


import enum
import os
from hashlib import shaaaa
from typing import Optional

from .. import config
from .logging import get_logger


SCREAMING_SNAKE_CASE :   int							      =				get_logger(__name__)






class _lowerCamelCase(		enum.Enum     ):
       lowercase_				:			Tuple									=    """all_checks"""
       lowercase_				:			Union[str, Any]									=    """basic_checks"""
       lowercase_				:			Tuple									=    """no_checks"""






class _lowerCamelCase(		_a     ):
       pass






class _lowerCamelCase(		_a     ):
       pass






class _lowerCamelCase(		_a     ):
       pass






class _lowerCamelCase(		_a     ):
       pass



def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_=None				)					->		Optional[Any]:
    if expected_checksums is None:
        logger.info('Unable to verify checksums.'				)
        return
    if len(set(lowerCamelCase_				) - set(lowerCamelCase_				)				) > 0:
        raise ExpectedMoreDownloadedFiles(str(set(lowerCamelCase_				) - set(lowerCamelCase_				)				)				)
    if len(set(lowerCamelCase_				) - set(lowerCamelCase_				)				) > 0:
        raise UnexpectedDownloadedFile(str(set(lowerCamelCase_				) - set(lowerCamelCase_				)				)				)
    _lowercase :							List[Any]   	=	[url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
    _lowercase :							Optional[Any]   	=	' for ' + verification_name if verification_name is not None else ''
    if len(lowerCamelCase_				) > 0:
        raise NonMatchingChecksumError(
            F'''Checksums didn\'t match{for_verification_name}:\n'''
            F'''{bad_urls}\n'''
            'Set `verification_mode=\'no_checks\'` to skip checksums verification and ignore this error'				)
    logger.info('All the checksums matched successfully' + for_verification_name				)






class _lowerCamelCase(		_a     ):
       pass






class _lowerCamelCase(		_a     ):
       pass






class _lowerCamelCase(		_a     ):
       pass






class _lowerCamelCase(		_a     ):
       pass



def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		str:
    if expected_splits is None:
        logger.info('Unable to verify splits sizes.'				)
        return
    if len(set(lowerCamelCase_				) - set(lowerCamelCase_				)				) > 0:
        raise ExpectedMoreSplits(str(set(lowerCamelCase_				) - set(lowerCamelCase_				)				)				)
    if len(set(lowerCamelCase_				) - set(lowerCamelCase_				)				) > 0:
        raise UnexpectedSplits(str(set(lowerCamelCase_				) - set(lowerCamelCase_				)				)				)
    _lowercase :							List[str]   	=	[
        {'expected': expected_splits[name], 'recorded': recorded_splits[name]}
        for name in expected_splits
        if expected_splits[name].num_examples != recorded_splits[name].num_examples
    ]
    if len(lowerCamelCase_				) > 0:
        raise NonMatchingSplitsSizesError(str(lowerCamelCase_				)				)
    logger.info('All the splits matched successfully.'				)



def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_ = True				)					->		dict:
    if record_checksum:
        _lowercase :							Dict   	=	shaaaa()
        with open(lowerCamelCase_							,				'rb'				) as f:
            for chunk in iter(lambda: f.read(1 << 20				)							,				B''				):
                m.update(lowerCamelCase_				)
            _lowercase :							Any   	=	m.hexdigest()
    else:
        _lowercase :							str   	=	None
    return {"num_bytes": os.path.getsize(lowerCamelCase_				), "checksum": checksum}



def        UpperCamelCase_(   lowerCamelCase_				)					->		List[Any]:
    if dataset_size and config.IN_MEMORY_MAX_SIZE:
        return dataset_size < config.IN_MEMORY_MAX_SIZE
    else:
        return False




import unittest

from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available

from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin


if is_bsa_available():
 from transformers import MarkupLMFeatureExtractor






class _lowerCamelCase(		unittest.TestCase     ):
       def __init__(      self,   lowerCamelCase) ->     List[str]:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	parent




       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           return {}



def        UpperCamelCase_(   )					->		List[str]:
    _lowercase :							int   	=	'<HTML>\n\n    <HEAD>\n    <TITLE>sample document</TITLE>\n    </HEAD>\n\n    <BODY BGCOLOR="FFFFFF">\n    <HR>\n    <a href="http://google.com">Goog</a>\n    <H1>This is one header</H1>\n    <H2>This is a another Header</H2>\n    <P>Travel from\n        <P>\n        <B>SFO to JFK</B>\n        <BR>\n        <B><I>on May 2, 2015 at 2:00 pm. For details go to confirm.com </I></B>\n        <HR>\n        <div style="color:#0000FF">\n            <h3>Traveler <b> name </b> is\n            <p> John Doe </p>\n        </div>'

    _lowercase :							List[Any]   	=	'\n    <!DOCTYPE html>\n    <html>\n    <body>\n\n    <h1>My First Heading</h1>\n    <p>My first paragraph.</p>\n\n    </body>\n    </html>\n    '

    return [html_string_a, html_string_a]






@require_bsa
class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Tuple									=    MarkupLMFeatureExtractor if is_bsa_available() else None
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Tuple   	=	MarkupLMFeatureExtractionTester(self)
       @property
       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           return self.feature_extract_tester.prepare_feat_extract_dict()




       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           _lowercase :							int   	=	self.feature_extraction_class()

           # Test not batched input
           _lowercase :							List[Any]   	=	get_html_strings()[0]
           _lowercase :							Optional[Any]   	=	feature_extractor(lowerCamelCase)

           # fmt: off
           _lowercase :							str   	=	[['sample document', 'Goog', 'This is one header', 'This is a another Header', 'Travel from', 'SFO to JFK', 'on May 2, 2015 at 2:00 pm. For details go to confirm.com', 'Traveler', 'name', 'is', 'John Doe']]
           _lowercase :							Dict   	=	[['/html/head/title', '/html/body/a', '/html/body/h1', '/html/body/h2', '/html/body/p', '/html/body/p/p/b[1]', '/html/body/p/p/b[2]/i', '/html/body/p/p/div/h3', '/html/body/p/p/div/h3/b', '/html/body/p/p/div/h3', '/html/body/p/p/div/h3/p']]
           # fmt: on

           self.assertEqual(encoding.nodes,   lowerCamelCase)
           self.assertEqual(encoding.xpaths,   lowerCamelCase)

           # Test batched
           _lowercase :							Optional[int]   	=	get_html_strings()
           _lowercase :							Tuple   	=	feature_extractor(lowerCamelCase)

           # fmt: off
           _lowercase :							List[Any]   	=	expected_nodes + [['My First Heading', 'My first paragraph.']]
           _lowercase :							List[str]   	=	expected_xpaths + [['/html/body/h1', '/html/body/p']]

           self.assertEqual(len(encoding.nodes),   2)
           self.assertEqual(len(encoding.xpaths),   2)

           self.assertEqual(encoding.nodes,   lowerCamelCase)
           self.assertEqual(encoding.xpaths,   lowerCamelCase)


