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arrow::Type::typepyarrow._dataset_parquet.ParquetFileFragment.row_groups.__get__string.from_py.__pyx_convert_string_from_py_6libcpp_6string_std__in_stringpyarrow._dataset_parquet.ParquetFactoryOptions.partition_base_dir.__set__pyarrow._dataset_parquet.ParquetFileFragment.num_row_groups.__get__pyarrow._dataset_parquet.ParquetDatasetFactory.initpyarrow._dataset_parquet.ParquetFragmentScanOptions.initpyarrow._dataset_parquet.ParquetFileWriteOptions.initpyarrow._dataset_parquet.ParquetFileFragment.initpyarrow._dataset_parquet.ParquetFileFormat.initvector.to_py.__pyx_convert_vector_to_py_intpyarrow._dataset_parquet.ParquetFileFragment.__reduce__pyarrow._dataset_parquet.ParquetFragmentScanOptions.cache_options.__set__pyarrow._dataset_parquet.ParquetFragmentScanOptions.arrow_extensions_enabled.__get__pyarrow._dataset_parquet.ParquetFragmentScanOptions.arrow_extensions_enabled.__set__pyarrow._dataset_parquet.ParquetFragmentScanOptions.cache_options.__get__pyarrow._dataset_parquet.ParquetFragmentScanOptions.pre_buffer.__get__pyarrow._dataset_parquet.ParquetFragmentScanOptions.pre_buffer.__set__pyarrow._dataset_parquet.ParquetFragmentScanOptions.page_checksum_verification.__set__pyarrow._dataset_parquet.ParquetFragmentScanOptions.page_checksum_verification.__get__pyarrow._dataset_parquet.ParquetFragmentScanOptions.thrift_container_size_limit.__get__pyarrow._dataset_parquet.ParquetFragmentScanOptions.thrift_string_size_limit.__get__pyarrow._dataset_parquet.ParquetFragmentScanOptions.buffer_size.__get__pyarrow._dataset_parquet.ParquetFragmentScanOptions.use_buffered_stream.__set__pyarrow._dataset_parquet.ParquetFragmentScanOptions.use_buffered_stream.__get__pyarrow._dataset_parquet.ParquetFileFormat.__repr__pyarrow._dataset_parquet.ParquetReadOptions.__repr__pyarrow._dataset_parquet.ParquetReadOptions.dictionary_columns.__set__pyarrow._dataset_parquet.ParquetReadOptions.__init__pyarrow._dataset_parquet.ParquetFileFormat.equalspyarrow._dataset_parquet.ParquetReadOptions.__reduce_cython__argument 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NoneTypepyarrow._dataset_parquet.ParquetFragmentScanOptions._reconstructpyarrow._dataset_parquet.ParquetReadOptions.__eq__pyarrow._dataset_parquet.ParquetReadOptions.list_type.__set__pyarrow._dataset_parquet.ParquetReadOptions.coerce_int96_timestamp_unit.__set__pyarrow._dataset_parquet.ParquetReadOptions._coerce_int96_timestamp_unit.__set__pyarrow._dataset_parquet.ParquetReadOptions._binary_type.__set__pyarrow._dataset_parquet.ParquetReadOptions._list_type.__set__string.to_py.__pyx_convert_PyBytes_string_to_py_6libcpp_6string_std__in_stringpyarrow._dataset_parquet.ParquetFactoryOptions.partition_base_dir.__get__pyarrow._dataset_parquet.ParquetFactoryOptions.validate_column_chunk_paths.__set__pyarrow._dataset_parquet.ParquetFactoryOptions.__init__pyarrow._dataset_parquet.ParquetFileFormat.__reduce__pyarrow._dataset_parquet.ParquetFileWriteOptions.__repr__pyarrow._dataset_parquet.ParquetReadOptions._list_type.__get__pyarrow._dataset_parquet.ParquetReadOptions._binary_type.__get__pyarrow._dataset_parquet.ParquetReadOptions._coerce_int96_timestamp_unit.__get__pyarrow._dataset_parquet.ParquetReadOptions.coerce_int96_timestamp_unit.__get__pyarrow._dataset_parquet.ParquetReadOptions.list_type.__get__pyarrow._dataset_parquet.ParquetReadOptions.binary_type.__get__pyarrow._dataset_parquet.RowGroupInfo.__eq__pyarrow._dataset_parquet.RowGroupInfo.__repr__too many values to unpack (expected %zd)need more than %zd value%.1s to unpackpyarrow._dataset_parquet.RowGroupInfo.statisticspyarrow._dataset_parquet.RowGroupInfo.total_byte_sizepyarrow._dataset_parquet.RowGroupInfo.num_rowspyarrow._dataset_parquet.RowGroupInfo.__init__pyarrow._dataset_parquet.ParquetFileFormat.read_options.__get__free variable '%s' referenced before assignment in enclosing scopepyarrow._dataset_parquet.RowGroupInfo.statistics.name_statsinstance exception may not have a separate valueraise: exception class must be a subclass of BaseExceptioncalling %R should have returned an instance of BaseException, not %Rdictionary changed size during iterationset changed size during iterationpyarrow._dataset_parquet.ParquetFileWriteOptions.updatepyarrow._dataset_parquet.ParquetFragmentScanOptions.decryption_properties.