





from __future__ import annotations

import os





class 		A__    :
	lowerCamelCase__		:			Optional[Any]       =(
	    "High card",
	    "One pair",
	    "Two pairs",
	    "Three of a kind",
	    "Straight",
	    "Flush",
	    "Full house",
	    "Four of a kind",
	    "Straight flush",
	    "Royal flush",
	)

	lowerCamelCase__		:			str       =(
	    "",  # placeholder as tuples are zero-indexed
	    "One",
	    "Two",
	    "Three",
	    "Four",
	    "Five",
	    "Six",
	    "Seven",
	    "Eight",
	    "Nine",
	    "Ten",
	    "Jack",
	    "Queen",
	    "King",
	    "Ace",
	)






	def __init__(     self    ,					lowerCamelCase						)				->       Tuple:




						"""simple docstring"""






						if not isinstance(__A    ,					__A						):
											__magic_name__ :							Any		       =							F'''Hand should be of type \'str\': {hand!r}'''
											raise TypeError(__A						)
						# split removes duplicate whitespaces so no need of strip
						if len(hand.split(''' '''						)						) != 5:
											__magic_name__ :							Optional[int]		       =							F'''Hand should contain only 5 cards: {hand!r}'''
											raise ValueError(__A						)
						__magic_name__ :							Union[str, Any]		       =							hand
						__magic_name__ :							Optional[int]		       =							0
						__magic_name__ :							Dict		       =							0
						__magic_name__ :							Optional[int]		       =							self._internal_state()
						__magic_name__ :							Optional[int]		       =							self._get_hand_type()
						__magic_name__ :							List[Any]		       =							self._card_values[0]






	@property
	def 			lowercase				(     self						)				->       Union[str, Any]:




						"""simple docstring"""






						return self._hand






	def 			lowercase				(     self    ,					lowerCamelCase						)				->       List[Any]:




						"""simple docstring"""






						if self._hand_type > other._hand_type:
											return "Win"
						elif self._hand_type < other._hand_type:
											return "Loss"
						elif self._first_pair == other._first_pair:
											if self._second_pair == other._second_pair:
																return self._compare_cards(__A						)
											else:
																return "Win" if self._second_pair > other._second_pair else "Loss"
						return "Win" if self._first_pair > other._first_pair else "Loss"






	def 			lowercase				(     self						)				->       Optional[int]:




						"""simple docstring"""






						__magic_name__ :							Dict		       =							PokerHand._HAND_NAME[self._hand_type - 14]
						__magic_name__ :							Optional[int]		       =							PokerHand._CARD_NAME[self._high_card]
						__magic_name__ :							Tuple		       =							PokerHand._CARD_NAME[self._first_pair]
						__magic_name__ :							str		       =							PokerHand._CARD_NAME[self._second_pair]
						if self._hand_type in [22, 19, 18]:
											return name + F''', {high}-high'''
						elif self._hand_type in [21, 17, 15]:
											return name + F''', {paira}s'''
						elif self._hand_type in [20, 16]:
											__magic_name__ :							List[str]		       =							"over" if self._hand_type == 20 else "and"
											return name + F''', {paira}s {join} {paira}s'''
						elif self._hand_type == 23:
											return name
						else:
											return name + F''', {high}'''






	def 			lowercase				(     self    ,					lowerCamelCase						)				->       Optional[int]:




						"""simple docstring"""






						for index, card_value in enumerate(self._card_values						):
											if card_value != other._card_values[index]:
																return "Win" if card_value > other._card_values[index] else "Loss"
						return "Tie"






	def 			lowercase				(     self						)				->       Dict:




						"""simple docstring"""






						if self._is_flush():
											if self._is_five_high_straight() or self._is_straight():
																return 23 if sum(self._card_values						) == 60 else 22
											return 19
						elif self._is_five_high_straight() or self._is_straight():
											return 18
						return 14 + self._is_same_kind()






	def 			lowercase				(     self						)				->       Dict:




						"""simple docstring"""






						return len(self._card_suit						) == 1






	def 			lowercase				(     self						)				->       List[str]:




						"""simple docstring"""






						if sorted(self._card_values						) == [2, 3, 4, 5, 14]:
											if self._card_values[0] == 14:
																# Remember, our list is sorted in reverse order
																__magic_name__ :							Any		       =							self._card_values.pop(0						)
																self._card_values.append(__A						)
											return True
						return False






	def 			lowercase				(     self						)				->       Optional[Any]:




						"""simple docstring"""






						for i in range(4						):
											if self._card_values[i] - self._card_values[i + 1] != 1:
																return False
						return True






	def 			lowercase				(     self						)				->       str:




