




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       (				lowerCAmelCase						,	lowerCAmelCase   )->  Optional[Any]:
		assert isinstance(lowerCAmelCase						,	lowerCAmelCase   )
		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       (				lowerCAmelCase						,	lowerCAmelCase						,	lowerCAmelCase   )->  int:
		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(lowerCAmelCase						,	cache_dir=lowerCAmelCase						,	keep_in_memory=lowerCAmelCase   ).read()
		_check_csv_dataset(lowerCAmelCase						,	lowerCAmelCase   )


@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       (				lowerCAmelCase						,	lowerCAmelCase						,	lowerCAmelCase   )->  Optional[int]:
		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(lowerCAmelCase   ) for feature, dtype in features.items()}   ) if features is not None else None
		)
		SCREAMING_SNAKE_CASE_							=       CsvDatasetReader(lowerCAmelCase						,	features=lowerCAmelCase						,	cache_dir=lowerCAmelCase   ).read()
		_check_csv_dataset(lowerCAmelCase						,	lowerCAmelCase   )


@pytest.mark.parametrize('split'						,	[None, NamedSplit('train'   ), 'train', 'test']   )
def 				_a       (				lowerCAmelCase						,	lowerCAmelCase						,	lowerCAmelCase   )->  List[Any]:
		SCREAMING_SNAKE_CASE_							=       tmp_path / 'cache'
		SCREAMING_SNAKE_CASE_							=       {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
		SCREAMING_SNAKE_CASE_							=       CsvDatasetReader(lowerCAmelCase						,	cache_dir=lowerCAmelCase						,	split=lowerCAmelCase   ).read()
		_check_csv_dataset(lowerCAmelCase						,	lowerCAmelCase   )
		assert dataset.split == split if split else "train"


@pytest.mark.parametrize('path_type'						,	[str, list]   )
def 				_a       (				lowerCAmelCase						,	lowerCAmelCase						,	lowerCAmelCase   )->  str:
		if issubclass(lowerCAmelCase						,	lowerCAmelCase   ):
				SCREAMING_SNAKE_CASE_							=       csv_path
		elif issubclass(lowerCAmelCase						,	lowerCAmelCase   ):
				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(lowerCAmelCase						,	cache_dir=lowerCAmelCase   ).read()
		_check_csv_dataset(lowerCAmelCase						,	lowerCAmelCase   )


def 				_a       (				lowerCAmelCase						,	lowerCAmelCase						,	lowerCAmelCase=("train",)   )->  List[Any]:
		assert isinstance(lowerCAmelCase						,	lowerCAmelCase   )
		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 				_a       (				lowerCAmelCase						,	lowerCAmelCase						,	lowerCAmelCase   )->  Any:
		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=lowerCAmelCase						,	keep_in_memory=lowerCAmelCase   ).read()
		_check_csv_datasetdict(lowerCAmelCase						,	lowerCAmelCase   )


@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       (				lowerCAmelCase						,	lowerCAmelCase						,	lowerCAmelCase   )->  int:
		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(lowerCAmelCase   ) for feature, dtype in features.items()}   ) if features is not None else None
		)
		SCREAMING_SNAKE_CASE_							=       CsvDatasetReader({'train': csv_path}						,	features=lowerCAmelCase						,	cache_dir=lowerCAmelCase   ).read()
		_check_csv_datasetdict(lowerCAmelCase						,	lowerCAmelCase   )


@pytest.mark.parametrize('split'						,	[None, NamedSplit('train'   ), 'train', 'test']   )
def 				_a       (				lowerCAmelCase						,	lowerCAmelCase						,	lowerCAmelCase   )->  Optional[int]:
		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(lowerCAmelCase						,	cache_dir=lowerCAmelCase   ).read()
		_check_csv_datasetdict(lowerCAmelCase						,	lowerCAmelCase						,	splits=list(path.keys()   )   )
		assert all(dataset[split].split == split for split in path.keys()   )


def 				_a       (				lowerCAmelCase   )->  str:
		with open(lowerCAmelCase						,	encoding='utf-8'   ) as csvfile:
				yield from csv.reader(lowerCAmelCase   )


def 				_a       (				lowerCAmelCase						,	lowerCAmelCase   )->  Union[str, Any]:
		SCREAMING_SNAKE_CASE_							=       tmp_path / 'cache'
		SCREAMING_SNAKE_CASE_							=       os.path.join(lowerCAmelCase						,	'tmp.csv'   )
		SCREAMING_SNAKE_CASE_							=       CsvDatasetReader({'train': csv_path}						,	cache_dir=lowerCAmelCase   ).read()
		CsvDatasetWriter(dataset['train']						,	lowerCAmelCase						,	num_proc=1   ).write()

		SCREAMING_SNAKE_CASE_							=       iter_csv_file(lowerCAmelCase   )
		SCREAMING_SNAKE_CASE_							=       iter_csv_file(lowerCAmelCase   )

