






import io
import json

import fsspec
import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases




def      __A					(     _lowercase					,			_lowercase ):

					'''simple docstring'''







					assert isinstance(_lowercase					,			_lowercase )
					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					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= tmp_path / '''cache'''
					_A								= {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
										_A								= JsonDatasetReader(_lowercase					,			cache_dir=_lowercase					,			keep_in_memory=_lowercase ).read()
					_check_json_dataset(_lowercase					,			_lowercase )




@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					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= tmp_path / '''cache'''
					_A								= {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					_A								= features.copy() if features else default_expected_features
					_A								= (
					    Features({feature: Value(_lowercase ) for feature, dtype in features.items()} ) if features is not None else None
					)
					_A								= JsonDatasetReader(_lowercase					,			features=_lowercase					,			cache_dir=_lowercase ).read()
					_check_json_dataset(_lowercase					,			_lowercase )




@pytest.mark.parametrize(
    '''features'''					,			[
        None,
        {'''col_3''': '''float64''', '''col_1''': '''string''', '''col_2''': '''int64'''},
    ]					,			)
def      __A					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= tmp_path / '''cache'''
					_A								= {'''col_3''': '''float64''', '''col_1''': '''string''', '''col_2''': '''int64'''}
					_A								= features.copy() if features else default_expected_features
					_A								= (
					    Features({feature: Value(_lowercase ) for feature, dtype in features.items()} ) if features is not None else None
					)
					_A								= JsonDatasetReader(_lowercase					,			features=_lowercase					,			cache_dir=_lowercase ).read()
					assert isinstance(_lowercase					,			_lowercase )
					assert dataset.num_rows == 2
					assert dataset.num_columns == 3
					assert dataset.column_names == ["col_3", "col_1", "col_2"]
					for feature, expected_dtype in expected_features.items():
										assert dataset.features[feature].dtype == expected_dtype




def      __A					(     _lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= {'''col_2''': '''int64''', '''col_3''': '''float64''', '''col_1''': '''string'''}
					_A								= features.copy()
					_A								= (
					    Features({feature: Value(_lowercase ) for feature, dtype in features.items()} ) if features is not None else None
					)
					_A								= tmp_path / '''cache'''
					_A								= JsonDatasetReader(_lowercase					,			features=_lowercase					,			cache_dir=_lowercase ).read()
					assert isinstance(_lowercase					,			_lowercase )
					assert dataset.num_rows == 2
					assert dataset.num_columns == 3
					assert dataset.column_names == ["col_2", "col_3", "col_1"]
					for feature, expected_dtype in expected_features.items():
										assert dataset.features[feature].dtype == expected_dtype




@pytest.mark.parametrize('''split'''					,			[None, NamedSplit('''train''' ), '''train''', '''test'''] )
def      __A					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= tmp_path / '''cache'''
					_A								= {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					_A								= JsonDatasetReader(_lowercase					,			cache_dir=_lowercase					,			split=_lowercase ).read()
					_check_json_dataset(_lowercase					,			_lowercase )
					assert dataset.split == split if split else "train"




@pytest.mark.parametrize('''path_type'''					,			[str, list] )
def      __A					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					if issubclass(_lowercase					,			_lowercase ):
										_A								= jsonl_path
					elif issubclass(_lowercase					,			_lowercase ):
										_A								= [jsonl_path]
					_A								= tmp_path / '''cache'''
					_A								= {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					_A								= JsonDatasetReader(_lowercase					,			cache_dir=_lowercase ).read()
					_check_json_dataset(_lowercase					,			_lowercase )




def      __A					(     _lowercase					,			_lowercase					,			_lowercase=("train",) ):

					'''simple docstring'''







					assert isinstance(_lowercase					,			_lowercase )
					for split in splits:
										_A								= 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					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= tmp_path / '''cache'''
					_A								= {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
										_A								= JsonDatasetReader({'''train''': jsonl_path}					,			cache_dir=_lowercase					,			keep_in_memory=_lowercase ).read()
					_check_json_datasetdict(_lowercase					,			_lowercase )




