def __init__(self):
self.log = logging.getLogger(__name__)
# Tweet Cache Manager
self.twitter = TweetManager()
self.twython = Twython(config.get('Twitter', 'consumer_key'),
config.get('Twitter', 'consumer_secret'),
config.get('Twitter', 'access_token'),
config.get('Twitter', 'access_secret'))
self.anime_link = config.get('SauceNao',
'source_link',
fallback='anidb').lower()
self.nsfw_previews = config.getboolean('TraceMoe',
'nsfw_previews',
fallback=False)
self.failed_responses = config.getboolean('SauceNao',
'respond_to_failed',
fallback=True)
self.ignored_indexes = [
int(i) for i in config.get(
'SauceNao', 'ignored_indexes', fallback='').split(',')
]
# Pixiv
self.pixiv = Pixiv()
# Cache some information about ourselves
self.my = api.me()
self.log.info(f"Connected as: {self.my.screen_name}")
# Image URL's are md5 hashed and cached here to prevent duplicate API queries. This is cleared every 24-hours.
# I'll update this in the future to use a real caching mechanism (database or redis)
self._cached_results = {}
# A cached list of ID's for parent posts we've already processed
# Used in the check_monitored() method to prevent re-posting sauces when posts are re-tweeted
self._posts_processed = []
# The ID cutoff, we populate this once via an initial query at startup
try:
self.mention_id = tweepy.Cursor(api.mentions_timeline,
tweet_mode='extended',
count=1).items(1).next().id
except StopIteration:
self.mention_id = 0
try:
self.self_id = tweepy.Cursor(api.user_timeline,
tweet_mode='extended',
count=1).items(1).next().id
except StopIteration:
self.self_id = 0
self.monitored_since = {}
def __init__(self):
self.log = logging.getLogger(__name__)
# Tweet Cache Manager
self.twitter = TweetManager()
self.twython = Twython(config.get('Twitter', 'consumer_key'),
config.get('Twitter', 'consumer_secret'),
config.get('Twitter', 'access_token'),
config.get('Twitter', 'access_secret'))
# SauceNao
self.minsim_mentioned = float(
config.get('SauceNao', 'min_similarity_mentioned', fallback=50.0))
self.minsim_monitored = float(
config.get('SauceNao', 'min_similarity_monitored', fallback=65.0))
self.minsim_searching = float(
config.get('SauceNao', 'min_similarity_searching', fallback=70.0))
self.persistent = config.getboolean('Twitter',
'enable_persistence',
fallback=False)
self.anime_link = config.get('SauceNao',
'source_link',
fallback='anidb').lower()
self.sauce = SauceNao(api_key=config.get('SauceNao',
'api_key',
fallback=None),
min_similarity=min(self.minsim_mentioned,
self.minsim_monitored,
self.minsim_searching),
priority=[21, 22, 5])
# Trace.moe
self.tracemoe = None # type: Optional[ATraceMoe]
if config.getboolean('TraceMoe', 'enabled', fallback=False):
self.tracemoe = ATraceMoe(
config.get('TraceMoe', 'token', fallback=None))
self.nsfw_previews = config.getboolean('TraceMoe',
'nsfw_previews',
fallback=False)
# Pixiv
self.pixiv = Pixiv()
# Cache some information about ourselves
self.my = api.me()
self.log.info(f"Connected as: {self.my.screen_name}")
# Image URL's are md5 hashed and cached here to prevent duplicate API queries. This is cleared every 24-hours.
# I'll update this in the future to use a real caching mechanism (database or redis)
self._cached_results = {}
# A cached list of ID's for parent posts we've already processed
# Used in the check_monitored() method to prevent re-posting sauces when posts are re-tweeted
self._posts_processed = []
# The ID cutoff, we populate this once via an initial query at startup
try:
self.since_id = tweepy.Cursor(api.mentions_timeline,
tweet_mode='extended',
count=1).items(1).next().id
except StopIteration:
self.since_id = 0
self.monitored_since = {}