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


def 				_a       (				lowerCAmelCase						,	lowerCAmelCase   )->  str:
		SCREAMING_SNAKE_CASE_							=       tmp_path / 'cache'
		SCREAMING_SNAKE_CASE_							=       os.path.join(lowerCAmelCase						,	'tmp.csv'   )
		SCREAMING_SNAKE_CASE_							=       CsvDatasetReader({'train': csv_path}						,	cache_dir=lowerCAmelCase   ).read()
		CsvDatasetWriter(dataset['train']						,	lowerCAmelCase						,	num_proc=2   ).write()

		SCREAMING_SNAKE_CASE_							=       iter_csv_file(lowerCAmelCase   )
		SCREAMING_SNAKE_CASE_							=       iter_csv_file(lowerCAmelCase   )

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




def 				_a       (				lowerCAmelCase						,	lowerCAmelCase   )->  Tuple:
		SCREAMING_SNAKE_CASE_							=       tmp_path / 'cache'
		SCREAMING_SNAKE_CASE_							=       os.path.join(lowerCAmelCase						,	'tmp.csv'   )
		SCREAMING_SNAKE_CASE_							=       CsvDatasetReader({'train': csv_path}						,	cache_dir=lowerCAmelCase   ).read()
		with pytest.raises(lowerCAmelCase   ):
				CsvDatasetWriter(dataset['train']						,	lowerCAmelCase						,	num_proc=0   )





from __future__ import annotations


def 				_a       (				lowerCAmelCase						,	lowerCAmelCase   )->  Union[str, Any]:
		SCREAMING_SNAKE_CASE_							=       0
		SCREAMING_SNAKE_CASE_							=       len(lowerCAmelCase   ) - 1
		while left <= right:
				SCREAMING_SNAKE_CASE_							=       (left + right) // 2
				if left == right:
						if sorted_list[middle] < item:
								SCREAMING_SNAKE_CASE_							=       middle + 1
						break
				elif sorted_list[middle] < item:
						SCREAMING_SNAKE_CASE_							=       middle + 1
				else:
						SCREAMING_SNAKE_CASE_							=       middle - 1
		sorted_list.insert(lowerCAmelCase						,	lowerCAmelCase   )
		return sorted_list


def 				_a       (				lowerCAmelCase						,	lowerCAmelCase   )->  Any:
		SCREAMING_SNAKE_CASE_							=       []
		while left and right:
				if left[0][0] < right[0][0]:
						result.append(left.pop(0   )   )
				else:
						result.append(right.pop(0   )   )
		return result + left + right


def 				_a       (				lowerCAmelCase   )->  List[str]:
		SCREAMING_SNAKE_CASE_							=       len(lowerCAmelCase   )
		if length <= 1:
				return list_ad
		SCREAMING_SNAKE_CASE_							=       length // 2
		return merge(sortlist_ad(list_ad[:middle]   )						,	sortlist_ad(list_ad[middle:]   )   )


def 				_a       (				lowerCAmelCase   )->  list[int]:

		if len(lowerCAmelCase   ) <= 1:
				return collection
		SCREAMING_SNAKE_CASE_							=       []
		SCREAMING_SNAKE_CASE_							=       False
		for i in range(0						,	len(lowerCAmelCase   )						,	2   ):
				if i == len(lowerCAmelCase   ) - 1:
						SCREAMING_SNAKE_CASE_							=       True
				else:
						if collection[i] < collection[i + 1]:
								two_paired_list.append([collection[i], collection[i + 1]]   )
						else:
								two_paired_list.append([collection[i + 1], collection[i]]   )
		SCREAMING_SNAKE_CASE_							=       sortlist_ad(lowerCAmelCase   )
		SCREAMING_SNAKE_CASE_							=       [i[0] for i in sorted_list_ad]
		result.append(sorted_list_ad[-1][1]   )
		if has_last_odd_item:
				SCREAMING_SNAKE_CASE_							=       collection[-1]
				SCREAMING_SNAKE_CASE_							=       binary_search_insertion(lowerCAmelCase						,	lowerCAmelCase   )
		SCREAMING_SNAKE_CASE_							=       False
		for i in range(len(lowerCAmelCase   ) - 1   ):
				if result[i] == collection[-1] and has_last_odd_item:
						SCREAMING_SNAKE_CASE_							=       True
				SCREAMING_SNAKE_CASE_							=       sorted_list_ad[i][1]
				# If last_odd_item is inserted before the item's index,
				# you should forward index one more.
				if is_last_odd_item_inserted_before_this_index:
						SCREAMING_SNAKE_CASE_							=       result[: i + 2] + binary_search_insertion(result[i + 2 :]						,	lowerCAmelCase   )
				else:
						SCREAMING_SNAKE_CASE_							=       result[: i + 1] + binary_search_insertion(result[i + 1 :]						,	lowerCAmelCase   )

		return result


if __name__ == "__main__":
						SCREAMING_SNAKE_CASE:    List[str]											=   input('''Enter numbers separated by a comma:\n''').strip()
						SCREAMING_SNAKE_CASE:    Any											=   [int(item) for item in user_input.split(''',''')]
						print(merge_insertion_sort(unsorted))