def __init__(self,
min_bundle_size=0,
desired_bundle_size=DEFAULT_DESIRED_BUNDLE_SIZE,
use_fastavro=_use_fastavro(),
label='ReadAllFiles'):
"""Initializes ``ReadAllFromAvro``.
Args:
min_bundle_size: the minimum size in bytes, to be considered when
splitting the input into bundles.
desired_bundle_size: the desired size in bytes, to be considered when
splitting the input into bundles.
"""
if sys.version_info[0] >= 3 and not use_fastavro:
warnings.warn(
"Due to a known issue in avro-python3 package, it is "
"recommended to use fastavro with Beam Avro IO on "
"Python 3 until BEAM-6522 is addressed.")
source_from_file = partial(_create_avro_source,
min_bundle_size=min_bundle_size,
use_fastavro=use_fastavro)
self._read_all_files = filebasedsource.ReadAllFiles(
True, CompressionTypes.AUTO, desired_bundle_size, min_bundle_size,
source_from_file)
self.label = label
def __init__(self,
min_bundle_size=0,
desired_bundle_size=DEFAULT_DESIRED_BUNDLE_SIZE,
use_fastavro=True,
with_filename=False,
label='ReadAllFiles'):
"""Initializes ``ReadAllFromAvro``.
Args:
min_bundle_size: the minimum size in bytes, to be considered when
splitting the input into bundles.
desired_bundle_size: the desired size in bytes, to be considered when
splitting the input into bundles.
use_fastavro (bool); when set, use the `fastavro` library for IO, which
is significantly faster, and is now the default.
with_filename: If True, returns a Key Value with the key being the file
name and the value being the actual data. If False, it only returns
the data.
"""
source_from_file = partial(_create_avro_source,
min_bundle_size=min_bundle_size,
use_fastavro=use_fastavro)
self._read_all_files = filebasedsource.ReadAllFiles(
True, CompressionTypes.AUTO, desired_bundle_size, min_bundle_size,
source_from_file, with_filename)
self.label = label
def __init__(
self,
representative_header_lines=None, # type: List[str]
desired_bundle_size=DEFAULT_DESIRED_BUNDLE_SIZE, # type: int
compression_type=CompressionTypes.AUTO, # type: str
allow_malformed_records=False, # type: bool
pre_infer_headers=False, # type: bool
sample_name_encoding=SampleNameEncoding.
WITHOUT_FILE_PATH, # type: int
use_1_based_coordinate=False, # type: bool
move_hom_ref_calls=False, # type: bool
**kwargs # type: **str
):
# type: (...) -> None
"""Initialize the :class:`ReadAllFromVcf` transform.
Args:
representative_header_lines: Header definitions to be used for parsing VCF
files. If supplied, header definitions in VCF files are ignored.
desired_bundle_size: Desired size of bundles that should be generated when
splitting this source into bundles. See
:class:`~apache_beam.io.filebasedsource.FileBasedSource` for more
details.
compression_type: Used to handle compressed input files.
Typical value is :attr:`CompressionTypes.AUTO
<apache_beam.io.filesystem.CompressionTypes.AUTO>`, in which case the
underlying file_path's extension will be used to detect the compression.
allow_malformed_records: If true, malformed records from VCF files will be
returned as :class:`MalformedVcfRecord` instead of failing the pipeline.
pre_infer_headers: If true, drop headers and make sure PySam return the
exact data for variants and calls, without type matching.
sample_name_encoding: specify how we want to encode sample_name mainly
to deal with same sample_name used across multiple VCF files.
use_1_based_coordinate: specify whether the coordinates should be stored
in BQ using 0-based exclusive (default) or 1-based inclusive coordinate.
move_hom_ref_calls: If true, filter out 0 GT data out of call list and add
the call name to a hom_ref_calls column.
"""
super().__init__(**kwargs)
source_from_file = partial(
_create_vcf_source,
representative_header_lines=representative_header_lines,
compression_type=compression_type,
allow_malformed_records=allow_malformed_records,
pre_infer_headers=pre_infer_headers,
sample_name_encoding=sample_name_encoding,
use_1_based_coordinate=use_1_based_coordinate,
move_hom_ref_calls=move_hom_ref_calls)
self._read_all_files = filebasedsource.ReadAllFiles(
True, # splittable
CompressionTypes.AUTO,
desired_bundle_size,
0, # min_bundle_size
source_from_file)
def __init__(self, min_bundle_size=0,
desired_bundle_size=DEFAULT_DESIRED_BUNDLE_SIZE):
"""Initializes ``ReadAllFromAvro``.
Args:
min_bundle_size: the minimum size in bytes, to be considered when
splitting the input into bundles.
desired_bundle_size: the desired size in bytes, to be considered when
splitting the input into bundles.
"""
source_from_file = partial(
_create_avro_source, min_bundle_size=min_bundle_size)
self._read_all_files = filebasedsource.ReadAllFiles(
True, CompressionTypes.AUTO, desired_bundle_size, min_bundle_size,
source_from_file)
