




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:    Optional[Any]       ,			lowerCamelCase:    Optional[int]  )   ->     Union[str, Any]:


      '''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:    List[Any]       ,			lowerCamelCase:    Dict       ,			lowerCamelCase:    Dict  )   ->     Optional[Any]:


      '''simple docstring'''




      lowerCamelCase__ 					=			tmp_path / 'cache'
      lowerCamelCase__ 					=			{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
      with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
            lowerCamelCase__ 					=			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:    str       ,			lowerCamelCase:    int       ,			lowerCamelCase:    Tuple  )   ->     Any:


      '''simple docstring'''




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


      '''simple docstring'''




      lowerCamelCase__ 					=			tmp_path / 'cache'
      lowerCamelCase__ 					=			{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
      lowerCamelCase__ 					=			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:    Any       ,			lowerCamelCase:    Optional[int]       ,			lowerCamelCase:    Dict  )   ->     Union[str, Any]:


      '''simple docstring'''




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

def      lowerCAmelCase_     (					lowerCamelCase:    List[str]       ,			lowerCamelCase:    int       ,			lowerCamelCase:    Optional[Any]=("train",)  )   ->     Tuple:


      '''simple docstring'''




      assert isinstance(lowerCamelCase       ,			lowerCamelCase  )
      for split in splits:
            lowerCamelCase__ 					=			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:    Optional[int]       ,			lowerCamelCase:    Optional[int]       ,			lowerCamelCase:    Union[str, Any]  )   ->     Union[str, Any]:


      '''simple docstring'''




      lowerCamelCase__ 					=			tmp_path / 'cache'
      lowerCamelCase__ 					=			{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
      with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
            lowerCamelCase__ 					=			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:    List[str]       ,			lowerCamelCase:    List[str]       ,			lowerCamelCase:    Optional[int]  )   ->     Optional[Any]:


      '''simple docstring'''




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


      '''simple docstring'''




      if split:
            lowerCamelCase__ 					=			{split: csv_path}
      else:
            lowerCamelCase__ 					=			{'train': csv_path, 'test': csv_path}
      lowerCamelCase__ 					=			tmp_path / 'cache'
      lowerCamelCase__ 					=			{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
      lowerCamelCase__ 					=			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:    Tuple  )   ->     List[Any]:


      '''simple docstring'''




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

def      lowerCAmelCase_     (					lowerCamelCase:    int       ,			lowerCamelCase:    int  )   ->     Dict:


      '''simple docstring'''




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

      lowerCamelCase__ 					=			iter_csv_file(lowerCamelCase  )
      lowerCamelCase__ 					=			iter_csv_file(lowerCamelCase  )

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

def      lowerCAmelCase_     (					lowerCamelCase:    List[str]       ,			lowerCamelCase:    Union[str, Any]  )   ->     List[str]:


      '''simple docstring'''




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

      lowerCamelCase__ 					=			iter_csv_file(lowerCamelCase  )
      lowerCamelCase__ 					=			iter_csv_file(lowerCamelCase  )

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


def      lowerCAmelCase_     (					lowerCamelCase:    Union[str, Any]       ,			lowerCamelCase:    Union[str, Any]  )   ->     Tuple:


      '''simple docstring'''




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





from __future__ import annotations

def      lowerCAmelCase_     (					lowerCamelCase:    list[int | float]  )   ->     int | float:


      '''simple docstring'''




      if len(lowerCamelCase  ) == 0:
            raise ValueError('find_max() arg is an empty sequence'  )
      lowerCamelCase__ 					=			nums[0]
      for x in nums:
            if x > max_num:
                  lowerCamelCase__ 					=			x
      return max_num


if __name__ == "__main__":
      import doctest

      doctest.testmod(verbose=True)