'''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					:		Optional[Any]							      =		re.compile('[^A-Za-z_0-9]')
# parameters used in DuplicationIndex
_UpperCamelCase					:		Optional[Any]							      =		10
_UpperCamelCase					:		Any							      =		2_56



def     __snake_case			(							lowerCAmelCase							:  List[str]      ):




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



def     __snake_case			(							lowerCAmelCase							:  str      ):
 return {t for t in NON_ALPHA.split(lowerCAmelCase      ) if len(t.strip()      ) > 0}

class 	_lowercase:



   """simple docstring"""





   def __init__(				self:     Optional[int]      ,*,
       a:     float = 0.85      ,):
    __UpperCAmelCase								=       duplication_jaccard_threshold
    __UpperCAmelCase								=       NUM_PERM
    __UpperCAmelCase								=       MinHashLSH(threshold=self._duplication_jaccard_threshold      ,num_perm=self._num_perm						)

    __UpperCAmelCase								=       defaultdict(_UpperCAmelCase						)





   def       snake_case						(				self:     List[Any]      ,a:     Tuple      ,a:     MinHash						):
    __UpperCAmelCase								=       self._index.query(_UpperCAmelCase						)
    if code_key in self._index.keys:
     print(f"""Duplicate key {code_key}"""						)
     return

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





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





   def       snake_case						(				self:     int      ,a:     str						):
    __UpperCAmelCase								=       self.get_duplicate_clusters()
    with open(_UpperCAmelCase      ,'w'						) as f:
     json.dump(_UpperCAmelCase      ,_UpperCAmelCase						)




def     __snake_case			(							lowerCAmelCase							:  Any      ):
 __UpperCAmelCase	,      __UpperCAmelCase								=       element
 __UpperCAmelCase								=       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     __snake_case			(							lowerCAmelCase							:  Type[Dataset]      ):




 with mp.Pool() as pool:
  for data in pool.imap_unordered(
      _compute_min_hash   ,	ThreadedIterator(lowerCAmelCase   ,	max_queue_size=1_0000      )   ,	chunksize=100   ,	):
   if data is not None:
    yield data



def     __snake_case			(							lowerCAmelCase							:  Type[Dataset]   ,	lowerCAmelCase							:  float      ):
 __UpperCAmelCase								=       DuplicationIndex(duplication_jaccard_threshold=lowerCAmelCase      )

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

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



def     __snake_case			(							lowerCAmelCase							:  str   ,	lowerCAmelCase							:  str      ):
 __UpperCAmelCase								=       get_tokens(lowerCAmelCase      )
 __UpperCAmelCase								=       get_tokens(lowerCAmelCase      )
 return len(tokensa & tokensa      ) / len(tokensa | tokensa      )


_UpperCamelCase					:		Tuple							      =		None



def     __snake_case			(							lowerCAmelCase							:  List[str]   ,	lowerCAmelCase							:  Optional[int]      ):
 __UpperCAmelCase								=       []
 for elementa in cluster:
  __UpperCAmelCase								=       _shared_dataset[elementa['base_index']]['content']
  for elementa in extremes:
   __UpperCAmelCase								=       _shared_dataset[elementa['base_index']]['content']
   if jaccard_similarity(lowerCAmelCase   ,	lowerCAmelCase      ) >= jaccard_threshold:
    elementa["copies"] += 1
    break
  else:
   __UpperCAmelCase								=       1
   extremes.append(lowerCAmelCase      )
 return extremes



def     __snake_case			(							lowerCAmelCase							:  Optional[int]   ,	lowerCAmelCase							:  Union[str, Any]   ,	lowerCAmelCase							:  Optional[Any]      ):
 global _shared_dataset
 __UpperCAmelCase								=       dataset
 __UpperCAmelCase								=       []
 __UpperCAmelCase								=       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     __snake_case			(							lowerCAmelCase							:  Type[Dataset]   ,	lowerCAmelCase							:  float = 0.85      ):
 __UpperCAmelCase								=       make_duplicate_clusters(lowerCAmelCase   ,	lowerCAmelCase      )
 __UpperCAmelCase								=       {x['base_index'] for cluster in duplicate_clusters for x in cluster}
 __UpperCAmelCase								=       {}
 __UpperCAmelCase								=       find_extremes(lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase      )
 for extremes in extremes_clusters:
  for element in extremes:
   __UpperCAmelCase								=       element
 __UpperCAmelCase								=       duplicate_indices - set(extreme_dict.keys()      )
 __UpperCAmelCase								=       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:
   __UpperCAmelCase								=       element['base_index'] in extreme_dict
   if element["is_extreme"]:
    __UpperCAmelCase								=       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







from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any



@dataclass
class 				A       :
					'''simple docstring'''






