
import pyarrow.parquet as pq
import pytest

from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases


def 						UpperCAmelCase			(	a_		,   a_						)		->	Any:







				"""simple docstring"""



				assert isinstance(a_		,   a_						)
				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 						UpperCAmelCase			(	a_		,   a_		,   a_						)		->	str:







				"""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   			= ParquetDatasetReader(a_		,   cache_dir=a_		,   keep_in_memory=a_						).read()
				_check_parquet_dataset(a_		,   a_						)


@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 						UpperCAmelCase			(	a_		,   a_		,   a_						)		->	int:







				"""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(a_						) for feature, dtype in features.items()}						) if features is not None else None
				)
				__A   			= ParquetDatasetReader(a_		,   features=a_		,   cache_dir=a_						).read()
				_check_parquet_dataset(a_		,   a_						)


@pytest.mark.parametrize("split"		,   [None, NamedSplit("train"						), "train", "test"]						)
def 						UpperCAmelCase			(	a_		,   a_		,   a_						)		->	Any:







				"""simple docstring"""



				__A   			= tmp_path / "cache"
				__A   			= {"col_1": "string", "col_2": "int64", "col_3": "float64"}
				__A   			= ParquetDatasetReader(a_		,   cache_dir=a_		,   split=a_						).read()
				_check_parquet_dataset(a_		,   a_						)
				assert dataset.split == split if split else "train"


@pytest.mark.parametrize("path_type"		,   [str, list]						)
def 						UpperCAmelCase			(	a_		,   a_		,   a_						)		->	List[str]:







				"""simple docstring"""



				if issubclass(a_		,   a_						):
								__A   			= parquet_path
				elif issubclass(a_		,   a_						):
								__A   			= [parquet_path]
				__A   			= tmp_path / "cache"
				__A   			= {"col_1": "string", "col_2": "int64", "col_3": "float64"}
				__A   			= ParquetDatasetReader(a_		,   cache_dir=a_						).read()
				_check_parquet_dataset(a_		,   a_						)


def 						UpperCAmelCase			(	a_		,   a_		,   a_=("train",)						)		->	List[str]:







				"""simple docstring"""



				assert isinstance(a_		,   a_						)
				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 						UpperCAmelCase			(	a_		,   a_		,   a_						)		->	int:







				"""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   			= ParquetDatasetReader(
								    {"train": parquet_path}		,   cache_dir=a_		,   keep_in_memory=a_						).read()
				_check_parquet_datasetdict(a_		,   a_						)


@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 						UpperCAmelCase			(	a_		,   a_		,   a_						)		->	List[str]:







				"""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(a_						) for feature, dtype in features.items()}						) if features is not None else None
				)
				__A   			= ParquetDatasetReader({"train": parquet_path}		,   features=a_		,   cache_dir=a_						).read()
				_check_parquet_datasetdict(a_		,   a_						)


@pytest.mark.parametrize("split"		,   [None, NamedSplit("train"						), "train", "test"]						)
def 						UpperCAmelCase			(	a_		,   a_		,   a_						)		->	int:







				"""simple docstring"""



				if split:
								__A   			= {split: parquet_path}
				else:
								__A   			= "train"
								__A   			= {"train": parquet_path, "test": parquet_path}
				__A   			= tmp_path / "cache"
				__A   			= {"col_1": "string", "col_2": "int64", "col_3": "float64"}
				__A   			= ParquetDatasetReader(a_		,   cache_dir=a_						).read()
				_check_parquet_datasetdict(a_		,   a_		,   splits=list(path.keys()						)						)
				assert all(dataset[split].split == split for split in path.keys()						)


def 						UpperCAmelCase			(	a_		,   a_						)		->	List[Any]:







				"""simple docstring"""



				__A   			= ParquetDatasetWriter(a_		,   tmp_path / "foo.parquet"						)
				assert writer.write() > 0
				__A   			= pq.ParquetFile(tmp_path / "foo.parquet"						)
				__A   			= pf.read()
				assert dataset.data.table == output_table


def 						UpperCAmelCase			(	a_		,   a_						)		->	str:







				"""simple docstring"""



				__A   			= str(shared_datadir / "test_image_rgb.jpg"						)
				__A   			= {"image": [image_path]}
				__A   			= Features({"image": Image()}						)
				__A   			= Dataset.from_dict(a_		,   features=a_						)
				__A   			= ParquetDatasetWriter(a_		,   tmp_path / "foo.parquet"						)
				assert writer.write() > 0

				__A   			= Dataset.from_parquet(str(tmp_path / "foo.parquet"						)						)
				assert dataset.features == reloaded_dataset.features

				__A   			= ParquetDatasetReader(str(tmp_path / "foo.parquet"						)		,   streaming=a_						).read()
				assert dataset.features == reloaded_iterable_dataset.features


