A simple semi-conversational, multi-step workflow slack bot framework.
Project description
SlackBorg
=========
SlackBorg is a framework for semi-conversational, multi-step workflow
Slack Bots. We're just getting started. Have an idea? File an issue.
Have some code? Open a pull request.
Concepts
========
SlackBorg has two main things you should care about, the ``@command``
decorator and the ``Conversation`` class.
``@command``
------------
``@command`` is a decorator you place on a function you implement to
respond to a given command. A command can be ``multi_step``, which is to
say that its function is called on the given conversation each time a
new message comes in, until the conversation is explicitly closed. It's
up to you how you handle a multi-step conversation. As you'll see, the
``Conversation`` object includes all the data you need to make decisions
each time your handler is called. If your command is not ``multi_step``,
the conversation is closed immediately after your handler returns.
``@command`` parameters:
~~~~~~~~~~~~~~~~~~~~~~~~
- ``match_string``: A RegEx string that you would pass into
``re.compile``. *Required*
- ``flags``: Any flags from the ``re`` module you would pass into
``re.compile``.
- ``multi_step``: Set to ``True`` if your command is multi-step.
Default ``False``.
``Conversation``
----------------
The ``Conversation`` object is the sole parameter to your command
handler. Conversations are unique to a given user in a given channel.
When a message comes in, the conversation manager checks to see if a
conversation exists for the sending user in the channel it is posted to.
If it doesn't yet exist, a Conversation object is constructed and the
command manager attempts to match a command to the Conversation. If it
finds one, its handler is called on the conversation. If a conversation
exists, it is updated with the latest message and its command's handler
called on the updated Conversation.
``Conversation`` fields:
~~~~~~~~~~~~~~~~~~~~~~~~
- ``user_id``: the sender's Slack User ID
- ``user_data``: the sender's full Slack User Data (fetched when the
Conversation is first created)
- ``channel_id``: the Conversation's Slack Channel ID
- ``channel_data``: the Conversation's full Slack Channel Data (fetched
when the Conversation is first created -- **only set if it's a
channel and not a DM**)
- ``initial_message``: the message that was responsible for the
creation of this Conversation.
- ``messages``: the rest of the messages. *Does not include
``initial_message``*.
- ``latest_message``: the most recent message.
- ``context``: a dictionary that you can put any data you want to
persist in the conversation across messages. This is where the magic
is for doing a multi-step command across a conversation.
``Conversation`` methods:
~~~~~~~~~~~~~~~~~~~~~~~~~
- ``say(message)``: send a message to the channel.
- ``close()``: close the conversation.
Installation
============
Right now, I'd probably suggest spinning up a ``virtualenv`` and running
``python setup.py develop`` inside of it.
Usage
=====
Write yourself a script to declare your commands and run your bot, like
so:
::
import os
import random
import re
import time
from slackborg import *
# Get Bot ID and API Token from env -- make sure to put these in your env!
BOT_ID = os.environ.get('SLACK_BOT_ID')
BOT_TOKEN = os.environ.get('SLACK_BOT_TOKEN')
# Define a default response to any non-matching commands. The default default is to silently ignore the command and close the conversation.
@default_command
def default_cmd(conversation):
conversation.say("I see, sir {}".format(conversation.user_data['profile']['first_name']))
# Define a command by a regex string, and optionally any flags you'd give the re.compile method.
@command('hello', flags=re.IGNORECASE)
def hello(conversation):
conversation.say("Hello! I am C-3PO, human-cyborg relations!")
# By default, a command is single-step and auto-closes its conversation upon the handler returning.
# You can override this.
@command('sum', flags=re.IGNORECASE, multi_step=True)
def do_sum(c):
print c
operands = c.context.setdefault('operands', [])
if len(c.messages):
if 'done' in c.latest_message.lower():
c.say("The sum of {} = {}".format(
" + ".join(str(o) for o in operands),
str(sum(operands))
)
)
c.close()
else:
try:
operands.append(int(c.latest_message))
c.say("So far: {}...".format(
" + ".join(str(o) for o in operands)
))
except:
c.say("That input wasn't a number. Try again!")
else:
c.say("Just enter your operands, one by one, and then type `done` when you're done!")
def main():
borg = SlackBorg(BOT_ID, BOT_TOKEN)
borg.run()
if __name__ == '__main__':
main()
# End
Thanks
~~~~~~
Some of the patterns used in this framework borrow ideologies from _lins05/slackbot, so I thank the existing developers of that library for their prior work. Perhaps we can bring these two libraries together, eventually! Or keep them separate :D
.. _lins05/slackbot: https://github.com/lins05/slackbot
=========
SlackBorg is a framework for semi-conversational, multi-step workflow
Slack Bots. We're just getting started. Have an idea? File an issue.