@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					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= tmp_path / '''cache'''
					_A								= {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					_A								= features.copy() if features else default_expected_features
					_A								= (
					    Features({feature: Value(_lowercase ) for feature, dtype in features.items()} ) if features is not None else None
					)
					_A								= JsonDatasetReader({'''train''': jsonl_path}					,			features=_lowercase					,			cache_dir=_lowercase ).read()
					_check_json_datasetdict(_lowercase					,			_lowercase )




@pytest.mark.parametrize('''split'''					,			[None, NamedSplit('''train''' ), '''train''', '''test'''] )
def      __A					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					if split:
										_A								= {split: jsonl_path}
					else:
										_A								= '''train'''
										_A								= {'''train''': jsonl_path, '''test''': jsonl_path}
					_A								= tmp_path / '''cache'''
					_A								= {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
					_A								= JsonDatasetReader(_lowercase					,			cache_dir=_lowercase ).read()
					_check_json_datasetdict(_lowercase					,			_lowercase					,			splits=list(path.keys() ) )
					assert all(dataset[split].split == split for split in path.keys() )




def      __A					(     _lowercase ):

					'''simple docstring'''







					return json.load(_lowercase )




def      __A					(     _lowercase ):

					'''simple docstring'''







					return [json.loads(_lowercase ) for line in buffer]





class 						SCREAMING_SNAKE_CASE				:





							"""simple docstring"""

							@pytest.mark.parametrize('''lines, load_json_function'''		,     [(True, load_json_lines), (False, load_json)]   )
							def       __A (  self:   Optional[Any]		,     __A:   Tuple		,     __A:   Any		,     __A:   Optional[int]   )    ->				List[str]:
												with io.BytesIO() as buffer:
																	JsonDatasetWriter(__A		,     __A		,     lines=__A   ).write()
																	buffer.seek(0   )
																	_A								= load_json_function(__A   )
												assert isinstance(__A		,     __A   )
												assert isinstance(exported_content[0]		,     __A   )
												assert len(__A   ) == 10

							@pytest.mark.parametrize(
							    '''orient, container, keys, len_at'''		,     [
							        ('''records''', list, {'''tokens''', '''labels''', '''answers''', '''id'''}, None),
							        ('''split''', dict, {'''columns''', '''data'''}, '''data'''),
							        ('''index''', dict, set('''0123456789'''   ), None),
							        ('''columns''', dict, {'''tokens''', '''labels''', '''answers''', '''id'''}, '''tokens'''),
							        ('''values''', list, None, None),
							        ('''table''', dict, {'''schema''', '''data'''}, '''data'''),
							    ]		,     )
							def       __A (  self:   Optional[Any]		,     __A:   Union[str, Any]		,     __A:   List[Any]		,     __A:   Union[str, Any]		,     __A:   Optional[int]		,     __A:   List[Any]   )    ->				Union[str, Any]:
												with io.BytesIO() as buffer:
																	JsonDatasetWriter(__A		,     __A		,     lines=__A		,     orient=__A   ).write()
																	buffer.seek(0   )
																	_A								= load_json(__A   )
												assert isinstance(__A		,     __A   )
												if keys:
																	if container is dict:
																						assert exported_content.keys() == keys
																	else:
																						assert exported_content[0].keys() == keys
												else:
																	assert not hasattr(__A		,     '''keys'''   ) and not hasattr(exported_content[0]		,     '''keys'''   )
												if len_at:
																	assert len(exported_content[len_at]   ) == 10
												else:
																	assert len(__A   ) == 10

							@pytest.mark.parametrize('''lines, load_json_function'''		,     [(True, load_json_lines), (False, load_json)]   )
							def       __A (  self:   int		,     __A:   Union[str, Any]		,     __A:   Union[str, Any]		,     __A:   Optional[Any]   )    ->				Tuple:
												with io.BytesIO() as buffer:
																	JsonDatasetWriter(__A		,     __A		,     lines=__A		,     num_proc=2   ).write()
																	buffer.seek(0   )
																	_A								= load_json_function(__A   )
												assert isinstance(__A		,     __A   )
												assert isinstance(exported_content[0]		,     __A   )
												assert len(__A   ) == 10

