The social rainbow mind machine sheep. credit
Social Sheep turn the normally reclusive and introverted Sheep into extroverted bots that can interact with the Twitterverse through tweets.
SocialSheep class implements the ability to search
for tweets matching a search term, and perform
actions with those tweets.
Sometimes you want a Twitter bot to do things like follow people, favorite tweets, or retweet tweets. That's what Social Sheep are for.
Social Sheep will search for the last N tweets matching a search term (e.g., a hashtag or a keyword) and will return them in a list.
Social Sheep can then:
- favorite all of the tweets in the list;
- retweet all of the tweets in the list;
- follow all of the users who wrote the tweets;
- any combination of the above, and more.
Toilet Training: Using the Social Sheep¶
Internally, the Social Sheep is performing a search for N tweets matching a given search term, and forms a small pool of tweets as a result. This pool of tweets is called a Toilet.
The toilet is
flush()ed each time a search is
performed. The Social Sheep can favorite the
toilet, follow the toilet, or retweet the toilet,
and when it is finished, it will take a nap,
then it will flush the toilet and repeat the
whole process again.
Creating a Shepherd that creates Social Sheep,
and then tells the Social Sheep to perform this
"forever" action, use the usual Keymaker,
then pass the SocialSheep type (part of the
rainbowmindmachine package) to the Sheperd
Here is some example code: three methods,
one to perform the OAuth authentication process
via the Keymaker, one to create a Shepherd and
tweet action using the bot account,
and the last to perform the
and repeatedly flush the toilet and favorite
everything in the toilet forever.
If you call the
retweet action it will retweet
the tweets in the toilet.
import rainbowmindmachine as rmm def setup(): """ Set up the flock """ k = rmm.Keymaker() k.set_apikeys_file('apikeys.json') k.make_a_key( name = 'social_bot', json_name = 'social_bot.json', keys_out_dir = 'keys' ) def tweet(): """ Each sheep is gonna tweet forever """ sh = rmm.Shepherd( json_keys_dir = 'keys/', flock_name = 'simple flock', sheep_class = rmm.SocialSheep ) sh.perform_action('tweet', publish = False, inner_sleep = 10, outer_sleep = 60 ) def favorite(): """ Each sheep is gonna favorite #rainbowmindmachine tweets forever """ sh = rmm.Shepherd( json_keys_dir = 'keys/', flock_name = 'simple flock', sheep_class = TestSocialSheep ) sh.perform_action('favorite', sleep = 60, search_term = '#rainbowmindmachine' )
Extending the Social Sheep¶
A quick example of how we can define our own
bot behavior by extending rainbow mind machine's
classes: here, we define a
method for our Social Sheep, which enables us
to customize both the tweeting and the favorite
toilet behavior of our Sheep:
import rainbowmindmachine as rmm class SuperTweetingSocialSheep(rmm.SocialSheep): """ Social Sheep that extends populate_queue(), so this Social Sheep can also tweet. """ def populate_queue(self): tweet_queue =  tweet_queue.append('hello world 1/3 #rainbowmindmachine') tweet_queue.append('i am not a bot 2/3 #rainbowmindmachine') tweet_queue.append('do not be alarmed 3/3 #rainbowmindmachine') return tweet_queue def setup(): """ Set up the flock """ k = rmm.Keymaker() k.set_apikeys_file('apikeys.json') k.make_a_key( name = 'social_bot', json_name = 'social_bot.json', keys_out_dir = 'keys' ) def tweet(): """ Tweet using the custom Sheep class """ sh = rmm.Shepherd( json_keys_dir = 'keys/', flock_name = 'simple flock', sheep_class = SuperTweetingSocialSheep ) sh.perform_action('tweet', inner_sleep = 10, outer_sleep = 60 )