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import types import zipfile from _typeshed import ( StrOrBytesPath, StrPath, SupportsKeysAndGetItem, SupportsRead, SupportsWrite, ) from collections.abc import Callable, Collection, Iterable, Iterator, Mapping, Sequence from re import Pattern from typing import ( IO, Any, ClassVar, Generic, Literal as L, Protocol, Self, TypeAlias, overload, type_check_only, ) from typing_extensions import TypeVar, override import numpy as np from numpy._core.multiarray import packbits, unpackbits from numpy._typing import ArrayLike, DTypeLike, NDArray, _DTypeLike, _SupportsArrayFunc from numpy.ma.mrecords import MaskedRecords from ._datasource import DataSource as DataSource __all__ = [ "fromregex", "genfromtxt", "load", "loadtxt", "packbits", "save", "savetxt", "savez", "savez_compressed", "unpackbits", ] _T = TypeVar("_T") _T_co = TypeVar("_T_co", covariant=True) _ScalarT = TypeVar("_ScalarT", bound=np.generic) _ScalarT_co = TypeVar("_ScalarT_co", bound=np.generic, default=Any, covariant=True) _FName: TypeAlias = StrPath | Iterable[str] | Iterable[bytes] _FNameRead: TypeAlias = StrPath | SupportsRead[str] | SupportsRead[bytes] _FNameWriteBytes: TypeAlias = StrPath | SupportsWrite[bytes] _FNameWrite: TypeAlias = _FNameWriteBytes | SupportsWrite[str] @type_check_only class _SupportsReadSeek(SupportsRead[_T_co], Protocol[_T_co]): def seek(self, offset: int, whence: int, /) -> object: ... class BagObj(Generic[_T_co]): def __init__(self, /, obj: SupportsKeysAndGetItem[str, _T_co]) -> None: ... def __getattribute__(self, key: str, /) -> _T_co: ... def __dir__(self) -> list[str]: ... class NpzFile(Mapping[str, NDArray[_ScalarT_co]]): _MAX_REPR_ARRAY_COUNT: ClassVar[int] = 5 zip: zipfile.ZipFile | None = None fid: IO[str] | None = None files: list[str] allow_pickle: bool pickle_kwargs: Mapping[str, Any] | None f: BagObj[NpzFile[_ScalarT_co]] # def __init__( self, /, fid: IO[Any], own_fid: bool = False, allow_pickle: bool = False, pickle_kwargs: Mapping[str, object] | None = None, *, max_header_size: int = 10_000, ) -> None: ... def __del__(self) -> None: ... def __enter__(self) -> Self: ... def __exit__(self, cls: type[BaseException] | None, e: BaseException | None, tb: types.TracebackType | None, /) -> None: ... @override def __len__(self) -> int: ... @override def __iter__(self) -> Iterator[str]: ... @override def __getitem__(self, key: str, /) -> NDArray[_ScalarT_co]: ... # @override @overload def get(self, key: str, default: None = None, /) -> NDArray[_ScalarT_co] | None: ... @overload def get(self, key: str, default: NDArray[_ScalarT_co] | _T, /) -> NDArray[_ScalarT_co] | _T: ... # pyright: ignore[reportIncompatibleMethodOverride] # def close(self) -> None: ... # NOTE: Returns a `NpzFile` if file is a zip file; # returns an `ndarray`/`memmap` otherwise def load( file: StrOrBytesPath | _SupportsReadSeek[bytes], mmap_mode: L["r+", "r", "w+", "c"] | None = None, allow_pickle: bool = False, fix_imports: bool = True, encoding: L["ASCII", "latin1", "bytes"] = "ASCII", *, max_header_size: int = 10_000, ) -> Any: ... def save(file: _FNameWriteBytes, arr: ArrayLike, allow_pickle: bool = True) -> None: ... def savez(file: _FNameWriteBytes, *args: ArrayLike, allow_pickle: bool = True, **kwds: ArrayLike) -> None: ... def savez_compressed(file: _FNameWriteBytes, *args: ArrayLike, allow_pickle: bool = True, **kwds: ArrayLike) -> None: ... # File-like objects only have to implement `__iter__` and, # optionally, `encoding` @overload def loadtxt( fname: _FName, dtype: None = None, comments: str | Sequence[str] | None = "#", delimiter: str | None = None, converters: Mapping[int | str, Callable[[str], Any]] | Callable[[str], Any] | None = None, skiprows: int = 0, usecols: int | Sequence[int] | None = None, unpack: bool = False, ndmin: L[0, 1, 2] = 0, encoding: str | None = None, max_rows: int | None = None, *, quotechar: str | None = None, like: _SupportsArrayFunc | None = None, ) -> NDArray[np.float64]: ... @overload def loadtxt( fname: _FName, dtype: _DTypeLike[_ScalarT], comments: str | Sequence[str] | None = "#", delimiter: str | None = None, converters: Mapping[int | str, Callable[[str], Any]] | Callable[[str], Any] | None = None, skiprows: int = 0, usecols: int | Sequence[int] | None = None, unpack: bool = False, ndmin: L[0, 1, 