__get__pyarrow._dataset_parquet.ParquetFragmentScanOptions.decryption_properties.__set__pyarrow._dataset_parquet.ParquetFragmentScanOptions.parquet_decryption_config.__get__pyarrow._dataset_parquet.ParquetFragmentScanOptions.parquet_decryption_config.__set__pyarrow._dataset_parquet.ParquetFileWriteOptions._set_encryption_configpyarrow._dataset_parquet.ParquetDatasetFactory.__setstate_cython__pyarrow._dataset_parquet.ParquetDatasetFactory.__reduce_cython__pyarrow._dataset_parquet.ParquetFactoryOptions.__setstate_cython__pyarrow._dataset_parquet.ParquetFactoryOptions.__reduce_cython__pyarrow._dataset_parquet.ParquetFileWriteOptions.__setstate_cython__pyarrow._dataset_parquet.ParquetFileWriteOptions.__reduce_cython__pyarrow._dataset_parquet.ParquetReadOptions.equalspyarrow._dataset_parquet.ParquetFileFormat.make_write_optionspyarrow._dataset_parquet.ParquetFragmentScanOptions.equalspyarrow._dataset_parquet.ParquetFragmentScanOptions.__reduce__pyarrow._dataset_parquet.ParquetFragmentScanOptions.thrift_container_size_limit.__set__'NoneType' object is not subscriptablehasattr(): attribute name must be stringpyarrow._dataset_parquet.__pyx_unpickle_ParquetReadOptions__set_statepyarrow._dataset_parquet.ParquetReadOptions.__setstate_cython____pyx_unpickle_ParquetReadOptionspyarrow._dataset_parquet.__pyx_unpickle_ParquetReadOptionspyarrow._dataset_parquet.ParquetFragmentScanOptions.buffer_size.__set__pyarrow._dataset_parquet.ParquetFragmentScanOptions.thrift_string_size_limit.__set__Unable to initialize pickling for %.200sModule '_dataset_parquet' has already been imported. Re-initialisation is not supported.compile time Python version %d.%d of module '%.100s' %s runtime version %d.%d%.200s does not export expected C variable %.200sC variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)struct __pyx_obj_7pyarrow_3lib_DataType *(enum  arrow::Type::type)PyObject *(enum  arrow::TimeUnit::type)enum  arrow::TimeUnit::type (PyObject *)std::shared_ptr< arrow::DataType>  (PyObject *)std::shared_ptr<parquet::WriterProperties>  (struct __pyx_opt_args_7pyarrow_8_parquet__create_writer_properties *__pyx_optional_args)std::shared_ptr<parquet::ArrowWriterProperties>  (struct __pyx_opt_args_7pyarrow_8_parquet__create_arrow_writer_properties *__pyx_optional_args)_create_arrow_writer_propertiesenum  arrow::Type::type (PyObject *)arrow::dataset::FileSource (PyObject *, struct __pyx_opt_args_7pyarrow_8_dataset__make_file_source *__pyx_optional_args)arrow::compute::Expression (struct __pyx_obj_7pyarrow_8_compute_Expression *, struct __pyx_obj_7pyarrow_3lib_Schema *)pyarrow._dataset_parquet.ParquetFileWriteOptions._set_arrow_propertiespyarrow._dataset_parquet.ParquetFileWriteOptions._set_propertiespyarrow._dataset_parquet.ParquetFileFragment.metadata.__get__pyarrow._dataset_parquet.ParquetFileFragment.ensure_complete_metadatapyarrow._dataset_parquet.ParquetFileFormat._set_default_fragment_scan_optionspyarrow._dataset_parquet.ParquetFileFormat._finish_writepyarrow._dataset_parquet.ParquetFragmentScanOptions.__init__pyarrow._dataset_parquet.ParquetReadOptions.binary_type.__set__pyarrow._dataset_parquet.ParquetFactoryOptions.partitioning.__set__pyarrow._dataset_parquet.ParquetFactoryOptions.partitioning_factory.__set__pyarrow._dataset_parquet.ParquetFactoryOptions.partitioning.__get__pyarrow._dataset_parquet.ParquetFactoryOptions.partitioning_factory.__get__pyarrow._dataset_parquet.ParquetFileFragment.split_by_row_grouppyarrow._dataset_parquet.ParquetDatasetFactory.__init__vector.from_py.__pyx_convert_vector_from_py_intpyarrow._dataset_parquet.ParquetFileFragment.subsetpyarrow._dataset_parquet.ParquetFileFormat.make_fragment'NoneType' object is not iterablepyarrow._dataset_parquet.ParquetFileFormat.__init___cython_3_1_3.cython_function_or_method_cython_3_1_3._common_types_metatypepyarrow._dataset_parquet.__pyx_scope_struct__statisticspyarrow._dataset_parquet.ParquetDatasetFactoryParquetDatasetFactory(metadata_path, FileSystem filesystem, FileFormat format, ParquetFactoryOptions options=None)

