

'''simple docstring'''



import argparse
from collections import defaultdict

import yaml


_UpperCamelCase						:  str							       =				"docs/source/en/_toctree.yml"


def       snake_case   (	snake_case      : Dict			) ->  Union[str, Any]:


    """simple docstring"""


    lowerCAmelCase 						=							defaultdict(snake_case			)
    lowerCAmelCase 						=							[]
    lowerCAmelCase 						=							[]
    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			)

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

    lowerCAmelCase 						=							[]
    for duplicate_key in duplicates:
        lowerCAmelCase 						=							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]			)
    lowerCAmelCase 						=							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      : List[Any]=False			) ->  Tuple:


    """simple docstring"""


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

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

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

    lowerCAmelCase 						=							api_doc[scheduler_idx]['sections']
    lowerCAmelCase 						=							clean_doc_toc(snake_case			)

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

    if diff:
        if overwrite:
            lowerCAmelCase 						=							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      : Any=False			) ->  Optional[int]:


    """simple docstring"""


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

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

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

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

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

    # sort overall pipeline doc
    lowerCAmelCase 						=							clean_doc_toc(snake_case			)

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

    if diff:
        if overwrite:
            lowerCAmelCase 						=							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__":
     _UpperCamelCase						:  Optional[int]							       =				argparse.ArgumentParser()
     parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
     _UpperCamelCase						:  Any							       =				parser.parse_args()

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








'''simple docstring'''



import itertools
from dataclasses import dataclass
from typing import Optional

import pandas as pd
import pyarrow as pa

import datasets
from datasets.table import table_cast



@dataclass
class 				_snake_case					(   datasets.BuilderConfig			):
  SCREAMING_SNAKE_CASE			:       Optional[datasets.Features]				=     None



class 				_snake_case					(   datasets.ArrowBasedBuilder			):
  SCREAMING_SNAKE_CASE			:       Tuple				=     PandasConfig

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      return datasets.DatasetInfo(features=self.config.features	)

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      if not self.config.data_files:
          raise ValueError(F'At least one data file must be specified, but got data_files={self.config.data_files}'	)
      lowerCAmelCase 						=							dl_manager.download_and_extract(self.config.data_files	)
      if isinstance(_SCREAMING_SNAKE_CASE      , (str, list, tuple)	):
          lowerCAmelCase 						=							data_files
          if isinstance(_SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE	):
              lowerCAmelCase 						=							[files]
          # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
          lowerCAmelCase 						=							[dl_manager.iter_files(_SCREAMING_SNAKE_CASE	) for file in files]
          return [datasets.SplitGenerator(name=datasets.Split.TRAIN      , gen_kwargs={'files': files}	)]
      lowerCAmelCase 						=							[]
      for split_name, files in data_files.items():
          if isinstance(_SCREAMING_SNAKE_CASE      , _SCREAMING_SNAKE_CASE	):
              lowerCAmelCase 						=							[files]
          # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
          lowerCAmelCase 						=							[dl_manager.iter_files(_SCREAMING_SNAKE_CASE	) for file in files]
          splits.append(datasets.SplitGenerator(name=_SCREAMING_SNAKE_CASE      , gen_kwargs={'files': files}	)	)
      return splits

  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      if self.config.features is not None:
          # more expensive cast to support nested features with keys in a different order
          # allows str <-> int/float or str to Audio for example
          lowerCAmelCase 						=							table_cast(_SCREAMING_SNAKE_CASE      , self.config.features.arrow_schema	)
      return pa_table


  def   _SCREAMING_SNAKE_CASE				(				self      , _SCREAMING_SNAKE_CASE	):





      '''simple docstring'''

      for i, file in enumerate(itertools.chain.from_iterable(_SCREAMING_SNAKE_CASE	)	):
          with open(_SCREAMING_SNAKE_CASE      , 'rb'	) as f:
              lowerCAmelCase 						=							pa.Table.from_pandas(pd.read_pickle(_SCREAMING_SNAKE_CASE	)	)
              yield i, self._cast_table(_SCREAMING_SNAKE_CASE	)





