
import importlib
import os

import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry

from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem

from .utils import require_lza, require_zstandard



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					assert "mock" in _fsspec_registry
					assert "bz2" in _fsspec_registry



def 	UpperCamelCase   (							):
					'''simple docstring'''
					assert "mock" not in _fsspec_registry
					assert "bz2" in _fsspec_registry



def 	UpperCamelCase   (							):
					'''simple docstring'''
					lowercase						     =						'''mock-s3-bucket'''
					lowercase						     =						f's3://{mock_bucket}'
					lowercase						     =						extract_path_from_uri(lowerCAmelCase__		)
					assert dataset_path.startswith('''s3://'''		) is False

					lowercase						     =						'''./local/path'''
					lowercase						     =						extract_path_from_uri(lowerCAmelCase__		)
					assert dataset_path == new_dataset_path



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						is_remote_filesystem(lowerCAmelCase__		)
					assert is_remote is True

					lowercase						     =						fsspec.filesystem('''file'''		)

					lowercase						     =						is_remote_filesystem(lowerCAmelCase__		)
					assert is_remote is False



@pytest.mark.parametrize('''compression_fs_class'''			,      lowerCAmelCase__		)
def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						{'''gzip''': gz_file, '''xz''': xz_file, '''zstd''': zstd_file, '''bz2''': bza_file, '''lz4''': lza_file}
					lowercase						     =						input_paths[compression_fs_class.protocol]
					if input_path is None:
										lowercase						     =						f'for \'{compression_fs_class.protocol}\' compression protocol, '
										if compression_fs_class.protocol == "lz4":
															reason += require_lza.kwargs["reason"]
										elif compression_fs_class.protocol == "zstd":
															reason += require_zstandard.kwargs["reason"]
										pytest.skip(lowerCAmelCase__		)
					lowercase						     =						fsspec.filesystem(compression_fs_class.protocol			,      fo=lowerCAmelCase__		)
					assert isinstance(lowerCAmelCase__			,      lowerCAmelCase__		)
					lowercase						     =						os.path.basename(lowerCAmelCase__		)
					lowercase						     =						expected_filename[: expected_filename.rindex('''.'''		)]
					assert fs.glob('''*'''		) == [expected_filename]
					with fs.open(lowerCAmelCase__			,      '''r'''			,      encoding='''utf-8'''		) as f, open(lowerCAmelCase__			,      encoding='''utf-8'''		) as expected_file:
										assert f.read() == expected_file.read()



@pytest.mark.parametrize('''protocol'''			,      ['''zip''', '''gzip''']		)
def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						{'''zip''': zip_jsonl_path, '''gzip''': jsonl_gz_path}
					lowercase						     =						compressed_file_paths[protocol]
					lowercase						     =						'''dataset.jsonl'''
					lowercase						     =						f'{protocol}://{member_file_path}::{compressed_file_path}'
					lowercase     ,						*lowercase						     =						fsspec.get_fs_token_paths(lowerCAmelCase__		)
					assert fs.isfile(lowerCAmelCase__		)
					assert not fs.isfile('''non_existing_''' + member_file_path		)



@pytest.mark.integration
def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						hf_api.dataset_info(lowerCAmelCase__			,      token=lowerCAmelCase__		)
					lowercase						     =						HfFileSystem(repo_info=lowerCAmelCase__			,      token=lowerCAmelCase__		)
					assert sorted(hffs.glob('''*'''		)		) == [".gitattributes", "data"]
					assert hffs.isdir('''data'''		)
					assert hffs.isfile('''.gitattributes'''		) and hffs.isfile('''data/text_data.txt'''		)
					with open(lowerCAmelCase__		) as f:
										assert hffs.open('''data/text_data.txt'''			,      '''r'''		).read() == f.read()



def 	UpperCamelCase   (							):
					'''simple docstring'''
					lowercase						     =						'''bz2'''

