


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_							:List[str]							)->Dict:
   '''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_							:Dict		,						lowerCAmelCase_							:List[Any]		,						lowerCAmelCase_							:List[str]							)->int:
   '''simple docstring'''






   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					{"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_					    =					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_							:List[str]		,						lowerCAmelCase_							:Optional[Any]		,						lowerCAmelCase_							:Optional[Any]							)->Optional[int]:
   '''simple docstring'''






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






   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
   snake_case_					    =					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_							:Dict		,						lowerCAmelCase_							:List[Any]							)->List[Any]:
   '''simple docstring'''






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



def 			_lowerCAmelCase						(							lowerCAmelCase_							:List[str]		,						lowerCAmelCase_							:Dict		,						lowerCAmelCase_							:List[str]=("train",)							)->Optional[Any]:
   '''simple docstring'''






   assert isinstance(lowerCAmelCase_		,						lowerCAmelCase_							)
   for split in splits:
      snake_case_					    =					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_							:Union[str, Any]		,						lowerCAmelCase_							:Dict		,						lowerCAmelCase_							:List[Any]							)->Any:
   '''simple docstring'''






   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					{"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_					    =					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[Any]		,						lowerCAmelCase_							:Optional[Any]		,						lowerCAmelCase_							:Any							)->str:
   '''simple docstring'''






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






   if split:
      snake_case_					    =					{split: csv_path}
   else:
      snake_case_					    =					{"train": csv_path, "test": csv_path}
   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
   snake_case_					    =					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							)->str:
   '''simple docstring'''






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



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Tuple		,						lowerCAmelCase_							:Dict							)->Any:
   '''simple docstring'''






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

   snake_case_					    =					iter_csv_file(lowerCAmelCase_							)
   snake_case_					    =					iter_csv_file(lowerCAmelCase_							)

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



def 			_lowerCAmelCase						(							lowerCAmelCase_							:str		,						lowerCAmelCase_							:Any							)->Union[str, Any]:
   '''simple docstring'''






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

   snake_case_					    =					iter_csv_file(lowerCAmelCase_							)
   snake_case_					    =					iter_csv_file(lowerCAmelCase_							)

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



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Any		,						lowerCAmelCase_							:Optional[int]							)->int:
   '''simple docstring'''






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








import safs


class     __lowerCAmelCase     ( safs.SaFileSystem					):






  """simple docstring"""




