

import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def 					a				(      A__     :       Optional[Any]				,       A__     :       str					)   ->				Any:





      """simple docstring"""



      assert isinstance(A__				,       A__					)
      assert dataset.num_rows == 4
      assert dataset.num_columns == 3
      assert dataset.column_names == ["col_1", "col_2", "col_3"]
      for feature, expected_dtype in expected_features.items():
            assert dataset.features[feature].dtype == expected_dtype
@pytest.mark.parametrize('keep_in_memory'				,       [False, True]					)
def 					a				(      A__     :       str				,       A__     :       Union[str, Any]				,       A__     :       Optional[Any]					)   ->				Union[str, Any]:





      """simple docstring"""



      _lowercase     	=tmp_path / """cache"""
      _lowercase     	={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
      with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
            _lowercase     	=CsvDatasetReader(A__				,       cache_dir=A__				,       keep_in_memory=A__					).read()
      _check_csv_dataset(A__				,       A__					)
@pytest.mark.parametrize(
    'features'				,       [
        None,
        {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'},
        {'col_1': 'string', 'col_2': 'string', 'col_3': 'string'},
        {'col_1': 'int32', 'col_2': 'int32', 'col_3': 'int32'},
        {'col_1': 'float32', 'col_2': 'float32', 'col_3': 'float32'},
    ]				,       )
def 					a				(      A__     :       str				,       A__     :       str				,       A__     :       Any					)   ->				Any:





      """simple docstring"""



      _lowercase     	=tmp_path / """cache"""
      # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
      _lowercase     	={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
      _lowercase     	=features.copy() if features else default_expected_features
      _lowercase     	=(
          Features({feature: Value(A__					) for feature, dtype in features.items()}					) if features is not None else None
      )
      _lowercase     	=CsvDatasetReader(A__				,       features=A__				,       cache_dir=A__					).read()
      _check_csv_dataset(A__				,       A__					)
@pytest.mark.parametrize('split'				,       [None, NamedSplit('train'					), 'train', 'test']					)
def 					a				(      A__     :       List[str]				,       A__     :       Optional[Any]				,       A__     :       int					)   ->				str:





      """simple docstring"""



      _lowercase     	=tmp_path / """cache"""
      _lowercase     	={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
      _lowercase     	=CsvDatasetReader(A__				,       cache_dir=A__				,       split=A__					).read()
      _check_csv_dataset(A__				,       A__					)
      assert dataset.split == split if split else "train"
@pytest.mark.parametrize('path_type'				,       [str, list]					)
def 					a				(      A__     :       Optional[Any]				,       A__     :       List[Any]				,       A__     :       Any					)   ->				List[Any]:





      """simple docstring"""



      if issubclass(A__				,       A__					):
            _lowercase     	=csv_path
      elif issubclass(A__				,       A__					):
            _lowercase     	=[csv_path]
      _lowercase     	=tmp_path / """cache"""
      _lowercase     	={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
      _lowercase     	=CsvDatasetReader(A__				,       cache_dir=A__					).read()
      _check_csv_dataset(A__				,       A__					)
def 					a				(      A__     :       int				,       A__     :       Dict				,       A__     :       List[str]=("train",)					)   ->				int:





      """simple docstring"""



      assert isinstance(A__				,       A__					)
      for split in splits:
            _lowercase     	=dataset_dict[split]
            assert dataset.num_rows == 4
            assert dataset.num_columns == 3
            assert dataset.column_names == ["col_1", "col_2", "col_3"]
            for feature, expected_dtype in expected_features.items():
                  assert dataset.features[feature].dtype == expected_dtype
@pytest.mark.parametrize('keep_in_memory'				,       [False, True]					)
def 					a				(      A__     :       Union[str, Any]				,       A__     :       List[Any]				,       A__     :       Optional[int]					)   ->				int:





      """simple docstring"""



      _lowercase     	=tmp_path / """cache"""
      _lowercase     	={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
      with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
            _lowercase     	=CsvDatasetReader({'train': csv_path}				,       cache_dir=A__				,       keep_in_memory=A__					).read()
      _check_csv_datasetdict(A__				,       A__					)
@pytest.mark.parametrize(
    'features'				,       [
        None,
        {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'},
        {'col_1': 'string', 'col_2': 'string', 'col_3': 'string'},
        {'col_1': 'int32', 'col_2': 'int32', 'col_3': 'int32'},
        {'col_1': 'float32', 'col_2': 'float32', 'col_3': 'float32'},
    ]				,       )
def 					a				(      A__     :       List[Any]				,       A__     :       Optional[Any]				,       A__     :       Dict					)   ->				List[str]:





      """simple docstring"""



      _lowercase     	=tmp_path / """cache"""
      # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
      _lowercase     	={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
      _lowercase     	=features.copy() if features else default_expected_features
      _lowercase     	=(
          Features({feature: Value(A__					) for feature, dtype in features.items()}					) if features is not None else None
      )
      _lowercase     	=CsvDatasetReader({'train': csv_path}				,       features=A__				,       cache_dir=A__					).read()
      _check_csv_datasetdict(A__				,       A__					)
@pytest.mark.parametrize('split'				,       [None, NamedSplit('train'					), 'train', 'test']					)
def 					a				(      A__     :       Optional[Any]				,       A__     :       Optional[int]				,       A__     :       Any					)   ->				Union[str, Any]:





      """simple docstring"""



      if split:
            _lowercase     	={split: csv_path}
      else:
            _lowercase     	={"""train""": csv_path, """test""": csv_path}
      _lowercase     	=tmp_path / """cache"""
      _lowercase     	={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
      _lowercase     	=CsvDatasetReader(A__				,       cache_dir=A__					).read()
      _check_csv_datasetdict(A__				,       A__				,       splits=list(path.keys()					)					)
      assert all(dataset[split].split == split for split in path.keys()					)
def 					a				(      A__     :       int					)   ->				int:





      """simple docstring"""



      with open(A__				,       encoding='utf-8'					) as csvfile:
            yield from csv.reader(A__					)
def 					a				(      A__     :       Dict				,       A__     :       List[str]					)   ->				Dict:





      """simple docstring"""



      _lowercase     	=tmp_path / """cache"""
      _lowercase     	=os.path.join(A__				,       'tmp.csv'					)
      _lowercase     	=CsvDatasetReader({'train': csv_path}				,       cache_dir=A__					).read()
      CsvDatasetWriter(dataset['train']				,       A__				,       num_proc=1					).write()

      _lowercase     	=iter_csv_file(A__					)
      _lowercase     	=iter_csv_file(A__					)

      for rowa, rowa in zip(A__				,       A__					):
            assert rowa == rowa
def 					a				(      A__     :       List[Any]				,       A__     :       Optional[int]					)   ->				Optional[int]:





      """simple docstring"""



      _lowercase     	=tmp_path / """cache"""
      _lowercase     	=os.path.join(A__				,       'tmp.csv'					)
      _lowercase     	=CsvDatasetReader({'train': csv_path}				,       cache_dir=A__					).read()
      CsvDatasetWriter(dataset['train']				,       A__				,       num_proc=2					).write()

      _lowercase     	=iter_csv_file(A__					)
      _lowercase     	=iter_csv_file(A__					)

      for rowa, rowa in zip(A__				,       A__					):
            assert rowa == rowa







def 					a				(      A__     :       Optional[int]				,       A__     :       Optional[int]					)   ->				Optional[int]:





      """simple docstring"""



      _lowercase     	=tmp_path / """cache"""
      _lowercase     	=os.path.join(A__				,       'tmp.csv'					)
      _lowercase     	=CsvDatasetReader({'train': csv_path}				,       cache_dir=A__					).read()
      with pytest.raises(A__					):
            CsvDatasetWriter(dataset['train']				,       A__				,       num_proc=0					)





from __future__ import annotations

import random
import string





class 			__lowerCAmelCase					:




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






        _lowercase     	=passcode or self.__passcode_creator()
        _lowercase     	=self.__make_key_list()
        _lowercase     	=self.__make_shift_key()




  def __str__(    self )  ->			str:
        '''simple docstring'''






        return "".join(self.__passcode )




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






        for i in range(1							,       len(lowerCAmelCase )							,       2 ):
              iterlist[i] *= -1
        return iterlist




  def   A__					(    self )  ->			list[str]:
        '''simple docstring'''






        _lowercase     	=string.ascii_letters + string.digits
        _lowercase     	=[random.choice(lowerCAmelCase ) for _ in range(random.randint(10							,       20 ) )]
        return password




  def   A__					(    self )  ->			list[str]:
        '''simple docstring'''






        _lowercase     	=(
            string.ascii_letters + string.digits + string.punctuation + ' \t\n'
        )

        _lowercase     	=[]

        # creates points known as breakpoints to break the key_list_options at those
        # points and pivot each substring
        _lowercase     	=sorted(set(self.__passcode ) )
        _lowercase     	=[]

        # algorithm for creating a new shuffled list, keys_l, out of key_list_options
        for i in key_list_options:
              temp_list.extend(lowerCAmelCase )

              # checking breakpoints at which to pivot temporary sublist and add it into
              # keys_l
              if i in breakpoints or i == key_list_options[-1]:
                    keys_l.extend(temp_list[::-1] )
                    temp_list.clear()

        # returning a shuffled keys_l to prevent brute force guessing of shift key
        return keys_l




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






        _lowercase     	=sum(self.__neg_pos([ord(lowerCAmelCase ) for x in self.__passcode] ) )
        return num if num > 0 else len(self.__passcode )




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






        _lowercase     	=''

        # decoding shift like Caesar cipher algorithm implementing negative shift or
        # reverse shift or left shift
        for i in encoded_message:
              _lowercase     	=self.__key_list.index(lowerCAmelCase )
              decoded_message += self.__key_list[
                  (position - self.__shift_key) % -len(self.__key_list )
              ]

        return decoded_message




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






        _lowercase     	=''

        # encoding shift like Caesar cipher algorithm implementing positive shift or
        # forward shift or right shift
        for i in plaintext:
              _lowercase     	=self.__key_list.index(lowerCAmelCase )
              encoded_message += self.__key_list[
                  (position + self.__shift_key) % len(self.__key_list )
              ]

        return encoded_message
def 					a				(      A__     :       str = "Hello, this is a modified Caesar cipher"					)   ->				str:





      """simple docstring"""



      _lowercase     	=ShuffledShiftCipher()
      return cipa.decrypt(cipa.encrypt(A__					)					)


if __name__ == "__main__":
  import doctest

  doctest.testmod()


