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Slack Machine

Join the chat at Slack image image image CI Status image

Slack Machine is a simple, yet powerful and extendable Slack bot framework. More than just a bot, Slack Machine is a framework that helps you develop your Slack workspace into a ChatOps powerhouse. Slack Machine is built with an intuitive plugin system that lets you build bots quickly, but also allows for easy code organization. A plugin can look as simple as this:

from machine.plugins.base import MachineBasePlugin, Message
from machine.plugins.decorators import respond_to

class DeploymentPlugin(MachineBasePlugin):
    """Deployments"""
    @respond_to(r"deploy (?P<application>\w+) to (?P<environment>\w+)")
    async def deploy(self, msg: Message, application, environment):
        """deploy <application> <environment>: deploy application to target environment"""
        await msg.say(f"Deploying {application} to {environment}")

Note

As of v0.30.0 Slack Machine dropped support for the old backend based on the RTM API. As such, Slack Machine is now fully based on AsyncIO. This means plugins written before the rewrite to asyncio aren't supported anymore. See here for a migration guide to get your old plugins working with the new version of Slack Machine.

It's really easy!

Features

  • Get started with mininal configuration
  • Built on top of the Slack Events API for smoothly responding to events in semi real-time. Uses Socket Mode so your bot doesn't need to be exposed to the internet!
  • Support for rich interactions using the Slack Web API
  • High-level API for maximum convenience when building plugins
  • Low-level API for maximum flexibility
  • Built on top of AsyncIO to ensure good performance by handling communication with Slack concurrently

Plugin API features:

  • Listen and respond to any regular expression
  • Capture parts of messages to use as variables in your functions
  • Respond to messages in channels, groups and direct message conversations
  • Respond with reactions
  • Respond in threads
  • Respond with ephemeral messages
  • Send DMs to any user
  • Support for blocks
  • Support for message attachments [Legacy 🏚]
  • Listen and respond to any Slack event supported by the Events API
  • Store and retrieve any kind of data in persistent storage (currently Redis, DynamoDB and in-memory storage are supported)
  • Schedule actions and messages
  • Emit and listen for events
  • Help texts for Plugins

Coming Soon

  • Support for Interactive Buttons
  • ... and much more

Installation

You can install Slack Machine using pip:

$ pip install slack-machine

or add it to your Poetry project:

poetry add slack-machine

It is strongly recommended that you install slack-machine inside a virtual environment!

Usage

  1. Create a directory for your Slack Machine bot: mkdir my-slack-bot && cd my-slack-bot

  2. Add a local_settings.py file to your bot directory: touch local_settings.py

  3. Create a new app in Slack: https://api.slack.com/apps

  4. Choose to create an app from an App manifest

  5. Copy/paste the following manifest: manifest.yaml

  6. Add the Slack App and Bot tokens to your local_settings.py like this:

    SLACK_APP_TOKEN = "xapp-my-app-token"
SLACK_BOT_TOKEN = "xoxb-my-bot-token"

  7. Start the bot with slack-machine-async

  8. ...

  9. Profit!

Documentation

You can find the documentation for Slack Machine here: https://dondebonair.github.io/slack-machine/

Go read it to learn how to properly configure Slack Machine, write plugins, and more!