






'''simple docstring'''
import importlib
import os
import platform
from pathlib import Path

from packaging import version

from .utils.logging import get_logger


__lowerCAmelCase							=get_logger(__name__)

# Datasets
__lowerCAmelCase							="https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets"
__lowerCAmelCase							="https://cdn-datasets.huggingface.co/datasets/datasets"
__lowerCAmelCase							="https://raw.githubusercontent.com/huggingface/datasets/{revision}/datasets/{path}/{name}"

# Metrics
__lowerCAmelCase							="https://s3.amazonaws.com/datasets.huggingface.co/datasets/metrics"
__lowerCAmelCase							="https://cdn-datasets.huggingface.co/datasets/metric"
__lowerCAmelCase							="https://raw.githubusercontent.com/huggingface/datasets/{revision}/metrics/{path}/{name}"

# Hub
__lowerCAmelCase							=os.environ.get("HF_ENDPOINT", "https://huggingface.co")
__lowerCAmelCase							=HF_ENDPOINT + "/datasets/{repo_id}/resolve/{revision}/{path}"
__lowerCAmelCase							="main"

__lowerCAmelCase							=version.parse(platform.python_version())

if PY_VERSION < version.parse("3.8"):
						import importlib_metadata
else:
						import importlib.metadata as importlib_metadata

# General environment variables accepted values for booleans
__lowerCAmelCase							={"1", "ON", "YES", "TRUE"}
__lowerCAmelCase							=ENV_VARS_TRUE_VALUES.union({"AUTO"})


# Imports
__lowerCAmelCase							=version.parse(importlib_metadata.version("dill"))
__lowerCAmelCase							=version.parse(importlib_metadata.version("pandas"))
__lowerCAmelCase							=version.parse(importlib_metadata.version("pyarrow"))

__lowerCAmelCase							=os.environ.get("USE_TF", "AUTO").upper()
__lowerCAmelCase							=os.environ.get("USE_TORCH", "AUTO").upper()
__lowerCAmelCase							=os.environ.get("USE_JAX", "AUTO").upper()

__lowerCAmelCase							="N/A"
__lowerCAmelCase							=False

if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
						__lowerCAmelCase							=importlib.util.find_spec("torch") is not None
						if TORCH_AVAILABLE:
												try:
																		__lowerCAmelCase							=version.parse(importlib_metadata.version("torch"))
																		logger.info(f'''PyTorch version {TORCH_VERSION} available.''')
												except importlib_metadata.PackageNotFoundError:
																		pass
else:
						logger.info("Disabling PyTorch because USE_TF is set")

__lowerCAmelCase							="N/A"
__lowerCAmelCase							=False

if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VALUES:
						__lowerCAmelCase							=importlib.util.find_spec("tensorflow") is not None
						if TF_AVAILABLE:
												# For the metadata, we have to look for both tensorflow and tensorflow-cpu
												for package in [
												    "tensorflow",
												    "tensorflow-cpu",
												    "tensorflow-gpu",
												    "tf-nightly",
												    "tf-nightly-cpu",
												    "tf-nightly-gpu",
												    "intel-tensorflow",
												    "tensorflow-rocm",
												    "tensorflow-macos",
												]:
																		try:
																								__lowerCAmelCase							=version.parse(importlib_metadata.version(package))
																		except importlib_metadata.PackageNotFoundError:
																								continue
																		else:
																								break
												else:
																		__lowerCAmelCase							=False
						if TF_AVAILABLE:
												if TF_VERSION.major < 2:
																		logger.info(f'''TensorFlow found but with version {TF_VERSION}. `datasets` requires version 2 minimum.''')
																		__lowerCAmelCase							=False
												else:
																		logger.info(f'''TensorFlow version {TF_VERSION} available.''')
else:
						logger.info("Disabling Tensorflow because USE_TORCH is set")


