



'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path

import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder


snake_case_					:      List[Any]    			=    '__DUMMY_TRANSFORMERS_USER__'
snake_case_					:      Tuple    			=    'Dummy User'
snake_case_					:      str    			=    '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'

snake_case_					:      Dict    			=    'https://hub-ci.huggingface.co'
snake_case_					:      List[Any]    			=    CI_HUB_ENDPOINT + '/datasets/{repo_id}/resolve/{revision}/{path}'
snake_case_					:      Any    			=    CI_HUB_ENDPOINT + '/{repo_id}/resolve/{revision}/{filename}'
snake_case_					:      Dict    			=    Path('~/.huggingface/hub_ci_token').expanduser()






@pytest.fixture
def A__       (	UpperCAmelCase_				):
						monkeypatch.setattr(
						    'huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE'    ,    _lowerCAmelCase				)






@pytest.fixture
def A__       (	UpperCAmelCase_				):
						monkeypatch.setattr('datasets.config.HF_ENDPOINT'    ,    _lowerCAmelCase				)
						monkeypatch.setattr('datasets.config.HUB_DATASETS_URL'    ,    _lowerCAmelCase				)






@pytest.fixture
def A__       (	UpperCAmelCase_				):
						monkeypatch.setattr('huggingface_hub.hf_api.HfFolder.path_token'    ,    _lowerCAmelCase				)






@pytest.fixture
def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						HfFolder.save_token(_lowerCAmelCase				)
						yield
						HfFolder.delete_token()






@pytest.fixture(scope='session'				)
def A__       (	):
						return HfApi(endpoint=_lowerCAmelCase				)






@pytest.fixture(scope='session'				)
def A__       (	UpperCAmelCase_				):
						_UpperCamelCase   :						str												=  HfFolder.get_token()
						HfFolder.save_token(_lowerCAmelCase				)
						yield CI_HUB_USER_TOKEN
						if previous_token is not None:
												HfFolder.save_token(_lowerCAmelCase				)






@pytest.fixture
def A__       (	UpperCAmelCase_				):






						def _cleanup_repo(UpperCAmelCase_				):
												hf_api.delete_repo(_lowerCAmelCase    ,    token=_lowerCAmelCase    ,    repo_type='dataset'				)

						return _cleanup_repo






@pytest.fixture
def A__       (	UpperCAmelCase_				):






						@contextmanager
						def _temporary_repo(UpperCAmelCase_				):
												try:
																		yield repo_id
												finally:
																		cleanup_repo(_lowerCAmelCase				)

						return _temporary_repo






@pytest.fixture(scope='session'				)
def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_				):
						_UpperCamelCase   :						Any												=  f'repo_txt_data-{int(time.time() * 10E3				)}'
						_UpperCamelCase   :						Optional[int]												=  f'{CI_HUB_USER}/{repo_name}'
						hf_api.create_repo(_lowerCAmelCase    ,    token=_lowerCAmelCase    ,    repo_type='dataset'    ,    private=_lowerCAmelCase				)
						hf_api.upload_file(
						    token=_lowerCAmelCase    ,    path_or_fileobj=str(_lowerCAmelCase				)    ,    path_in_repo='data/text_data.txt'    ,    repo_id=_lowerCAmelCase    ,    repo_type='dataset'    ,    )
						yield repo_id
						try:
												hf_api.delete_repo(_lowerCAmelCase    ,    token=_lowerCAmelCase    ,    repo_type='dataset'				)
						except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
												pass






@pytest.fixture()
def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_				):
						return hf_private_dataset_repo_txt_data_






@pytest.fixture(scope='session'				)
def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_				):
						_UpperCamelCase   :						int												=  f'repo_zipped_txt_data-{int(time.time() * 10E3				)}'
						_UpperCamelCase   :						Union[str, Any]												=  f'{CI_HUB_USER}/{repo_name}'
						hf_api.create_repo(_lowerCAmelCase    ,    token=_lowerCAmelCase    ,    repo_type='dataset'    ,    private=_lowerCAmelCase				)
						hf_api.upload_file(
						    token=_lowerCAmelCase    ,    path_or_fileobj=str(_lowerCAmelCase				)    ,    path_in_repo='data.zip'    ,    repo_id=_lowerCAmelCase    ,    repo_type='dataset'    ,    )
						yield repo_id
						try:
												hf_api.delete_repo(_lowerCAmelCase    ,    token=_lowerCAmelCase    ,    repo_type='dataset'				)
						except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
												pass






@pytest.fixture()
def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_				):
						return hf_private_dataset_repo_zipped_txt_data_






