

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


lowercase_             =     re.compile('[^A-Za-z_0-9]')
# parameters used in DuplicationIndex
lowercase_             =     1_0
lowercase_             =     2_5_6
def   a   (    A__			:     List[str]  )					->   Optional[MinHash]:





      """simple docstring"""



      if len(A__  ) < MIN_NUM_TOKENS:
            return None
      _lowercase			 =MinHash(num_perm=A__  )
      for token in set(A__  ):
            min_hash.update(token.encode()  )
      return min_hash
def   a   (    A__			:     str  )					->   Set[str]:





      """simple docstring"""



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





class 				__lowerCAmelCase  :




  def __init__(       self							,     *,
      lowerCAmelCase = 0.85							,     )						->				Any:
        '''simple docstring'''






        _lowercase			 =duplication_jaccard_threshold
        _lowercase			 =NUM_PERM
        _lowercase			 =MinHashLSH(threshold=self._duplication_jaccard_threshold							,     num_perm=self._num_perm      )

        _lowercase			 =defaultdict(lowerCAmelCase      )




  def 						A__  (       self							,     lowerCAmelCase							,     lowerCAmelCase      )						->				None:
        '''simple docstring'''






        _lowercase			 =self._index.query(lowerCAmelCase      )
        if code_key in self._index.keys:
              print(F'''Duplicate key {code_key}'''      )
              return

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




  def 						A__  (       self      )						->				List[List[Dict]]:
        '''simple docstring'''






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




  def 						A__  (       self							,     lowerCAmelCase      )						->				None:
        '''simple docstring'''






        _lowercase			 =self.get_duplicate_clusters()
        with open(lowerCAmelCase							,     'w'      ) as f:
              json.dump(lowerCAmelCase							,     lowerCAmelCase      )
def   a   (    A__			:     List[str]  )					->   Optional[Any]:





      """simple docstring"""



      _lowercase , _lowercase			 =element
      _lowercase			 =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   a   (    A__			:     Type[Dataset]  )					->   Tuple:





      """simple docstring"""



      with mp.Pool() as pool:
            for data in pool.imap_unordered(
                _compute_min_hash   ,     ThreadedIterator(A__   ,     max_queue_size=10000  )   ,     chunksize=100   ,     ):
                  if data is not None:
                        yield data
def   a   (    A__			:     Type[Dataset]   ,     A__			:     float  )					->   List[str]:





      """simple docstring"""



      _lowercase			 =DuplicationIndex(duplication_jaccard_threshold=A__  )

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

      # Returns a List[Cluster] where Cluster is List[str] with the filenames.
      return di.get_duplicate_clusters()
def   a   (    A__			:     str   ,     A__			:     str  )					->   float:





      """simple docstring"""



      _lowercase			 =get_tokens(A__  )
      _lowercase			 =get_tokens(A__  )
      return len(tokensa & tokensa  ) / len(tokensa | tokensa  )


lowercase_             =     None
def   a   (    A__			:     str   ,     A__			:     Union[str, Any]  )					->   Optional[int]:





      """simple docstring"""



      _lowercase			 =[]
      for elementa in cluster:
            _lowercase			 =_shared_dataset[elementa['base_index']]['content']
            for elementa in extremes:
                  _lowercase			 =_shared_dataset[elementa['base_index']]['content']
                  if jaccard_similarity(A__   ,     A__  ) >= jaccard_threshold:
                        elementa["copies"] += 1
                        break
            else:
                  _lowercase			 =1
                  extremes.append(A__  )
      return extremes
def   a   (    A__			:     Any   ,     A__			:     int   ,     A__			:     str  )					->   str:





      """simple docstring"""



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







def   a   (    A__			:     Type[Dataset]   ,     A__			:     float = 0.85  )					->   Tuple[Type[Dataset], List[List[Dict]]]:





      """simple docstring"""



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

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

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

      return ds_filter, duplicate_clusters





from __future__ import annotations

from typing import Any





class 				__lowerCAmelCase  :




  def __init__(       self							,     lowerCAmelCase      )						->				None:
        '''simple docstring'''






        _lowercase			 =num_of_nodes
        _lowercase			 =[]
        _lowercase			 ={}




  def 						A__  (       self							,     lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase      )						->				None:
        '''simple docstring'''






        self.m_edges.append([u_node, v_node, weight]      )




  def 						A__  (       self							,     lowerCAmelCase      )						->				int:
        '''simple docstring'''






        if self.m_component[u_node] == u_node:
              return u_node
        return self.find_component(self.m_component[u_node]      )




  def 						A__  (       self							,     lowerCAmelCase      )						->				None:
        '''simple docstring'''






        if self.m_component[u_node] != u_node:
              for k in self.m_component:
                    _lowercase			 =self.find_component(lowerCAmelCase      )




  def 						A__  (       self							,     lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase      )						->				None:
        '''simple docstring'''






        if component_size[u_node] <= component_size[v_node]:
              _lowercase			 =v_node
              component_size[v_node] += component_size[u_node]
              self.set_component(lowerCAmelCase      )

        elif component_size[u_node] >= component_size[v_node]:
              _lowercase			 =self.find_component(lowerCAmelCase      )
              component_size[u_node] += component_size[v_node]
              self.set_component(lowerCAmelCase      )




  def 						A__  (       self      )						->				None:
        '''simple docstring'''






        _lowercase			 =[]
        _lowercase			 =0

        _lowercase			 =[-1] * self.m_num_of_nodes

        # A list of components (initialized to all of the nodes)
        for node in range(self.m_num_of_nodes      ):
              self.m_component.update({node: node}      )
              component_size.append(1      )

        _lowercase			 =self.m_num_of_nodes

        while num_of_components > 1:
              for edge in self.m_edges:
                    _lowercase , _lowercase , _lowercase			 =edge

                    _lowercase			 =self.m_component[u]
                    _lowercase			 =self.m_component[v]

                    if u_component != v_component:

                          for component in (u_component, v_component):
                                if (
                                    minimum_weight_edge[component] == -1
                                    or minimum_weight_edge[component][2] > w
                                ):
                                      _lowercase			 =[u, v, w]

              for edge in minimum_weight_edge:
                    if isinstance(lowerCAmelCase							,     lowerCAmelCase      ):
                          _lowercase , _lowercase , _lowercase			 =edge

                          _lowercase			 =self.m_component[u]
                          _lowercase			 =self.m_component[v]

                          if u_component != v_component:
                                mst_weight += w
                                self.union(lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase      )
                                print(F'''Added edge [{u} - {v}]\nAdded weight: {w}\n'''      )
                                num_of_components -= 1

              _lowercase			 =[-1] * self.m_num_of_nodes
        print(F'''The total weight of the minimal spanning tree is: {mst_weight}'''      )
def   a   (    )					->   None:





      """simple docstring"""





if __name__ == "__main__":
  import doctest

  doctest.testmod()


