





"""simple docstring"""




import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Any   )					->Optional[int]:






	'''simple docstring'''






	a :						Tuple      =							{}

	a :						Any      =							job["started_at"]
	a :						int      =							job["completed_at"]

	a :						Tuple      =							date_parser.parse(_lowercase   )
	a :						str      =							date_parser.parse(_lowercase   )

	a :						Tuple      =							round((end_datetime - start_datetime).total_seconds() / 60.0   )

	a :						Optional[Any]      =							start
	a :						Optional[int]      =							end
	a :						Any      =							duration_in_min

	return job_info






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Union[str, Any]       ,			_lowercase		:       Dict=None   )					->int:






	'''simple docstring'''






	a :						Optional[Any]      =							None
	if token is not None:
		a :						List[Any]      =							{"Accept": "application/vnd.github+json", "Authorization": F"""Bearer {token}"""}

	a :						Tuple      =							F"""https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"""
	a :						Dict      =							requests.get(_lowercase       ,			headers=_lowercase   ).json()
	a :						List[str]      =							{}

	try:
		job_time.update({job["name"]: extract_time_from_single_job(_lowercase   ) for job in result["jobs"]}   )
		a :						List[Any]      =							math.ceil((result["total_count"] - 100) / 100   )

		for i in range(_lowercase   ):
			a :						Dict      =							requests.get(url + F"""&page={i + 2}"""       ,			headers=_lowercase   ).json()
			job_time.update({job["name"]: extract_time_from_single_job(_lowercase   ) for job in result["jobs"]}   )

		return job_time
	except Exception:
		print(F"""Unknown error, could not fetch links:\n{traceback.format_exc()}"""   )

	return {}


if __name__ == "__main__":
		a		:					int	      =     argparse.ArgumentParser()
		# Required parameters
		parser.add_argument('''--workflow_run_id''', type=str, required=True, help='''A GitHub Actions workflow run id.''')
		a		:					Optional[int]	      =     parser.parse_args()

		a		:					List[Any]	      =     get_job_time(args.workflow_run_id)
		a		:					Any	      =     dict(sorted(job_time.items(), key=lambda item: item[1]["duration"], reverse=True))

		for k, v in job_time.items():
				print(F'''{k}: {v["duration"]}''')









"""simple docstring"""




from __future__ import annotations

import matplotlib.pyplot as plt  # type: ignore
import numpy

# initial triangle of Koch snowflake
a		:					int	      =     numpy.array([0, 0])
a		:					Optional[Any]	      =     numpy.array([0.5, 0.866_0254])
a		:					Tuple	      =     numpy.array([1, 0])
a		:					List[str]	      =     [VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list[numpy.ndarray]       ,			_lowercase		:       int   )					->list[numpy.ndarray]:






	'''simple docstring'''






	a :						List[str]      =							initial_vectors
	for _ in range(_lowercase   ):
		a :						Optional[Any]      =							iteration_step(_lowercase   )
	return vectors






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list[numpy.ndarray]   )					->list[numpy.ndarray]:






	'''simple docstring'''






	a :						Union[str, Any]      =							[]
	for i, start_vector in enumerate(vectors[:-1]   ):
		a :						str      =							vectors[i + 1]
		new_vectors.append(_lowercase   )
		a :						Optional[int]      =							end_vector - start_vector
		new_vectors.append(start_vector + difference_vector / 3   )
		new_vectors.append(
		    start_vector + difference_vector / 3 + rotate(difference_vector / 3       ,			60   )   )
		new_vectors.append(start_vector + difference_vector * 2 / 3   )
	new_vectors.append(vectors[-1]   )
	return new_vectors






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       numpy.ndarray       ,			_lowercase		:       float   )					->numpy.ndarray:






	'''simple docstring'''






	a :						int      =							numpy.radians(_lowercase   )
	a,			a :						Optional[int]      =							numpy.cos(_lowercase   ), numpy.sin(_lowercase   )
	a :						Dict      =							numpy.array(((c, -s), (s, c))   )
	return numpy.dot(_lowercase       ,			_lowercase   )






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       list[numpy.ndarray]   )					->None:






	'''simple docstring'''






	a :						Dict      =							plt.gca()
	axes.set_aspect("equal"   )

	# matplotlib.pyplot.plot takes a list of all x-coordinates and a list of all
	# y-coordinates as inputs, which are constructed from the vector-list using
	# zip()
	a,			a :						Any      =							zip(*_lowercase   )
	plt.plot(_lowercase       ,			_lowercase   )
	plt.show()


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		a		:					Optional[int]	      =     iterate(INITIAL_VECTORS, 5)
		plot(processed_vectors)


