django-bubblehouse-slackbot 1.3.1

Create a Slack bot inside a Django application

django-slackbot

Build a Slack bot as a regular Django app.

django-slackbot is a thin Django integration around slack-bolt, plus a small set of conventions for organising bot code and running it alongside the rest of your Django stack. You write Slack event/command/action handlers as decorated functions in any installed app's chat.py; a management command (or Celery beat) wires them up at startup.

pip install django-bubblehouse-slackbot

PyPI: https://pypi.org/project/django-bubblehouse-slackbot/

What you get

• slack-bolt App, lifted into Django. The django_slackbot.chat.app object is a fully-configured slack_bolt.App instance. Use @app.command, @app.action, @app.event, @app.message, @app.shortcut, @app.error exactly as you would with raw slack-bolt.
• Per-app handler discovery. Drop a chat.py in any installed Django app and manage.py run_slackbot autodiscovers it, so handlers live next to the rest of that app's code.
• Periodic tasks via Celery beat. @app.schedule("*/5 * * * *") registers a function as a Celery task and a beat-schedule entry in one decorator. Workers and beat run as their own services; see compose.yaml.
• Socket Mode by default. No public ingress required for development — the chatbot connects out to Slack over a WebSocket. manage.py run_slackbot starts the listener.

Quickstart

1. Configure your Slack app

1. Create an app at https://api.slack.com/apps and use slack-app.yml as the manifest (App Manifest → paste contents → Save → Install).
2. Enable Socket Mode and generate an app-level token (xapp-…) with connections:write.
3. From OAuth & Permissions, copy the bot user OAuth token (xoxb-…).

2. Wire the package into a Django project

Add the apps to INSTALLED_APPS:

INSTALLED_APPS = [
    # …
    "django_celery_results",   # required if you use @app.schedule
    "django_slackbot",
    "django_slackbot.app_home",
    "django_slackbot.frinkiac",
]

Set up a Celery app (mirroring examples/celery.py / examples/celeryconfig.py) and hook the chat-schedule registry into it:

# myproject/celery.py
from celery import Celery
from django.utils.module_loading import autodiscover_modules
from django_slackbot.celery_support import install_chat_schedules

app = Celery("myproject")
app.config_from_object("myproject.celeryconfig")
app.autodiscover_tasks()

@app.on_after_finalize.connect
def _wire_chat_schedules(sender, **kwargs):
    autodiscover_modules("chat")
    install_chat_schedules(sender)

Export it from your project package so Django sees it at startup:

# myproject/__init__.py
from .celery import app as celery_app
__all__ = ("celery_app",)

3. Write a handler

# myapp/chat.py
from django_slackbot.chat import app

@app.command("/hello")
def hello(ack, respond, command):
    ack()
    respond(f"Hi, <@{command['user_id']}>!")

@app.schedule("*/5 * * * *")
def heartbeat():
    # Runs every five minutes via Celery beat → worker
    ...

4. Run it

Locally, with the included compose stack:

cp compose.override.yaml.example compose.override.yaml   # add your SLACK_*_TOKEN
docker compose up --build

That brings up nginx, webapp (Django + uWSGI), chatbot (Socket Mode listener), worker (Celery), beat (Celery beat), and redis.

Without Docker:

export SLACK_BOT_TOKEN=xoxb-…  SLACK_APP_TOKEN=xapp-…
python manage.py run_slackbot          # chatbot
celery -A myproject worker -l INFO     # background tasks + scheduled jobs
celery -A myproject beat   -l INFO     # scheduler

Layout

django_slackbot/
  chat.py              # the shared slack_bolt App; exports `app` and `@app.schedule`
  celery_support.py    # bridge between @app.schedule and the consumer's Celery app
  management/commands/run_slackbot.py
  app_home/chat.py     # example: app_home_opened handler
  frinkiac/chat.py     # example: /frink + /morbo slash commands
  frinkiac/comic_payload.py   # binary encoder for frinkiac/morbotron's /comic/img endpoint
examples/              # a minimal Django project that wires everything together
  celery.py            # Celery app
  celeryconfig.py      # broker, result backend, logging
  log_filters.py       # filters out slack-bolt's noisy DEBUG dumps
  settings.py

Development

uv sync --all-extras
uv run pytest -n auto       # 38+ tests
uv run ruff check .
uv run pre-commit run --all-files

The test suite uses pytest-spec for human-readable output and pytest-xdist for parallelism.

License

AGPL-3.0-only.