"""simple docstring"""


import numpy as np





def 			lowerCamelCase_ (					__lowerCAmelCase   ,    __lowerCAmelCase="utf-8"   ,    __lowerCAmelCase="surrogatepass"				)							->					Dict:




						'''simple docstring'''



						lowerCamelCase__					=bin(int.from_bytes(text.encode(__lowerCAmelCase   ,    __lowerCAmelCase				)   ,    "big"				)				)[2:]
						return bits.zfill(8 * ((len(__lowerCAmelCase				) + 7) // 8)				)





def 			lowerCamelCase_ (					__lowerCAmelCase   ,    __lowerCAmelCase="utf-8"   ,    __lowerCAmelCase="surrogatepass"				)							->					Optional[Any]:




						'''simple docstring'''



						lowerCamelCase__					=int(__lowerCAmelCase   ,    2				)
						return n.to_bytes((n.bit_length() + 7) // 8   ,    "big"				).decode(__lowerCAmelCase   ,    __lowerCAmelCase				) or "\0"





def 			lowerCamelCase_ (					__lowerCAmelCase   ,    __lowerCAmelCase				)							->					Optional[Any]:




						'''simple docstring'''



						if size_par + len(__lowerCAmelCase				) <= 2**size_par - (len(__lowerCAmelCase				) - 1):
												raise ValueError("size of parity don't match with size of data"				)

						lowerCamelCase__					=[]
						lowerCamelCase__					=[]
						lowerCamelCase__					=[bin(__lowerCAmelCase				)[2:] for x in range(1   ,    size_par + len(__lowerCAmelCase				) + 1				)]

						# sorted information data for the size of the output data
						lowerCamelCase__					=[]
						# data position template + parity
						lowerCamelCase__					=[]
						# parity bit counter
						lowerCamelCase__					=0
						# counter position of data bits
						lowerCamelCase__					=0

						for x in range(1   ,    size_par + len(__lowerCAmelCase				) + 1				):
												# Performs a template of bit positions - who should be given,
												# and who should be parity
												if qtd_bp < size_par:
																		if (np.log(__lowerCAmelCase				) / np.log(2				)).is_integer():
																								data_out_gab.append("P"				)
																								lowerCamelCase__					=qtd_bp + 1
																		else:
																								data_out_gab.append("D"				)
												else:
																		data_out_gab.append("D"				)

												# Sorts the data to the new output size
												if data_out_gab[-1] == "D":
																		data_ord.append(data[cont_data]				)
																		cont_data += 1
												else:
																		data_ord.append(__lowerCAmelCase				)

    # Calculates parity
						lowerCamelCase__					=0  # parity bit counter
						for bp in range(1   ,    size_par + 1				):
												# Bit counter one for a given parity
												lowerCamelCase__					=0
												# counter to control the loop reading
												lowerCamelCase__					=0
												for x in data_ord:
																		if x is not None:
																								try:
																														lowerCamelCase__					=(bin_pos[cont_loop])[-1 * (bp)]
																								except IndexError:
																														lowerCamelCase__					="0"
																								if aux == "1" and x == "1":
																														cont_bo += 1
																		cont_loop += 1
												parity.append(cont_bo % 2				)

												qtd_bp += 1

						# Mount the message
						lowerCamelCase__					=0  # parity bit counter
						for x in range(0   ,    size_par + len(__lowerCAmelCase				)				):
												if data_ord[x] is None:
																		data_out.append(str(parity[cont_bp]				)				)
																		cont_bp += 1
												else:
																		data_out.append(data_ord[x]				)

						return data_out





def 			lowerCamelCase_ (					__lowerCAmelCase   ,    __lowerCAmelCase				)							->					Optional[Any]:




