






"""simple docstring"""





import multiprocessing
from typing import TYPE_CHECKING, Optional, Union

from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream


if TYPE_CHECKING:
    import sqlitea

    import sqlalchemy


class      _lowercase (     lowerCAmelCase						):


      def __init__(    self				:	List[Any]							,   a				:	Union[str, "sqlalchemy.sql.Selectable"]							,   a				:	Union[str, "sqlalchemy.engine.Connection", "sqlalchemy.engine.Engine", "sqlite3.Connection"]							,   a				:	Optional[Features] = None							,   a				:	str = None							,   a				:	bool = False							,   **a				:	Any							,   ):





            """simple docstring"""







            super().__init__(features=a							,   cache_dir=a							,   keep_in_memory=a							,   **a						)
            __snake_case      :    Optional[Any]  			=Sql(
                cache_dir=a							,   features=a							,   sql=a							,   con=a							,   **a							,   )







      def _UpperCamelCase						(    self				:	List[str]						):





            """simple docstring"""







            __snake_case      :    Any  			=None
            __snake_case      :    Dict  			=None
            __snake_case      :    int  			=None
            __snake_case      :    str  			=None

            self.builder.download_and_prepare(
                download_config=a							,   download_mode=a							,   verification_mode=a							,   base_path=a							,   )

            # Build dataset for splits
            __snake_case      :    List[Any]  			=self.builder.as_dataset(
                split='''train'''							,   verification_mode=a							,   in_memory=self.keep_in_memory						)
            return dataset



class      _lowercase :


      def __init__(    self				:	Optional[int]							,   a				:	Dataset							,   a				:	str							,   a				:	Union[str, "sqlalchemy.engine.Connection", "sqlalchemy.engine.Engine", "sqlite3.Connection"]							,   a				:	Optional[int] = None							,   a				:	Optional[int] = None							,   **a				:	List[Any]							,   ):





            """simple docstring"""







            if num_proc is not None and num_proc <= 0:
                  raise ValueError(f'''num_proc {num_proc} must be an integer > 0.'''						)

            __snake_case      :    List[Any]  			=dataset
            __snake_case      :    List[str]  			=name
            __snake_case      :    Any  			=con
            __snake_case      :    Any  			=batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
            __snake_case      :    Optional[Any]  			=num_proc
            __snake_case      :    Optional[int]  			=to_sql_kwargs


      def _UpperCamelCase						(    self				:	List[Any]						):





            """simple docstring"""







            __snake_case      :    List[Any]  			=self.to_sql_kwargs.pop('''sql'''							,   a						)
            __snake_case      :    Union[str, Any]  			=self.to_sql_kwargs.pop('''con'''							,   a						)
            __snake_case      :    Any  			=self.to_sql_kwargs.pop('''index'''							,   a						)

            __snake_case      :    Any  			=self._write(index=a							,   **self.to_sql_kwargs						)
            return written


      def _UpperCamelCase						(    self				:	Optional[Any]							,   a				:	Optional[Any]						):





            """simple docstring"""







            __snake_case			,				__snake_case			,				__snake_case      :    int  			=args
            __snake_case      :    str  			={**to_sql_kwargs, '''if_exists''': '''append'''} if offset > 0 else to_sql_kwargs
            __snake_case      :    List[Any]  			=query_table(
                table=self.dataset.data							,   key=slice(a							,   offset + self.batch_size						)							,   indices=self.dataset._indices							,   )
            __snake_case      :    Optional[int]  			=batch.to_pandas()
            __snake_case      :    Tuple  			=df.to_sql(self.name							,   self.con							,   index=a							,   **a						)
            return num_rows or len(a						)







      def _UpperCamelCase						(    self				:	Union[str, Any]							,   a				:	Optional[Any]							,   **a				:	str						):





            """simple docstring"""







            __snake_case      :    int  			=0

            if self.num_proc is None or self.num_proc == 1:
                  for offset in logging.tqdm(
                      range(0							,   len(self.dataset						)							,   self.batch_size						)							,   unit='''ba'''							,   disable=not logging.is_progress_bar_enabled()							,   desc='''Creating SQL from Arrow format'''							,   ):
                        written += self._batch_sql((offset, index, to_sql_kwargs)						)
            else:
                  __snake_case			,				__snake_case      :    List[Any]  			=len(self.dataset						), self.batch_size
                  with multiprocessing.Pool(self.num_proc						) as pool:
                        for num_rows in logging.tqdm(
                            pool.imap(
                                self._batch_sql							,   [(offset, index, to_sql_kwargs) for offset in range(0							,   a							,   a						)]							,   )							,   total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size							,   unit='''ba'''							,   disable=not logging.is_progress_bar_enabled()							,   desc='''Creating SQL from Arrow format'''							,   ):
                              written += num_rows

            return written










"""simple docstring"""





import os
from datetime import datetime as dt

from github import Github


UpperCamelCase_	:				List[str]										= [
    """good first issue""",
    """good second issue""",
    """good difficult issue""",
    """enhancement""",
    """new pipeline/model""",
    """new scheduler""",
    """wip""",
]



def     __lowercase					(    )					->					Optional[Any]:
      __snake_case      :    List[Any]  			=Github(os.environ['''GITHUB_TOKEN'''] )
      __snake_case      :    int  			=g.get_repo('''huggingface/diffusers''' )
      __snake_case      :    Any  			=repo.get_issues(state='''open''' )

      for issue in open_issues:
            __snake_case      :    Dict  			=sorted(issue.get_comments()       ,		key=lambda a : i.created_at       ,		reverse=a )
            __snake_case      :    Dict  			=comments[0] if len(a ) > 0 else None
            if (
                last_comment is not None
                and last_comment.user.login == "github-actions[bot]"
                and (dt.utcnow() - issue.updated_at).days > 7
                and (dt.utcnow() - issue.created_at).days >= 30
                and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels() )
            ):
                  # Closes the issue after 7 days of inactivity since the Stalebot notification.
                  issue.edit(state='''closed''' )
            elif (
                "stale" in issue.get_labels()
                and last_comment is not None
                and last_comment.user.login != "github-actions[bot]"
            ):
                  # Opens the issue if someone other than Stalebot commented.
                  issue.edit(state='''open''' )
                  issue.remove_from_labels('''stale''' )
            elif (
                (dt.utcnow() - issue.updated_at).days > 23
                and (dt.utcnow() - issue.created_at).days >= 30
                and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels() )
            ):
                  # Post a Stalebot notification after 23 days of inactivity.
                  issue.create_comment(
                      '''This issue has been automatically marked as stale because it has not had '''
                      '''recent activity. If you think this still needs to be addressed '''
                      '''please comment on this thread.\n\nPlease note that issues that do not follow the '''
                      '''[contributing guidelines](https://github.com/huggingface/diffusers/blob/main/CONTRIBUTING.md) '''
                      '''are likely to be ignored.''' )
                  issue.add_to_labels('''stale''' )


if __name__ == "__main__":
    main()


