





import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict


@pytest.mark.parametrize(
    'files'		,      [
        ['full:README.md', 'dataset_infos.json'],
        ['empty:README.md', 'dataset_infos.json'],
        ['dataset_infos.json'],
        ['full:README.md'],
    ]		,      )
def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase					)     ->	Tuple:
    lowerCamelCase__       : Optional[Any]   					=						tmp_path_factory.mktemp('dset_infos_dir'					)
    if "full:README.md" in files:
        with open(dataset_infos_dir / 'README.md'		,      'w'					) as f:
            f.write('---\ndataset_info:\n  dataset_size: 42\n---'					)
    if "empty:README.md" in files:
        with open(dataset_infos_dir / 'README.md'		,      'w'					) as f:
            f.write(''					)
    # we want to support dataset_infos.json for backward compatibility
    if "dataset_infos.json" in files:
        with open(dataset_infos_dir / 'dataset_infos.json'		,      'w'					) as f:
            f.write('{"default": {"dataset_size": 42}}'					)
    lowerCamelCase__       : List[str]   					=						DatasetInfosDict.from_directory(_UpperCAmelCase					)
    assert dataset_infos
    assert dataset_infos["default"].dataset_size == 42


@pytest.mark.parametrize(
    'dataset_info'		,      [
        DatasetInfo(),
        DatasetInfo(
            description='foo'		,      features=Features({'a': Value('int32'					)}					)		,      builder_name='builder'		,      config_name='config'		,      version='1.0.0'		,      splits=[{'name': 'train'}]		,      download_size=42		,      ),
    ]		,      )
def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase					)     ->	Union[str, Any]:
    lowerCamelCase__       : Union[str, Any]   					=						str(_UpperCAmelCase					)
    dataset_info.write_to_directory(_UpperCAmelCase					)
    lowerCamelCase__       : Optional[int]   					=						DatasetInfo.from_directory(_UpperCAmelCase					)
    assert dataset_info == reloaded
    assert os.path.exists(os.path.join(_UpperCAmelCase		,      'dataset_info.json'					)					)


def 			SCREAMING_SNAKE_CASE (			)     ->	Union[str, Any]:
    lowerCamelCase__       : Optional[int]   					=						DatasetInfo(
        description='foo'		,      citation='bar'		,      homepage='https://foo.bar'		,      license='CC0'		,      features=Features({'a': Value('int32'					)}					)		,      post_processed={}		,      supervised_keys=()		,      task_templates=[]		,      builder_name='builder'		,      config_name='config'		,      version='1.0.0'		,      splits=[{'name': 'train', 'num_examples': 42}]		,      download_checksums={}		,      download_size=1337		,      post_processing_size=442		,      dataset_size=1234		,      size_in_bytes=1337 + 442 + 1234		,      )
    lowerCamelCase__       : Optional[int]   					=						dataset_info._to_yaml_dict()
    assert sorted(_UpperCAmelCase					) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML					)
    for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
        assert key in dataset_info_yaml_dict
        assert isinstance(dataset_info_yaml_dict[key]		,      (list, dict, int, str)					)
    lowerCamelCase__       : List[str]   					=						yaml.safe_dump(_UpperCAmelCase					)
    lowerCamelCase__       : Optional[Any]   					=						yaml.safe_load(_UpperCAmelCase					)
    assert dataset_info_yaml_dict == reloaded


def 			SCREAMING_SNAKE_CASE (			)     ->	Dict:
    lowerCamelCase__       : Any   					=						DatasetInfo()
    lowerCamelCase__       : List[str]   					=						dataset_info._to_yaml_dict()
    assert dataset_info_yaml_dict == {}


@pytest.mark.parametrize(
    'dataset_infos_dict'		,      [
        DatasetInfosDict(),
        DatasetInfosDict({'default': DatasetInfo()}					),
        DatasetInfosDict({'my_config_name': DatasetInfo()}					),
        DatasetInfosDict(
            {
                'default': DatasetInfo(
                    description='foo'		,      features=Features({'a': Value('int32'					)}					)		,      builder_name='builder'		,      config_name='config'		,      version='1.0.0'		,      splits=[{'name': 'train'}]		,      download_size=42		,      )
            }					),
        DatasetInfosDict(
            {
                'v1': DatasetInfo(dataset_size=42					),
                'v2': DatasetInfo(dataset_size=1337					),
            }					),
    ]		,      )
def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase					)     ->	Tuple:
    lowerCamelCase__       : Dict   					=						str(_UpperCAmelCase					)
    dataset_infos_dict.write_to_directory(_UpperCAmelCase					)
    lowerCamelCase__       : List[str]   					=						DatasetInfosDict.from_directory(_UpperCAmelCase					)

