| # 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 |