arraykit/src/__init__.pyi at f1e466f831ed89294261713e8a45bb413ee5a589 · static-frame/arraykit · GitHub

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import typing as tp

import numpy as np  # type: ignore

_T = tp.TypeVar('_T')

__version__: str

class ArrayGO:

    values: np.ndarray
    def __init__(
        self, iterable: tp.Iterable[object], *, own_iterable: bool = ...
    ) -> None: ...
    def __iter__(self) -> tp.Iterator[tp.Any]: ...
    def __getitem__(self, __key: object) -> tp.Any: ...
    def __len__(self) -> int: ...
    def __getnewargs__(self) -> tp.Tuple[np.ndarray]: ...
    def append(self, __value: object) -> None: ...
    def copy(self: _T) -> _T: ...
    def extend(self, __values: tp.Iterable[object]) -> None: ...

def iterable_str_to_array_1d(
        iterable: tp.Iterable[str],
        *,
        dtype: tp.Optional[tp.Any] = None,
        thousandschar: str = ',',
        decimalchar: str = '.',
        ) -> np.ndarray: ...

def delimited_to_arrays(
        file_like: tp.Iterable[str],
        *,
        axis: int = 0,
        dtypes: tp.Optional[tp.Callable[[int], tp.Any]] = None,
        line_select: tp.Optional[tp.Callable[[int], bool]] = None,
        delimiter: str = ',',
        doublequote: bool = True,
        escapechar: str = '',
        quotechar: str = '"',
        quoting: int = 0,
        skipinitialspace: bool = False,
        strict: bool = False,
        thousandschar: str = ',',
        decimalchar: str = '.',
        ) -> tp.List[np.array]: ...

def split_after_count(
        string: str,
        *,
        delimiter: str = ',',
        count: int = 0,
        doublequote: bool = True,
        escapechar: str = '',
        quotechar: str = '"',
        quoting: int = 0,
        strict: bool = False,
        ) -> tp.Tuple[str, str]: ...

def count_iteration(__iterable: tp.Iterable) -> int: ...

def immutable_filter(__array: np.ndarray) -> np.ndarray: ...
def mloc(__array: np.ndarray) -> int: ...
def name_filter(__name: tp.Hashable) -> tp.Hashable: ...
def shape_filter(__array: np.ndarray) -> np.ndarray: ...
def column_2d_filter(__array: np.ndarray) -> np.ndarray: ...
def column_1d_filter(__array: np.ndarray) -> np.ndarray: ...
def row_1d_filter(__array: np.ndarray) -> np.ndarray: ...
def array_deepcopy(__array: np.ndarray, memo: tp.Dict[int, tp.Any]) -> np.ndarray: ...
def resolve_dtype(__d1: np.dtype, __d2: np.dtype) -> np.dtype: ...
def resolve_dtype_iter(__dtypes: tp.Iterable[np.dtype]) -> np.dtype: ...
def isna_element(__value: tp.Any, include_none: bool = True) -> bool: ...
def dtype_from_element(__value: tp.Optional[tp.Hashable]) -> np.dtype: ...
def get_new_indexers_and_screen(indexers: np.ndarray, positions: np.ndarray) -> tp.Tuple[np.ndarray, np.ndarray]: ...
def is_sorted(arr: np.ndarray) -> bool: ...

def first_true_1d(__array: np.ndarray, *, forward: bool) -> int: ...
def first_true_2d(__array: np.ndarray, *, forward: bool, axis: int) -> np.ndarray: ...