

import itertools
from dataclasses import dataclass
from io import StringIO
from typing import Optional

import pyarrow as pa

import datasets
from datasets.features.features import require_storage_cast
from datasets.table import table_cast


_UpperCamelCase			      =		datasets.utils.logging.get_logger(__name__)







@dataclass
class   __lowercase				(datasets.BuilderConfig			):
 _UpperCamelCase        =  None
 _UpperCamelCase        =  "utf-8"
 _UpperCamelCase        =  None
 _UpperCamelCase        =  10 << 20  # 10MB
 _UpperCamelCase        =  False
 _UpperCamelCase        =  "line"







class   __lowercase				(datasets.ArrowBasedBuilder			):
 _UpperCamelCase        =  TextConfig
 def      UpperCamelCase__  (							self ) ->Tuple:



       '''simple docstring'''





       return datasets.DatasetInfo(features=self.config.features )
 def      UpperCamelCase__  (							self				,							A_ ) ->Dict:



       '''simple docstring'''





       if not self.config.data_files:
             raise ValueError(f"""At least one data file must be specified, but got data_files={self.config.data_files}""" )
       __lowerCAmelCase :						Tuple = dl_manager.download_and_extract(self.config.data_files )
       if isinstance(A_				,							(str, list, tuple) ):
             __lowerCAmelCase :						int = data_files
             if isinstance(A_				,							A_ ):
                   __lowerCAmelCase :						List[str] = [files]
             __lowerCAmelCase :						List[Any] = [dl_manager.iter_files(A_ ) for file in files]
             return [datasets.SplitGenerator(name=datasets.Split.TRAIN				,							gen_kwargs={'''files''': files} )]
       __lowerCAmelCase :						Optional[int] = []
       for split_name, files in data_files.items():
             if isinstance(A_				,							A_ ):
                   __lowerCAmelCase :						Tuple = [files]
             __lowerCAmelCase :						Any = [dl_manager.iter_files(A_ ) for file in files]
             splits.append(datasets.SplitGenerator(name=A_				,							gen_kwargs={'''files''': files} ) )
       return splits
 def      UpperCamelCase__  (							self				,							A_ ) ->pa.Table:



       '''simple docstring'''





       if self.config.features is not None:
             __lowerCAmelCase :						Any = self.config.features.arrow_schema
             if all(not require_storage_cast(A_ ) for feature in self.config.features.values() ):
                   # cheaper cast
                   __lowerCAmelCase :						int = pa_table.cast(A_ )
             else:
                   # more expensive cast; allows str <-> int/float or str to Audio for example
                   __lowerCAmelCase :						Union[str, Any] = table_cast(A_				,							A_ )
             return pa_table
       else:
             return pa_table.cast(pa.schema({'''text''': pa.string()} ) )





 def      UpperCamelCase__  (							self				,							A_ ) ->str:



       '''simple docstring'''





       __lowerCAmelCase :						int = list(self.config.features ) if self.config.features is not None else ['''text''']
       for file_idx, file in enumerate(itertools.chain.from_iterable(A_ ) ):
             # open in text mode, by default translates universal newlines ("\n", "\r\n" and "\r") into "\n"
             with open(A_				,							encoding=self.config.encoding				,							errors=self.config.errors ) as f:
                   if self.config.sample_by == "line":
                         __lowerCAmelCase :						Optional[Any] = 0
                         while True:
                               __lowerCAmelCase :						str = f.read(self.config.chunksize )
                               if not batch:
                                     break
                               batch += f.readline()  # finish current line
                               # StringIO.readlines, by default splits only on "\n" (and keeps line breaks)
                               __lowerCAmelCase :						Any = StringIO(A_ ).readlines()
                               if not self.config.keep_linebreaks:
                                     __lowerCAmelCase :						int = [line.rstrip('''\n''' ) for line in batch]
                               __lowerCAmelCase :						Optional[int] = pa.Table.from_arrays([pa.array(A_ )]				,							names=A_ )
                               # Uncomment for debugging (will print the Arrow table size and elements)
                               # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                               # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                               yield (file_idx, batch_idx), self._cast_table(A_ )
                               batch_idx += 1
                   elif self.config.sample_by == "paragraph":
                         __lowerCAmelCase :						str = 0
                         __lowerCAmelCase :						Optional[int] = ''''''
                         while True:
                               __lowerCAmelCase :						str = f.read(self.config.chunksize )
                               if not new_batch:
                                     break
                               batch += new_batch
                               batch += f.readline()  # finish current line
                               __lowerCAmelCase :						Any = batch.split('''\n\n''' )
                               __lowerCAmelCase :						Union[str, Any] = pa.Table.from_arrays(
                                   [pa.array([example for example in batch[:-1] if example] )]				,							names=A_ )
                               # Uncomment for debugging (will print the Arrow table size and elements)
                               # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                               # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                               yield (file_idx, batch_idx), self._cast_table(A_ )
                               batch_idx += 1
                               __lowerCAmelCase :						Tuple = batch[-1]
                         if batch:
                               __lowerCAmelCase :						List[Any] = pa.Table.from_arrays([pa.array([batch] )]				,							names=A_ )
                               yield (file_idx, batch_idx), self._cast_table(A_ )
                   elif self.config.sample_by == "document":
                         __lowerCAmelCase :						str = f.read()
                         __lowerCAmelCase :						List[Any] = pa.Table.from_arrays([pa.array([text] )]				,							names=A_ )
                         yield file_idx, self._cast_table(A_ )





import heapq







def 		_lowercase			(					lowercase__       ,     lowercase__       ,     lowercase__						):
      __lowerCAmelCase :						Union[str, Any] = [(0, start)]  # cost from start node,end node
      __lowerCAmelCase :						Any = set()
      while heap:
            ((__lowerCAmelCase),							(__lowerCAmelCase)) :						str = heapq.heappop(lowercase__						)
            if u in visited:
                  continue
            visited.add(lowercase__						)
            if u == end:
                  return cost
            for v, c in graph[u]:
                  if v in visited:
                        continue
                  __lowerCAmelCase :						str = cost + c
                  heapq.heappush(lowercase__       ,     (next_item, v)						)
      return -1


_UpperCamelCase			      =		{
    "A": [["B", 2], ["C", 5]],
    "B": [["A", 2], ["D", 3], ["E", 1], ["F", 1]],
    "C": [["A", 5], ["F", 3]],
    "D": [["B", 3]],
    "E": [["B", 4], ["F", 3]],
    "F": [["C", 3], ["E", 3]],
}
_UpperCamelCase			      =		{
    "B": [["C", 1]],
    "C": [["D", 1]],
    "D": [["F", 1]],
    "E": [["B", 1], ["F", 3]],
    "F": [],
}
_UpperCamelCase			      =		{
    "B": [["C", 1]],
    "C": [["D", 1]],
    "D": [["F", 1]],
    "E": [["B", 1], ["G", 2]],
    "F": [],
    "G": [["F", 1]],
}

_UpperCamelCase			      =		dijkstra(G, "E", "C")
print(short_distance)  # E -- 3 --> F -- 3 --> C == 6

_UpperCamelCase			      =		dijkstra(Ga, "E", "F")
print(short_distance)  # E -- 3 --> F == 3

_UpperCamelCase			      =		dijkstra(Ga, "E", "F")
print(short_distance)  # E -- 2 --> G -- 1 --> F == 3

if __name__ == "__main__":
 import doctest

 doctest.testmod()