						"""simple docstring"""






						__magic_name__ :							int		       =							0
						for i in range(4						):
											# Compare two cards at a time, if they are same increase 'kind',
											# add the value of the card to val1, if it is repeating again we
											# will add 2 to 'kind' as there are now 3 cards with same value.
											# If we get card of different value than val1, we will do the same
											# thing with val2
											if self._card_values[i] == self._card_values[i + 1]:
																if not vala:
																					__magic_name__ :							Tuple		       =							self._card_values[i]
																					kind += 1
																elif vala == self._card_values[i]:
																					kind += 2
																elif not vala:
																					__magic_name__ :							Any		       =							self._card_values[i]
																					kind += 1
																elif vala == self._card_values[i]:
																					kind += 2
											 # For consistency in hand type (look at note in _get_hand_type function)
						__magic_name__ :							Optional[Any]		       =							kind + 2 if kind in [4, 5] else kind
						# first meaning first pair to compare in 'compare_with'
						__magic_name__ :							Optional[int]		       =							max(__A    ,					__A						)
						__magic_name__ :							int		       =							min(__A    ,					__A						)
						# If it's full house (three count pair + two count pair), make sure
						# first pair is three count and if not then switch them both.
						if kind == 6 and self._card_values.count(__A						) != 3:
											__magic_name__ :							Union[str, Any]		       =							second, first
						__magic_name__ :							List[Any]		       =							first
						__magic_name__ :							List[Any]		       =							second
						return kind






	def 			lowercase				(     self						)				->       str:




						"""simple docstring"""






						__magic_name__ :							dict		       =							{"T": "10", "J": "11", "Q": "12", "K": "13", "A": "14"}
						__magic_name__ :							List[Any]		       =							self._hand.translate(str.maketrans(__A						)						).split()
						__magic_name__ :							Optional[int]		       =							[int(card[:-1]						) for card in new_hand]
						__magic_name__ :							Dict		       =							{card[-1] for card in new_hand}
						return sorted(__A    ,					reverse=__A						), card_suit






	def __repr__(     self						)				->       List[Any]:




						"""simple docstring"""






						return F'''{self.__class__}(\"{self._hand}\")'''






	def __str__(     self						)				->       Tuple:




						"""simple docstring"""






						return self._hand






	def __eq__(     self    ,					lowerCamelCase						)				->       int:




						"""simple docstring"""






						if isinstance(__A    ,					__A						):
											return self.compare_with(__A						) == "Tie"
						return NotImplemented






	def __lt__(     self    ,					lowerCamelCase						)				->       Union[str, Any]:




						"""simple docstring"""






						if isinstance(__A    ,					__A						):
											return self.compare_with(__A						) == "Loss"
						return NotImplemented






	def __le__(     self    ,					lowerCamelCase						)				->       Optional[int]:




						"""simple docstring"""






						if isinstance(__A    ,					__A						):
											return self < other or self == other
						return NotImplemented






	def __gt__(     self    ,					lowerCamelCase						)				->       Any:




						"""simple docstring"""






						if isinstance(__A    ,					__A						):
											return not self < other and self != other
						return NotImplemented






	def __ge__(     self    ,					lowerCamelCase						)				->       int:




						"""simple docstring"""






						if isinstance(__A    ,					__A						):
											return not self < other
						return NotImplemented






	def __hash__(     self						)				->       Union[str, Any]:




						"""simple docstring"""






						return object.__hash__(self						)







def 			lowerCAmelCase  (     )  ->Union[str, Any]:






					"""simple docstring"""






					__magic_name__ :							int		       =							0
					__magic_name__ :							Dict		       =							os.path.abspath(os.path.dirname(SCREAMING_SNAKE_CASE_	)	)
					__magic_name__ :							Optional[int]		       =							os.path.join(SCREAMING_SNAKE_CASE_,     '''poker_hands.txt'''	)
					with open(SCREAMING_SNAKE_CASE_	) as file_hand:
										for line in file_hand:
															__magic_name__ :							Optional[Any]		       =							line[:14].strip()
															__magic_name__ :							str		       =							line[15:].strip()
															__magic_name__ :							int		       =							PokerHand(SCREAMING_SNAKE_CASE_	), PokerHand(SCREAMING_SNAKE_CASE_	)
															__magic_name__ :							Optional[Any]		       =							player.compare_with(SCREAMING_SNAKE_CASE_	)
															if output == "Win":
																				answer += 1
					return answer


if __name__ == "__main__":
				solution()









import importlib
import os
import platform
from pathlib import Path

from packaging import version

from .utils.logging import get_logger


lowercase_		=							get_logger(__name__)

