

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__						=	1_0_0_0

# Size of the preloaded record batch in `Dataset.__iter__`
lowerCAmelCase__						=	1_0

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

# 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_0_0
lowerCAmelCase__						=	1_0_0
lowerCAmelCase__						=	1_0_0

# 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_5_5

# Streaming
lowerCAmelCase__						=	2_0
lowerCAmelCase__						=	5

# Datasets without script
lowerCAmelCase__						=	2_0_0
lowerCAmelCase__						=	1_0
lowerCAmelCase__						=	2_0_0

# Progress bars
lowerCAmelCase__						=	0.0_5  # 20 progress updates per sec




from .balanced_parentheses import balanced_parentheses
from .stack import Stack



def    lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							str )     -> int:




				'''simple docstring'''





				return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(SCREAMING_SNAKE_CASE_		,    -1 )



def    lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							str )     -> str:




				'''simple docstring'''





				if not balanced_parentheses(SCREAMING_SNAKE_CASE_ ):
								raise ValueError("Mismatched parentheses" )
				A__            =     Stack()
				A__            =     []
				for char in expression_str:
								if char.isalpha() or char.isdigit():
												postfix.append(SCREAMING_SNAKE_CASE_ )
								elif char == "(":
												stack.push(SCREAMING_SNAKE_CASE_ )
								elif char == ")":
												while not stack.is_empty() and stack.peek() != "(":
																postfix.append(stack.pop() )
												stack.pop()
								else:
												while not stack.is_empty() and precedence(SCREAMING_SNAKE_CASE_ ) <= precedence(stack.peek() ):
																postfix.append(stack.pop() )
												stack.push(SCREAMING_SNAKE_CASE_ )
				while not stack.is_empty():
								postfix.append(stack.pop() )
				return " ".join(SCREAMING_SNAKE_CASE_ )


if __name__ == "__main__":
	from doctest import testmod

	testmod()
	lowerCAmelCase__						=	"""a+b*(c^d-e)^(f+g*h)-i"""

	print("""Infix to Postfix Notation demonstration:\n""")
	print("""Infix notation: """ + expression)
	print("""Postfix notation: """ + infix_to_postfix(expression))