    # the config_name of the dataset_infos_dict take over the attribute
    for config_name, dataset_info in dataset_infos_dict.items():
        lowerCamelCase__       : Any   					=						config_name
        # the yaml representation doesn't include fields like description or citation
        # so we just test that we can recover what we can from the yaml
        lowerCamelCase__       : str   					=						DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()					)
    assert dataset_infos_dict == reloaded

    if dataset_infos_dict:
        assert os.path.exists(os.path.join(_UpperCAmelCase		,      'README.md'					)					)












from __future__ import annotations

import time
from collections.abc import Sequence
from random import randint

from matplotlib import pyplot as plt


def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)     ->	tuple[int | None, int | None, float]:
    if not arr:
        return None, None, 0
    if low == high:
        return low, high, arr[low]

    lowerCamelCase__       : Union[str, Any]   					=						(low + high) // 2
    lowerCamelCase__					,				lowerCamelCase__					,				lowerCamelCase__       : str   					=						max_subarray(_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)
    lowerCamelCase__					,				lowerCamelCase__					,				lowerCamelCase__       : Optional[Any]   					=						max_subarray(_UpperCAmelCase		,      mid + 1		,      _UpperCAmelCase					)
    lowerCamelCase__					,				lowerCamelCase__					,				lowerCamelCase__       : int   					=						max_cross_sum(_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)
    if left_sum >= right_sum and left_sum >= cross_sum:
        return left_low, left_high, left_sum
    elif right_sum >= left_sum and right_sum >= cross_sum:
        return right_low, right_high, right_sum
    return cross_left, cross_right, cross_sum


def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)     ->	tuple[int, int, float]:
    lowerCamelCase__					,				lowerCamelCase__       : Union[str, Any]   					=						float('-inf'					), -1
    lowerCamelCase__					,				lowerCamelCase__       : Tuple   					=						float('-inf'					), -1

    lowerCamelCase__       : int | float   					=						0
    for i in range(_UpperCAmelCase		,      low - 1		,      -1					):
        summ += arr[i]
        if summ > left_sum:
            lowerCamelCase__       : Optional[int]   					=						summ
            lowerCamelCase__       : Tuple   					=						i

    lowerCamelCase__       : int   					=						0
    for i in range(mid + 1		,      high + 1					):
        summ += arr[i]
        if summ > right_sum:
            lowerCamelCase__       : int   					=						summ
            lowerCamelCase__       : List[Any]   					=						i

    return max_left, max_right, (left_sum + right_sum)


def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase					)     ->	float:
    lowerCamelCase__       : Any   					=						[randint(1		,      _UpperCAmelCase					) for _ in range(_UpperCAmelCase					)]
    lowerCamelCase__       : Tuple   					=						time.time()
    max_subarray(_UpperCAmelCase		,      0		,      input_size - 1					)
    lowerCamelCase__       : List[Any]   					=						time.time()
    return end - start


def 			SCREAMING_SNAKE_CASE (			)     ->	None:
    lowerCamelCase__       : Optional[Any]   					=						[10, 100, 1000, 1_0000, 5_0000, 10_0000, 20_0000, 30_0000, 40_0000, 50_0000]
    lowerCamelCase__       : Optional[Any]   					=						[time_max_subarray(_UpperCAmelCase					) for input_size in input_sizes]
    print('No of Inputs\t\tTime Taken'					)
    for input_size, runtime in zip(_UpperCAmelCase		,      _UpperCAmelCase					):
        print(_UpperCAmelCase		,      '\t\t'		,      _UpperCAmelCase					)
    plt.plot(_UpperCAmelCase		,      _UpperCAmelCase					)
    plt.xlabel('Number of Inputs'					)
    plt.ylabel('Time taken in seconds'					)
    plt.show()


if __name__ == "__main__":
    from doctest import testmod

    testmod()