@pytest.mark.parametrize(
    "feature, expected"		,   [
        (Features({"foo": Value("int32"						)}						), None),
        (Features({"image": Image(), "foo": Value("int32"						)}						), config.PARQUET_ROW_GROUP_SIZE_FOR_IMAGE_DATASETS),
        (Features({"nested": Sequence(Audio()						)}						), config.PARQUET_ROW_GROUP_SIZE_FOR_AUDIO_DATASETS),
    ]		,   )
def 						UpperCAmelCase			(	a_		,   a_						)		->	Union[str, Any]:







				"""simple docstring"""



				assert get_writer_batch_size(a_						) == expected




"""simple docstring"""







from __future__ import annotations

import math


class       SCREAMING_SNAKE_CASE__				:
       """simple docstring"""


       def __init__(						self		,     snake_case__						):






         """simple docstring"""





         lowerCAmelCase     :     Any								=							size
         # approximate the overall size of segment tree with given value
         lowerCAmelCase     :     Optional[int]								=							[0 for i in range(0		,     4 * size						)]
         # create array to store lazy update
         lowerCAmelCase     :     List[str]								=							[0 for i in range(0		,     4 * size						)]
         lowerCAmelCase     :     Dict								=							[0 for i in range(0		,     4 * size						)]  # flag for lazy update

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         return idx * 2

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         return idx * 2 + 1

       def        lowercase__							(						self		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__						):






         """simple docstring"""





         if left_element == right_element:
           lowerCAmelCase     :     List[str]								=							a[left_element - 1]
         else:
           lowerCAmelCase     :     Tuple								=							(left_element + right_element) // 2
           self.build(self.left(snake_case__						)		,     snake_case__		,     snake_case__		,     snake_case__						)
           self.build(self.right(snake_case__						)		,     mid + 1		,     snake_case__		,     snake_case__						)
           lowerCAmelCase     :     Tuple								=							max(
               self.segment_tree[self.left(snake_case__						)]		,     self.segment_tree[self.right(snake_case__						)]						)

       def        lowercase__							(						self		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__						):






         """simple docstring"""





         if self.flag[idx] is True:
           lowerCAmelCase     :     Optional[int]								=							self.lazy[idx]
           lowerCAmelCase     :     List[str]								=							False
           if left_element != right_element:
             lowerCAmelCase     :     Optional[Any]								=							self.lazy[idx]
             lowerCAmelCase     :     List[Any]								=							self.lazy[idx]
             lowerCAmelCase     :     List[Any]								=							True
             lowerCAmelCase     :     Optional[Any]								=							True

         if right_element < a or left_element > b:
           return True
         if left_element >= a and right_element <= b:
           lowerCAmelCase     :     str								=							val
           if left_element != right_element:
             lowerCAmelCase     :     Optional[Any]								=							val
             lowerCAmelCase     :     Union[str, Any]								=							val
             lowerCAmelCase     :     int								=							True
             lowerCAmelCase     :     int								=							True
           return True
         lowerCAmelCase     :     List[str]								=							(left_element + right_element) // 2
         self.update(self.left(snake_case__						)		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__						)
         self.update(self.right(snake_case__						)		,     mid + 1		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__						)
         lowerCAmelCase     :     Optional[int]								=							max(
             self.segment_tree[self.left(snake_case__						)]		,     self.segment_tree[self.right(snake_case__						)]						)
         return True

       def        lowercase__							(						self		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__						):






         """simple docstring"""





         if self.flag[idx] is True:
           lowerCAmelCase     :     List[Any]								=							self.lazy[idx]
           lowerCAmelCase     :     str								=							False
           if left_element != right_element:
             lowerCAmelCase     :     Tuple								=							self.lazy[idx]
             lowerCAmelCase     :     List[Any]								=							self.lazy[idx]
             lowerCAmelCase     :     Optional[int]								=							True
             lowerCAmelCase     :     str								=							True
         if right_element < a or left_element > b:
           return -math.inf
         if left_element >= a and right_element <= b:
           return self.segment_tree[idx]
         lowerCAmelCase     :     Any								=							(left_element + right_element) // 2
         lowerCAmelCase     :     Optional[int]								=							self.query(self.left(snake_case__						)		,     snake_case__		,     snake_case__		,     snake_case__		,     snake_case__						)
         lowerCAmelCase     :     Dict								=							self.query(self.right(snake_case__						)		,     mid + 1		,     snake_case__		,     snake_case__		,     snake_case__						)
         return max(snake_case__		,     snake_case__						)







       def __str__(						self						):






         """simple docstring"""





         return str([self.query(1		,     1		,     self.size		,     snake_case__		,     snake_case__						) for i in range(1		,     self.size + 1						)]						)


if __name__ == "__main__":
     lowerCAmelCase__      				=   [1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
     lowerCAmelCase__      				=   15
     lowerCAmelCase__      				=   SegmentTree(size)
     segt.build(1, 1, size, A)
     print(segt.query(1, 1, size, 4, 6))
     print(segt.query(1, 1, size, 7, 11))
     print(segt.query(1, 1, size, 7, 12))
     segt.update(1, 1, size, 1, 3, 111)
     print(segt.query(1, 1, size, 1, 15))
     segt.update(1, 1, size, 7, 8, 235)
     print(segt)