Create a ParquetDatasetFactory from a Parquet `_metadata` file.

Parameters
----------
metadata_path : str
    Path to the `_metadata` parquet metadata-only file generated with
    `pyarrow.parquet.write_metadata`.
filesystem : pyarrow.fs.FileSystem
    Filesystem to read the metadata_path from, and subsequent parquet
    files.
format : ParquetFileFormat
    Parquet format options.
options : ParquetFactoryOptions, optional
    Various flags influencing the discovery of filesystem paths.pyarrow._dataset_parquet.ParquetFactoryOptionsParquetFactoryOptions(partition_base_dir=None, partitioning=None, validate_column_chunk_paths=False)

Influences the discovery of parquet dataset.

Parameters
----------
partition_base_dir : str, optional
    For the purposes of applying the partitioning, paths will be
    stripped of the partition_base_dir. Files not matching the
    partition_base_dir prefix will be skipped for partitioning discovery.
    The ignored files will still be part of the Dataset, but will not
    have partition information.
partitioning : Partitioning, PartitioningFactory, optional
    The partitioning scheme applied to fragments, see ``Partitioning``.
validate_column_chunk_paths : bool, default False
    Assert that all ColumnChunk paths are consistent. The parquet spec
    allows for ColumnChunk data to be stored in multiple files, but
    ParquetDatasetFactory supports only a single file with all ColumnChunk
    data. If this flag is set construction of a ParquetDatasetFactory will
    raise an error if ColumnChunk data is not resident in a single file.Partitioning to apply to discovered files.

        NOTE: setting this property will overwrite partitioning_factory.
        PartitioningFactory to apply to discovered files and
        discover a Partitioning.

        NOTE: setting this property will overwrite partitioning.
        
        Base directory to strip paths before applying the partitioning.
        pyarrow._dataset_parquet.ParquetReadOptionsParquetReadOptions(dictionary_columns=None, coerce_int96_timestamp_unit=None, binary_type=None, list_type=None)

Parquet format specific options for reading.

Parameters
----------
dictionary_columns : list of string, default None
    Names of columns which should be dictionary encoded as
    they are read
coerce_int96_timestamp_unit : str, default None
    Cast timestamps that are stored in INT96 format to a particular
    resolution (e.g. 'ms'). Setting to None is equivalent to 'ns'
    and therefore INT96 timestamps will be inferred as timestamps
    in nanoseconds
binary_type : pyarrow.DataType, default None
    If given, Parquet binary columns will be read as this datatype.
    This setting is ignored if a serialized Arrow schema is found in
    the Parquet metadata.
list_type : subclass of pyarrow.DataType, default None
    If given, non-MAP repeated columns will be read as an instance of
    this datatype (either pyarrow.ListType or pyarrow.LargeListType).
    This setting is ignored if a serialized Arrow schema is found in
    the Parquet metadata._coerce_int96_timestamp_unit: 'TimeUnit'pyarrow._dataset_parquet.ParquetFileFragmentA Fragment representing a parquet file.
        Return the number of row groups viewed by this fragment (not the
        number of row groups in the origin file).
        pyarrow._dataset_parquet.ParquetFileFormatParquetFileFormat(read_options=None, default_fragment_scan_options=None, **kwargs)

FileFormat for Parquet

Parameters
----------
read_options : ParquetReadOptions
    Read options for the file.
default_fragment_scan_options : ParquetFragmentScanOptions
    Scan Options for the file.
**kwargs : dict
    Additional options for read option or scan optionpyarrow._dataset_parquet.ParquetFileWriteOptionspyarrow._dataset_parquet.ParquetFragmentScanOptionsParquetFragmentScanOptions(bool use_buffered_stream=False, *, buffer_size=8192, bool pre_buffer=True, cache_options=None, thrift_string_size_limit=None, thrift_container_size_limit=None, decryption_config=None, decryption_properties=None, bool page_checksum_verification=False, bool arrow_extensions_enabled=False)

Scan-specific options for Parquet fragments.