Have some code? Open a pull request.
Concepts
========
SlackBorg has two main things you should care about, the ``@command``
decorator and the ``Conversation`` class.
``@command``
------------
``@command`` is a decorator you place on a function you implement to
respond to a given command. A command can be ``multi_step``, which is to
say that its function is called on the given conversation each time a
new message comes in, until the conversation is explicitly closed. It's
up to you how you handle a multi-step conversation. As you'll see, the
``Conversation`` object includes all the data you need to make decisions
each time your handler is called. If your command is not ``multi_step``,
the conversation is closed immediately after your handler returns.
``@command`` parameters:
~~~~~~~~~~~~~~~~~~~~~~~~
- ``match_string``: A RegEx string that you would pass into
``re.compile``. *Required*
- ``flags``: Any flags from the ``re`` module you would pass into
``re.compile``.
- ``multi_step``: Set to ``True`` if your command is multi-step.
Default ``False``.
``Conversation``
----------------
The ``Conversation`` object is the sole parameter to your command
handler. Conversations are unique to a given user in a given channel.
When a message comes in, the conversation manager checks to see if a
conversation exists for the sending user in the channel it is posted to.
If it doesn't yet exist, a Conversation object is constructed and the
command manager attempts to match a command to the Conversation. If it
finds one, its handler is called on the conversation. If a conversation
exists, it is updated with the latest message and its command's handler
called on the updated Conversation.
``Conversation`` fields:
~~~~~~~~~~~~~~~~~~~~~~~~
- ``user_id``: the sender's Slack User ID
- ``user_data``: the sender's full Slack User Data (fetched when the
Conversation is first created)
- ``channel_id``: the Conversation's Slack Channel ID
- ``channel_data``: the Conversation's full Slack Channel Data (fetched
when the Conversation is first created -- **only set if it's a
channel and not a DM**)
- ``initial_message``: the message that was responsible for the
creation of this Conversation.
- ``messages``: the rest of the messages. *Does not include
``initial_message``*.
- ``latest_message``: the most recent message.
- ``context``: a dictionary that you can put any data you want to
persist in the conversation across messages. This is where the magic
is for doing a multi-step command across a conversation.
``Conversation`` methods:
~~~~~~~~~~~~~~~~~~~~~~~~~
- ``say(message)``: send a message to the channel.
- ``close()``: close the conversation.
Installation
============
Right now, I'd probably suggest spinning up a ``virtualenv`` and running
``python setup.py develop`` inside of it.
Usage
=====
Write yourself a script to declare your commands and run your bot, like
so:
::
import os
import random
import re
import time
from slackborg import *
# Get Bot ID and API Token from env -- make sure to put these in your env!
BOT_ID = os.environ.get('SLACK_BOT_ID')
BOT_TOKEN = os.environ.get('SLACK_BOT_TOKEN')
# Define a default response to any non-matching commands. The default default is to silently ignore the command and close the conversation.
@default_command
def default_cmd(conversation):
conversation.say("I see, sir {}".format(conversation.user_data['profile']['first_name']))
# Define a command by a regex string, and optionally any flags you'd give the re.compile method.
@command('hello', flags=re.IGNORECASE)
def hello(conversation):
conversation.say("Hello! I am C-3PO, human-cyborg relations!")
# By default, a command is single-step and auto-closes its conversation upon the handler returning.
# You can override this.
@command('sum', flags=re.IGNORECASE, multi_step=True)
def do_sum(c):
print c
operands = c.context.setdefault('operands', [])
if len(c.messages):
if 'done' in c.latest_message.lower():
c.say("The sum of {} = {}".format(
" + ".join(str(o) for o in operands),
str(sum(operands))
)
)
c.close()
else:
try:
operands.append(int(c.latest_message))
c.say("So far: {}...".format(
" + ".join(str(o) for o in operands)
))
except:
c.say("That input wasn't a number. Try again!")
else:
c.say("Just enter your operands, one by one, and then type `done` when you're done!")
def main():
borg = SlackBorg(BOT_ID, BOT_TOKEN)
borg.run()
if __name__ == '__main__':
main()
# End
Thanks
~~~~~~
Some of the patterns used in this framework borrow ideologies from _lins05/slackbot, so I thank the existing developers of that library for their prior work. Perhaps we can bring these two libraries together, eventually! Or keep them separate :D
.. _lins05/slackbot: https://github.com/lins05/slackbot
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