




"""simple docstring"""




import unittest

from huggingface_hub import hf_hub_download

from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_decord,
    require_tf,
    require_torch,
    require_torch_or_tf,
    require_vision,
)

from .test_pipelines_common import ANY






@is_pipeline_test
@require_torch_or_tf
@require_vision
@require_decord
class 					__magic_name__							( unittest.TestCase       ):






				'''simple docstring'''
				__UpperCamelCase    						=		MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING





				def      _lowerCAmelCase       ( self	,				_a	,				_a	,				_a				):





							"""simple docstring"""
							lowerCamelCase       =      hf_hub_download(
							    repo_id="""nateraw/video-demo"""	,				filename="""archery.mp4"""	,				repo_type="""dataset"""				)
							lowerCamelCase       =      VideoClassificationPipeline(model=_a	,				image_processor=_a	,				top_k=2				)
							lowerCamelCase       =      [
							    example_video_filepath,
							    """https://huggingface.co/datasets/nateraw/video-demo/resolve/main/archery.mp4""",
							]
							return video_classifier, examples





				def      _lowerCAmelCase       ( self	,				_a	,				_a				):





							"""simple docstring"""
							for example in examples:
										lowerCamelCase       =      video_classifier(_a				)

										self.assertEqual(
										    _a	,				[
										        {"""score""": ANY(_a				), """label""": ANY(_a				)},
										        {"""score""": ANY(_a				), """label""": ANY(_a				)},
										    ]	,				)





				@require_torch
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase       =      """hf-internal-testing/tiny-random-VideoMAEForVideoClassification"""
							lowerCamelCase       =      VideoMAEFeatureExtractor(
							    size={"""shortest_edge""": 10}	,				crop_size={"""height""": 10, """width""": 10}				)
							lowerCamelCase       =      pipeline(
							    """video-classification"""	,				model=_a	,				feature_extractor=_a	,				frame_sampling_rate=4				)

							lowerCamelCase       =      hf_hub_download(repo_id="""nateraw/video-demo"""	,				filename="""archery.mp4"""	,				repo_type="""dataset"""				)
							lowerCamelCase       =      video_classifier(_a	,				top_k=2				)
							self.assertEqual(
							    nested_simplify(_a	,				decimals=4				)	,				[{"""score""": 0.5_199, """label""": """LABEL_0"""}, {"""score""": 0.4_801, """label""": """LABEL_1"""}]	,				)

							lowerCamelCase       =      video_classifier(
							    [
							        video_file_path,
							        video_file_path,
							    ]	,				top_k=2	,				)
							self.assertEqual(
							    nested_simplify(_a	,				decimals=4				)	,				[
							        [{"""score""": 0.5_199, """label""": """LABEL_0"""}, {"""score""": 0.4_801, """label""": """LABEL_1"""}],
							        [{"""score""": 0.5_199, """label""": """LABEL_0"""}, {"""score""": 0.4_801, """label""": """LABEL_1"""}],
							    ]	,				)





				@require_tf
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							pass









"""simple docstring"""




from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

lowerCAmelCase							:    List[Any]  							=							{"""UserAgent""": UserAgent().random}



def 					a__				(       snake_case__       )		->      dict:
			lowerCamelCase       =      script.contents[0]
			lowerCamelCase       =      json.loads(data[data.find("""{\"config\""""       ) : -1]       )
			return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]






class 					__magic_name__							:






				'''simple docstring'''





				def __init__( self	,				_a				):





							"""simple docstring"""
							lowerCamelCase       =      f'https://www.instagram.com/{username}/'
							lowerCamelCase       =      self.get_json()





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase       =      requests.get(self.url	,				headers=_a				).text
							lowerCamelCase       =      BeautifulSoup(_a	,				"""html.parser"""				).find_all("""script"""				)
							try:
										return extract_user_profile(scripts[4]				)
							except (json.decoder.JSONDecodeError, KeyError):
										return extract_user_profile(scripts[3]				)





				def __repr__( self				):





							"""simple docstring"""
							return f'{self.__class__.__name__}(\'{self.username}\')'





				def __str__( self				):





							"""simple docstring"""
							return f'{self.fullname} ({self.username}) is {self.biography}'





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["username"]





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["full_name"]





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["biography"]





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["business_email"]





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["external_url"]





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["edge_followed_by"]["count"]





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["edge_follow"]["count"]





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["edge_owner_to_timeline_media"]["count"]





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["profile_pic_url_hd"]





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["is_verified"]





				@property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return self.user_data["is_private"]




def 					a__				(       snake_case__ = "github"       )		->      None:
			import os

			if os.environ.get("""CI"""       ):
						return  # test failing on GitHub Actions
			lowerCamelCase       =      InstagramUser(snake_case__       )
			assert instagram_user.user_data
			assert isinstance(instagram_user.user_data ,				snake_case__       )
			assert instagram_user.username == username
			if username != "github":
						return
			assert instagram_user.fullname == "GitHub"
			assert instagram_user.biography == "Built for developers."
			assert instagram_user.number_of_posts > 1_50
			assert instagram_user.number_of_followers > 12_00_00
			assert instagram_user.number_of_followings > 15
			assert instagram_user.email == "support@github.com"
			assert instagram_user.website == "https://github.com/readme"
			assert instagram_user.profile_picture_url.startswith("""https://instagram."""       )
			assert instagram_user.is_verified is True
			assert instagram_user.is_private is False


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					lowerCAmelCase							:    str  							=							InstagramUser("""github""")
					print(instagram_user)
					print(F"""{instagram_user.number_of_posts = }""")
					print(F"""{instagram_user.number_of_followers = }""")
					print(F"""{instagram_user.number_of_followings = }""")
					print(F"""{instagram_user.email = }""")
					print(F"""{instagram_user.website = }""")
					print(F"""{instagram_user.profile_picture_url = }""")
					print(F"""{instagram_user.is_verified = }""")
					print(F"""{instagram_user.is_private = }""")



