




'''simple docstring'''



import importlib
import os
import platform
from pathlib import Path

from packaging import version

from .utils.logging import get_logger


UpperCAmelCase_       :  Dict      =		get_logger(__name__)

# Datasets
UpperCAmelCase_       :  Optional[Any]      =		"https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets"
UpperCAmelCase_       :  Optional[int]      =		"https://cdn-datasets.huggingface.co/datasets/datasets"
UpperCAmelCase_       :  Tuple      =		"https://raw.githubusercontent.com/huggingface/datasets/{revision}/datasets/{path}/{name}"

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

# Hub
UpperCAmelCase_       :  Any      =		os.environ.get('''HF_ENDPOINT''', '''https://huggingface.co''')
UpperCAmelCase_       :  Any      =		HF_ENDPOINT + "/datasets/{repo_id}/resolve/{revision}/{path}"
UpperCAmelCase_       :  List[str]      =		"main"

UpperCAmelCase_       :  Optional[Any]      =		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
UpperCAmelCase_       :  Dict      =		{"1", "ON", "YES", "TRUE"}
UpperCAmelCase_       :  Dict      =		ENV_VARS_TRUE_VALUES.union({'''AUTO'''})


# Imports
UpperCAmelCase_       :  Union[str, Any]      =		version.parse(importlib_metadata.version('''dill'''))
UpperCAmelCase_       :  List[str]      =		version.parse(importlib_metadata.version('''pandas'''))
UpperCAmelCase_       :  str      =		version.parse(importlib_metadata.version('''pyarrow'''))

UpperCAmelCase_       :  Tuple      =		os.environ.get('''USE_TF''', '''AUTO''').upper()
UpperCAmelCase_       :  Optional[Any]      =		os.environ.get('''USE_TORCH''', '''AUTO''').upper()
UpperCAmelCase_       :  Any      =		os.environ.get('''USE_JAX''', '''AUTO''').upper()

UpperCAmelCase_       :  int      =		"N/A"
UpperCAmelCase_       :  Union[str, Any]      =		False

if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
     UpperCAmelCase_       :  str      =		importlib.util.find_spec('''torch''') is not None
     if TORCH_AVAILABLE:
          try:
               UpperCAmelCase_       :  Dict      =		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''')

UpperCAmelCase_       :  Optional[int]      =		"N/A"
UpperCAmelCase_       :  Any      =		False

if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VALUES:
     UpperCAmelCase_       :  Optional[Any]      =		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:
                    UpperCAmelCase_       :  Optional[Any]      =		version.parse(importlib_metadata.version(package))
               except importlib_metadata.PackageNotFoundError:
                    continue
               else:
                    break
          else:
               UpperCAmelCase_       :  int      =		False
     if TF_AVAILABLE:
          if TF_VERSION.major < 2:
               logger.info(F"""TensorFlow found but with version {TF_VERSION}. `datasets` requires version 2 minimum.""")
               UpperCAmelCase_       :  Any      =		False
          else:
               logger.info(F"""TensorFlow version {TF_VERSION} available.""")
else:
     logger.info('''Disabling Tensorflow because USE_TORCH is set''')


UpperCAmelCase_       :  int      =		"N/A"
UpperCAmelCase_       :  Optional[Any]      =		False

if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES:
     UpperCAmelCase_       :  List[Any]      =		importlib.util.find_spec('''jax''') is not None and importlib.util.find_spec('''jaxlib''') is not None
     if JAX_AVAILABLE:
          try:
               UpperCAmelCase_       :  Optional[Any]      =		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''')


UpperCAmelCase_       :  int      =		os.environ.get('''USE_BEAM''', '''AUTO''').upper()
UpperCAmelCase_       :  List[str]      =		"N/A"
UpperCAmelCase_       :  List[Any]      =		False
if USE_BEAM in ENV_VARS_TRUE_AND_AUTO_VALUES:
     try:
          UpperCAmelCase_       :  Dict      =		version.parse(importlib_metadata.version('''apache_beam'''))
          UpperCAmelCase_       :  Optional[Any]      =		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
UpperCAmelCase_       :  List[str]      =		importlib.util.find_spec('''sqlalchemy''') is not None

# Optional tools for feature decoding
UpperCAmelCase_       :  int      =		importlib.util.find_spec('''PIL''') is not None
UpperCAmelCase_       :  Any      =		importlib.util.find_spec('''soundfile''') is not None and version.parse(
    importlib.import_module('''soundfile''').__libsndfile_version__
) >= version.parse('''1.0.31''')
UpperCAmelCase_       :  Tuple      =		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
UpperCAmelCase_       :  Dict      =		importlib.util.find_spec('''rarfile''') is not None
UpperCAmelCase_       :  Dict      =		importlib.util.find_spec('''zstandard''') is not None
UpperCAmelCase_       :  Optional[Any]      =		importlib.util.find_spec('''lz4''') is not None
UpperCAmelCase_       :  Optional[Any]      =		importlib.util.find_spec('''py7zr''') is not None


# Cache location
UpperCAmelCase_       :  str      =		"~/.cache"
UpperCAmelCase_       :  List[Any]      =		os.getenv('''XDG_CACHE_HOME''', DEFAULT_XDG_CACHE_HOME)
UpperCAmelCase_       :  Tuple      =		os.path.join(XDG_CACHE_HOME, '''huggingface''')
UpperCAmelCase_       :  Any      =		os.path.expanduser(os.getenv('''HF_HOME''', DEFAULT_HF_CACHE_HOME))