							@pytest.mark.parametrize(
							    '''orient, container, keys, len_at'''		,     [
							        ('''records''', list, {'''tokens''', '''labels''', '''answers''', '''id'''}, None),
							        ('''split''', dict, {'''columns''', '''data'''}, '''data'''),
							        ('''index''', dict, set('''0123456789'''   ), None),
							        ('''columns''', dict, {'''tokens''', '''labels''', '''answers''', '''id'''}, '''tokens'''),
							        ('''values''', list, None, None),
							        ('''table''', dict, {'''schema''', '''data'''}, '''data'''),
							    ]		,     )
							def       __A (  self:   Tuple		,     __A:   int		,     __A:   List[str]		,     __A:   List[Any]		,     __A:   List[Any]		,     __A:   List[Any]   )    ->				Union[str, Any]:
												with io.BytesIO() as buffer:
																	JsonDatasetWriter(__A		,     __A		,     lines=__A		,     orient=__A		,     num_proc=2   ).write()
																	buffer.seek(0   )
																	_A								= load_json(__A   )
												assert isinstance(__A		,     __A   )
												if keys:
																	if container is dict:
																						assert exported_content.keys() == keys
																	else:
																						assert exported_content[0].keys() == keys
												else:
																	assert not hasattr(__A		,     '''keys'''   ) and not hasattr(exported_content[0]		,     '''keys'''   )
												if len_at:
																	assert len(exported_content[len_at]   ) == 10
												else:
																	assert len(__A   ) == 10

							def       __A (  self:   Tuple		,     __A:   Optional[int]   )    ->				Optional[int]:
												with pytest.raises(__A   ):
																	with io.BytesIO() as buffer:
																						JsonDatasetWriter(__A		,     __A		,     num_proc=0   )



							@pytest.mark.parametrize('''compression, extension'''		,     [('''gzip''', '''gz'''), ('''bz2''', '''bz2'''), ('''xz''', '''xz''')]   )
							def       __A (  self:   Dict		,     __A:   Tuple		,     __A:   Dict		,     __A:   Tuple		,     __A:   Optional[Any]		,     __A:   int   )    ->				Optional[Any]:
												_A								= tmp_path_factory.mktemp('''data'''   ) / f"""test.json.{extension}"""
												_A								= str(shared_datadir / f"""test_file.json.{extension}"""   )
												JsonDatasetWriter(__A		,     __A		,     compression=__A   ).write()

												with fsspec.open(__A		,     '''rb'''		,     compression='''infer'''   ) as f:
																	_A								= f.read()
												with fsspec.open(__A		,     '''rb'''		,     compression='''infer'''   ) as f:
																	_A								= f.read()
												assert exported_content == original_content











from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup




def      __A					(     _lowercase = "" ):

					'''simple docstring'''







					_A								= url or '''https://www.imdb.com/chart/top/?ref_=nv_mv_250'''
					_A								= BeautifulSoup(requests.get(_lowercase ).text					,			'''html.parser''' )
					_A								= soup.find_all('''td'''					,			attrs='''titleColumn''' )
					_A								= soup.find_all('''td'''					,			class_='''ratingColumn imdbRating''' )
					return {
					    title.a.text: float(rating.strong.text )
					    for title, rating in zip(_lowercase					,			_lowercase )
					}




def      __A					(     _lowercase = "IMDb_Top_250_Movies.csv" ):

					'''simple docstring'''







					_A								= get_imdb_top_aaa_movies()
					with open(_lowercase					,			'''w'''					,			newline='''''' ) as out_file:
										_A								= csv.writer(_lowercase )
										writer.writerow(['''Movie title''', '''IMDb rating'''] )
										for title, rating in movies.items():
															writer.writerow([title, rating] )


if __name__ == "__main__":
				write_movies()



