> Iterator[_T]: ...
def iequals(*iterables: Iterable[object]) -> bool: ...
def constrained_batches(
iterable: Iterable[object],
max_size: int,
max_count: Optional[int] = ...,
get_len: Callable[[_T], object] = ...,
strict: bool = ...,
) -> Iterator[Tuple[_T]]: ...