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pyarrow.ipc.RecordBatchFileReader — Apache Arrow v20.0.0

class pyarrow.ipc.RecordBatchFileReader(source, footer_offset=None, *, options=None, memory_pool=None)[source]#

Bases: _RecordBatchFileReader

Class for reading Arrow record batch data from the Arrow binary file format

Parameters:

sourcebytes/buffer-like, pyarrow.NativeFile, or file-like Python object

Either an in-memory buffer, or a readable file object. If you want to use memory map use MemoryMappedFile as source.

footer_offsetint, default None

If the file is embedded in some larger file, this is the byte offset to the very end of the file data

optionspyarrow.ipc.IpcReadOptions

Options for IPC serialization. If None, default values will be used.

memory_poolMemoryPool, default None

If None, default memory pool is used.

__init__(source, footer_offset=None, *, options=None, memory_pool=None)[source]#

Methods

Attributes

get_batch(self, int i)#

Read the record batch with the given index.

Parameters:

iint

The index of the record batch in the IPC file.

Returns:

batchRecordBatch

get_batch_with_custom_metadata(self, int i)#

Read the record batch with the given index along with its custom metadata

Parameters:

iint

The index of the record batch in the IPC file.

Returns:

batchRecordBatch

custom_metadataKeyValueMetadata

get_record_batch(self, int i)#

Read the record batch with the given index.

Parameters:

iint

The index of the record batch in the IPC file.

Returns:

batchRecordBatch

num_record_batches#

The number of record batches in the IPC file.

read_all(self)#

Read all record batches as a pyarrow.Table

read_pandas(self, **options)#

Read contents of stream to a pandas.DataFrame.

Read all record batches as a pyarrow.Table then convert it to a pandas.DataFrame using Table.to_pandas.

Parameters:

**options

Arguments to forward to Table.to_pandas().

Returns:

dfpandas.DataFrame

schema#

stats#

Current IPC read statistics.

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