
'''simple docstring'''







from __future__ import annotations

import os






class 					lowerCAmelCase__  :
					lowerCAmelCase_	  =	(
					    '''High card''',
					    '''One pair''',
					    '''Two pairs''',
					    '''Three of a kind''',
					    '''Straight''',
					    '''Flush''',
					    '''Full house''',
					    '''Four of a kind''',
					    '''Straight flush''',
					    '''Royal flush''',
					)

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






					def __init__(  self							,				__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





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






					@property
					def       _snake_case       (  self						):


											"""simple docstring"""





											return self._hand






					def       _snake_case       (  self							,				__SCREAMING_SNAKE_CASE						):


											"""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(__SCREAMING_SNAKE_CASE						)
																	else:
																							return "Win" if self._second_pair > other._second_pair else "Loss"
											return "Win" if self._first_pair > other._first_pair else "Loss"






					def       _snake_case       (  self						):


											"""simple docstring"""





											lowercase_      :	str						=			PokerHand._HAND_NAME[self._hand_type - 14]
											lowercase_      :	List[str]						=			PokerHand._CARD_NAME[self._high_card]
											lowercase_      :	Union[str, Any]						=			PokerHand._CARD_NAME[self._first_pair]
											lowercase_      :	Optional[Any]						=			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]:
																	lowercase_      :	int						=			'''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       _snake_case       (  self							,				__SCREAMING_SNAKE_CASE						):


											"""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       _snake_case       (  self						):


											"""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       _snake_case       (  self						):


											"""simple docstring"""





											return len(self._card_suit						) == 1






					def       _snake_case       (  self						):


											"""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
																							lowercase_      :	List[str]						=			self._card_values.pop(0						)
																							self._card_values.append(__SCREAMING_SNAKE_CASE						)
																	return True
											return False






					def       _snake_case       (  self						):


											"""simple docstring"""





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






					def       _snake_case       (  self						):


											"""simple docstring"""





											lowercase_      :	Union[str, Any]						=			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:
																													lowercase_      :	Optional[Any]						=			self._card_values[i]
																													kind += 1
																							elif vala == self._card_values[i]:
																													kind += 2
																							elif not vala:
																													lowercase_      :	List[str]						=			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)
											lowercase_      :	List[str]						=			kind + 2 if kind in [4, 5] else kind
											# first meaning first pair to compare in 'compare_with'
											lowercase_      :	Any						=			max(__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE						)
											lowercase_      :	Any						=			min(__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE						)
											# 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(__SCREAMING_SNAKE_CASE						) != 3:
																	lowercase_		,					lowercase_      :	Dict						=			second, first
											lowercase_      :	Any						=			first
											lowercase_      :	List[str]						=			second
											return kind






					def       _snake_case       (  self						):


											"""simple docstring"""





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






					def __repr__(  self						):


											"""simple docstring"""





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






					def __str__(  self						):


											"""simple docstring"""





											return self._hand






					def __eq__(  self							,				__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





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






					def __lt__(  self							,				__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





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






					def __le__(  self							,				__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





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






					def __gt__(  self							,				__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





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






					def __ge__(  self							,				__SCREAMING_SNAKE_CASE						):


											"""simple docstring"""





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






					def __hash__(  self						):


											"""simple docstring"""





											return object.__hash__(self						)







def    snake_case_						(							):



						"""simple docstring"""





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


if __name__ == "__main__":
							solution()





'''simple docstring'''







import importlib
from typing import List, Optional, Union

from seqeval.metrics import accuracy_score, classification_report

import datasets


_lowercase					:    Optional[int]       				=			"\\n@inproceedings{ramshaw-marcus-1995-text,\n    title = \"Text Chunking using Transformation-Based Learning\",\n    author = \"Ramshaw, Lance  and\n      Marcus, Mitch\",\n    booktitle = \"Third Workshop on Very Large Corpora\",\n    year = \"1995\",\n    url = \"https://www.aclweb.org/anthology/W95-0107\",\n}\n@misc{seqeval,\n  title={{seqeval}: A Python framework for sequence labeling evaluation},\n  url={https://github.com/chakki-works/seqeval},\n  note={Software available from https://github.com/chakki-works/seqeval},\n  author={Hiroki Nakayama},\n  year={2018},\n}\n"

_lowercase					:    List[Any]       				=			"\\nseqeval is a Python framework for sequence labeling evaluation.\nseqeval can evaluate the performance of chunking tasks such as named-entity recognition, part-of-speech tagging, semantic role labeling and so on.\n\nThis is well-tested by using the Perl script conlleval, which can be used for\nmeasuring the performance of a system that has processed the CoNLL-2000 shared task data.\n\nseqeval supports following formats:\nIOB1\nIOB2\nIOE1\nIOE2\nIOBES\n\nSee the [README.md] file at https://github.com/chakki-works/seqeval for more information.\n"