					# Import module
					import datasets.filesystems

					# Overwrite protocol and reload
					register_implementation(lowerCAmelCase__			,      lowerCAmelCase__			,      clobber=lowerCAmelCase__		)
					with pytest.warns(lowerCAmelCase__		) as warning_info:
										importlib.reload(datasets.filesystems		)

					assert len(lowerCAmelCase__		) == 1
					assert (
					    str(warning_info[0].message		)
					    == f'A filesystem protocol was already set for {protocol} and will be overwritten.'
					)






import os
from typing import BinaryIO, Optional, Union

import numpy as np
import pyarrow.parquet as pq

from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_MODULES
from ..packaged_modules.parquet.parquet import Parquet
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						np.inf

					def set_batch_size(lowerCAmelCase__		) -> None:
										nonlocal batch_size
										if isinstance(lowerCAmelCase__			,      lowerCAmelCase__		):
															lowercase						     =						min(lowerCAmelCase__			,      config.PARQUET_ROW_GROUP_SIZE_FOR_IMAGE_DATASETS		)
										elif isinstance(lowerCAmelCase__			,      lowerCAmelCase__		):
															lowercase						     =						min(lowerCAmelCase__			,      config.PARQUET_ROW_GROUP_SIZE_FOR_AUDIO_DATASETS		)
										elif isinstance(lowerCAmelCase__			,      lowerCAmelCase__		) and feature.dtype == "binary":
															lowercase						     =						min(lowerCAmelCase__			,      config.PARQUET_ROW_GROUP_SIZE_FOR_BINARY_DATASETS		)

					_visit(lowerCAmelCase__			,      lowerCAmelCase__		)

					return None if batch_size is np.inf else batch_size







class     lowercase		( SCREAMING_SNAKE_CASE__		):




							def __init__(    self       ,A__       ,A__ = None       ,A__ = None       ,A__ = None       ,A__ = False       ,A__ = False       ,A__ = None       ,**A__       ,):
												super().__init__(
												    A__       ,split=A__       ,features=A__       ,cache_dir=A__       ,keep_in_memory=A__       ,streaming=A__       ,num_proc=A__       ,**A__       ,)
												lowercase						     =						path_or_paths if isinstance(A__       ,A__) else {self.split: path_or_paths}
												lowercase						     =						_PACKAGED_DATASETS_MODULES['''parquet'''][1]
												lowercase						     =						Parquet(
												    cache_dir=A__       ,data_files=A__       ,features=A__       ,hash=A__       ,**A__       ,)





							def 			A__				(    self):
												# Build iterable dataset
												if self.streaming:
																	lowercase						     =						self.builder.as_streaming_dataset(split=self.split)
												# Build regular (map-style) dataset
												else:
																	lowercase						     =						None
																	lowercase						     =						None
																	lowercase						     =						None
																	lowercase						     =						None

																	self.builder.download_and_prepare(
																	    download_config=A__       ,download_mode=A__       ,verification_mode=A__       ,base_path=A__       ,num_proc=self.num_proc       ,)
																	lowercase						     =						self.builder.as_dataset(
																	    split=self.split       ,verification_mode=A__       ,in_memory=self.keep_in_memory)
												return dataset







class     lowercase		:




							def __init__(    self       ,A__       ,A__       ,A__ = None       ,**A__       ,):
												lowercase						     =						dataset
												lowercase						     =						path_or_buf
												lowercase						     =						batch_size or get_writer_batch_size(dataset.features)
												lowercase						     =						parquet_writer_kwargs




							def 			A__				(    self):
												lowercase						     =						self.batch_size if self.batch_size else config.DEFAULT_MAX_BATCH_SIZE

												if isinstance(self.path_or_buf       ,(str, bytes, os.PathLike)):
																	with open(self.path_or_buf       ,'''wb+''') as buffer:
																						lowercase						     =						self._write(file_obj=A__       ,batch_size=A__       ,**self.parquet_writer_kwargs)
												else:
																	lowercase						     =						self._write(file_obj=self.path_or_buf       ,batch_size=A__       ,**self.parquet_writer_kwargs)
												return written





							def 			A__				(    self       ,A__       ,A__       ,**A__):
												lowercase						     =						0
												lowercase						     =						parquet_writer_kwargs.pop('''path_or_buf'''       ,A__)
												lowercase						     =						self.dataset.features.arrow_schema

												lowercase						     =						pq.ParquetWriter(A__       ,schema=A__       ,**A__)

												for offset in logging.tqdm(
												    range(0       ,len(self.dataset)       ,A__)       ,unit='''ba'''       ,disable=not logging.is_progress_bar_enabled()       ,desc='''Creating parquet from Arrow format'''       ,):
																	lowercase						     =						query_table(
																	    table=self.dataset._data       ,key=slice(A__       ,offset + batch_size)       ,indices=self.dataset._indices if self.dataset._indices is not None else None       ,)
																	writer.write_table(A__)
																	written += batch.nbytes
												writer.close()
												return written




