

'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_utils import Literal


_snake_case      =    datasets.utils.logging.get_logger(__name__)

_snake_case      =    ["names", "prefix"]
_snake_case      =    ["warn_bad_lines", "error_bad_lines", "mangle_dupe_cols"]
_snake_case      =    ["encoding_errors", "on_bad_lines"]
_snake_case      =    ["date_format"]


@dataclass
class   a__    (				datasets.BuilderConfig    ):
   _SCREAMING_SNAKE_CASE       :	str      			=				","
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[Union[int, List[int], str]]      			=				"infer"
   _SCREAMING_SNAKE_CASE       :	Optional[List[str]]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[List[str]]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[Union[int, str, List[int], List[str]]]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[Union[List[int], List[str]]]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				None
   _SCREAMING_SNAKE_CASE       :	bool      			=				True
   _SCREAMING_SNAKE_CASE       :	Optional[Literal["c", "python", "pyarrow"]]      			=				None
   _SCREAMING_SNAKE_CASE       :	Dict[Union[int, str], Callable[[Any], Any]]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[list]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[list]      			=				None
   _SCREAMING_SNAKE_CASE       :	bool      			=				False
   _SCREAMING_SNAKE_CASE       :	Optional[Union[int, List[int]]]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[int]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[Union[str, List[str]]]      			=				None
   _SCREAMING_SNAKE_CASE       :	bool      			=				True
   _SCREAMING_SNAKE_CASE       :	bool      			=				True
   _SCREAMING_SNAKE_CASE       :	bool      			=				False
   _SCREAMING_SNAKE_CASE       :	bool      			=				True
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				None
   _SCREAMING_SNAKE_CASE       :	str      			=				"."
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				None
   _SCREAMING_SNAKE_CASE       :	str      			=				'"'
   _SCREAMING_SNAKE_CASE       :	int      			=				0
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				None
   _SCREAMING_SNAKE_CASE       :	bool      			=				True
   _SCREAMING_SNAKE_CASE       :	bool      			=				True
   _SCREAMING_SNAKE_CASE       :	int      			=				0
   _SCREAMING_SNAKE_CASE       :	bool      			=				True
   _SCREAMING_SNAKE_CASE       :	bool      			=				False
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				None
   _SCREAMING_SNAKE_CASE       :	int      			=				1_0000
   _SCREAMING_SNAKE_CASE       :	Optional[datasets.Features]      			=				None
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				"strict"
   _SCREAMING_SNAKE_CASE       :	Literal["error", "warn", "skip"]      			=				"error"
   _SCREAMING_SNAKE_CASE       :	Optional[str]      			=				None


   def 		_lowerCamelCase  (					self    ):





      """simple docstring"""





      if self.delimiter is not None:
         _lowercase     : Union[str, Any]     	=  self.delimiter
      if self.column_names is not None:
         _lowercase     : int     	=  self.column_names






   @property
   def 		_lowerCamelCase  (					self    ):





      """simple docstring"""





      _lowercase     : Any     	=  {
          "sep": self.sep,
          "header": self.header,
          "names": self.names,
          "index_col": self.index_col,
          "usecols": self.usecols,
          "prefix": self.prefix,
          "mangle_dupe_cols": self.mangle_dupe_cols,
          "engine": self.engine,
          "converters": self.converters,
          "true_values": self.true_values,
          "false_values": self.false_values,
          "skipinitialspace": self.skipinitialspace,
          "skiprows": self.skiprows,
          "nrows": self.nrows,
          "na_values": self.na_values,
          "keep_default_na": self.keep_default_na,
          "na_filter": self.na_filter,
          "verbose": self.verbose,
          "skip_blank_lines": self.skip_blank_lines,
          "thousands": self.thousands,
          "decimal": self.decimal,
          "lineterminator": self.lineterminator,
          "quotechar": self.quotechar,
          "quoting": self.quoting,
          "escapechar": self.escapechar,
          "comment": self.comment,
          "encoding": self.encoding,
          "dialect": self.dialect,
          "error_bad_lines": self.error_bad_lines,
          "warn_bad_lines": self.warn_bad_lines,
          "skipfooter": self.skipfooter,
          "doublequote": self.doublequote,
          "memory_map": self.memory_map,
          "float_precision": self.float_precision,
          "chunksize": self.chunksize,
          "encoding_errors": self.encoding_errors,
          "on_bad_lines": self.on_bad_lines,
          "date_format": self.date_format,
      }

