
import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


lowercase__			  =   namedtuple(
    "_TestCommandArgs",
    [
        "dataset",
        "name",
        "cache_dir",
        "data_dir",
        "all_configs",
        "save_infos",
        "ignore_verifications",
        "force_redownload",
        "clear_cache",
    ],
    defaults=[None, None, None, False, False, False, False, False],
)



def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					return (abs(source - target		) / target) < 0.01



@pytest.mark.integration
def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						_TestCommandArgs(dataset=lowerCAmelCase__			,      all_configs=lowerCAmelCase__			,      save_infos=lowerCAmelCase__		)
					lowercase						     =						TestCommand(*lowerCAmelCase__		)
					test_command.run()
					lowercase						     =						os.path.join(lowerCAmelCase__			,      '''README.md'''		)
					assert os.path.exists(lowerCAmelCase__		)
					lowercase						     =						DatasetInfosDict.from_directory(lowerCAmelCase__		)
					lowercase						     =						DatasetInfosDict(
					    {
					        '''default''': DatasetInfo(
					            features=Features(
					                {
					                    '''tokens''': Sequence(Value('''string'''		)		),
					                    '''ner_tags''': Sequence(
					                        ClassLabel(names=['''O''', '''B-PER''', '''I-PER''', '''B-ORG''', '''I-ORG''', '''B-LOC''', '''I-LOC''']		)		),
					                    '''langs''': Sequence(Value('''string'''		)		),
					                    '''spans''': Sequence(Value('''string'''		)		),
					                }		)			,      splits=[
					                {
					                    '''name''': '''train''',
					                    '''num_bytes''': 235_1563,
					                    '''num_examples''': 1_0000,
					                },
					                {
					                    '''name''': '''validation''',
					                    '''num_bytes''': 23_8418,
					                    '''num_examples''': 1000,
					                },
					            ]			,      download_size=394_0680			,      dataset_size=258_9981			,      )
					    }		)
					assert dataset_infos.keys() == expected_dataset_infos.keys()
					for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
										lowercase     ,						lowercase						     =						getattr(dataset_infos['''default''']			,      lowerCAmelCase__		), getattr(expected_dataset_infos['''default''']			,      lowerCAmelCase__		)
										if key == "num_bytes":
															assert is_apercent_close(lowerCAmelCase__			,      lowerCAmelCase__		)
										elif key == "splits":
															assert list(lowerCAmelCase__		) == list(lowerCAmelCase__		)
															for split in result:
																				assert result[split].name == expected[split].name
																				assert result[split].num_examples == expected[split].num_examples
																				assert is_apercent_close(result[split].num_bytes			,      expected[split].num_bytes		)
										else:
															result == expected






from pathlib import Path

import fire
from tqdm import tqdm



def 	UpperCamelCase   (							lowerCAmelCase__="ro"			,      lowerCAmelCase__="en"			,      lowerCAmelCase__="wmt16"			,      lowerCAmelCase__=None		):
					'''simple docstring'''
					try:
										import datasets
					except (ModuleNotFoundError, ImportError):
										raise ImportError('''run pip install datasets'''		)
					lowercase						     =						f'{src_lang}-{tgt_lang}'
					print(f'Converting {dataset}-{pair}'		)
					lowercase						     =						datasets.load_dataset(lowerCAmelCase__			,      lowerCAmelCase__		)
					if save_dir is None:
										lowercase						     =						f'{dataset}-{pair}'
					lowercase						     =						Path(lowerCAmelCase__		)
					save_dir.mkdir(exist_ok=lowerCAmelCase__		)

					for split in ds.keys():
										print(f'Splitting {split} with {ds[split].num_rows} records'		)

										# to save to val.source, val.target like summary datasets
										lowercase						     =						'''val''' if split == '''validation''' else split
										lowercase						     =						save_dir.joinpath(f'{fn}.source'		)
										lowercase						     =						save_dir.joinpath(f'{fn}.target'		)
										lowercase						     =						src_path.open('''w+'''		)
										lowercase						     =						tgt_path.open('''w+'''		)

										# reader is the bottleneck so writing one record at a time doesn't slow things down
										for x in tqdm(ds[split]		):
															lowercase						     =						x['''translation''']
															src_fp.write(ex[src_lang] + '''\n'''		)
															tgt_fp.write(ex[tgt_lang] + '''\n'''		)

					print(f'Saved {dataset} dataset to {save_dir}'		)


if __name__ == "__main__":
							fire.Fire(download_wmt_dataset)




