class YoutubeAPI(AliceSkill):
"""
Author: Psychokiller1888
Description: Access and manage your youtube account
"""
def __init__(self):
super().__init__()
try:
self._youtube: Optional[YouTubeDataAPI] = None
except ValueError:
raise SkillStartingFailed('Youtube api key not valid')
def onStart(self):
super().onStart()
self._youtube = YouTubeDataAPI(self.getConfig('youtubeApiKey'))
if not self._youtube.verify_key():
raise SkillStartingFailed('Youtube api key not valid')
@IntentHandler('GetYoutubeChannelStats')
def getChannelStats(self, session: DialogSession, **_kwargs):
metadata = self._youtube.get_channel_metadata('')
if not metadata:
self.endDialog(sessionId=session.sessionId,
text=self.randomTalk(text='error'))
return
print(metadata)
self.endDialog(sessionId=session.sessionId,
text=self.randomTalk(text='myText', replace=[sub]))
def run(self):
# Please input your youtube-data-v3 api key!
api_key = ''
yt = YouTubeDataAPI(api_key)
dir = yt.get_channel_metadata(self.user)
# Channel name, subscribers, views, description
channel = [dir['title'], dir['subscription_count'], dir['view_count'],
re.sub('\n', ' ', dir['description'])]
for col in range(2, 6):
# Thousands seperator
if channel[col-2].isdigit():
channel[col-2] = format(int(channel[col-2]), ',')
self.sheet.cell(row=self.index+2, column=col).value = channel[col-2]
if col == 3:
self.sheet.cell(row=self.index+2, column=col).font = Font(color='FF0000')
# Hidden value
for x in range(len(channel)):
if channel[x] == '0':
self.sheet.cell(row=self.index+2, column=x+2).value = 'HIDDEN'
self.sheet.cell(row=self.index+2, column=x+2).font = Font(color='808080')
channel_meta_map[meta_obj["id"]] = line.strip()
# For each channel;, get its upload playlist
upload_playlists = []
with open(channel_metadata_cache_file, "w") as out_file:
for channel_id in channel_ids:
print("Getting Channel Metadata:", channel_id)
meta_obj = None
# Check if we've cached this data
if (channel_id in channel_meta_map):
metadata = channel_meta_map[channel_id]
meta_obj = json.loads(metadata)
else:
meta_obj = yt.get_channel_metadata(channel_id, parser=lambda x: x)
if len(meta_obj) == 0:
print("Error: %s returns empty set" % channel_id)
continue
meta_obj["minerva_collected"] = time.time()
# Write data to cache file and add the upload list to
#. the map of data we'll pull
out_file.write("%s\n" % json.dumps(meta_obj))
uploads = meta_obj["contentDetails"]["relatedPlaylists"]["uploads"]
upload_playlists.append((channel_id, uploads))
# we store channel data in a directory for each channel
if not os.path.exists("channels"):
os.mkdir("channels")
#GET HANDLES TO QUERY
db_connection_str = 'mysql+pymysql://app:xxx^%gv$$@localhost/sotrics'
db_connection = create_engine(db_connection_str)
#SELECT DISTINCT INCASE
df = pd.read_sql('SELECT distinct handle FROM yt_users', con=db_connection)
li = df['handle'].tolist()
for handle in li:
try:
#configure API credentials
#Extract channel meta data - extract multiple user data by passing list.
channel_meta = yt.get_channel_metadata(str(handle))
channel = pd.DataFrame(channel_meta, index=[0])
#From that channel, take the playlist_id_uploads and extract all the videos
channelID = channel['playlist_id_uploads'].values[0]
all_videos = yt.get_videos_from_playlist_id(
channelID) #UUvlJkDfgfG3J38pup6lvrPg
videos_list = pd.DataFrame(all_videos)
def convert_time(row):
new_time = time.strftime('%Y-%m-%d %H:%M:%S',
time.localtime(row['publish_date']))
return new_time
videos_list.reset_index()
yt = YouTubeDataAPI(api_key)
sonic_search = yt.search(q="Sonic The Headgehog", max_results=5, parser=None)
spy
df_sonic = pd.DataFrame(sonic_search)
df_sonic.head(5)
trailer = df_sonic.iloc[0]
trailer.video_id
comments = yt.get_video_comments(trailer.video_id, max_results=10)
df_comments = pd.DataFrame(comments)
df_graph_data = pd.DataFrame(columns=[
'comment_id', 'commenter_channel_id', 'channel_country', 'text', 'date',
'neg', 'neu', 'pos', 'compound'
])
channel_id = df_comments.iloc[0].commenter_channel_id
channel_data = yt.get_channel_metadata(channel_id)
# for index, row in df_comments.iterrows():
# channel_id = df_comments.iloc[0].commenter_channel_id
# channel_data = yt.get_channel_metadata(channel_id)
# print
# score = analyser.polarity_scores(row['text'])
# graph_row = {'comment_id': row['comment_id'], 'commenter_channel_id': row['commenter_channel_id'], 'channel_country' : channel_data['country'], 'text' : row['text'], 'date': row['collection_date'], 'neg': score['neg'], 'neu': score['neu'], 'pos': score['pos'], 'compound': score['compound']}
# df_graph_data = df_graph_data.append(graph_row, ignore_index=True)