Repository navigation
Expand file tree
/
Copy pathrecord_batch.py
More file actions
101 lines (77 loc) · 3.58 KB
/
Copy pathrecord_batch.py
File metadata and controls
101 lines (77 loc) · 3.58 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
# 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.
"""This module provides the classes for handling record batches.
These are typically the result of dataframe
:py:func:`datafusion.dataframe.execute_stream` operations.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
import pyarrow as pa
import typing_extensions
import datafusion._internal as df_internal
class RecordBatch:
"""This class is essentially a wrapper for :py:class:`pa.RecordBatch`."""
def __init__(self, record_batch: df_internal.RecordBatch) -> None:
"""This constructor is generally not called by the end user.
See the :py:class:`RecordBatchStream` iterator for generating this class.
"""
self.record_batch = record_batch
def to_pyarrow(self) -> pa.RecordBatch:
"""Convert to :py:class:`pa.RecordBatch`."""
return self.record_batch.to_pyarrow()
def __arrow_c_array__(
self, requested_schema: object | None = None
) -> tuple[object, object]:
"""Export the record batch via the Arrow C Data Interface.
This allows zero-copy interchange with libraries that support the
`Arrow PyCapsule interface <https://arrow.apache.org/docs/format/
CDataInterface/PyCapsuleInterface.html>`_.
Args:
requested_schema: Attempt to provide the record batch using this
schema. Only straightforward projections such as column
selection or reordering are applied.
Returns:
Two Arrow PyCapsule objects representing the ``ArrowArray`` and
``ArrowSchema``.
"""
return self.record_batch.__arrow_c_array__(requested_schema)
class RecordBatchStream:
"""This class represents a stream of record batches.
These are typically the result of a
:py:func:`~datafusion.dataframe.DataFrame.execute_stream` operation.
"""
def __init__(self, record_batch_stream: df_internal.RecordBatchStream) -> None:
"""This constructor is typically not called by the end user."""
self.rbs = record_batch_stream
def next(self) -> RecordBatch:
"""See :py:func:`__next__` for the iterator function."""
return next(self)
async def __anext__(self) -> RecordBatch:
"""Return the next :py:class:`RecordBatch` in the stream asynchronously."""
next_batch = await self.rbs.__anext__()
return RecordBatch(next_batch)
def __next__(self) -> RecordBatch:
"""Return the next :py:class:`RecordBatch` in the stream."""
next_batch = next(self.rbs)
return RecordBatch(next_batch)
def __aiter__(self) -> typing_extensions.Self:
"""Return an asynchronous iterator over record batches."""
return self
def __iter__(self) -> typing_extensions.Self:
"""Return an iterator over record batches."""
return self