



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			(		__UpperCAmelCase							,					__UpperCAmelCase	)       ->       Union[str, Any]:



						'''simple docstring'''






						assert isinstance(__UpperCAmelCase							,					__UpperCAmelCase	)
						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			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       str:



						'''simple docstring'''






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







@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			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       Tuple:



						'''simple docstring'''






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







@pytest.mark.parametrize('''split'''							,					[None, NamedSplit('''train'''	), '''train''', '''test''']	)
def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       List[str]:



						'''simple docstring'''






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







@pytest.mark.parametrize('''path_type'''							,					[str, list]	)
def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       Optional[int]:



						'''simple docstring'''






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







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase=("train",)	)       ->       Any:



						'''simple docstring'''






						assert isinstance(__UpperCAmelCase							,					__UpperCAmelCase	)
						for split in splits:
												UpperCAmelCase_     							=     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			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       List[str]:



						'''simple docstring'''






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







@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			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       Optional[int]:



						'''simple docstring'''






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







@pytest.mark.parametrize('''split'''							,					[None, NamedSplit('''train'''	), '''train''', '''test''']	)
def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       Union[str, Any]:



						'''simple docstring'''






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







def 				A			(		__UpperCAmelCase	)       ->       str:



						'''simple docstring'''






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







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase	)       ->       Dict:



						'''simple docstring'''






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

						UpperCAmelCase_     							=     iter_csv_file(__UpperCAmelCase	)
						UpperCAmelCase_     							=     iter_csv_file(__UpperCAmelCase	)

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







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase	)       ->       Tuple:



						'''simple docstring'''






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

						UpperCAmelCase_     							=     iter_csv_file(__UpperCAmelCase	)
						UpperCAmelCase_     							=     iter_csv_file(__UpperCAmelCase	)

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







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase	)       ->       Dict:



						'''simple docstring'''






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










from __future__ import annotations

from pathlib import Path







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase	)       ->       int:



						'''simple docstring'''






						return pointa[0] * pointa[1] - pointa[1] * pointa[0]







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       bool:



						'''simple docstring'''






						UpperCAmelCase_     							=     (xa, ya)
						UpperCAmelCase_     							=     (xa - xa, ya - ya)
						UpperCAmelCase_     							=     (xa - xa, ya - ya)
						UpperCAmelCase_     							=     -vector_product(__UpperCAmelCase							,					__UpperCAmelCase	) / vector_product(
						    __UpperCAmelCase							,					__UpperCAmelCase	)
						UpperCAmelCase_     							=     +vector_product(__UpperCAmelCase							,					__UpperCAmelCase	) / vector_product(
						    __UpperCAmelCase							,					__UpperCAmelCase	)

						return a > 0 and b > 0 and a + b < 1







def 				A			(		__UpperCAmelCase = "p102_triangles.txt"	)       ->       int:



						'''simple docstring'''






						UpperCAmelCase_     							=     Path(__UpperCAmelCase	).parent.joinpath(__UpperCAmelCase	).read_text(encoding='''utf-8'''	)

						UpperCAmelCase_     							=     []
						for line in data.strip().split('''\n'''	):
												triangles.append([int(__UpperCAmelCase	) for number in line.split(''','''	)]	)

						UpperCAmelCase_     							=     0
						UpperCAmelCase_     							=     42

						for triangle in triangles:
												ret += contains_origin(*__UpperCAmelCase	)

						return ret


if __name__ == "__main__":
							print(f"{solution() = }")





