


"""simple docstring"""





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     					=   re.compile("[^A-Za-z_0-9]")
# parameters used in DuplicationIndex
__UpperCAmelCase     					=   10
__UpperCAmelCase     					=   256





def      lowercase__						(	lowerCamelCase  :	str					)       ->  Tuple:
  if len(lowerCamelCase					) < MIN_NUM_TOKENS:
    return None
  lowerCAmelCase__     :     Optional[Any]										=       MinHash(num_perm=lowerCamelCase					)
  for token in set(lowerCamelCase					):
    min_hash.update(token.encode()					)
  return min_hash





def      lowercase__						(	lowerCamelCase  :	List[Any]					)       ->  str:
  return {t for t in NON_ALPHA.split(lowerCamelCase					) if len(t.strip()					) > 0}

class 			lowercase_	:







      def __init__(   self			:				Tuple		,	*,
          _lowercase			:				List[str] = 0.85		,	):
        lowerCAmelCase__     :     Optional[int]										=       duplication_jaccard_threshold
        lowerCAmelCase__     :     int										=       NUM_PERM
        lowerCAmelCase__     :     List[str]										=       MinHashLSH(threshold=self._duplication_jaccard_threshold		,	num_perm=self._num_perm     )

        lowerCAmelCase__     :     Union[str, Any]										=       defaultdict(snake_case_     )







      def 					_lowerCAmelCase							(   self			:				Optional[int]		,	_lowercase			:				Tuple		,	_lowercase			:				str     ):
        lowerCAmelCase__     :     Dict										=       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 					_lowerCAmelCase							(   self			:				Union[str, Any]     ):
        lowerCAmelCase__     :     Tuple										=       []
        for base, duplicates in self._duplicate_clusters.items():
          lowerCAmelCase__     :     Optional[Any]										=       [base] + list(snake_case_     )
          # reformat the cluster to be a list of dict
          lowerCAmelCase__     :     Tuple										=       [{"""base_index""": el[0], """repo_name""": el[1], """path""": el[2]} for el in cluster]
          duplicate_clusters.append(snake_case_     )
        return duplicate_clusters







      def 					_lowerCAmelCase							(   self			:				List[Any]		,	_lowercase			:				Dict     ):
        lowerCAmelCase__     :     str										=       self.get_duplicate_clusters()
        with open(snake_case_		,	"w"     ) as f:
          json.dump(snake_case_		,	snake_case_     )





def      lowercase__						(	lowerCamelCase  :	List[Any]					)       ->  Union[str, Any]:
  lowerCAmelCase__     :     Optional[int]										=       element
  lowerCAmelCase__     :     Tuple										=       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      lowercase__						(	lowerCamelCase  :	Optional[int]					)       ->  List[str]:
  with mp.Pool() as pool:
    for data in pool.imap_unordered(
        _compute_min_hash					,						ThreadedIterator(lowerCamelCase					,						max_queue_size=1_0_0_0_0					)					,						chunksize=1_0_0					,						):
      if data is not None:
        yield data





def      lowercase__						(	lowerCamelCase  :	int					,						lowerCamelCase  :	Optional[Any]					)       ->  List[Any]:
  lowerCAmelCase__     :     Optional[int]										=       DuplicationIndex(duplication_jaccard_threshold=lowerCamelCase					)

  for filename, min_hash in tqdm(ThreadedIterator(minhash_iter(enumerate(lowerCamelCase					)					)					,						max_queue_size=1_0_0					)					):
    di.add(lowerCamelCase					,						lowerCamelCase					)

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





def      lowercase__						(	lowerCamelCase  :	Any					,						lowerCamelCase  :	Dict					)       ->  List[str]:
  lowerCAmelCase__     :     List[Any]										=       get_tokens(lowerCamelCase					)
  lowerCAmelCase__     :     Any										=       get_tokens(lowerCamelCase					)
  return len(tokensa & tokensa					) / len(tokensa | tokensa					)