						'''simple docstring'''



						lowerCamelCase__					=[]
						# Parity bit counter
						lowerCamelCase__					=0
						# Counter p data bit reading
						lowerCamelCase__					=0
						# list of parity received
						lowerCamelCase__					=[]
						lowerCamelCase__					=[]

						for x in range(1   ,    len(__lowerCAmelCase				) + 1				):
												# Performs a template of bit positions - who should be given,
												#  and who should be parity
												if qtd_bp < size_par and (np.log(__lowerCAmelCase				) / np.log(2				)).is_integer():
																		data_out_gab.append("P"				)
																		lowerCamelCase__					=qtd_bp + 1
												else:
																		data_out_gab.append("D"				)

												# Sorts the data to the new output size
												if data_out_gab[-1] == "D":
																		data_output.append(data[cont_data]				)
												else:
																		parity_received.append(data[cont_data]				)
												cont_data += 1

						# -----------calculates the parity with the data
						lowerCamelCase__					=[]
						lowerCamelCase__					=[]
						lowerCamelCase__					=[bin(__lowerCAmelCase				)[2:] for x in range(1   ,    size_par + len(__lowerCAmelCase				) + 1				)]

						#  sorted information data for the size of the output data
						lowerCamelCase__					=[]
						# Data position feedback + parity
						lowerCamelCase__					=[]
						# Parity bit counter
						lowerCamelCase__					=0
						# Counter p data bit reading
						lowerCamelCase__					=0

						for x in range(1   ,    size_par + len(__lowerCAmelCase				) + 1				):
												# Performs a template position of bits - who should be given,
												# and who should be parity
												if qtd_bp < size_par and (np.log(__lowerCAmelCase				) / np.log(2				)).is_integer():
																		data_out_gab.append("P"				)
																		lowerCamelCase__					=qtd_bp + 1
												else:
																		data_out_gab.append("D"				)

												# Sorts the data to the new output size
												if data_out_gab[-1] == "D":
																		data_ord.append(data_output[cont_data]				)
																		cont_data += 1
												else:
																		data_ord.append(__lowerCAmelCase				)

    # Calculates parity
						lowerCamelCase__					=0  # parity bit counter
						for bp in range(1   ,    size_par + 1				):
												# Bit counter one for a certain parity
												lowerCamelCase__					=0
												# Counter to control loop reading
												lowerCamelCase__					=0
												for x in data_ord:
																		if x is not None:
																								try:
																														lowerCamelCase__					=(bin_pos[cont_loop])[-1 * (bp)]
																								except IndexError:
																														lowerCamelCase__					="0"
																								if aux == "1" and x == "1":
																														cont_bo += 1
																		cont_loop += 1
												parity.append(str(cont_bo % 2				)				)

												qtd_bp += 1

						# Mount the message
						lowerCamelCase__					=0  # Parity bit counter
						for x in range(0   ,    size_par + len(__lowerCAmelCase				)				):
												if data_ord[x] is None:
																		data_out.append(str(parity[cont_bp]				)				)
																		cont_bp += 1
												else:
																		data_out.append(data_ord[x]				)

						lowerCamelCase__					=parity_received == parity
						return data_output, ack










"""simple docstring"""


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 			snake_case  (A_      :Dict	,			A_      :Tuple      ):







  '''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 			snake_case  (A_      :str	,			A_      :List[Any]	,			A_      :Optional[Any]      ):







  '''simple docstring'''

  a     :			List[Any]				=   tmp_path / 'cache'
  a     :			str				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    a     :			Union[str, Any]				=   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 			snake_case  (A_      :List[str]	,			A_      :Union[str, Any]	,			A_      :Union[str, Any]      ):







  '''simple docstring'''

  a     :			str				=   tmp_path / 'cache'
  # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
  a     :			Optional[int]				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  a     :			Dict				=   features.copy() if features else default_expected_features
  a     :			Dict				=   (
      Features({feature: Value(A_      ) for feature, dtype in features.items()}      ) if features is not None else None
  )
  a     :			Tuple				=   CsvDatasetReader(A_	,			features=A_	,			cache_dir=A_      ).read()
  _check_csv_dataset(A_	,			A_      )




@pytest.mark.parametrize('split'	,			[None, NamedSplit('train'      ), 'train', 'test']      )
def 			snake_case  (A_      :List[str]	,			A_      :str	,			A_      :int      ):







