


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 	lowercase_							(A			:			List[Any]		, A			:			Optional[int]				):
       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 	lowercase_							(A			:			List[Any]		, A			:			Dict		, A			:			List[str]				):
       snake_case__							:     int            =     tmp_path / 'cache'
       snake_case__							:     Tuple            =     {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
       with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
              snake_case__							:     str            =     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 	lowercase_							(A			:			Optional[int]		, A			:			Optional[Any]		, A			:			List[str]				):
       snake_case__							:     int            =     tmp_path / 'cache'
       # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
       snake_case__							:     int            =     {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
       snake_case__							:     str            =     features.copy() if features else default_expected_features
       snake_case__							:     Dict            =     (
           Features({feature: Value(A				) for feature, dtype in features.items()}				) if features is not None else None
       )
       snake_case__							:     str            =     CsvDatasetReader(A		, features=A		, cache_dir=A				).read()
       _check_csv_dataset(A		, A				)
@pytest.mark.parametrize('split'		, [None, NamedSplit('train'				), 'train', 'test']				)
def 	lowercase_							(A			:			Any		, A			:			Union[str, Any]		, A			:			int				):
       snake_case__							:     Optional[int]            =     tmp_path / 'cache'
       snake_case__							:     Union[str, Any]            =     {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
       snake_case__							:     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 	lowercase_							(A			:			Dict		, A			:			Optional[int]		, A			:			Any				):
       if issubclass(A		, A				):
              snake_case__							:     str            =     csv_path
       elif issubclass(A		, A				):
              snake_case__							:     List[str]            =     [csv_path]
       snake_case__							:     Dict            =     tmp_path / 'cache'
       snake_case__							:     List[str]            =     {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
       snake_case__							:     Optional[int]            =     CsvDatasetReader(A		, cache_dir=A				).read()
       _check_csv_dataset(A		, A				)
def 	lowercase_							(A			:			Optional[int]		, A			:			Dict		, A			:			int=("train",)				):
       assert isinstance(A		, A				)
       for split in splits:
              snake_case__							:     str            =     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 	lowercase_							(A			:			Optional[int]		, A			:			Union[str, Any]		, A			:			Optional[Any]				):
       snake_case__							:     str            =     tmp_path / 'cache'
       snake_case__							:     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():
              snake_case__							:     Optional[int]            =     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 	lowercase_							(A			:			Tuple		, A			:			Tuple		, A			:			Any				):
       snake_case__							:     Optional[int]            =     tmp_path / 'cache'
       # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
       snake_case__							:     Tuple            =     {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
       snake_case__							:     int            =     features.copy() if features else default_expected_features
       snake_case__							:     Union[str, Any]            =     (
           Features({feature: Value(A				) for feature, dtype in features.items()}				) if features is not None else None
       )
       snake_case__							:     Optional[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 	lowercase_							(A			:			Tuple		, A			:			Union[str, Any]		, A			:			Dict				):
       if split:
              snake_case__							:     Any            =     {split: csv_path}
       else:
              snake_case__							:     Union[str, Any]            =     {'train': csv_path, 'test': csv_path}
       snake_case__							:     str            =     tmp_path / 'cache'
       snake_case__							:     Any            =     {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
       snake_case__							:     int            =     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 	lowercase_							(A			:			int				):
       with open(A		, encoding='utf-8'				) as csvfile:
              yield from csv.reader(A				)
def 	lowercase_							(A			:			Optional[int]		, A			:			int				):
       snake_case__							:     Optional[Any]            =     tmp_path / 'cache'
       snake_case__							:     List[Any]            =     os.path.join(A		, 'tmp.csv'				)
       snake_case__							:     Dict            =     CsvDatasetReader({'train': csv_path}		, cache_dir=A				).read()
       CsvDatasetWriter(dataset['train']		, A		, num_proc=1				).write()

       snake_case__							:     int            =     iter_csv_file(A				)
       snake_case__							:     List[Any]            =     iter_csv_file(A				)

       for rowa, rowa in zip(A		, A				):
              assert rowa == rowa
def 	lowercase_							(A			:			Any		, A			:			Optional[int]				):
       snake_case__							:     str            =     tmp_path / 'cache'
       snake_case__							:     Optional[int]            =     os.path.join(A		, 'tmp.csv'				)
       snake_case__							:     Dict            =     CsvDatasetReader({'train': csv_path}		, cache_dir=A				).read()
       CsvDatasetWriter(dataset['train']		, A		, num_proc=2				).write()

       snake_case__							:     Union[str, Any]            =     iter_csv_file(A				)
       snake_case__							:     List[str]            =     iter_csv_file(A				)

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





def 	lowercase_							(A			:			str		, A			:			Optional[int]				):
       snake_case__							:     Optional[Any]            =     tmp_path / 'cache'
       snake_case__							:     List[Any]            =     os.path.join(A		, 'tmp.csv'				)
       snake_case__							:     str            =     CsvDatasetReader({'train': csv_path}		, cache_dir=A				).read()
       with pytest.raises(A				):
              CsvDatasetWriter(dataset['train']		, A		, num_proc=0				)











def 	lowercase_							(A			:			Dict				):
       snake_case__							:     Optional[int]            =     len(A				)
       for i in range(length - 1				):
              snake_case__							:     List[str]            =     False
              for j in range(length - 1 - i				):
                     if collection[j] > collection[j + 1]:
                            snake_case__							:     Optional[Any]            =     True
                            snake_case__     ,    snake_case__							:     Dict            =     collection[j + 1], collection[j]
              if not swapped:
                     break  # Stop iteration if the collection is sorted.
       return collection


if __name__ == "__main__":
 import doctest
 import time

 doctest.testmod()

 a_       :Any				  =				input("Enter numbers separated by a comma:").strip()
 a_       :Optional[Any]				  =				[int(item) for item in user_input.split(",")]
 a_       :Optional[int]				  =				time.process_time()
 print(*bubble_sort(unsorted), sep=",")
 print(F"""Processing time: {(time.process_time() - start)%1e9 + 7}""")






