def fetch(tweet_id: int,
index_no: int = 0,
cutoff: int = 86400) -> typing.Optional['TweetSauceCache']:
"""
Attempt to load a cached saucenao lookup
Args:
tweet_id(int): Tweet ID to look up
index_no (int): The media indice for tweets with multiple media uploads
cutoff (int): Only retrieve cache entries up to `cutoff` seconds old. (Default is 1-day)
Returns:
typing.Optional[TweetSauceCache]
"""
now = int(time.time())
cutoff_ts = 0 if not cutoff else (now - cutoff)
sauce = TweetSauceCache.get(tweet_id=tweet_id, index_no=index_no)
if sauce:
log.debug(
f'[SYSTEM] Sauce cache hit on index {index_no} for tweet {tweet_id}'
)
if sauce.created_at < cutoff_ts:
log.info(
f'[SYSTEM] Sauce cache query on index {index_no} for tweet {tweet_id} has expired'
)
return None
return sauce
def fetch(tweet_id: int) -> typing.Optional['TweetCache']:
"""
Attempt to retrieve a tweet from our local cache
Args:
tweet_id(int): Tweet ID to look up
Returns:
typing.Optional[TweetCache]
"""
tweet = TweetCache.get(tweet_id=tweet_id)
if tweet:
log.debug(f'[SYSTEM] Tweet {tweet_id} cache hit')
return tweet
def set(tweet: TweetCache,
sauce_results: typing.Optional[SauceNaoResults] = None,
index_no: int = 0,
trigger: str = TRIGGER_MENTION) -> 'TweetSauceCache':
"""
Cache a SauceNao query
Args:
tweet (TweetCache): Cached Tweet entry
sauce_results (Optional[SauceNaoResults]): Results to filter and process
index_no (int): The media indice for tweets with multiple media uploads
trigger (str): The event that triggered the sauce lookup (purely for analytics)
Returns:
TweetSauceCache
"""
# Delete any existing cache entry. This is just for safety; it shouldn't actually be triggered.
cache = TweetSauceCache.get(tweet_id=tweet.tweet_id, index_no=index_no)
if cache:
log.info(
f'[SYSTEM] Overwriting sauce cache entry for tweet {tweet.tweet_id}'
)
cache.delete()
commit()
# If there are no results, we log a cache entry anyways to prevent making additional queries
def no_results():
log.info(
f'[SYSTEM] Logging a failed Sauce lookup for tweet {tweet.tweet_id} on indice {index_no}'
)
_cache = TweetSauceCache(tweet_id=tweet.tweet_id,
index_no=index_no,
trigger=trigger,
created_at=int(time.time()))
return _cache
if not sauce_results or not sauce_results.results:
return no_results()
# Get the first result and make sure it meets our minimum similarity requirement
similarity_cutoff = int(
config.getfloat('Twitter',
f"min_similarity_{trigger}",
fallback=50.0))
sauce = sauce_results.results[0]
# Finally, make sure the sauce result actually meets our minimum similarity requirements
if (sauce.similarity < similarity_cutoff):
log.debug(
f"[SYSTEM] Sauce potentially found for tweet {tweet.tweet_id}, but it didn't meet the minimum {trigger} similarity requirements"
)
return no_results()
log.info(
f'[SYSTEM] Caching a successful sauce lookup query for tweet {tweet.tweet_id} on indice {index_no}'
)
cache = TweetSauceCache(tweet_id=tweet.tweet_id,
index_no=index_no,
sauce_header=sauce.header,
sauce_data=sauce.data,
sauce_class=type(sauce).__name__,
sauce_index=sauce.index,
trigger=trigger,
created_at=int(time.time()))
return cache