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https://github.com/bfontaine/blabbr

Twitter bot
https://github.com/bfontaine/blabbr

bot python twitter

Last synced: about 1 month ago
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Twitter bot

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README 

        
# Blabbr



`blabbr` is a bot that tweets randomly-generated texts using

[Markov chains][markovify].



[markovify]: https://github.com/jsvine/markovify



## Setup



    pip install blabbr



Then follow the interactive setup:



    blabbr setup



You can also initialize a configuration file with `blabbr config init` then

fill it by hand. Check the _Config_ section below for more info.



## Run



Running a bot with `blabbr` is done in two steps: first, feed the model. Then,

use that model to generate tweets.



You can feed your model either from Twitter using a few users as a seed or from

a file that contains one tweet per line:



    # feed from Twitter

    $ blabbr populate



    # feed from a file

    $ blabbr populate --from-raw mytweets.txt



You can also retrieve tweets in a file instead of feeding them directly to the

model. This is useful in combination with `--from-raw` to check the tweets

before feeding them:



    # append tweets to tweets.txt, one per line

    $ blabbr populate --raw tweets.txt



By default the model is stored in `blabbr.json` in the current directory. You

can change that by using the `--model` option:



    $ blabbr --model mymodel.json populate



Populating an existing model doesn’t erase its previous content.



---



Once you’re happy with your model run it:



    blabbr run



The default bot follows a few rules to behave well with its human friends:



* It doesn’t tweet during the night

* It tweets less during work hours

* It never tweets more than twice in a couple of minutes



### Config



A bot needs a configuration file to run. By default it tries to find

`blabbr.cfg` in the current directory and fallback on `~/.blabbr.cfg`. You can

give a custom path with `--cfg `.



The default config file looks like this:



```ini

[seeds]

screen_names = 



[auth]

token = 

consumer_secret = 

consumer_key = 

token_secret = 



[bot]

timezone = Europe/Paris

lang = en

```



* `seeds.screen_names` should be a comma-separated list of Twitter usernames.

  Those are used as seeds to retrieve tweets. By default it fetches their last

  1000 tweets then check 10 of the users they follow and so on. See

  `blabbr populate --help` for more info on how to change that behavior.

* `auth.token` and similar keys are needed for the Twitter API. Run

   `blabbr setup --help` for more info.

* `bot.timezone` is the bot’s timezone. This is important so that it doesn’t

  tweet in the middle of the night.

* `bot.lang` is used to filter tweets when populating the model.

* `bot.follow` and other boolean options are flags to enable/disable some of

  the bot's actions. Right now only the `tweet` feature is implemented.



A few more variables can be set:



* `bot.screen_name`: Your bot's screen name. It’ll be automatically set if you

  use `blabbr setup`. This is used to save an API call when the bot needs to

  know its own name, in order to e.g. filter out its own tweets from its home

  timeline.



You can print your configuration with `blabbr config`. Use `--cfg` to specify

another path:



    $ blabbr --cfg ~/.config/blabbr.cfg  [options...]



Check your authentication configuration with `blabbr setup --check`.



### Limitations



The most notable limitation right now is that you have to build the model

_before_ running the bot. It’d be a lot more interesting if it could feed its

model in (near-)real-time.



Additionally, I made this toolkit for my own usage and thus it’s best suited

for tweets in French. It’ll work for other languages but the text cleaning step

won’t be as good.