

import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type

from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import ThreadedIterator
from tqdm import tqdm


_UpperCAmelCase	:     List[Any]		       = re.compile("""[^A-Za-z_0-9]""")
# parameters used in DuplicationIndex
_UpperCAmelCase	:     int		       = 10
_UpperCAmelCase	:     List[Any]		       = 256





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							if len(UpperCamelCase__   ) < MIN_NUM_TOKENS:
														return None
							snake_case_           =					MinHash(num_perm=UpperCamelCase__   )
							for token in set(UpperCamelCase__   ):
														min_hash.update(token.encode()   )
							return min_hash





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							return {t for t in NON_ALPHA.split(UpperCamelCase__   ) if len(t.strip()   ) > 0}







class 				lowercase       :




				def __init__(      self   ,     *,
				    snake_case = 0.85   ,     ):
											snake_case_           =					duplication_jaccard_threshold
											snake_case_           =					NUM_PERM
											snake_case_           =					MinHashLSH(threshold=self._duplication_jaccard_threshold   ,     num_perm=self._num_perm )

											snake_case_           =					defaultdict(snake_case )




				def 					a							(      self   ,     snake_case   ,     snake_case ):
											snake_case_           =					self._index.query(snake_case )
											if code_key in self._index.keys:
																		print(F'''Duplicate key {code_key}''' )
																		return

											self._index.insert(snake_case   ,     snake_case )
											if len(snake_case ) > 0:
																		for base_duplicate in close_duplicates:
																									if base_duplicate in self._duplicate_clusters:
																																self._duplicate_clusters[base_duplicate].add(snake_case )
																																break
																		else:
																									self._duplicate_clusters[close_duplicates[0]].add(snake_case )




				def 					a							(      self ):
											snake_case_           =					[]
											for base, duplicates in self._duplicate_clusters.items():
																		snake_case_           =					[base] + list(snake_case )
																		# reformat the cluster to be a list of dict
																		snake_case_           =					[{'base_index': el[0], 'repo_name': el[1], 'path': el[2]} for el in cluster]
																		duplicate_clusters.append(snake_case )
											return duplicate_clusters




				def 					a							(      self   ,     snake_case ):
											snake_case_           =					self.get_duplicate_clusters()
											with open(snake_case   ,     'w' ) as f:
																		json.dump(snake_case   ,     snake_case )





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_       ,					snake_case_           =					element
							snake_case_           =					get_min_hash([t for t in NON_ALPHA.split(data['content']   ) if len(t.strip()   ) > 0]   )
							if min_hash is not None:
														return (index, data["repo_name"], data["path"]), min_hash





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							with mp.Pool() as pool:
														for data in pool.imap_unordered(
														    _compute_min_hash     ,							ThreadedIterator(UpperCamelCase__     ,							max_queue_size=10000   )     ,							chunksize=100     ,							):
																					if data is not None:
																												yield data





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					DuplicationIndex(duplication_jaccard_threshold=UpperCamelCase__   )

							for filename, min_hash in tqdm(ThreadedIterator(minhash_iter(enumerate(UpperCamelCase__   )   )     ,							max_queue_size=100   )   ):
														di.add(UpperCamelCase__     ,							UpperCamelCase__   )

							# Returns a List[Cluster] where Cluster is List[str] with the filenames.
							return di.get_duplicate_clusters()





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					get_tokens(UpperCamelCase__   )
							snake_case_           =					get_tokens(UpperCamelCase__   )
							return len(tokensa & tokensa   ) / len(tokensa | tokensa   )


_UpperCAmelCase	:     Optional[int]		       = None





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					[]
							for elementa in cluster:
														snake_case_           =					_shared_dataset[elementa['base_index']]['content']
														for elementa in extremes:
																					snake_case_           =					_shared_dataset[elementa['base_index']]['content']
																					if jaccard_similarity(UpperCamelCase__     ,							UpperCamelCase__   ) >= jaccard_threshold:
																												elementa["copies"] += 1
																												break
														else:
																					snake_case_           =					1
																					extremes.append(UpperCamelCase__   )
							return extremes





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							global _shared_dataset
							snake_case_           =					dataset
							snake_case_           =					[]
							snake_case_           =					partial(_find_cluster_extremes_shared     ,							jaccard_threshold=UpperCamelCase__   )
							with mp.Pool() as pool:
														for extremes in tqdm(
														    pool.imap_unordered(
														        UpperCamelCase__     ,							UpperCamelCase__     ,							)     ,							total=len(UpperCamelCase__   )     ,							):
																					extremes_list.append(UpperCamelCase__   )
							return extremes_list





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__ = 0.85   ):







							'''simple docstring'''






							snake_case_           =					make_duplicate_clusters(UpperCamelCase__     ,							UpperCamelCase__   )
							snake_case_           =					{x['base_index'] for cluster in duplicate_clusters for x in cluster}
							snake_case_           =					{}
							snake_case_           =					find_extremes(UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__   )
							for extremes in extremes_clusters:
														for element in extremes:
																					snake_case_           =					element
							snake_case_           =					duplicate_indices - set(extreme_dict.keys()   )
							snake_case_           =					dataset.filter(lambda UpperCamelCase__     ,							UpperCamelCase__   : idx not in remove_indices     ,							with_indices=UpperCamelCase__   )

							# update duplicate_clusters
							for cluster in duplicate_clusters:
														for element in cluster:
																					snake_case_           =					element['base_index'] in extreme_dict
																					if element["is_extreme"]:
																												snake_case_           =					extreme_dict[element['base_index']]['copies']

							print(F'''Original dataset size: {len(UpperCamelCase__   )}'''   )
							print(F'''Number of duplicate clusters: {len(UpperCamelCase__   )}'''   )
							print(F'''Files in duplicate cluster: {len(UpperCamelCase__   )}'''   )
							print(F'''Unique files in duplicate cluster: {len(UpperCamelCase__   )}'''   )
							print(F'''Filtered dataset size: {len(UpperCamelCase__   )}'''   )

							return ds_filter, duplicate_clusters







def       __lowerCamelCase			(				UpperCamelCase__ = 50000000   ):







							'''simple docstring'''






							snake_case_           =					set()
							snake_case_           =					int((limit - 24) ** (1 / 2)   )

							snake_case_           =					set(range(3     ,							prime_square_limit + 1     ,							2   )   )
							primes.add(2   )
							for p in range(3     ,							prime_square_limit + 1     ,							2   ):
														if p not in primes:
																					continue
														primes.difference_update(set(range(p * p     ,							prime_square_limit + 1     ,							UpperCamelCase__   )   )   )

							for primea in primes:
														snake_case_           =					primea * primea
														for primea in primes:
																					snake_case_           =					primea * primea * primea
																					if square + cube >= limit - 16:
																												break
																					for primea in primes:
																												snake_case_           =					primea * primea * primea * primea
																												snake_case_           =					square + cube + tetr
																												if total >= limit:
																																			break
																												ret.add(UpperCamelCase__   )

							return len(UpperCamelCase__   )


if __name__ == "__main__":
					print(F'''{solution() = }''')