Parameters
----------
use_buffered_stream : bool, default False
    Read files through buffered input streams rather than loading entire
    row groups at once. This may be enabled to reduce memory overhead.
    Disabled by default.
buffer_size : int, default 8192
    Size of buffered stream, if enabled. Default is 8KB.
pre_buffer : bool, default True
    If enabled, pre-buffer the raw Parquet data instead of issuing one
    read per column chunk. This can improve performance on high-latency
    filesystems (e.g. S3, GCS) by coalescing and issuing file reads in
    parallel using a background I/O thread pool.
    Set to False if you want to prioritize minimal memory usage
    over maximum speed.
cache_options : pyarrow.CacheOptions, default None
    Cache options used when pre_buffer is enabled. The default values should
    be good for most use cases. You may want to adjust these for example if
    you have exceptionally high latency to the file system.
thrift_string_size_limit : int, default None
    If not None, override the maximum total string size allocated
    when decoding Thrift structures. The default limit should be
    sufficient for most Parquet files.
thrift_container_size_limit : int, default None
    If not None, override the maximum total size of containers allocated
    when decoding Thrift structures. The default limit should be
    sufficient for most Parquet files.
decryption_config : pyarrow.dataset.ParquetDecryptionConfig, default None
    If not None, use the provided ParquetDecryptionConfig to decrypt the
    Parquet file.
decryption_properties : pyarrow.parquet.FileDecryptionProperties, default None
    If not None, use the provided FileDecryptionProperties to decrypt encrypted
    Parquet file.
page_checksum_verification : bool, default False
    If True, verify the page checksum for each page read from the file.
arrow_extensions_enabled : bool, default False
    If True, read Parquet logical types as Arrow extension types where possible,
    (e.g., read JSON as the canonical `arrow.json` extension type or UUID as
    the canonical `arrow.uuid` extension type).Called Open() on an uninitialized FileSource4ýÿ\ýÿ~ýÿ ýÿÂýÿçýÿýÿ1ýÿVýÿ{ýÿ ýÿÔþÿÈþÿ¼þÿ°þÿ¤þÿ!þÿš"þÿx þÿð þÿ!þÿ»hþÿ°hþÿ¤hþÿ˜hþÿŒhþÿ´"ÿÿ¥"ÿÿ–"ÿÿ‡"ÿÿx"ÿÿçNÿÿÙNÿÿÊNÿÿ»Nÿÿ¬Nÿÿ__pyx_unpickle_ParquetReadOptions(__pyx_type, long __pyx_checksum, __pyx_state)ParquetDatasetFactory.__setstate_cython__(self, __pyx_state)ParquetDatasetFactory.__reduce_cython__(self)ParquetFactoryOptions.__setstate_cython__(self, __pyx_state)ParquetFactoryOptions.__reduce_cython__(self)ParquetFragmentScanOptions.__reduce__(self)ParquetFragmentScanOptions._reconstruct(kwargs)ParquetFragmentScanOptions.equals(self, ParquetFragmentScanOptions other)

Parameters
----------
other : pyarrow.dataset.ParquetFragmentScanOptions

Returns
-------
boolParquetFileWriteOptions.__setstate_cython__(self, __pyx_state)ParquetFileWriteOptions.__reduce_cython__(self)ParquetFileWriteOptions._set_encryption_config(self)ParquetFileWriteOptions._set_arrow_properties(self)ParquetFileWriteOptions._set_properties(self)ParquetFileWriteOptions.update(self, **kwargs)

Parameters
----------
**kwargs : dictParquetReadOptions.__setstate_cython__(self, __pyx_state)ParquetReadOptions.__reduce_cython__(self)ParquetReadOptions.equals(self, ParquetReadOptions other)

Parameters
----------
other : pyarrow.dataset.ParquetReadOptions

Returns
-------
boolParquetFileFragment.subset(self, Expression filter=None, Schema schema=None, row_group_ids=None)

Create a subset of the fragment (viewing a subset of the row groups).

Subset can be specified by either a filter predicate (with optional
schema) or by a list of row group IDs. Note that when using a filter,
the resulting fragment can be empty (viewing no row groups).

