Slack Machine

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:

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from machine.plugins.base import MachineBasePlugin
from machine.plugins.message import 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}")

Breaking Changes

Dropped support for Python 3.8 (v0.38.0)

As of v0.38.0, support for Python 3.8 has been
dropped. Python 3.8 has reached end-of-life on 2024-10-07.

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
• Respond to Slash Commands
• 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 🏚]
• Support for interactive elements
• Support for modals
• 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, SQLite and in-memory storage are
  supported)
• Schedule actions and messages
• Emit and listen for events
• Help texts for Plugins

Coming Soon

• Support for shortcuts
• ... and much more

Installation

You can add Slack Machine to your uv project by running:

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uv add slack-machine

or add it to your Poetry project:

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poetry add slack-machine

Lastly, you can install it using pip (not recommended):

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$ pip install 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:

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

7. Start the bot with slack-machine

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!

There is also an example plugin that shows off many of the features of Slack Machine:
Slack Machine Kitchensink Plugin