pyarrow.RecordBatchReader#

class pyarrow.RecordBatchReader#

Bases: _Weakrefable

Base class for reading stream of record batches.

Record batch readers function as iterators of record batches that also provide the schema (without the need to get any batches).

Warning

Do not call this class’s constructor directly, use one of the RecordBatchReader.from_* functions instead.

Notes

To import and export using the Arrow C stream interface, use the _import_from_c and _export_to_c methods. However, keep in mind this interface is intended for expert users.

Examples

>>> import pyarrow as pa
>>> schema = pa.schema([('x', pa.int64())])
>>> def iter_record_batches():
...     for i in range(2):
...         yield pa.RecordBatch.from_arrays([pa.array([1, 2, 3])], schema=schema)
>>> reader = pa.RecordBatchReader.from_batches(schema, iter_record_batches())
>>> print(reader.schema)
x: int64
>>> for batch in reader:
...     print(batch)
pyarrow.RecordBatch
x: int64
----
x: [1,2,3]
pyarrow.RecordBatch
x: int64
----
x: [1,2,3]

__init__(*args, **kwargs)#

Methods

`__init__`(args, *kwargs)
`cast`(self, target_schema)	Wrap this reader with one that casts each batch lazily as it is pulled.
`close`(self)	Release any resources associated with the reader.
`from_batches`(Schema schema, batches)	Create RecordBatchReader from an iterable of batches.
`from_stream`(data[, schema])	Create RecordBatchReader from a Arrow-compatible stream object.
`iter_batches_with_custom_metadata`(self)	Iterate over record batches from the stream along with their custom metadata.
`read_all`(self)	Read all record batches as a pyarrow.Table.
`read_next_batch`(self)	Read next RecordBatch from the stream.
`read_next_batch_with_custom_metadata`(self)	Read next RecordBatch from the stream along with its custom metadata.
`read_pandas`(self, **options)	Read contents of stream to a pandas.DataFrame.

Attributes

schema

Shared schema of the record batches in the stream.

cast(self, target_schema)#

Wrap this reader with one that casts each batch lazily as it is pulled. Currently only a safe cast to target_schema is implemented.

Parameters:

target_schemaSchema: Schema to cast to, the names and order of fields must match.

Returns:

RecordBatchReader

close(self)#: Release any resources associated with the reader.

static from_batches(Schema schema, batches)#

Create RecordBatchReader from an iterable of batches.

Parameters:

schemaSchema: The shared schema of the record batches
batchesIterable[RecordBatch]: The batches that this reader will return.

Returns:

readerRecordBatchReader

static from_stream(data, schema=None)#

Create RecordBatchReader from a Arrow-compatible stream object.

This accepts objects implementing the Arrow PyCapsule Protocol for streams, i.e. objects that have a __arrow_c_stream__ method.

Parameters:

dataArrow-compatible stream object: Any object that implements the Arrow PyCapsule Protocol for streams.
schemaSchema, default None: The schema to which the stream should be casted, if supported by the stream object.

Returns:

RecordBatchReader

iter_batches_with_custom_metadata(self)#

Iterate over record batches from the stream along with their custom metadata.

Yields:

RecordBatchWithMetadata

read_all(self)#

Read all record batches as a pyarrow.Table.

Returns:

Table

read_next_batch(self)#