					A__     =					42
					A__     =					None
					A__     =					None






def 					UpperCamelCase   (      )  ->    Node | None:
		"""simple docstring"""




		lowercase__	     =						Node(1	)
		lowercase__	     =						Node(2	)
		lowercase__	     =						Node(3	)
		lowercase__	     =						Node(4	)
		lowercase__	     =						Node(5	)
		return tree






def 					UpperCamelCase   (      __magic_name__	:				Node | None	)  ->    list[int]:
		"""simple docstring"""




		return [root.data, *preorder(root.left	), *preorder(root.right	)] if root else []






def 					UpperCamelCase   (      __magic_name__	:				Node | None	)  ->    list[int]:
		"""simple docstring"""




		return postorder(root.left	) + postorder(root.right	) + [root.data] if root else []






def 					UpperCamelCase   (      __magic_name__	:				Node | None	)  ->    list[int]:
		"""simple docstring"""




		return [*inorder(root.left	), root.data, *inorder(root.right	)] if root else []






def 					UpperCamelCase   (      __magic_name__	:				Node | None	)  ->    int:
		"""simple docstring"""




		return (max(height(root.left	)       ,       height(root.right	)	) + 1) if root else 0






def 					UpperCamelCase   (      __magic_name__	:				Node | None	)  ->    Sequence[Node | None]:
		"""simple docstring"""




		lowercase__	     =						[]

		if root is None:
				return output

		lowercase__	     =						deque([root]	)

		while process_queue:
				lowercase__	     =						process_queue.popleft()
				output.append(node.data	)

				if node.left:
						process_queue.append(node.left	)
				if node.right:
						process_queue.append(node.right	)
		return output






def 					UpperCamelCase   (      __magic_name__	:				Node | None       ,       __magic_name__	:				int	)  ->    Sequence[Node | None]:
		"""simple docstring"""




		lowercase__	     =						[]

		def populate_output(__magic_name__	:				Node | None       ,       __magic_name__	:				int	) -> None:
				if not root:
						return
				if level == 1:
						output.append(root.data	)
				elif level > 1:
						populate_output(root.left       ,       level - 1	)
						populate_output(root.right       ,       level - 1	)

		populate_output(__magic_name__       ,       __magic_name__	)
		return output






def 					UpperCamelCase   (      __magic_name__	:				Node | None       ,       __magic_name__	:				int	)  ->    Sequence[Node | None]:
		"""simple docstring"""




		lowercase__	     =						[]

		def populate_output(__magic_name__	:				Node | None       ,       __magic_name__	:				int	) -> None:
				if root is None:
						return
				if level == 1:
						output.append(root.data	)
				elif level > 1:
						populate_output(root.right       ,       level - 1	)
						populate_output(root.left       ,       level - 1	)

		populate_output(__magic_name__       ,       __magic_name__	)
		return output






def 					UpperCamelCase   (      __magic_name__	:				Node | None	)  ->    Sequence[Node | None] | list[Any]:
		"""simple docstring"""




		if root is None:
				return []

		lowercase__	     =						[]

		lowercase__	     =						0
		lowercase__	     =						height(__magic_name__	)

		for h in range(1       ,       height_tree + 1	):
				if not flag:
						output.append(get_nodes_from_left_to_right(__magic_name__       ,       __magic_name__	)	)
						lowercase__	     =						1
				else:
						output.append(get_nodes_from_right_to_left(__magic_name__       ,       __magic_name__	)	)
						lowercase__	     =						0

		return output






def 					UpperCamelCase   (      )  ->    None:  # Main function for testing.
		"""simple docstring"""




		lowercase__	     =						make_tree()
		print(f'''In-order Traversal: {inorder(__magic_name__	)}'''	)
		print(f'''Pre-order Traversal: {preorder(__magic_name__	)}'''	)
		print(f'''Post-order Traversal: {postorder(__magic_name__	)}'''       ,       """\n"""	)

		print(f'''Height of Tree: {height(__magic_name__	)}'''       ,       """\n"""	)

		print("""Complete Level Order Traversal: """	)
		print(level_order(__magic_name__	)       ,       """\n"""	)

		print("""Level-wise order Traversal: """	)

		for level in range(1       ,       height(__magic_name__	) + 1	):
				print(f'''Level {level}:'''       ,       get_nodes_from_left_to_right(__magic_name__       ,       level=__magic_name__	)	)

		print("""\nZigZag order Traversal: """	)
		print(zigzag(__magic_name__	)	)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()

