


import os
import tempfile
from pathlib import Path
from unittest import TestCase

import pyarrow as pa
import pytest

from datasets.arrow_dataset import Dataset
from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
from datasets.info import DatasetInfo
from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo

from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases


class     __lowerCAmelCase     ( a					):






  """simple docstring"""





  def 					lowerCAmelCase__  (     self       :       List[str]    ,				_lowerCAmelCase       :       int    ,				_lowerCAmelCase       :       Optional[int]=False  )   -> Any:




     """simple docstring"""
     snake_case_    ,    snake_case_    ,    snake_case_					    =					(
         filename_skip_take["filename"],
         filename_skip_take["skip"] if "skip" in filename_skip_take else None,
         filename_skip_take["take"] if "take" in filename_skip_take else None,
     )
     open(os.path.join(_lowerCAmelCase  )    ,				"wb"  ).close()
     snake_case_					    =					pa.Table.from_pydict({"filename": [Path(_lowerCAmelCase  ).name] * 1_0_0}  )
     if take == -1:
        snake_case_					    =					len(_lowerCAmelCase  ) - skip
     if skip is not None and take is not None:
        snake_case_					    =					pa_table.slice(_lowerCAmelCase    ,				_lowerCAmelCase  )
     return pa_table






class     __lowerCAmelCase     ( a					):






  """simple docstring"""





  def 					lowerCAmelCase__  (     self       :       Any  )   -> List[str]:




     """simple docstring"""
     snake_case_					    =					"my_name"
     snake_case_					    =					SplitInfo(name="train"    ,				num_examples=1_0_0  )
     snake_case_					    =					SplitInfo(name="test"    ,				num_examples=1_0_0  )
     snake_case_					    =					[train_info, test_info]
     snake_case_					    =					SplitDict()
     split_dict.add(_lowerCAmelCase  )
     split_dict.add(_lowerCAmelCase  )
     snake_case_					    =					DatasetInfo(splits=_lowerCAmelCase  )

     with tempfile.TemporaryDirectory() as tmp_dir:
        snake_case_					    =					ReaderTest(_lowerCAmelCase    ,				_lowerCAmelCase  )

        snake_case_					    =					"test[:33%]"
        snake_case_					    =					Dataset(**reader.read(_lowerCAmelCase    ,				_lowerCAmelCase    ,				_lowerCAmelCase  )  )
        self.assertEqual(dset["filename"][0]    ,				F'''{name}-test'''  )
        self.assertEqual(dset.num_rows    ,				3_3  )
        self.assertEqual(dset.num_columns    ,				1  )

        snake_case_					    =					["train", "test[:33%]"]
        snake_case_					    =					[Split.TRAIN, ReadInstruction.from_spec("test[:33%]"  )]
        for instructions in [instructionsa, instructionsa]:
           snake_case_					    =					[reader.read(_lowerCAmelCase    ,				_lowerCAmelCase    ,				_lowerCAmelCase  ) for instr in instructions]
           snake_case_    ,    snake_case_					    =					(Dataset(**_lowerCAmelCase  ) for dataset_kwargs in datasets_kwargs)
           self.assertEqual(train_dset["filename"][0]    ,				F'''{name}-train'''  )
           self.assertEqual(train_dset.num_rows    ,				1_0_0  )
           self.assertEqual(train_dset.num_columns    ,				1  )
           self.assertIsInstance(train_dset.split    ,				_lowerCAmelCase  )
           self.assertEqual(str(train_dset.split  )    ,				"train"  )
           self.assertEqual(test_dset["filename"][0]    ,				F'''{name}-test'''  )
           self.assertEqual(test_dset.num_rows    ,				3_3  )
           self.assertEqual(test_dset.num_columns    ,				1  )
           self.assertIsInstance(test_dset.split    ,				_lowerCAmelCase  )
           self.assertEqual(str(test_dset.split  )    ,				"test[:33%]"  )
           del train_dset, test_dset



  def 					lowerCAmelCase__  (     self       :       Optional[Any]  )   -> str:




     """simple docstring"""
     snake_case_					    =					"my_name"
     snake_case_					    =					SplitInfo(name="train"    ,				num_examples=1_0_0_0    ,				shard_lengths=[1_0_0] * 1_0  )
     snake_case_					    =					[train_info]
     snake_case_					    =					SplitDict()
     split_dict.add(_lowerCAmelCase  )
     snake_case_					    =					DatasetInfo(splits=_lowerCAmelCase  )

     with tempfile.TemporaryDirectory() as tmp_dir:
        snake_case_					    =					ReaderTest(_lowerCAmelCase    ,				_lowerCAmelCase  )

        snake_case_					    =					"train[:33%]"
        snake_case_					    =					Dataset(**reader.read(_lowerCAmelCase    ,				_lowerCAmelCase    ,				_lowerCAmelCase  )  )
        self.assertEqual(dset["filename"][0]    ,				F'''{name}-train-00000-of-00010'''  )
        self.assertEqual(dset["filename"][-1]    ,				F'''{name}-train-00003-of-00010'''  )
        self.assertEqual(dset.num_rows    ,				3_3_0  )
        self.assertEqual(dset.num_columns    ,				1  )



  def 					lowerCAmelCase__  (     self       :       str  )   -> Dict:




     """simple docstring"""
     snake_case_					    =					SplitInfo(name="train"    ,				num_examples=1_0_0  )
     snake_case_					    =					SplitInfo(name="test"    ,				num_examples=1_0_0  )
     snake_case_					    =					SplitDict()
     split_dict.add(_lowerCAmelCase  )
     split_dict.add(_lowerCAmelCase  )
     snake_case_					    =					DatasetInfo(splits=_lowerCAmelCase  )

     with tempfile.TemporaryDirectory() as tmp_dir:
        snake_case_					    =					ReaderTest(_lowerCAmelCase    ,				_lowerCAmelCase  )

        snake_case_					    =					[
            {"filename": os.path.join(_lowerCAmelCase    ,				"train"  )},
            {"filename": os.path.join(_lowerCAmelCase    ,				"test"  ), "skip": 1_0, "take": 1_0},
        ]
        snake_case_					    =					Dataset(**reader.read_files(_lowerCAmelCase    ,				original_instructions="train+test[10:20]"  )  )
        self.assertEqual(dset.num_rows    ,				1_1_0  )
        self.assertEqual(dset.num_columns    ,				1  )
        del dset






@pytest.mark.parametrize("in_memory"		,						[False, True]							)
def 			_lowerCAmelCase						(							lowerCAmelCase_							:Optional[Any]		,						lowerCAmelCase_							:Union[str, Any]		,						lowerCAmelCase_							:str							)->List[Any]:
   '''simple docstring'''






   snake_case_					    =					arrow_file
   with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
      snake_case_					    =					ArrowReader.read_table(lowerCAmelCase_		,						in_memory=lowerCAmelCase_							)
   assert table.shape == dataset.data.shape
   assert set(table.column_names							) == set(dataset.data.column_names							)
   assert dict(table.to_pydict()							) == dict(dataset.data.to_pydict()							)  # to_pydict returns OrderedDict



@pytest.mark.parametrize("in_memory"		,						[False, True]							)
def 			_lowerCAmelCase						(							lowerCAmelCase_							:Optional[int]		,						lowerCAmelCase_							:Tuple		,						lowerCAmelCase_							:List[Any]							)->Union[str, Any]:
   '''simple docstring'''






   snake_case_					    =					arrow_file
   snake_case_					    =					ArrowReader(""		,						lowerCAmelCase_							)
   with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
      snake_case_					    =					reader.read_files([{"filename": filename}]		,						in_memory=lowerCAmelCase_							)
   assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
   snake_case_					    =					dataset_kwargs["arrow_table"]
   assert table.shape == dataset.data.shape
   assert set(table.column_names							) == set(dataset.data.column_names							)
   assert dict(table.to_pydict()							) == dict(dataset.data.to_pydict()							)  # to_pydict returns OrderedDict