__lowerCAmelCase							="N/A"
__lowerCAmelCase							=False

if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES:
						__lowerCAmelCase							=importlib.util.find_spec("jax") is not None and importlib.util.find_spec("jaxlib") is not None
						if JAX_AVAILABLE:
												try:
																		__lowerCAmelCase							=version.parse(importlib_metadata.version("jax"))
																		logger.info(f'''JAX version {JAX_VERSION} available.''')
												except importlib_metadata.PackageNotFoundError:
																		pass
else:
						logger.info("Disabling JAX because USE_JAX is set to False")


__lowerCAmelCase							=os.environ.get("USE_BEAM", "AUTO").upper()
__lowerCAmelCase							="N/A"
__lowerCAmelCase							=False
if USE_BEAM in ENV_VARS_TRUE_AND_AUTO_VALUES:
						try:
												__lowerCAmelCase							=version.parse(importlib_metadata.version("apache_beam"))
												__lowerCAmelCase							=True
												logger.info(f'''Apache Beam version {BEAM_VERSION} available.''')
						except importlib_metadata.PackageNotFoundError:
												pass
else:
						logger.info("Disabling Apache Beam because USE_BEAM is set to False")


# Optional tools for data loading
__lowerCAmelCase							=importlib.util.find_spec("sqlalchemy") is not None

# Optional tools for feature decoding
__lowerCAmelCase							=importlib.util.find_spec("PIL") is not None
__lowerCAmelCase							=importlib.util.find_spec("soundfile") is not None and version.parse(
    importlib.import_module("soundfile").__libsndfile_version__
) >= version.parse("1.0.31")
__lowerCAmelCase							=importlib.util.find_spec("soundfile") is not None and version.parse(
    importlib.import_module("soundfile").__libsndfile_version__
) >= version.parse("1.1.0")

# Optional compression tools
__lowerCAmelCase							=importlib.util.find_spec("rarfile") is not None
__lowerCAmelCase							=importlib.util.find_spec("zstandard") is not None
__lowerCAmelCase							=importlib.util.find_spec("lz4") is not None
__lowerCAmelCase							=importlib.util.find_spec("py7zr") is not None


# Cache location
__lowerCAmelCase							="~/.cache"
__lowerCAmelCase							=os.getenv("XDG_CACHE_HOME", DEFAULT_XDG_CACHE_HOME)
__lowerCAmelCase							=os.path.join(XDG_CACHE_HOME, "huggingface")
__lowerCAmelCase							=os.path.expanduser(os.getenv("HF_HOME", DEFAULT_HF_CACHE_HOME))

__lowerCAmelCase							=os.path.join(HF_CACHE_HOME, "datasets")
__lowerCAmelCase							=Path(os.getenv("HF_DATASETS_CACHE", DEFAULT_HF_DATASETS_CACHE))

__lowerCAmelCase							=os.path.join(HF_CACHE_HOME, "metrics")
__lowerCAmelCase							=Path(os.getenv("HF_METRICS_CACHE", DEFAULT_HF_METRICS_CACHE))

__lowerCAmelCase							=os.path.join(HF_CACHE_HOME, "modules")
__lowerCAmelCase							=Path(os.getenv("HF_MODULES_CACHE", DEFAULT_HF_MODULES_CACHE))

__lowerCAmelCase							="downloads"
__lowerCAmelCase							=os.path.join(HF_DATASETS_CACHE, DOWNLOADED_DATASETS_DIR)
__lowerCAmelCase							=Path(os.getenv("HF_DATASETS_DOWNLOADED_DATASETS_PATH", DEFAULT_DOWNLOADED_DATASETS_PATH))

__lowerCAmelCase							="extracted"
__lowerCAmelCase							=os.path.join(DEFAULT_DOWNLOADED_DATASETS_PATH, EXTRACTED_DATASETS_DIR)
__lowerCAmelCase							=Path(os.getenv("HF_DATASETS_EXTRACTED_DATASETS_PATH", DEFAULT_EXTRACTED_DATASETS_PATH))

# Download count for the website
__lowerCAmelCase							=(
    os.environ.get("HF_UPDATE_DOWNLOAD_COUNTS", "AUTO").upper() in ENV_VARS_TRUE_AND_AUTO_VALUES
)