__UpperCAmelCase     					=   None





def      lowercase__						(	lowerCamelCase  :	Dict					,						lowerCamelCase  :	Tuple					)       ->  List[str]:
  lowerCAmelCase__     :     int										=       []
  for elementa in cluster:
    lowerCAmelCase__     :     List[str]										=       _shared_dataset[elementa["""base_index"""]]["""content"""]
    for elementa in extremes:
      lowerCAmelCase__     :     Union[str, Any]										=       _shared_dataset[elementa["""base_index"""]]["""content"""]
      if jaccard_similarity(lowerCamelCase					,						lowerCamelCase					) >= jaccard_threshold:
        elementa["copies"] += 1
        break
    else:
      lowerCAmelCase__     :     Tuple										=       1
      extremes.append(lowerCamelCase					)
  return extremes





def      lowercase__						(	lowerCamelCase  :	int					,						lowerCamelCase  :	str					,						lowerCamelCase  :	Any					)       ->  Optional[Any]:
  global _shared_dataset
  lowerCAmelCase__     :     int										=       dataset
  lowerCAmelCase__     :     Optional[int]										=       []
  lowerCAmelCase__     :     str										=       partial(_find_cluster_extremes_shared					,						jaccard_threshold=lowerCamelCase					)
  with mp.Pool() as pool:
    for extremes in tqdm(
        pool.imap_unordered(
            lowerCamelCase					,						lowerCamelCase					,						)					,						total=len(lowerCamelCase					)					,						):
      extremes_list.append(lowerCamelCase					)
  return extremes_list







def      lowercase__						(	lowerCamelCase  :	Tuple					,						lowerCamelCase  :	Any = 0.85					)       ->  List[Any]:
  lowerCAmelCase__     :     Optional[int]										=       make_duplicate_clusters(lowerCamelCase					,						lowerCamelCase					)
  lowerCAmelCase__     :     List[Any]										=       {x["""base_index"""] for cluster in duplicate_clusters for x in cluster}
  lowerCAmelCase__     :     List[str]										=       {}
  lowerCAmelCase__     :     int										=       find_extremes(lowerCamelCase					,						lowerCamelCase					,						lowerCamelCase					)
  for extremes in extremes_clusters:
    for element in extremes:
      lowerCAmelCase__     :     str										=       element
  lowerCAmelCase__     :     Optional[Any]										=       duplicate_indices - set(extreme_dict.keys()					)
  lowerCAmelCase__     :     str										=       dataset.filter(lambda lowerCamelCase					,						lowerCamelCase					: idx not in remove_indices					,						with_indices=lowerCamelCase					)

  # update duplicate_clusters
  for cluster in duplicate_clusters:
    for element in cluster:
      lowerCAmelCase__     :     Any										=       element["""base_index"""] in extreme_dict
      if element["is_extreme"]:
        lowerCAmelCase__     :     int										=       extreme_dict[element["""base_index"""]]["""copies"""]

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

  return ds_filter, duplicate_clusters

"""simple docstring"""



import math
from collections.abc import Iterator
from itertools import takewhile

def  _A(		lowerCAmelCase							):

							if 1 < number < 4:
														# 2 and 3 are primes
														return True
							elif number < 2 or number % 2 == 0 or number % 3 == 0:
														# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
														return False

							# All primes number are in format of 6k +/- 1
							for i in range(5			,  int(math.sqrt(lowerCAmelCase							) + 1							)			,  6							):
														if number % i == 0 or number % (i + 2) == 0:
																					return False
							return True

def  _A(		):
							A__       :     List[str]								=			2
							while True:
														if is_prime(lowerCAmelCase							):
																					yield num
														num += 1

def  _A(		lowerCAmelCase = 200_0000							):
							return sum(takewhile(lambda lowerCAmelCase							: x < n			,  prime_generator()							)							)


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