  '''simple docstring'''

  a     :			str				=   tmp_path / 'cache'
  a     :			Tuple				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  a     :			List[str]				=   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 			snake_case  (A_      :int	,			A_      :List[Any]	,			A_      :str      ):







  '''simple docstring'''

  if issubclass(A_	,			A_      ):
    a     :			Dict				=   csv_path
  elif issubclass(A_	,			A_      ):
    a     :			Optional[Any]				=   [csv_path]
  a     :			Tuple				=   tmp_path / 'cache'
  a     :			str				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  a     :			Any				=   CsvDatasetReader(A_	,			cache_dir=A_      ).read()
  _check_csv_dataset(A_	,			A_      )




def 			snake_case  (A_      :List[str]	,			A_      :Dict	,			A_      :Optional[Any]=("train",)      ):







  '''simple docstring'''

  assert isinstance(A_	,			A_      )
  for split in splits:
    a     :			List[Any]				=   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 			snake_case  (A_      :str	,			A_      :Any	,			A_      :List[str]      ):







  '''simple docstring'''

  a     :			Any				=   tmp_path / 'cache'
  a     :			int				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    a     :			str				=   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 			snake_case  (A_      :Optional[int]	,			A_      :List[Any]	,			A_      :Tuple      ):







  '''simple docstring'''

  a     :			Dict				=   tmp_path / 'cache'
  # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
  a     :			Any				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  a     :			Tuple				=   features.copy() if features else default_expected_features
  a     :			Optional[int]				=   (
      Features({feature: Value(A_      ) for feature, dtype in features.items()}      ) if features is not None else None
  )
  a     :			Any				=   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 			snake_case  (A_      :List[str]	,			A_      :Optional[Any]	,			A_      :str      ):







  '''simple docstring'''

  if split:
    a     :			List[Any]				=   {split: csv_path}
  else:
    a     :			str				=   {'train': csv_path, 'test': csv_path}
  a     :			Union[str, Any]				=   tmp_path / 'cache'
  a     :			Tuple				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  a     :			List[str]				=   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 			snake_case  (A_      :Dict      ):







  '''simple docstring'''

  with open(A_	,			encoding='utf-8'      ) as csvfile:
    yield from csv.reader(A_      )




def 			snake_case  (A_      :int	,			A_      :Optional[int]      ):







  '''simple docstring'''

  a     :			str				=   tmp_path / 'cache'
  a     :			List[str]				=   os.path.join(A_	,			'tmp.csv'      )
  a     :			Union[str, Any]				=   CsvDatasetReader({'train': csv_path}	,			cache_dir=A_      ).read()
  CsvDatasetWriter(dataset['train']	,			A_	,			num_proc=1      ).write()

  a     :			int				=   iter_csv_file(A_      )
  a     :			Optional[Any]				=   iter_csv_file(A_      )

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




def 			snake_case  (A_      :Tuple	,			A_      :Tuple      ):







  '''simple docstring'''

  a     :			Union[str, Any]				=   tmp_path / 'cache'
  a     :			List[Any]				=   os.path.join(A_	,			'tmp.csv'      )
  a     :			Union[str, Any]				=   CsvDatasetReader({'train': csv_path}	,			cache_dir=A_      ).read()
  CsvDatasetWriter(dataset['train']	,			A_	,			num_proc=2      ).write()

  a     :			Dict				=   iter_csv_file(A_      )
  a     :			List[Any]				=   iter_csv_file(A_      )

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






def 			snake_case  (A_      :Union[str, Any]	,			A_      :List[Any]      ):







  '''simple docstring'''

  a     :			List[Any]				=   tmp_path / 'cache'
  a     :			Dict				=   os.path.join(A_	,			'tmp.csv'      )
  a     :			Union[str, Any]				=   CsvDatasetReader({'train': csv_path}	,			cache_dir=A_      ).read()
  with pytest.raises(A_      ):
    CsvDatasetWriter(dataset['train']	,			A_	,			num_proc=0      )