# Batch size constants. For more info, see:
# https://github.com/apache/arrow/blob/master/docs/source/cpp/arrays.rst#size-limitations-and-recommendations)
__lowerCAmelCase							=1000

# Size of the preloaded record batch in `Dataset.__iter__`
__lowerCAmelCase							=10

# Pickling tables works only for small tables (<4GiB)
# For big tables, we write them on disk instead
__lowerCAmelCase							=4 << 30

# Max shard size in bytes (e.g. to shard parquet datasets in push_to_hub or download_and_prepare)
__lowerCAmelCase							="500MB"

# Parquet configuration
__lowerCAmelCase							=100
__lowerCAmelCase							=100
__lowerCAmelCase							=100

# Offline mode
__lowerCAmelCase							=os.environ.get("HF_DATASETS_OFFLINE", "AUTO").upper() in ENV_VARS_TRUE_VALUES

# In-memory
__lowerCAmelCase							=0  # Disabled
__lowerCAmelCase							=float(os.environ.get("HF_DATASETS_IN_MEMORY_MAX_SIZE", DEFAULT_IN_MEMORY_MAX_SIZE))

# File names
__lowerCAmelCase							="dataset.arrow"
__lowerCAmelCase							="indices.arrow"
__lowerCAmelCase							="state.json"
__lowerCAmelCase							="dataset_info.json"
__lowerCAmelCase							="dataset_infos.json"
__lowerCAmelCase							="LICENSE"
__lowerCAmelCase							="metric_info.json"
__lowerCAmelCase							="dataset_dict.json"

__lowerCAmelCase							="datasets_modules"

__lowerCAmelCase							=255

# Streaming
__lowerCAmelCase							=20
__lowerCAmelCase							=5

# Datasets without script
__lowerCAmelCase							=200
__lowerCAmelCase							=10
__lowerCAmelCase							=200

# Progress bars
__lowerCAmelCase							=0.05  # 20 progress updates per sec









'''simple docstring'''
class    _snake_case   :

					"""simple docstring"""





					def __init__(     self   , UpperCAmelCase__     )      ->	None:
										a_									=   data
										a_									=   42
										a_									=   42



def 							a	(   _UpperCAmelCase )				->				None:






					"""simple docstring"""







					a_									=   0
					a_									=   x

def 							a	(   _UpperCAmelCase					,  _UpperCAmelCase )				->				None:






					"""simple docstring"""







					a_							,					a_									=   find_set(_UpperCAmelCase ), find_set(_UpperCAmelCase )
					if x == y:
										return

					elif x.rank > y.rank:
										a_									=   x
					else:
										a_									=   y
										if x.rank == y.rank:
															y.rank += 1

def 							a	(   _UpperCAmelCase )				->				Node:






					"""simple docstring"""







					if x != x.parent:
										a_									=   find_set(x.parent )
					return x.parent

def 							a	(   _UpperCAmelCase )				->				set:






					"""simple docstring"""







					a_									=   ({0, 1, 2}, {3, 4, 5})
					for s in sets:
										if node.data in s:
															return s
					a_									=   F'''{node.data} is not in {sets}'''
					raise ValueError(_UpperCAmelCase )

def 							a	(   )				->				None:






					"""simple docstring"""







					a_									=   [Node(_UpperCAmelCase ) for i in range(6 )]
					for v in vertex:
										make_set(_UpperCAmelCase )

					union_set(vertex[0]					,  vertex[1] )
					union_set(vertex[1]					,  vertex[2] )
					union_set(vertex[3]					,  vertex[4] )
					union_set(vertex[3]					,  vertex[5] )

					for nodea in vertex:
										for nodea in vertex:
															if find_python_set(_UpperCAmelCase ).isdisjoint(find_python_set(_UpperCAmelCase ) ):
																				assert find_set(_UpperCAmelCase ) != find_set(_UpperCAmelCase )
															else:
																				assert find_set(_UpperCAmelCase ) == find_set(_UpperCAmelCase )


if __name__ == "__main__":
						test_disjoint_set()