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

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

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

lowercase_		=							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
lowercase_		=							{'''1''', '''ON''', '''YES''', '''TRUE'''}
lowercase_		=							ENV_VARS_TRUE_VALUES.union({'''AUTO'''})


# Imports
lowercase_		=							version.parse(importlib_metadata.version('''dill'''))
lowercase_		=							version.parse(importlib_metadata.version('''pandas'''))
lowercase_		=							version.parse(importlib_metadata.version('''pyarrow'''))

lowercase_		=							os.environ.get('''USE_TF''', '''AUTO''').upper()
lowercase_		=							os.environ.get('''USE_TORCH''', '''AUTO''').upper()
lowercase_		=							os.environ.get('''USE_JAX''', '''AUTO''').upper()

lowercase_		=							'''N/A'''
lowercase_		=							False

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

lowercase_		=							'''N/A'''
lowercase_		=							False

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


lowercase_		=							'''N/A'''
lowercase_		=							False

if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES:
				lowercase_		=							importlib.util.find_spec('''jax''') is not None and importlib.util.find_spec('''jaxlib''') is not None
				if JAX_AVAILABLE:
								try:
												lowercase_		=							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''')


lowercase_		=							os.environ.get('''USE_BEAM''', '''AUTO''').upper()
lowercase_		=							'''N/A'''
lowercase_		=							False
if USE_BEAM in ENV_VARS_TRUE_AND_AUTO_VALUES:
				try:
								lowercase_		=							version.parse(importlib_metadata.version('''apache_beam'''))
								lowercase_		=							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
lowercase_		=							importlib.util.find_spec('''sqlalchemy''') is not None

# Optional tools for feature decoding
lowercase_		=							importlib.util.find_spec('''PIL''') is not None
lowercase_		=							importlib.util.find_spec('''soundfile''') is not None and version.parse(
    importlib.import_module('''soundfile''').__libsndfile_version__
) >= version.parse('''1.0.31''')
lowercase_		=							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
lowercase_		=							importlib.util.find_spec('''rarfile''') is not None
lowercase_		=							importlib.util.find_spec('''zstandard''') is not None
lowercase_		=							importlib.util.find_spec('''lz4''') is not None
lowercase_		=							importlib.util.find_spec('''py7zr''') is not None


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

lowercase_		=							os.path.join(HF_CACHE_HOME, '''datasets''')
lowercase_		=							Path(os.getenv('''HF_DATASETS_CACHE''', DEFAULT_HF_DATASETS_CACHE))

lowercase_		=							os.path.join(HF_CACHE_HOME, '''metrics''')
lowercase_		=							Path(os.getenv('''HF_METRICS_CACHE''', DEFAULT_HF_METRICS_CACHE))

lowercase_		=							os.path.join(HF_CACHE_HOME, '''modules''')
lowercase_		=							Path(os.getenv('''HF_MODULES_CACHE''', DEFAULT_HF_MODULES_CACHE))

lowercase_		=							'''downloads'''
lowercase_		=							os.path.join(HF_DATASETS_CACHE, DOWNLOADED_DATASETS_DIR)
lowercase_		=							Path(os.getenv('''HF_DATASETS_DOWNLOADED_DATASETS_PATH''', DEFAULT_DOWNLOADED_DATASETS_PATH))

lowercase_		=							'''extracted'''
lowercase_		=							os.path.join(DEFAULT_DOWNLOADED_DATASETS_PATH, EXTRACTED_DATASETS_DIR)
lowercase_		=							Path(os.getenv('''HF_DATASETS_EXTRACTED_DATASETS_PATH''', DEFAULT_EXTRACTED_DATASETS_PATH))

# Download count for the website
lowercase_		=							(
    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)
lowercase_		=							1000

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

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

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

# Parquet configuration
lowercase_		=							100
lowercase_		=							100
lowercase_		=							100

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

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

# File names
lowercase_		=							'''dataset.arrow'''
lowercase_		=							'''indices.arrow'''
lowercase_		=							'''state.json'''
lowercase_		=							'''dataset_info.json'''
lowercase_		=							'''dataset_infos.json'''
lowercase_		=							'''LICENSE'''
lowercase_		=							'''metric_info.json'''
lowercase_		=							'''dataset_dict.json'''

lowercase_		=							'''datasets_modules'''

lowercase_		=							255

# Streaming
lowercase_		=							20
lowercase_		=							5

# Datasets without script
lowercase_		=							200
lowercase_		=							10
lowercase_		=							200

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



