AlenkaF commented on code in PR #14804: URL: https://github.com/apache/arrow/pull/14804#discussion_r1049656266
########## python/pyarrow/interchange/column.py: ########## @@ -0,0 +1,507 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +from __future__ import annotations + +import enum +from typing import ( + Any, + Dict, + Iterable, + Optional, + Tuple, +) + +import sys +if sys.version_info >= (3, 8): + from typing import TypedDict +else: + from typing_extensions import TypedDict + +import pyarrow as pa +import pyarrow.compute as pc +from pyarrow.interchange.buffer import _PyArrowBuffer + + +class DtypeKind(enum.IntEnum): + """ + Integer enum for data types. + Attributes + ---------- + INT : int + Matches to signed integer data type. + UINT : int + Matches to unsigned integer data type. + FLOAT : int + Matches to floating point data type. + BOOL : int + Matches to boolean data type. + STRING : int + Matches to string data type (UTF-8 encoded). + DATETIME : int + Matches to datetime data type. + CATEGORICAL : int + Matches to categorical data type. + """ + + INT = 0 + UINT = 1 + FLOAT = 2 + BOOL = 20 + STRING = 21 # UTF-8 + DATETIME = 22 + CATEGORICAL = 23 + + +Dtype = Tuple[DtypeKind, int, str, str] # see Column.dtype + + +_PYARROW_KINDS = { + pa.int8(): (DtypeKind.INT, "c"), + pa.int16(): (DtypeKind.INT, "s"), + pa.int32(): (DtypeKind.INT, "i"), + pa.int64(): (DtypeKind.INT, "l"), + pa.uint8(): (DtypeKind.UINT, "C"), + pa.uint16(): (DtypeKind.UINT, "S"), + pa.uint32(): (DtypeKind.UINT, "I"), + pa.uint64(): (DtypeKind.UINT, "L"), + pa.float16(): (DtypeKind.FLOAT, "e"), + pa.float32(): (DtypeKind.FLOAT, "f"), + pa.float64(): (DtypeKind.FLOAT, "g"), + pa.bool_(): (DtypeKind.BOOL, "b"), + pa.string(): (DtypeKind.STRING, "u"), # utf-8 + pa.large_string(): (DtypeKind.STRING, "U"), +} + + +class ColumnNullType(enum.IntEnum): + """ + Integer enum for null type representation. + Attributes + ---------- + NON_NULLABLE : int + Non-nullable column. + USE_NAN : int + Use explicit float NaN value. + USE_SENTINEL : int + Sentinel value besides NaN. + USE_BITMASK : int + The bit is set/unset representing a null on a certain position. + USE_BYTEMASK : int + The byte is set/unset representing a null on a certain position. + """ + + NON_NULLABLE = 0 + USE_NAN = 1 + USE_SENTINEL = 2 + USE_BITMASK = 3 + USE_BYTEMASK = 4 + + +class ColumnBuffers(TypedDict): + # first element is a buffer containing the column data; + # second element is the data buffer's associated dtype + data: Tuple[_PyArrowBuffer, Dtype] + + # first element is a buffer containing mask values indicating missing data; + # second element is the mask value buffer's associated dtype. + # None if the null representation is not a bit or byte mask + validity: Optional[Tuple[_PyArrowBuffer, Dtype]] + + # first element is a buffer containing the offset values for + # variable-size binary data (e.g., variable-length strings); + # second element is the offsets buffer's associated dtype. + # None if the data buffer does not have an associated offsets buffer + offsets: Optional[Tuple[_PyArrowBuffer, Dtype]] + + +class CategoricalDescription(TypedDict): + # whether the ordering of dictionary indices is semantically meaningful + is_ordered: bool + # whether a dictionary-style mapping of categorical values to other objects + # exists + is_dictionary: bool + # Python-level only (e.g. ``{int: str}``). + # None if not a dictionary-style categorical. + # categories: Optional[Column] Review Comment: Hm, I do not remember why I commented it out. Will revert and see. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