def 			_lowerCAmelCase						(							)->int:
   '''simple docstring'''






   assert ReadInstruction("train"		,						to=10		,						unit="abs"							).to_spec() == "train[:10]"
   assert ReadInstruction("train"		,						from_=-80		,						to=10		,						unit="%"							).to_spec() == "train[-80%:10%]"

   snake_case_					    =					"train+test"
   assert ReadInstruction.from_spec(lowerCAmelCase_							).to_spec() == spec_train_test

   snake_case_					    =					"train[2:10]"
   assert ReadInstruction.from_spec(lowerCAmelCase_							).to_spec() == spec_train_abs

   snake_case_					    =					"train[15%:-20%]"
   assert ReadInstruction.from_spec(lowerCAmelCase_							).to_spec() == spec_train_pct

   snake_case_					    =					"train[:10%](closest)"
   assert ReadInstruction.from_spec(lowerCAmelCase_							).to_spec() == "train[:10%]"

   snake_case_					    =					"train[:10%](pct1_dropremainder)"
   assert ReadInstruction.from_spec(lowerCAmelCase_							).to_spec() == spec_train_pct_rounding

   snake_case_					    =					"train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"
   assert ReadInstruction.from_spec(lowerCAmelCase_							).to_spec() == spec_train_test_pct_rounding



def 			_lowerCAmelCase						(							)->int:
   '''simple docstring'''






   snake_case_					    =					"dummy"
   snake_case_					    =					[SplitInfo(name="train"		,						num_examples=100							)]
   snake_case_					    =					"train[:33%]"
   snake_case_					    =					"arrow"
   snake_case_					    =					"prefix"

   snake_case_					    =					make_file_instructions(lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_							)
   assert isinstance(lowerCAmelCase_		,						lowerCAmelCase_							)
   assert file_instructions.num_examples == 33
   assert file_instructions.file_instructions == [
       {"filename": os.path.join(lowerCAmelCase_		,						F'''{name}-train.arrow'''							), "skip": 0, "take": 33}
   ]

   snake_case_					    =					[SplitInfo(name="train"		,						num_examples=100		,						shard_lengths=[10] * 10							)]
   snake_case_					    =					make_file_instructions(lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_							)
   assert isinstance(lowerCAmelCase_		,						lowerCAmelCase_							)
   assert file_instructions.num_examples == 33
   assert file_instructions.file_instructions == [
       {"filename": os.path.join(lowerCAmelCase_		,						F'''{name}-train-00000-of-00010.arrow'''							), "skip": 0, "take": -1},
       {"filename": os.path.join(lowerCAmelCase_		,						F'''{name}-train-00001-of-00010.arrow'''							), "skip": 0, "take": -1},
       {"filename": os.path.join(lowerCAmelCase_		,						F'''{name}-train-00002-of-00010.arrow'''							), "skip": 0, "take": -1},
       {"filename": os.path.join(lowerCAmelCase_		,						F'''{name}-train-00003-of-00010.arrow'''							), "skip": 0, "take": 3},
   ]



@pytest.mark.parametrize("name, expected_exception"		,						[(None, TypeError), ("", ValueError)]							)
def 			_lowerCAmelCase						(							lowerCAmelCase_							:Dict		,						lowerCAmelCase_							:Optional[Any]							)->List[str]:
   '''simple docstring'''






   snake_case_					    =					[SplitInfo(name="train"		,						num_examples=100							)]
   snake_case_					    =					"train"
   snake_case_					    =					"arrow"
   snake_case_					    =					"prefix_path"
   with pytest.raises(lowerCAmelCase_							):
      snake_case_					    =					make_file_instructions(lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_							)








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							)




