

import os
from datetime import datetime as dt

from github import Github


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







def 			UpperCAmelCase_ ():
			__UpperCamelCase     :     Tuple										=   Github(os.environ["GITHUB_TOKEN"]		)
			__UpperCamelCase     :     int										=   g.get_repo("huggingface/diffusers"		)
			__UpperCamelCase     :     Tuple										=   repo.get_issues(state="open"		)

			for issue in open_issues:
						__UpperCamelCase     :     Tuple										=   sorted(issue.get_comments()  ,      key=lambda _lowerCAmelCase		: i.created_at  ,      reverse=lowerCamelCase_		)
						__UpperCamelCase     :     List[Any]										=   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()




"""simple docstring"""







import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil

@pytest.fixture
def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							Optional[Any] ):
						"""simple docstring"""






						snake_case   :			str						    = tmp_path / "file.csv"
						snake_case   :			Tuple						    = textwrap.dedent(
						    "\\n        header1,header2\n        1,2\n        10,20\n        " )
						with open(lowerCamelCase_     ,		"w" ) as f:
												f.write(lowerCamelCase_ )
						return str(lowerCamelCase_ )

@pytest.fixture
def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							List[str] ):
						"""simple docstring"""






						snake_case   :			List[Any]						    = tmp_path / "malformed_file.csv"
						snake_case   :			Union[str, Any]						    = textwrap.dedent(
						    "\\n        header1,header2\n        1,2\n        10,20,\n        " )
						with open(lowerCamelCase_     ,		"w" ) as f:
												f.write(lowerCamelCase_ )
						return str(lowerCamelCase_ )

@pytest.fixture
def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							int     ,		lowerCamelCase_:							Optional[Any] ):
						"""simple docstring"""






						snake_case   :			Dict						    = tmp_path / "csv_with_image.csv"
						snake_case   :			List[Any]						    = textwrap.dedent(
						    f'''\
        image
        {image_file}
        ''' )
						with open(lowerCamelCase_     ,		"w" ) as f:
												f.write(lowerCamelCase_ )
						return str(lowerCamelCase_ )

@pytest.fixture
def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							List[str] ):
						"""simple docstring"""






						snake_case   :			Optional[Any]						    = tmp_path / "csv_with_label.csv"
						snake_case   :			Tuple						    = textwrap.dedent(
						    "\\n        label\n        good\n        bad\n        good\n        " )
						with open(lowerCamelCase_     ,		"w" ) as f:
												f.write(lowerCamelCase_ )
						return str(lowerCamelCase_ )

@pytest.fixture
def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							List[Any] ):
						"""simple docstring"""






						snake_case   :			Union[str, Any]						    = tmp_path / "csv_with_int_list.csv"
						snake_case   :			Optional[int]						    = textwrap.dedent(
						    "\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        " )
						with open(lowerCamelCase_     ,		"w" ) as f:
												f.write(lowerCamelCase_ )
						return str(lowerCamelCase_ )

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							List[str]     ,		lowerCamelCase_:							Any     ,		lowerCamelCase_:							List[str] ):
						"""simple docstring"""






						snake_case   :			Tuple						    = Csv()
						snake_case   :			str						    = csv._generate_tables([[csv_file, malformed_csv_file]] )
						with pytest.raises(lowerCamelCase_     ,		match="Error tokenizing data" ):
												for _ in generator:
																		pass
						assert any(
						    record.levelname == "ERROR"
						    and "Failed to read file" in record.message
						    and os.path.basename(lowerCamelCase_ ) in record.message
						    for record in caplog.records )

@require_pil
def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							str ):
						"""simple docstring"""






						with open(lowerCamelCase_     ,		encoding="utf-8" ) as f:
												snake_case   :			List[Any]						    = f.read().splitlines()[1]
						snake_case   :			List[str]						    = Csv(encoding="utf-8"     ,		features=Features({"image": Image()} ) )
						snake_case   :			Optional[int]						    = csv._generate_tables([[csv_file_with_image]] )
						snake_case   :			List[Any]						    = pa.concat_tables([table for _, table in generator] )
						assert pa_table.schema.field("image" ).type == Image()()
						snake_case   :			str						    = pa_table.to_pydict()["image"]
						assert generated_content == [{"path": image_file, "bytes": None}]

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							int ):
						"""simple docstring"""






						with open(lowerCamelCase_     ,		encoding="utf-8" ) as f:
												snake_case   :			Optional[Any]						    = f.read().splitlines()[1:]
						snake_case   :			List[str]						    = Csv(encoding="utf-8"     ,		features=Features({"label": ClassLabel(names=["good", "bad"] )} ) )
						snake_case   :			int						    = csv._generate_tables([[csv_file_with_label]] )
						snake_case   :			Dict						    = pa.concat_tables([table for _, table in generator] )
						assert pa_table.schema.field("label" ).type == ClassLabel(names=["good", "bad"] )()
						snake_case   :			Dict						    = pa_table.to_pydict()["label"]
						assert generated_content == [ClassLabel(names=["good", "bad"] ).straint(lowerCamelCase_ ) for label in labels]

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							Union[str, Any] ):
						"""simple docstring"""






						snake_case   :			List[Any]						    = Csv(encoding="utf-8"     ,		sep=","     ,		converters={"int_list": lambda lowerCamelCase_ : [int(lowerCamelCase_ ) for i in x.split()]} )
						snake_case   :			Tuple						    = csv._generate_tables([[csv_file_with_int_list]] )
						snake_case   :			str						    = pa.concat_tables([table for _, table in generator] )
						assert pa.types.is_list(pa_table.schema.field("int_list" ).type )
						snake_case   :			Any						    = pa_table.to_pydict()["int_list"]
						assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]



