




"""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 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


						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 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


						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__    :   List[str]							     =   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 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


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



@pytest.mark.parametrize('''split''' ,     [None, NamedSplit('''train'''						), '''train''', '''test''']						)
def 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


						snake_case__    :   str							     =   tmp_path / '''cache'''
						snake_case__    :   List[Any]							     =   {'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						snake_case__    :   Optional[int]							     =   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 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


						if issubclass(lowerCamelCase ,     lowerCamelCase						):
												snake_case__    :   List[Any]							     =   csv_path
						elif issubclass(lowerCamelCase ,     lowerCamelCase						):
												snake_case__    :   int							     =   [csv_path]
						snake_case__    :   List[Any]							     =   tmp_path / '''cache'''
						snake_case__    :   Any							     =   {'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						snake_case__    :   List[Any]							     =   CsvDatasetReader(lowerCamelCase ,     cache_dir=lowerCamelCase						).read()
						_check_csv_dataset(lowerCamelCase ,     lowerCamelCase						)



def 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase ,     lowerCamelCase=("train",)						):
						'''simple docstring'''


						assert isinstance(lowerCamelCase ,     lowerCamelCase						)
						for split in splits:
												snake_case__    :   int							     =   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 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


						snake_case__    :   List[Any]							     =   tmp_path / '''cache'''
						snake_case__    :   List[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():
												snake_case__    :   Tuple							     =   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 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


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


						if split:
												snake_case__    :   Union[str, Any]							     =   {split: csv_path}
						else:
												snake_case__    :   Optional[Any]							     =   {'''train''': csv_path, '''test''': csv_path}
						snake_case__    :   Dict							     =   tmp_path / '''cache'''
						snake_case__    :   List[str]							     =   {'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						snake_case__    :   Tuple							     =   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 						lowerCAmelCase							(	lowerCamelCase						):
						'''simple docstring'''


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



def 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


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

						snake_case__    :   Optional[int]							     =   iter_csv_file(lowerCamelCase						)
						snake_case__    :   List[str]							     =   iter_csv_file(lowerCamelCase						)

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



def 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


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

						snake_case__    :   List[Any]							     =   iter_csv_file(lowerCamelCase						)
						snake_case__    :   Dict							     =   iter_csv_file(lowerCamelCase						)

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



def 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


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








"""simple docstring"""





from __future__ import annotations

import math
import random

def 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


						snake_case__    :   Tuple							     =   d * e - 1
						snake_case__    :   Optional[int]							     =   0
						snake_case__    :   Tuple							     =   0
						while p == 0:
												snake_case__    :   Optional[int]							     =   random.randint(2 ,     n - 1						)
												snake_case__    :   Tuple							     =   k
												while True:
																		if t % 2 == 0:
																								snake_case__    :   List[Any]							     =   t // 2
																								snake_case__    :   Union[str, Any]							     =   (g**t) % n
																								snake_case__    :   Dict							     =   math.gcd(x - 1 ,     lowerCamelCase						)
																								if x > 1 and y > 1:
																														snake_case__    :   Union[str, Any]							     =   y
																														snake_case__    :   str							     =   n // y
																														break  # find the correct factors
																		else:
																								break  # t is not divisible by 2, break and choose another g
						return sorted([p, q]						)


if __name__ == "__main__":
							import doctest

							doctest.testmod()


