##// END OF EJS Templates
phases: large rewrite on retract boundary...
phases: large rewrite on retract boundary The new code is still pure Python, so we still have room to going significantly faster. However its complexity of the complex part is `O(|[min_new_draft, tip]|)` instead of `O(|[min_draft, tip]|` which should help tremendously one repository with old draft (like mercurial-devel or mozilla-try). This is especially useful as the most common "retract boundary" operation happens when we commit/rewrite new drafts or when we push new draft to a non-publishing server. In this case, the smallest new_revs is very close to the tip and there is very few work to do. A few smaller optimisation could be done for these cases and will be introduced in later changesets. We still have iterate over large sets of roots, but this is already a great improvement for a very small amount of work. We gather information on the affected changeset as we go as we can put it to use in the next changesets. This extra data collection might slowdown the `register_new` case a bit, however for register_new, it should not really matters. The set of new nodes is either small, so the impact is negligible, or the set of new nodes is large, and the amount of work to do to had them will dominate the overhead the collecting information in `changed_revs`. As this new code compute the changes on the fly, it unlock other interesting improvement to be done in later changeset.

File last commit:

r50538:e1c586b9 default
r52302:2f39c7ae default
Show More
validators.pyi
80 lines | 2.3 KiB | text/x-python | PythonLexer
from typing import (
Any,
AnyStr,
Callable,
Container,
ContextManager,
Iterable,
List,
Mapping,
Match,
Optional,
Pattern,
Tuple,
Type,
TypeVar,
Union,
overload,
)
from . import _ValidatorType
from . import _ValidatorArgType
_T = TypeVar("_T")
_T1 = TypeVar("_T1")
_T2 = TypeVar("_T2")
_T3 = TypeVar("_T3")
_I = TypeVar("_I", bound=Iterable)
_K = TypeVar("_K")
_V = TypeVar("_V")
_M = TypeVar("_M", bound=Mapping)
def set_disabled(run: bool) -> None: ...
def get_disabled() -> bool: ...
def disabled() -> ContextManager[None]: ...
# To be more precise on instance_of use some overloads.
# If there are more than 3 items in the tuple then we fall back to Any
@overload
def instance_of(type: Type[_T]) -> _ValidatorType[_T]: ...
@overload
def instance_of(type: Tuple[Type[_T]]) -> _ValidatorType[_T]: ...
@overload
def instance_of(
type: Tuple[Type[_T1], Type[_T2]]
) -> _ValidatorType[Union[_T1, _T2]]: ...
@overload
def instance_of(
type: Tuple[Type[_T1], Type[_T2], Type[_T3]]
) -> _ValidatorType[Union[_T1, _T2, _T3]]: ...
@overload
def instance_of(type: Tuple[type, ...]) -> _ValidatorType[Any]: ...
def provides(interface: Any) -> _ValidatorType[Any]: ...
def optional(
validator: Union[_ValidatorType[_T], List[_ValidatorType[_T]]]
) -> _ValidatorType[Optional[_T]]: ...
def in_(options: Container[_T]) -> _ValidatorType[_T]: ...
def and_(*validators: _ValidatorType[_T]) -> _ValidatorType[_T]: ...
def matches_re(
regex: Union[Pattern[AnyStr], AnyStr],
flags: int = ...,
func: Optional[
Callable[[AnyStr, AnyStr, int], Optional[Match[AnyStr]]]
] = ...,
) -> _ValidatorType[AnyStr]: ...
def deep_iterable(
member_validator: _ValidatorArgType[_T],
iterable_validator: Optional[_ValidatorType[_I]] = ...,
) -> _ValidatorType[_I]: ...
def deep_mapping(
key_validator: _ValidatorType[_K],
value_validator: _ValidatorType[_V],
mapping_validator: Optional[_ValidatorType[_M]] = ...,
) -> _ValidatorType[_M]: ...
def is_callable() -> _ValidatorType[_T]: ...
def lt(val: _T) -> _ValidatorType[_T]: ...
def le(val: _T) -> _ValidatorType[_T]: ...
def ge(val: _T) -> _ValidatorType[_T]: ...
def gt(val: _T) -> _ValidatorType[_T]: ...
def max_len(length: int) -> _ValidatorType[_T]: ...
def min_len(length: int) -> _ValidatorType[_T]: ...