
"""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 		a__						(      datasets.BuilderConfig						):
   __lowerCAmelCase            =				None


class 		a__						(      datasets.ArrowBasedBuilder						):
   __lowerCAmelCase            =				PandasConfig
   def 			__magic_name__			(			self				):
          return datasets.DatasetInfo(features=self.config.features				)
   def 			__magic_name__			(			self	,    _a				):
          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    :				Tuple       		=							dl_manager.download_and_extract(self.config.data_files				)
          if isinstance(_a	,    (str, list, tuple)				):
                 lowercase    :				Tuple       		=							data_files
                 if isinstance(_a	,    _a				):
                        lowercase    :				Optional[Any]       		=							[files]
                 # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
                 lowercase    :				List[Any]       		=							[dl_manager.iter_files(_a				) for file in files]
                 return [datasets.SplitGenerator(name=datasets.Split.TRAIN	,    gen_kwargs={"files": files}				)]
          lowercase    :				Any       		=							[]
          for split_name, files in data_files.items():
                 if isinstance(_a	,    _a				):
                        lowercase    :				Tuple       		=							[files]
                 # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
                 lowercase    :				Optional[int]       		=							[dl_manager.iter_files(_a				) for file in files]
                 splits.append(datasets.SplitGenerator(name=_a	,    gen_kwargs={"files": files}				)				)
          return splits
   def 			__magic_name__			(			self	,    _a				):
          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
                 lowercase    :				Optional[Any]       		=							table_cast(_a	,    self.config.features.arrow_schema				)
          return pa_table

   def 			__magic_name__			(			self	,    _a				):
          for i, file in enumerate(itertools.chain.from_iterable(_a				)				):
                 with open(_a	,    "rb"				) as f:
                        lowercase    :				Any       		=							pa.Table.from_pandas(pd.read_pickle(_a				)				)
                        yield i, self._cast_table(_a				)




"""simple docstring"""




import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links


def   __magic_name__	(      __snake_case				:       Union[str, Any]     , __snake_case				:       List[str]=7  ) ->				str:
       lowercase    :				int       		=							None
       if token is not None:
              lowercase    :				Any       		=							{"Accept": "application/vnd.github+json", "Authorization": f"""Bearer {token}"""}

       # The id of a workflow (not of a workflow run)
       lowercase    :				int       		=							"636036"

       lowercase    :				Dict       		=							f"""https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs"""
       # On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
       url += f"""?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}"""

       lowercase    :				int       		=							requests.get(__snake_case     , headers=__snake_case  ).json()

       return result["workflow_runs"]


def   __magic_name__	(      __snake_case				:       Dict  ) ->				Tuple:
       lowercase    :				Tuple       		=							get_daily_ci_runs(__snake_case  )
       lowercase    :				Union[str, Any]       		=							None
       for workflow_run in workflow_runs:
              if workflow_run["status"] == "completed":
                     lowercase    :				List[Any]       		=							workflow_run["id"]
                     break

       return workflow_run_id


def   __magic_name__	(      __snake_case				:       Optional[int]     , __snake_case				:       Optional[Any]     , __snake_case				:       Union[str, Any]  ) ->				int:
       lowercase    :				Dict       		=							get_last_daily_ci_runs(__snake_case  )
       if workflow_run_id is not None:
              lowercase    :				Dict       		=							get_artifacts_links(worflow_run_id=__snake_case     , token=__snake_case  )
              for artifact_name in artifact_names:
                     if artifact_name in artifacts_links:
                            lowercase    :				Optional[int]       		=							artifacts_links[artifact_name]
                            download_artifact(
                                artifact_name=__snake_case     , artifact_url=__snake_case     , output_dir=__snake_case     , token=__snake_case  )


def   __magic_name__	(      __snake_case				:       List[Any]     , __snake_case				:       Optional[int]     , __snake_case				:       Tuple  ) ->				Optional[int]:
       get_last_daily_ci_artifacts(__snake_case     , __snake_case     , __snake_case  )

       lowercase    :				str       		=							{}
       for artifact_name in artifact_names:
              lowercase    :				Optional[Any]       		=							os.path.join(__snake_case     , f"""{artifact_name}.zip"""  )
              if os.path.isfile(__snake_case  ):
                     lowercase    :				List[Any]       		=							{}
                     with zipfile.ZipFile(__snake_case  ) as z:
                            for filename in z.namelist():
                                   if not os.path.isdir(__snake_case  ):
                                          # read the file
                                          with z.open(__snake_case  ) as f:
                                                 lowercase    :				str       		=							f.read().decode("UTF-8"  )

       return results


