
"""simple docstring"""




import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


lowerCAmelCase__				=					namedtuple(
    '_TestCommandArgs',
    [
        'dataset',
        'name',
        'cache_dir',
        'data_dir',
        'all_configs',
        'save_infos',
        'ignore_verifications',
        'force_redownload',
        'clear_cache',
    ],
    defaults=[None, None, None, False, False, False, False, False],
)



def 							_lowerCamelCase			(			__a,				__a     ):
		return (abs(source - target     ) / target) < 0.0_1



@pytest.mark.integration
def 							_lowerCamelCase			(			__a     ):
		SCREAMING_SNAKE_CASE_    			=			_TestCommandArgs(dataset=__a,				all_configs=__a,				save_infos=__a     )
		SCREAMING_SNAKE_CASE_    			=			TestCommand(*__a     )
		test_command.run()
		SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				'''README.md'''     )
		assert os.path.exists(__a     )
		SCREAMING_SNAKE_CASE_    			=			DatasetInfosDict.from_directory(__a     )
		SCREAMING_SNAKE_CASE_    			=			DatasetInfosDict(
		    {
		        '''default''': DatasetInfo(
		            features=Features(
		                {
		                    '''tokens''': Sequence(Value('''string'''     )     ),
		                    '''ner_tags''': Sequence(
		                        ClassLabel(names=['''O''', '''B-PER''', '''I-PER''', '''B-ORG''', '''I-ORG''', '''B-LOC''', '''I-LOC''']     )     ),
		                    '''langs''': Sequence(Value('''string'''     )     ),
		                    '''spans''': Sequence(Value('''string'''     )     ),
		                }     ),				splits=[
		                {
		                    '''name''': '''train''',
		                    '''num_bytes''': 2_351_563,
		                    '''num_examples''': 10_000,
		                },
		                {
		                    '''name''': '''validation''',
		                    '''num_bytes''': 238_418,
		                    '''num_examples''': 1_000,
		                },
		            ],				download_size=3_940_680,				dataset_size=2_589_981,				)
		    }     )
		assert dataset_infos.keys() == expected_dataset_infos.keys()
		for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
				SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_    			=			getattr(dataset_infos['''default'''],				__a     ), getattr(expected_dataset_infos['''default'''],				__a     )
				if key == "num_bytes":
						assert is_apercent_close(__a,				__a     )
				elif key == "splits":
						assert list(__a     ) == list(__a     )
						for split in result:
								assert result[split].name == expected[split].name
								assert result[split].num_examples == expected[split].num_examples
								assert is_apercent_close(result[split].num_bytes,				expected[split].num_bytes     )
				else:
						result == expected

"""simple docstring"""




from __future__ import annotations

from collections.abc import Callable



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a = 100,				):
		SCREAMING_SNAKE_CASE_    			=			x_start
		SCREAMING_SNAKE_CASE_    			=			fnc(__a     )
		SCREAMING_SNAKE_CASE_    			=			0.0
		for _ in range(__a     ):
				# Approximates small segments of curve as linear and solve
				# for trapezoidal area
				SCREAMING_SNAKE_CASE_    			=			(x_end - x_start) / steps + xa
				SCREAMING_SNAKE_CASE_    			=			fnc(__a     )
				area += abs(fxa + fxa     ) * (xa - xa) / 2
				# Increment step
				SCREAMING_SNAKE_CASE_    			=			xa
				SCREAMING_SNAKE_CASE_    			=			fxa
		return area


if __name__ == "__main__":



						def 							_lowerCamelCase			(			__a     ):
								return x**3 + x**2

						print('f(x) = x^3 + x^2')
						print('The area between the curve, x = -5, x = 5 and the x axis is:')
						lowerCAmelCase__				=					10
						while i <= 100000:
												print(f'''with {i} steps: {trapezoidal_area(f, -5, 5, i)}''')
												i *= 10