      # some kwargs must not be passed if they don't have a default value
      # some others are deprecated and we can also not pass them if they are the default value
      for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
         if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig()     ,							_UpperCamelCase    ):
            del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 2.0 new arguments
      if not (datasets.config.PANDAS_VERSION.major >= 2):
         for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_2_0_0_PARAMETERS:
            del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 1.3 new arguments
      if not (datasets.config.PANDAS_VERSION.major >= 1 and datasets.config.PANDAS_VERSION.minor >= 3):
         for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_1_3_0_PARAMETERS:
            del pd_read_csv_kwargs[pd_read_csv_parameter]

      return pd_read_csv_kwargs




class   a__    (				datasets.ArrowBasedBuilder    ):
   _SCREAMING_SNAKE_CASE       :	str      			=				CsvConfig


   def 		_lowerCamelCase  (					self    ):





      """simple docstring"""





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


   def 		_lowerCamelCase  (					self     ,							_UpperCamelCase    ):





      """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}'''    )
      _lowercase     : Optional[int]     	=  dl_manager.download_and_extract(self.config.data_files    )
      if isinstance(_UpperCamelCase     ,							(str, list, tuple)    ):
         _lowercase     : Optional[int]     	=  data_files
         if isinstance(_UpperCamelCase     ,							_UpperCamelCase    ):
            _lowercase     : List[Any]     	=  [files]
         _lowercase     : str     	=  [dl_manager.iter_files(_UpperCamelCase    ) for file in files]
         return [datasets.SplitGenerator(name=datasets.Split.TRAIN     ,							gen_kwargs={"files": files}    )]
      _lowercase     : int     	=  []
      for split_name, files in data_files.items():
         if isinstance(_UpperCamelCase     ,							_UpperCamelCase    ):
            _lowercase     : int     	=  [files]
         _lowercase     : str     	=  [dl_manager.iter_files(_UpperCamelCase    ) for file in files]
         splits.append(datasets.SplitGenerator(name=_UpperCamelCase     ,							gen_kwargs={"files": files}    )    )
      return splits


   def 		_lowerCamelCase  (					self     ,							_UpperCamelCase    ):





      """simple docstring"""





      if self.config.features is not None:
         _lowercase     : int     	=  self.config.features.arrow_schema
         if all(not require_storage_cast(_UpperCamelCase    ) for feature in self.config.features.values()    ):
            # cheaper cast
            _lowercase     : Optional[int]     	=  pa.Table.from_arrays([pa_table[field.name] for field in schema]     ,							schema=_UpperCamelCase    )
         else:
            # more expensive cast; allows str <-> int/float or str to Audio for example
            _lowercase     : List[str]     	=  table_cast(_UpperCamelCase     ,							_UpperCamelCase    )
      return pa_table






   def 		_lowerCamelCase  (					self     ,							_UpperCamelCase    ):





      """simple docstring"""





      _lowercase     : int     	=  self.config.features.arrow_schema if self.config.features else None
      # dtype allows reading an int column as str
      _lowercase     : Any     	=  (
          {
              name: dtype.to_pandas_dtype() if not require_storage_cast(_UpperCamelCase    ) else object
              for name, dtype, feature in zip(schema.names     ,							schema.types     ,							self.config.features.values()    )
          }
          if schema is not None
          else None
      )
      for file_idx, file in enumerate(itertools.chain.from_iterable(_UpperCamelCase    )    ):
         _lowercase     : Any     	=  pd.read_csv(_UpperCamelCase     ,							iterator=_UpperCamelCase     ,							dtype=_UpperCamelCase     ,							**self.config.pd_read_csv_kwargs    )
         try:
            for batch_idx, df in enumerate(_UpperCamelCase    ):
               _lowercase     : str     	=  pa.Table.from_pandas(_UpperCamelCase    )
               # Uncomment for debugging (will print the Arrow table size and elements)
               # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
               # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
               yield (file_idx, batch_idx), self._cast_table(_UpperCamelCase    )
         except ValueError as e:
            logger.error(f'''Failed to read file \'{file}\' with error {type(_UpperCamelCase    )}: {e}'''    )
            raise










import os
from datetime import datetime as dt

from github import Github


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






def 	__lowerCamelCase						(							):





			'''simple docstring'''




			lowerCamelCase    		=  Github(os.environ["""GITHUB_TOKEN"""]      )
			lowerCamelCase    		=  g.get_repo("""huggingface/diffusers"""      )
			lowerCamelCase    		=  repo.get_issues(state="""open"""      )

			for issue in open_issues:
						lowerCamelCase    		=  sorted(issue.get_comments()  ,							key=lambda lowerCamelCase__      : i.created_at  ,							reverse=lowerCamelCase__      )
						lowerCamelCase    		=  comments[0] if len(lowerCamelCase__      ) > 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()