_lowercase					:    int       				=			"\nProduces labelling scores along with its sufficient statistics\nfrom a source against one or more references.\n\nArgs:\n    predictions: List of List of predicted labels (Estimated targets as returned by a tagger)\n    references: List of List of reference labels (Ground truth (correct) target values)\n    suffix: True if the IOB prefix is after type, False otherwise. default: False\n    scheme: Specify target tagging scheme. Should be one of [\"IOB1\", \"IOB2\", \"IOE1\", \"IOE2\", \"IOBES\", \"BILOU\"].\n        default: None\n    mode: Whether to count correct entity labels with incorrect I/B tags as true positives or not.\n        If you want to only count exact matches, pass mode=\"strict\". default: None.\n    sample_weight: Array-like of shape (n_samples,), weights for individual samples. default: None\n    zero_division: Which value to substitute as a metric value when encountering zero division. Should be on of 0, 1,\n        \"warn\". \"warn\" acts as 0, but the warning is raised.\n\nReturns:\n    'scores': dict. Summary of the scores for overall and per type\n        Overall:\n            'accuracy': accuracy,\n            'precision': precision,\n            'recall': recall,\n            'f1': F1 score, also known as balanced F-score or F-measure,\n        Per type:\n            'precision': precision,\n            'recall': recall,\n            'f1': F1 score, also known as balanced F-score or F-measure\nExamples:\n\n    >>> predictions = [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]\n    >>> references = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]\n    >>> seqeval = datasets.load_metric(\"seqeval\")\n    >>> results = seqeval.compute(predictions=predictions, references=references)\n    >>> print(list(results.keys()))\n    ['MISC', 'PER', 'overall_precision', 'overall_recall', 'overall_f1', 'overall_accuracy']\n    >>> print(results[\"overall_f1\"])\n    0.5\n    >>> print(results[\"PER\"][\"f1\"])\n    1.0\n"






@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION       ,		_KWARGS_DESCRIPTION	)
class 					lowerCAmelCase__  (    datasets.Metric	):






					def       _snake_case       (  self						):


											"""simple docstring"""





											return datasets.MetricInfo(
											    description=_DESCRIPTION							,				citation=_CITATION							,				homepage='''https://github.com/chakki-works/seqeval'''							,				inputs_description=_KWARGS_DESCRIPTION							,				features=datasets.Features(
											        {
											            '''predictions''': datasets.Sequence(datasets.Value('''string'''							,				id='''label'''						)							,				id='''sequence'''						),
											            '''references''': datasets.Sequence(datasets.Value('''string'''							,				id='''label'''						)							,				id='''sequence'''						),
											        }						)							,				codebase_urls=['''https://github.com/chakki-works/seqeval''']							,				reference_urls=['''https://github.com/chakki-works/seqeval''']							,				)






					def       _snake_case       (  self							,				__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE = False							,				__SCREAMING_SNAKE_CASE = None							,				__SCREAMING_SNAKE_CASE = None							,				__SCREAMING_SNAKE_CASE = None							,				__SCREAMING_SNAKE_CASE = "warn"							,				):


											"""simple docstring"""





											if scheme is not None:
																	try:
																							lowercase_      :	List[str]						=			importlib.import_module('''seqeval.scheme'''						)
																							lowercase_      :	int						=			getattr(__SCREAMING_SNAKE_CASE							,				__SCREAMING_SNAKE_CASE						)
																	except AttributeError:
																							raise ValueError(F'''Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {scheme}'''						)
											lowercase_      :	List[Any]						=			classification_report(
											    y_true=__SCREAMING_SNAKE_CASE							,				y_pred=__SCREAMING_SNAKE_CASE							,				suffix=__SCREAMING_SNAKE_CASE							,				output_dict=__SCREAMING_SNAKE_CASE							,				scheme=__SCREAMING_SNAKE_CASE							,				mode=__SCREAMING_SNAKE_CASE							,				sample_weight=__SCREAMING_SNAKE_CASE							,				zero_division=__SCREAMING_SNAKE_CASE							,				)
											report.pop('''macro avg'''						)
											report.pop('''weighted avg'''						)
											lowercase_      :	int						=			report.pop('''micro avg'''						)

											lowercase_      :	List[Any]						=			{
											    type_name: {
											        '''precision''': score['''precision'''],
											        '''recall''': score['''recall'''],
											        '''f1''': score['''f1-score'''],
											        '''number''': score['''support'''],
											    }
											    for type_name, score in report.items()
											}
											lowercase_      :	Optional[Any]						=			overall_score['''precision''']
											lowercase_      :	Optional[Any]						=			overall_score['''recall''']
											lowercase_      :	Optional[int]						=			overall_score['''f1-score''']
											lowercase_      :	Optional[int]						=			accuracy_score(y_true=__SCREAMING_SNAKE_CASE							,				y_pred=__SCREAMING_SNAKE_CASE						)

											return scores



