Mudah untuk menghitung berapa banyak lalu lintas yang berasal dari saluran YouTube. Misalnya, buka Metrik Yandex atau penghitung Google Analytics. Dan Anda mencoba mencari tahu apa yang terjadi pada video Anda di saluran tersebut. Siapa yang memandangnya, yang ditambahkan ke favorit, dan siapa yang tidak suka. Tetapi untuk membongkar data seperti itu, Anda memerlukan skrip Python.
Dinamika kegiatan YoutubeAPI Youtube cukup sederhana. Kami akan mengunggah daftar daftar putar dan untuk setiap statistik unggahan daftar putar di video.
YOUTUBE_API_URL = 'https://www.googleapis.com/youtube/v3' YOUTUBE_API_KEY = '...' YOUTUBE_CHANNEL_ID = '...'
Pengidentifikasi saluran dapat ditemukan dalam kode halaman. Anda dapat membaca tentang cara mendapatkan kunci akses di
sini . Buat kelas report_client dan tentukan prosedur di dalamnya.
class report_client: def __init__(self, api_url, api_key, proxies): self._url = api_url self._key = api_key self._proxies = proxies def req_video(self, channel_id = YOUTUBE_CHANNEL_ID): url = ('{0}/activities?channelId={1}&key={2}&part=snippet%2CcontentDetails&maxResults=50') r = requests.get(url.format(self._url, channel_id,self._key) , proxies = self._proxies) parsed = json.loads(r.text) res_df = pd.DataFrame(columns=['video_id']) for i in parsed['items']: temp = {} if 'upload' in i['contentDetails']: temp['video_id'] = i['contentDetails']['upload']['videoId'] res_df = res_df.append(temp, ignore_index=True) return res_df def req_playlist(self, channel_id = YOUTUBE_CHANNEL_ID): url = ('{0}/playlists?channelId={1}&key={2}&part=snippet%2CcontentDetails&maxResults=50') r = requests.get(url.format(self._url, channel_id, self._key) , proxies = self._proxies) parsed = json.loads(r.text) res_df = pd.DataFrame(columns=['playlist_id', 'playlist_name']) for i in parsed['items']: temp = {} temp['playlist_id'] = i['id'] temp['playlist_name'] = i['snippet']['title'] res_df = res_df.append(temp, ignore_index=True) return res_df def req_playlist_stat(self, playlist_id, channel_id = YOUTUBE_CHANNEL_ID): res_df = pd.DataFrame(columns=['video_id', 'playlist_id', 'playlist_name']) for i,k in playlist_id.iterrows(): url = ('{0}/playlistItems?playlistId={1}&key={2}&part=snippet&maxResults=50') r = requests.get(url.format(self._url, k['playlist_id'],self._key) , proxies = self._proxies) parsed = json.loads(r.text) for j in parsed['items']: temp = {} temp['video_id'] = j['snippet']['resourceId']['videoId'] temp['playlist_id'] = k['playlist_id'] temp['playlist_name'] = k['playlist_name'] res_df = res_df.append(temp, ignore_index=True) stop = 0 while 'nextPageToken' in parsed: url = ('{0}/playlistItems?playlistId={1}&key={2}&part=snippet&maxResults=50&pageToken={3}') r = requests.get(url.format(self._url, k['playlist_id'],self._key,parsed['nextPageToken']) , proxies = self._proxies) parsed = json.loads(r.text) for j in parsed['items']: temp = {} temp['video_id'] = j['snippet']['resourceId']['videoId'] temp['playlist_id'] = k['playlist_id'] temp['playlist_name'] = k['playlist_name'] res_df = res_df.append(temp, ignore_index=True) stop = stop + 1 if stop == 1: break return res_df def req_stat(self, video_id): res_df = pd.DataFrame(columns=['video_id','publishedAt','title','description',\ 'tags','local_title','viewCount','likeCount',\ 'dislikeCount','favoriteCount','commentCount'\ , 'playlist_id', 'playlist_name']) for i,k in video_id.iterrows(): url = ('{0}/videos?id={1}&key={2}&part=snippet,contentDetails,statistics,status&maxResults=50') r = requests.get(url.format(self._url, k['video_id'], self._key) , proxies = self._proxies) parsed = json.loads(r.text) if 'error' in parsed.keys(): break temp = {} if 'items' in parsed: if parsed['items']: temp['video_id'] = parsed['items'][0]['id'] temp['publishedAt'] = parsed['items'][0]['snippet']['publishedAt'] temp['title'] = parsed['items'][0]['snippet']['title'] temp['description'] = parsed['items'][0]['snippet']['description'] temp['playlist_id'] = k['playlist_id'] temp['playlist_name'] = k['playlist_name'] if 'tags' in parsed['items'][0]['snippet']: temp['tags'] = parsed['items'][0]['snippet']['tags'] if 'title' in parsed['items'][0]['snippet']['localized']: temp['local_title'] = parsed['items'][0]['snippet']['localized']['title'] if 'viewCount' in parsed['items'][0]['statistics']: temp['viewCount'] = parsed['items'][0]['statistics']['viewCount'] if 'likeCount' in parsed['items'][0]['statistics']: temp['likeCount'] = parsed['items'][0]['statistics']['likeCount'] if 'dislikeCount' in parsed['items'][0]['statistics']: temp['dislikeCount'] = parsed['items'][0]['statistics']['dislikeCount'] if 'favoriteCount' in parsed['items'][0]['statistics']: temp['favoriteCount'] = parsed['items'][0]['statistics']['favoriteCount'] if 'commentCount' in parsed['items'][0]['statistics']: temp['commentCount'] = parsed['items'][0]['statistics']['commentCount'] res_df = res_df.append(temp, ignore_index=True) return res_df
Selanjutnya, untuk mendapatkan pembongkaran, kita perlu menginisialisasi kelas dan mulai membongkar.
def youtube_reports(): a = report_client(YOUTUBE_API_URL,YOUTUBE_API_KEY,{}) method_rep = getattr(a, "req_playlist") playlist_id = method_rep() method_rep = getattr(a, "req_playlist_stat") video_id = method_rep(playlist_id) report_list = ["req_stat"] for rep in report_list: result_local_file_name = 'df_{0}.csv'.format(rep) method_rep = getattr(a, rep) df = method_rep(video_id) df.to_csv(r'C:\\Users\\User\\Desktop\\youtube.csv', index=False, header=True, sep='\t', quoting = csv.QUOTE_ALL, encoding="utf-8") to_sql_server(df, 'youtube_{0}'.format(rep)) youtube_reports()
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