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Add type hints for matplotlib.dates module#30126
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I've only done up to the formatters; please correct the default values in the rest.
| @@ -0,0 +1,200 @@ | |||
| import datetime | |||
| import numpy as np | |||
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NumPy is third-party and thus should be in the second block between stdlib and first-party imports.
| def get_epoch() -> str: ... | ||
| def _dt64_to_ordinalf(d: np.datetime64 | np.ndarray) -> float | np.ndarray: ... |
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There seems to be a bug here; it doesn't actually acceptnp.datetime64 or return afloat, but crashes. Maybe something to be fixed, or else the type hint shouldn't mention them.
| def datestr2num(d: str | Sequence[str], default: datetime.datetime | None = ...) -> float | np.ndarray: ... | ||
| def date2num(d: datetime.datetime | np.datetime64 | Sequence[datetime.datetime | np.datetime64]) -> float | np.ndarray: ... | ||
| def num2date(x: float | Sequence[float], tz: str | datetime.tzinfo | None = ...) -> datetime.datetime | list[datetime.datetime]: ... | ||
| def num2timedelta(x: float | Sequence[float]) -> datetime.timedelta | list[datetime.timedelta]: ... |
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We may want overloads on these for single input vs sequence input.
| # --- Formatter Classes --- | ||
| class DateFormatter(Formatter): | ||
| tz: str | datetime.tzinfo | None |
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This is passed through_get_tz_info before assignment, so should always be adatetime.tzinfo.
| class DateFormatter(Formatter): | ||
| tz: str | datetime.tzinfo | None | ||
| fmt: str | ||
| _usetex: bool | None |
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NeverNone, though since this is private and not part of the API, I'm not sure we should type hint it..
| class ConciseDateFormatter(Formatter): | ||
| _locator: Locator | ||
| _tz: str | datetime.tzinfo | None | ||
| formats: List[str] |
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Missingdefaultfmt?
| def __init__(self, locator: Locator, | ||
| tz: str | datetime.tzinfo | None = None, | ||
| defaultfmt: str = '%Y-%m-%d', | ||
| *, usetex: bool | None = None) -> None: ... | ||
| def _set_locator(self, locator: Locator) -> None: ... | ||
| def __call__(self, x: float, pos: int | None = 0) -> str: ... |
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| def__init__(self,locator:Locator, | |
| tz:str|datetime.tzinfo|None=None, | |
| defaultfmt:str='%Y-%m-%d', | |
| *,usetex:bool|None=None)->None: ... | |
| def_set_locator(self,locator:Locator)->None: ... | |
| def__call__(self,x:float,pos:int|None=0)->str: ... | |
| def__init__(self,locator:Locator, | |
| tz:str|datetime.tzinfo|None=..., | |
| defaultfmt:str=..., | |
| *,usetex:bool|None=...)->None: ... | |
| def_set_locator(self,locator:Locator)->None: ... | |
| def__call__(self,x:float,pos:int|None=...)->str: ... |
| def set(self, **kwargs: Any) -> None: ... | ||
| def _update_rrule(self, **kwargs: Any) -> None: ... | ||
| def _attach_tzinfo(self, dt: datetime.datetime, tzinfo: datetime.tzinfo) -> datetime.datetime: ... | ||
| def _aware_return_wrapper(self, f: Callable[..., Any], returns_list: bool = False) -> Callable[..., Any]: ... |
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| def_aware_return_wrapper(self,f:Callable[...,Any],returns_list:bool=False)->Callable[...,Any]: ... | |
| def_aware_return_wrapper(self,f:Callable[...,Any],returns_list:bool=...)->Callable[...,Any]: ... |
| defaultfmt: str | ||
| _formatter: DateFormatter | ||
| _usetex: bool | None | ||
| scaled: dict |
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Missing key/value types.
| def _set_locator(self, locator: Locator) -> None: ... | ||
| def __call__(self, x: float, pos: int | None = 0) -> str: ... | ||
| # --- rrulewrapper (assuming it's in rrule.py and this is its stub) --- |
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I don't know what this parentheses means.
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PR Summary
This pull request introduces comprehensive type hint stubs (
.pyifiles) for thematplotlib.datesmodule.Why this change is necessary:
By providing explicit type information, this enhancement significantly improves static type checking capabilities for
matplotlib.dates. Developers using tools like MyPy, Pyright, or Ruff can now catch potential type-related errors earlier in the development cycle, leading to more robust and maintainable code.Problem solved:
This PR addresses the current lack of precise type information for
matplotlib.datesclasses and functions during static analysis. It makes the module's API more explicit and easier for automated type-checking tools to understand and validate.Implementation reasoning:
The implementation involves adding
.pyifiles that define the types for the core classes and functions withinmatplotlib.dates.py. This change directly contributes to Matplotlib's ongoing initiative to expand and improve type hinting coverage across its codebase, fostering better developer experience and code quality.Closes#29994
PR Checklist
matplotlib.dates.DateFormatter#29994" is in the body of the PR description tolink the related issuemypyor similar type checkers to ensure no errors are introduced.Test Result
mypy, ruff and Pyright with the new
dates.pyi