UpperCAmelCase_       :  str      =		os.path.join(HF_CACHE_HOME, '''datasets''')
UpperCAmelCase_       :  str      =		Path(os.getenv('''HF_DATASETS_CACHE''', DEFAULT_HF_DATASETS_CACHE))

UpperCAmelCase_       :  Union[str, Any]      =		os.path.join(HF_CACHE_HOME, '''metrics''')
UpperCAmelCase_       :  Optional[int]      =		Path(os.getenv('''HF_METRICS_CACHE''', DEFAULT_HF_METRICS_CACHE))

UpperCAmelCase_       :  Dict      =		os.path.join(HF_CACHE_HOME, '''modules''')
UpperCAmelCase_       :  List[str]      =		Path(os.getenv('''HF_MODULES_CACHE''', DEFAULT_HF_MODULES_CACHE))

UpperCAmelCase_       :  Any      =		"downloads"
UpperCAmelCase_       :  Optional[Any]      =		os.path.join(HF_DATASETS_CACHE, DOWNLOADED_DATASETS_DIR)
UpperCAmelCase_       :  Dict      =		Path(os.getenv('''HF_DATASETS_DOWNLOADED_DATASETS_PATH''', DEFAULT_DOWNLOADED_DATASETS_PATH))

UpperCAmelCase_       :  Optional[Any]      =		"extracted"
UpperCAmelCase_       :  Optional[Any]      =		os.path.join(DEFAULT_DOWNLOADED_DATASETS_PATH, EXTRACTED_DATASETS_DIR)
UpperCAmelCase_       :  List[Any]      =		Path(os.getenv('''HF_DATASETS_EXTRACTED_DATASETS_PATH''', DEFAULT_EXTRACTED_DATASETS_PATH))

# Download count for the website
UpperCAmelCase_       :  Optional[Any]      =		(
    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)
UpperCAmelCase_       :  List[Any]      =		1_0_0_0

# Size of the preloaded record batch in `Dataset.__iter__`
UpperCAmelCase_       :  List[str]      =		1_0

# Pickling tables works only for small tables (<4GiB)
# For big tables, we write them on disk instead
UpperCAmelCase_       :  int      =		4 << 3_0

# Max shard size in bytes (e.g. to shard parquet datasets in push_to_hub or download_and_prepare)
UpperCAmelCase_       :  Union[str, Any]      =		"500MB"

# Parquet configuration
UpperCAmelCase_       :  Optional[Any]      =		1_0_0
UpperCAmelCase_       :  int      =		1_0_0
UpperCAmelCase_       :  List[Any]      =		1_0_0

# Offline mode
UpperCAmelCase_       :  str      =		os.environ.get('''HF_DATASETS_OFFLINE''', '''AUTO''').upper() in ENV_VARS_TRUE_VALUES

# In-memory
UpperCAmelCase_       :  Any      =		0  # Disabled
UpperCAmelCase_       :  Optional[int]      =		float(os.environ.get('''HF_DATASETS_IN_MEMORY_MAX_SIZE''', DEFAULT_IN_MEMORY_MAX_SIZE))

# File names
UpperCAmelCase_       :  List[Any]      =		"dataset.arrow"
UpperCAmelCase_       :  str      =		"indices.arrow"
UpperCAmelCase_       :  str      =		"state.json"
UpperCAmelCase_       :  str      =		"dataset_info.json"
UpperCAmelCase_       :  Any      =		"dataset_infos.json"
UpperCAmelCase_       :  Any      =		"LICENSE"
UpperCAmelCase_       :  Optional[Any]      =		"metric_info.json"
UpperCAmelCase_       :  int      =		"dataset_dict.json"

UpperCAmelCase_       :  Optional[int]      =		"datasets_modules"

UpperCAmelCase_       :  Tuple      =		2_5_5

# Streaming
UpperCAmelCase_       :  List[Any]      =		2_0
UpperCAmelCase_       :  Dict      =		5

# Datasets without script
UpperCAmelCase_       :  str      =		2_0_0
UpperCAmelCase_       :  Optional[Any]      =		1_0
UpperCAmelCase_       :  Optional[int]      =		2_0_0

# Progress bars
UpperCAmelCase_       :  Union[str, Any]      =		0.05  # 20 progress updates per sec





'''simple docstring'''



from datetime import date

import requests

UpperCAmelCase_       :  str      =		'''https://api.carbonintensity.org.uk/intensity'''







def 			_UpperCamelCase ()->   str:




     '''simple docstring'''





     __snake_case    					=  requests.get(_lowerCamelCase	).json()['''data'''][0]
     return last_half_hour["intensity"]["actual"]







def 			_UpperCamelCase (_lowerCamelCase							:     Dict   ,	_lowerCamelCase							:     List[Any]	)->   list:




     '''simple docstring'''





     return requests.get(f'''{BASE_URL}/{start}/{end}'''	).json()["data"]


if __name__ == "__main__":
     for entry in fetch_from_to(start=date(2_0_2_0, 1_0, 1), end=date(2_0_2_0, 1_0, 3)):
          print('''from {from} to {to}: {intensity[actual]}'''.format(**entry))
     print(F"""{fetch_last_half_hour() = }""")






