


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									=				10_00

# 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									=				1_00
__lowerCAmelCase									=				1_00
__lowerCAmelCase									=				1_00

# 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									=				2_55

# Streaming
__lowerCAmelCase									=				20
__lowerCAmelCase									=				5

# Datasets without script
__lowerCAmelCase									=				2_00
__lowerCAmelCase									=				10
__lowerCAmelCase									=				2_00

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






class     __a     :
 def __init__(  self					)   ->							Tuple:




        '''simple docstring'''
        lowercase__:  str         =  []
        lowercase__:  Any         =  0
        lowercase__:  int         =  0
 def __str__(  self					)   ->							Any:




        '''simple docstring'''
        lowercase__:  str         =  '<' + str(self.entries					)[1:-1] + '>'
        return printed
 def 						SCREAMING_SNAKE_CASE__  (  self							,					lowerCAmelCase__					)   ->							List[str]:




        '''simple docstring'''
        self.entries.append(lowerCAmelCase__					)
        lowercase__:  List[str]         =  self.length + 1
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							str:




        '''simple docstring'''
        lowercase__:  Any         =  self.length - 1
        lowercase__:  Optional[int]         =  self.entries[self.front]
        # self.front-=1
        # self.entries = self.entries[self.front:]
        lowercase__:  int         =  self.entries[1:]
        return dequeued
 def 						SCREAMING_SNAKE_CASE__  (  self							,					lowerCAmelCase__					)   ->							List[str]:




        '''simple docstring'''
        for _ in range(lowerCAmelCase__					):
               self.put(self.get()					)
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Union[str, Any]:




        '''simple docstring'''
        return self.entries[0]
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Optional[int]:




        '''simple docstring'''
        return self.length


