




"""simple docstring"""

from unittest import TestCase

from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset





class     lowercase_	(					__lowerCAmelCase							):



	'''simple docstring'''

	def       lowerCAmelCase_							(			self	:	List[str]		):
							return [
							    {"col_1": 3, "col_2": "a"},
							    {"col_1": 2, "col_2": "b"},
							    {"col_1": 1, "col_2": "c"},
							    {"col_1": 0, "col_2": "d"},
							]

	def       lowerCAmelCase_							(			self	:	Tuple		):
							_A        =       {'''col_1''': [3, 2, 1, 0], '''col_2''': ['''a''', '''b''', '''c''', '''d''']}
							return Dataset.from_dict(lowerCamelCase__		)

	def       lowerCAmelCase_							(			self	:	Any		):
							_A        =       self._create_example_records()
							_A        =       Dataset.from_list(lowerCamelCase__		)
							self.assertListEqual(dset.column_names   ,							['col_1', 'col_2']		)
							for i, r in enumerate(lowerCamelCase__		):
													self.assertDictEqual(lowerCamelCase__   ,							example_records[i]		)

	def       lowerCAmelCase_							(			self	:	Optional[Any]		):
							_A        =       self._create_example_records()
							_A        =       Dataset.from_list(lowerCamelCase__		)
							_A        =       Dataset.from_dict({k: [r[k] for r in example_records] for k in example_records[0]}		)
							self.assertEqual(dset.info   ,							dset_from_dict.info		)

	def       lowerCAmelCase_							(			self	:	Union[str, Any]		):  # checks what happens with missing columns
							_A        =       [{'''col_1''': 1}, {'''col_2''': '''x'''}]
							_A        =       Dataset.from_list(lowerCamelCase__		)
							self.assertDictEqual(dset[0]   ,							{'col_1': 1}		)
							self.assertDictEqual(dset[1]   ,							{'col_1': None}		)  # NB: first record is used for columns

	def       lowerCAmelCase_							(			self	:	List[Any]		):  # checks if the type can be inferred from the second record
							_A        =       [{'''col_1''': []}, {'''col_1''': [1, 2]}]
							_A        =       Dataset.from_list(lowerCamelCase__		)
							self.assertEqual(dset.info.features['col_1']   ,							Sequence(Value('int64'		)		)		)



	def       lowerCAmelCase_							(			self	:	Dict		):
							_A        =       Dataset.from_list([]		)
							self.assertEqual(len(lowerCamelCase__		)   ,							0		)
							self.assertListEqual(dset.column_names   ,							[]		)







"""simple docstring"""

import argparse
from collections import defaultdict

import yaml


a         =      '''docs/source/en/_toctree.yml'''






def 						_snake_case					( _snake_case							: List[Any]							)   -> Optional[Any]:






      '''simple docstring'''


      _A        =       defaultdict(_snake_case							)
      _A        =       []
      _A        =       []
      for doc in doc_list:
            if "local" in doc:
                  counts[doc["local"]] += 1

            if doc["title"].lower() == "overview":
                  overview_doc.append({'local': doc['local'], 'title': doc['title']}							)
            else:
                  new_doc_list.append(_snake_case							)

      _A        =       new_doc_list
      _A        =       [key for key, value in counts.items() if value > 1]

      _A        =       []
      for duplicate_key in duplicates:
            _A        =       list({doc['title'] for doc in doc_list if doc['local'] == duplicate_key}							)
            if len(_snake_case							) > 1:
                  raise ValueError(
                      F'''{duplicate_key} is present several times in the documentation table of content at '''
                      '`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '
                      'others.'							)
            # Only add this once
            new_doc.append({'local': duplicate_key, 'title': titles[0]}							)

      # Add none duplicate-keys
      new_doc.extend([doc for doc in doc_list if 'local' not in counts or counts[doc['local']] == 1]							)
      _A        =       sorted(_snake_case    ,  key=lambda _snake_case							: s["title"].lower()							)

      # "overview" gets special treatment and is always first
      if len(_snake_case							) > 1:
            raise ValueError('{doc_list} has two \'overview\' docs which is not allowed.'							)

      overview_doc.extend(_snake_case							)

      # Sort
      return overview_doc






def 						_snake_case					( _snake_case							: Tuple=False							)   -> List[Any]:






      '''simple docstring'''


      with open(_snake_case    ,  encoding='utf-8'							) as f:
            _A        =       yaml.safe_load(f.read()							)

      # Get to the API doc
      _A        =       0
      while content[api_idx]["title"] != "API":
            api_idx += 1
      _A        =       content[api_idx]['sections']

      # Then to the model doc
      _A        =       0
      while api_doc[scheduler_idx]["title"] != "Schedulers":
            scheduler_idx += 1

      _A        =       api_doc[scheduler_idx]['sections']
      _A        =       clean_doc_toc(_snake_case							)

      _A        =       False
      if new_scheduler_doc != scheduler_doc:
            _A        =       True
            if overwrite:
                  _A        =       new_scheduler_doc

      if diff:
            if overwrite:
                  _A        =       api_doc
                  with open(_snake_case    ,  'w'    ,  encoding='utf-8'							) as f:
                        f.write(yaml.dump(_snake_case    ,  allow_unicode=_snake_case							)							)
            else:
                  raise ValueError(
                      'The model doc part of the table of content is not properly sorted, run `make style` to fix this.'							)






def 						_snake_case					( _snake_case							: str=False							)   -> Union[str, Any]:






      '''simple docstring'''


      with open(_snake_case    ,  encoding='utf-8'							) as f:
            _A        =       yaml.safe_load(f.read()							)

      # Get to the API doc
      _A        =       0
      while content[api_idx]["title"] != "API":
            api_idx += 1
      _A        =       content[api_idx]['sections']

      # Then to the model doc
      _A        =       0
      while api_doc[pipeline_idx]["title"] != "Pipelines":
            pipeline_idx += 1

      _A        =       False
      _A        =       api_doc[pipeline_idx]['sections']
      _A        =       []

      # sort sub pipeline docs
      for pipeline_doc in pipeline_docs:
            if "section" in pipeline_doc:
                  _A        =       pipeline_doc['section']
                  _A        =       clean_doc_toc(_snake_case							)
                  if overwrite:
                        _A        =       new_sub_pipeline_doc
            new_pipeline_docs.append(_snake_case							)

      # sort overall pipeline doc
      _A        =       clean_doc_toc(_snake_case							)

      if new_pipeline_docs != pipeline_docs:
            _A        =       True
            if overwrite:
                  _A        =       new_pipeline_docs

      if diff:
            if overwrite:
                  _A        =       api_doc
                  with open(_snake_case    ,  'w'    ,  encoding='utf-8'							) as f:
                        f.write(yaml.dump(_snake_case    ,  allow_unicode=_snake_case							)							)
            else:
                  raise ValueError(
                      'The model doc part of the table of content is not properly sorted, run `make style` to fix this.'							)


if __name__ == "__main__":
       a         =      argparse.ArgumentParser()
       parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
       a         =      parser.parse_args()

       check_scheduler_doc(args.fix_and_overwrite)
       check_pipeline_doc(args.fix_and_overwrite)

