




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






from __future__ import annotations





def 							lowerCamelCase    (							UpperCAmelCase_	:      list[int | float]      )->			int | float:

       """simple docstring"""




       if len(UpperCAmelCase_      ) == 0:
              raise ValueError("""find_min() arg is an empty sequence"""      )
       a			   =nums[0]
       for num in nums:
              a			   =min(UpperCAmelCase_   ,       UpperCAmelCase_      )
       return min_num


if __name__ == "__main__":
    import doctest

    doctest.testmod(verbose=True)