@pytest.fixture(scope='session'				)
def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_				):
						_UpperCamelCase   :						int												=  f'repo_zipped_img_data-{int(time.time() * 10E3				)}'
						_UpperCamelCase   :						int												=  f'{CI_HUB_USER}/{repo_name}'
						hf_api.create_repo(_lowerCAmelCase    ,    token=_lowerCAmelCase    ,    repo_type='dataset'    ,    private=_lowerCAmelCase				)
						hf_api.upload_file(
						    token=_lowerCAmelCase    ,    path_or_fileobj=str(_lowerCAmelCase				)    ,    path_in_repo='data.zip'    ,    repo_id=_lowerCAmelCase    ,    repo_type='dataset'    ,    )
						yield repo_id
						try:
												hf_api.delete_repo(_lowerCAmelCase    ,    token=_lowerCAmelCase    ,    repo_type='dataset'				)
						except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
												pass






@pytest.fixture()
def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_				):
						return hf_private_dataset_repo_zipped_img_data_






# flake8: noqa
# Lint as: python3

from typing import Dict, List, Optional, Type

from .. import config
from ..utils import logging
from .formatting import (
    ArrowFormatter,
    CustomFormatter,
    Formatter,
    PandasFormatter,
    PythonFormatter,
    TensorFormatter,
    format_table,
    query_table,
)
from .np_formatter import NumpyFormatter


A				:       Union[str, Any]      =  logging.get_logger(__name__)

A				:       Dict[Optional[str], Type[Formatter]]      =  {}
A				:       Dict[Optional[str], str]      =  {}
A				:       Dict[Optional[str], Exception]      =  {}





def 						_lowerCAmelCase							(     _lowerCAmelCase   ,						_lowerCAmelCase   ,						_lowerCAmelCase = None   ,						)    ->						str:


						'''simple docstring'''






						__snake_case				=		aliases if aliases is not None else []
						if format_type in _FORMAT_TYPES:
												logger.warning(
												    F'''Overwriting format type \'{format_type}\' ({_FORMAT_TYPES[format_type].__name__} -> {formatter_cls.__name__})'''			)
						__snake_case				=		formatter_cls
						for alias in set(aliases + [format_type]			):
												if alias in _FORMAT_TYPES_ALIASES:
																		logger.warning(
																		    F'''Overwriting format type alias \'{alias}\' ({_FORMAT_TYPES_ALIASES[alias]} -> {format_type})'''			)
												__snake_case				=		format_type





def 						_lowerCAmelCase							(     _lowerCAmelCase   ,						_lowerCAmelCase   ,						_lowerCAmelCase = None			)    ->						List[Any]:


						'''simple docstring'''






						__snake_case				=		aliases if aliases is not None else []
						for alias in set(aliases + [format_type]			):
												__snake_case				=		unavailable_error


# Here we define all the available formatting functions that can be used by `Dataset.set_format`
_register_formatter(PythonFormatter, None, aliases=['python'])
_register_formatter(ArrowFormatter, 'arrow', aliases=['pa', 'pyarrow'])
_register_formatter(NumpyFormatter, 'numpy', aliases=['np'])
_register_formatter(PandasFormatter, 'pandas', aliases=['pd'])
_register_formatter(CustomFormatter, 'custom')

if config.TORCH_AVAILABLE:
	from .torch_formatter import TorchFormatter

	_register_formatter(TorchFormatter, 'torch', aliases=['pt', 'pytorch'])
else:
	A				:       Any      =  ValueError('PyTorch needs to be installed to be able to return PyTorch tensors.')
	_register_unavailable_formatter(_torch_error, 'torch', aliases=['pt', 'pytorch'])

if config.TF_AVAILABLE:
	from .tf_formatter import TFFormatter

	_register_formatter(TFFormatter, 'tensorflow', aliases=['tf'])
else:
	A				:       Tuple      =  ValueError('Tensorflow needs to be installed to be able to return Tensorflow tensors.')
	_register_unavailable_formatter(_tf_error, 'tensorflow', aliases=['tf'])

if config.JAX_AVAILABLE:
	from .jax_formatter import JaxFormatter

	_register_formatter(JaxFormatter, 'jax', aliases=[])
else:
	A				:       Optional[int]      =  ValueError('JAX needs to be installed to be able to return JAX arrays.')
	_register_unavailable_formatter(_jax_error, 'jax', aliases=[])





def 						_lowerCAmelCase							(     _lowerCAmelCase			)    ->						Optional[str]:


						'''simple docstring'''






						if format_type in _FORMAT_TYPES_ALIASES:
												return _FORMAT_TYPES_ALIASES[format_type]
						else:
												return format_type





def 						_lowerCAmelCase							(     _lowerCAmelCase   ,						**_lowerCAmelCase			)    ->						Formatter:


						'''simple docstring'''






						__snake_case				=		get_format_type_from_alias(_lowerCAmelCase			)
						if format_type in _FORMAT_TYPES:
												return _FORMAT_TYPES[format_type](**_lowerCAmelCase			)
						if format_type in _FORMAT_TYPES_ALIASES_UNAVAILABLE:
												raise _FORMAT_TYPES_ALIASES_UNAVAILABLE[format_type]
						else:
												raise ValueError(
												    F'''Return type should be None or selected in {list(type for type in _FORMAT_TYPES.keys() if type != None			)}, but got \'{format_type}\''''			)





