

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__							(  lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







     assert isinstance(__lowercase,       __lowercase     )
     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__							(  lowerCAmelCase_,       lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE 		=tmp_path / 'cache'
     SCREAMING_SNAKE_CASE 		={'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
     with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
          SCREAMING_SNAKE_CASE 		=CsvDatasetReader(__lowercase,       cache_dir=__lowercase,       keep_in_memory=__lowercase     ).read()
     _check_csv_dataset(__lowercase,       __lowercase     )







@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__							(  lowerCAmelCase_,       lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







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







@pytest.mark.parametrize('split',       [None, NamedSplit('train'     ), 'train', 'test']     )
def      snake_case__							(  lowerCAmelCase_,       lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE 		=tmp_path / 'cache'
     SCREAMING_SNAKE_CASE 		={'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
     SCREAMING_SNAKE_CASE 		=CsvDatasetReader(__lowercase,       cache_dir=__lowercase,       split=__lowercase     ).read()
     _check_csv_dataset(__lowercase,       __lowercase     )
     assert dataset.split == split if split else "train"







@pytest.mark.parametrize('path_type',       [str, list]     )
def      snake_case__							(  lowerCAmelCase_,       lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







     if issubclass(__lowercase,       __lowercase     ):
          SCREAMING_SNAKE_CASE 		=csv_path
     elif issubclass(__lowercase,       __lowercase     ):
          SCREAMING_SNAKE_CASE 		=[csv_path]
     SCREAMING_SNAKE_CASE 		=tmp_path / 'cache'
     SCREAMING_SNAKE_CASE 		={'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
     SCREAMING_SNAKE_CASE 		=CsvDatasetReader(__lowercase,       cache_dir=__lowercase     ).read()
     _check_csv_dataset(__lowercase,       __lowercase     )







def      snake_case__							(  lowerCAmelCase_,       lowerCAmelCase_,       lowerCAmelCase_=("train",)     ):





     """simple docstring"""







     assert isinstance(__lowercase,       __lowercase     )
     for split in splits:
          SCREAMING_SNAKE_CASE 		=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__							(  lowerCAmelCase_,       lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE 		=tmp_path / 'cache'
     SCREAMING_SNAKE_CASE 		={'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
     with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
          SCREAMING_SNAKE_CASE 		=CsvDatasetReader({'train': csv_path},       cache_dir=__lowercase,       keep_in_memory=__lowercase     ).read()
     _check_csv_datasetdict(__lowercase,       __lowercase     )







@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__							(  lowerCAmelCase_,       lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE 		=tmp_path / 'cache'
     # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
     SCREAMING_SNAKE_CASE 		={'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
     SCREAMING_SNAKE_CASE 		=features.copy() if features else default_expected_features
     SCREAMING_SNAKE_CASE 		=(
         Features({feature: Value(__lowercase     ) for feature, dtype in features.items()}     ) if features is not None else None
     )
     SCREAMING_SNAKE_CASE 		=CsvDatasetReader({'train': csv_path},       features=__lowercase,       cache_dir=__lowercase     ).read()
     _check_csv_datasetdict(__lowercase,       __lowercase     )







@pytest.mark.parametrize('split',       [None, NamedSplit('train'     ), 'train', 'test']     )
def      snake_case__							(  lowerCAmelCase_,       lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







     if split:
          SCREAMING_SNAKE_CASE 		={split: csv_path}
     else:
          SCREAMING_SNAKE_CASE 		={'train': csv_path, 'test': csv_path}
     SCREAMING_SNAKE_CASE 		=tmp_path / 'cache'
     SCREAMING_SNAKE_CASE 		={'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
     SCREAMING_SNAKE_CASE 		=CsvDatasetReader(__lowercase,       cache_dir=__lowercase     ).read()
     _check_csv_datasetdict(__lowercase,       __lowercase,       splits=list(path.keys()     )     )
     assert all(dataset[split].split == split for split in path.keys()     )







def      snake_case__							(  lowerCAmelCase_     ):





     """simple docstring"""







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







def      snake_case__							(  lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







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

     SCREAMING_SNAKE_CASE 		=iter_csv_file(__lowercase     )
     SCREAMING_SNAKE_CASE 		=iter_csv_file(__lowercase     )

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







def      snake_case__							(  lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







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

     SCREAMING_SNAKE_CASE 		=iter_csv_file(__lowercase     )
     SCREAMING_SNAKE_CASE 		=iter_csv_file(__lowercase     )

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







def      snake_case__							(  lowerCAmelCase_,       lowerCAmelCase_     ):





     """simple docstring"""







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





"""simple docstring"""


def   a__			(					__lowercase )						->						bool:
				# must be
				_A       	=      [list(__lowercase ) for row in matrix]
				if matrix and isinstance(__lowercase  ,      __lowercase ):
								if isinstance(matrix[0]  ,      __lowercase ):
												_A       	=      0
												for row in matrix:
																if prev_len == 0:
																				_A       	=      len(__lowercase )
																				_A       	=      True
																else:
																				_A       	=      prev_len == len(__lowercase )
								else:
												_A       	=      True
				else:
								_A       	=      False

				return result






def   a__			(					__lowercase )						->						None:
				if check_matrix(__lowercase ) and len(__lowercase ) > 0:
								_A       	=      [list(__lowercase ) for row in a]
								_A       	=      len(__lowercase )
								if isinstance(a[0]  ,      __lowercase ):
												_A       	=      len(a[0] )
								else:
												for dat in a:
																print(__lowercase )
												return

								# horizotal printing increasing
								for i in range(0  ,      __lowercase ):
												print(a[0][i] )
								# vertical printing down
								for i in range(1  ,      __lowercase ):
												print(a[i][mat_col - 1] )
								# horizotal printing decreasing
								if mat_row > 1:
												for i in range(mat_col - 2  ,      -1  ,      -1 ):
																print(a[mat_row - 1][i] )
        # vertical printing up
								for i in range(mat_row - 2  ,      0  ,      -1 ):
												print(a[i][0] )
								_A       	=      [row[1 : mat_col - 1] for row in a[1 : mat_row - 1]]
								if len(__lowercase ) > 0:
												spiral_print_clockwise(__lowercase )
								else:
												return
				else:
								print("Not a valid matrix" )
								return






def   a__			(					__lowercase )						->						list[int]:
				if matrix:
								return list(matrix.pop(0 ) ) + spiral_traversal(list(zip(*__lowercase ) )[::-1] )
				else:
								return []


# driver code
if __name__ == "__main__":
		import doctest

		doctest.testmod()

		a_											=     [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
		spiral_print_clockwise(a)