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| from typing import (
| Hashable,
| Literal,
| )
|
| import numpy as np
|
| from pandas._typing import (
| ArrayLike,
| Dtype,
| npt,
| )
|
| STR_NA_VALUES: set[str]
|
| def sanitize_objects(
| values: npt.NDArray[np.object_],
| na_values: set,
| ) -> int: ...
|
| class TextReader:
| unnamed_cols: set[str]
| table_width: int # int64_t
| leading_cols: int # int64_t
| header: list[list[int]] # non-negative integers
| def __init__(
| self,
| source,
| delimiter: bytes | str = ..., # single-character only
| header=...,
| header_start: int = ..., # int64_t
| header_end: int = ..., # uint64_t
| index_col=...,
| names=...,
| tokenize_chunksize: int = ..., # int64_t
| delim_whitespace: bool = ...,
| converters=...,
| skipinitialspace: bool = ...,
| escapechar: bytes | str | None = ..., # single-character only
| doublequote: bool = ...,
| quotechar: str | bytes | None = ..., # at most 1 character
| quoting: int = ...,
| lineterminator: bytes | str | None = ..., # at most 1 character
| comment=...,
| decimal: bytes | str = ..., # single-character only
| thousands: bytes | str | None = ..., # single-character only
| dtype: Dtype | dict[Hashable, Dtype] = ...,
| usecols=...,
| error_bad_lines: bool = ...,
| warn_bad_lines: bool = ...,
| na_filter: bool = ...,
| na_values=...,
| na_fvalues=...,
| keep_default_na: bool = ...,
| true_values=...,
| false_values=...,
| allow_leading_cols: bool = ...,
| skiprows=...,
| skipfooter: int = ..., # int64_t
| verbose: bool = ...,
| float_precision: Literal["round_trip", "legacy", "high"] | None = ...,
| skip_blank_lines: bool = ...,
| encoding_errors: bytes | str = ...,
| ) -> None: ...
| def set_noconvert(self, i: int) -> None: ...
| def remove_noconvert(self, i: int) -> None: ...
| def close(self) -> None: ...
| def read(self, rows: int | None = ...) -> dict[int, ArrayLike]: ...
| def read_low_memory(self, rows: int | None) -> list[dict[int, ArrayLike]]: ...
|
| # _maybe_upcast, na_values are only exposed for testing
|
| def _maybe_upcast(
| arr, use_dtype_backend: bool = ..., dtype_backend: str = ...
| ) -> np.ndarray: ...
|
|