2] = 0, encoding: str | None = None, max_rows: int | None = None, *, quotechar: str | None = None, like: _SupportsArrayFunc | None = None, ) -> NDArray[_ScalarT]: ... @overload def loadtxt( fname: _FName, dtype: DTypeLike | None, comments: str | Sequence[str] | None = "#", delimiter: str | None = None, converters: Mapping[int | str, Callable[[str], Any]] | Callable[[str], Any] | None = None, skiprows: int = 0, usecols: int | Sequence[int] | None = None, unpack: bool = False, ndmin: L[0, 1, 2] = 0, encoding: str | None = None, max_rows: int | None = None, *, quotechar: str | None = None, like: _SupportsArrayFunc | None = None, ) -> NDArray[Any]: ... def savetxt( fname: _FNameWrite, X: ArrayLike, fmt: str | Sequence[str] = "%.18e", delimiter: str = " ", newline: str = "\n", header: str = "", footer: str = "", comments: str = "# ", encoding: str | None = None, ) -> None: ... @overload def fromregex( file: _FNameRead, regexp: str | bytes | Pattern[Any], dtype: _DTypeLike[_ScalarT], encoding: str | None = None, ) -> NDArray[_ScalarT]: ... @overload def fromregex( file: _FNameRead, regexp: str | bytes | Pattern[Any], dtype: DTypeLike | None, encoding: str | None = None, ) -> NDArray[Any]: ... @overload def genfromtxt( fname: _FName, dtype: None = None, comments: str = "#", delimiter: str | int | Iterable[int] | None = None, skip_header: int = 0, skip_footer: int = 0, converters: Mapping[int | str, Callable[[str], Any]] | None = None, missing_values: Any = None, filling_values: Any = None, usecols: Sequence[int] | None = None, names: L[True] | str | Collection[str] | None = None, excludelist: Sequence[str] | None = None, deletechars: str = " !#$%&'()*+,-./:;<=>?@[\\]^{|}~", replace_space: str = "_", autostrip: bool = False, case_sensitive: bool | L["upper", "lower"] = True, defaultfmt: str = "f%i", unpack: bool | None = None, usemask: bool = False, loose: bool = True, invalid_raise: bool = True, max_rows: int | None = None, encoding: str | None = None, *, ndmin: L[0, 1, 2] = 0, like: _SupportsArrayFunc | None = None, ) -> NDArray[Any]: ... @overload def genfromtxt( fname: _FName, dtype: _DTypeLike[_ScalarT], comments: str = "#", delimiter: str | int | Iterable[int] | None = None, skip_header: int = 0, skip_footer: int = 0, converters: Mapping[int | str, Callable[[str], Any]] | None = None, missing_values: Any = None, filling_values: Any = None, usecols: Sequence[int] | None = None, names: L[True] | str | Collection[str] | None = None, excludelist: Sequence[str] | None = None, deletechars: str = " !#$%&'()*+,-./:;<=>?@[\\]^{|}~", replace_space: str = "_", autostrip: bool = False, case_sensitive: bool | L["upper", "lower"] = True, defaultfmt: str = "f%i", unpack: bool | None = None, usemask: bool = False, loose: bool = True, invalid_raise: bool = True, max_rows: int | None = None, encoding: str | None = None, *, ndmin: L[0, 1, 2] = 0, like: _SupportsArrayFunc | None = None, ) -> NDArray[_ScalarT]: ... @overload def genfromtxt( fname: _FName, dtype: DTypeLike | None, comments: str = "#", delimiter: str | int | Iterable[int] | None = None, skip_header: int = 0, skip_footer: int = 0, converters: Mapping[int | str, Callable[[str], Any]] | None = None, missing_values: Any = None, filling_values: Any = None, usecols: Sequence[int] | None = None, names: L[True] | str | Collection[str] | None = None, excludelist: Sequence[str] | None = None, deletechars: str = " !#$%&'()*+,-./:;<=>?@[\\]^{|}~", replace_space: str = "_", autostrip: bool = False, case_sensitive: bool | L["upper", "lower"] = True, defaultfmt: str = "f%i", unpack: bool | None = None, usemask: bool = False, loose: bool = True, invalid_raise: bool = True, max_rows: int | None = None, encoding: str | None = None, *, ndmin: L[0, 1, 2] = 0, like: _SupportsArrayFunc | None = None, ) -> NDArray[Any]: ... @overload def recfromtxt(fname: _FName, *, usemask: L[False] = False, **kwargs: object) -> np.recarray[Any, np.dtype[np.record]]: ... @overload def recfromtxt(fname: _FName, *, usemask: L[True], **kwargs: object) -> MaskedRecords[Any, np.dtype[np.void]]: ... @overload def recfromcsv(fname: _FName, *, usemask: L[False] = False, **kwargs: object) -> np.recarray[Any, np.dtype[np.record]]: ... @overload def recfromcsv(fname: _FName, *, usemask: L[True], **kwargs: object) -> MaskedRecords[Any, np.dtype[np.void]]: ...