Parameters
----------
filter : Expression, default None
    Only include the row groups which satisfy this predicate (using
    the Parquet RowGroup statistics).
schema : Schema, default None
    Schema to use when filtering row groups. Defaults to the
    Fragment's physical schema
row_group_ids : list of ints
    The row group IDs to include in the subset. Can only be specified
    if `filter` is None.

Returns
-------
ParquetFileFragmentParquetFileFragment.split_by_row_group(self, Expression filter=None, Schema schema=None)

Split the fragment into multiple fragments.

Yield a Fragment wrapping each row group in this ParquetFileFragment.
Row groups will be excluded whose metadata contradicts the optional
filter.

Parameters
----------
filter : Expression, default None
    Only include the row groups which satisfy this predicate (using
    the Parquet RowGroup statistics).
schema : Schema, default None
    Schema to use when filtering row groups. Defaults to the
    Fragment's physical schema

Returns
-------
A list of FragmentsParquetFileFragment.ensure_complete_metadata(self)

Ensure that all metadata (statistics, physical schema, ...) have
been read and cached in this fragment.ParquetFileFragment.__reduce__(self)RowGroupInfo.__eq__(self, other)RowGroupInfo.__repr__(self)RowGroupInfo.statistics(self)RowGroupInfo.total_byte_size(self)RowGroupInfo.num_rows(self)RowGroupInfo.__init__(self, id, metadata, schema)ParquetFileFormat.make_fragment(self, file, filesystem=None, Expression partition_expression=None, row_groups=None, *, file_size=None)

Make a FileFragment from a given file.

Parameters
----------
file : file-like object, path-like or str
    The file or file path to make a fragment from.
filesystem : Filesystem, optional
    If `filesystem` is given, `file` must be a string and specifies
    the path of the file to read from the filesystem.
partition_expression : Expression, optional
    An expression that is guaranteed true for all rows in the fragment.  Allows
    fragment to be potentially skipped while scanning with a filter.
row_groups : Iterable, optional
    The indices of the row groups to include
file_size : int, optional
    The size of the file in bytes. Can improve performance with high-latency filesystems
    when file size needs to be known before reading.

Returns
-------
fragment : Fragment
    The file fragmentParquetFileFormat.__reduce__(self)ParquetFileFormat.equals(self, ParquetFileFormat other)

Parameters
----------
other : pyarrow.dataset.ParquetFileFormat

Returns
-------
boolParquetFileFormat.make_write_options(self, **kwargs)

Parameters
----------
**kwargs : dict

Returns
-------
pyarrow.dataset.FileWriteOptionsEncryption is not enabled in your installation of pyarrow, but a decryption_config was provided.Encryption is not enabled in your installation of pyarrow, but decryption_properties were provided.self.options cannot be converted to a Python object for picklingself.factory,self.parquet_factory,self.wrapped cannot be converted to a Python object for picklingself.c_options,self.parquet_options,self.wrapped cannot be converted to a Python object for picklingpyarrow._dataset_parquet_encryptionmake_write_options() should be called on an instance of ParquetFileFormatUnable to access encryption features. Encryption is not enabled in your installation of pyarrow.RowGroupInfo.statistics.<locals>.name_statsParquetReadOptions.__setstate_cython__ParquetReadOptions.__reduce_cython__ParquetFragmentScanOptions.equalsParquetFragmentScanOptions._reconstructParquetFragmentScanOptions.__reduce__ParquetFileWriteOptions._set_propertiesParquetFileWriteOptions._set_encryption_configParquetFileWriteOptions._set_arrow_propertiesParquetFileWriteOptions.__setstate_cython__ParquetFileWriteOptions.__reduce_cython__ParquetFileFragment.split_by_row_groupParquetFileFragment.ensure_complete_metadataParquetFileFormat.make_write_optionsParquetFactoryOptions.__setstate_cython__ParquetFactoryOptions.__reduce_cython__ParquetDatasetFactory.__setstate_cython__ParquetDatasetFactory.__reduce_cython__Note that Cython is deliberately stricter than PEP-484 and rejects subclasses of builtin types. If you need to pass subclasses then set the 'annotation_typing' directive to False.Need to specify one of 'filter' or 'row_group_ids'Incompatible checksums (0x%x vs (0x85ac265, 0xf36e86f, 0x6a6734d) = (_binary_type, _coerce_int96_timestamp_unit, _list_type, dictionary_columns))If `default_fragment_scan_options` is given, cannot specify Encryption is not enabled in your installation of pyarrow, but an encryption_config was provided.Dataset support for Parquet file format.Cannot specify both 'filter' and 'row_group_ids'.€AØ.¨d°!àÐ!Ð!:¸!ؘ|¨1¨AؘL¨
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