Building my first Slack Bot

I had added a project to my OmniFocus database in November of 2021 which was, "Build a Slackbot" after watching a Video by Mason Egger. I had hoped that I would be able to spend some time on it over the holidays, but I was never able to really find the time.

A few weeks ago, Bob Belderbos tweeted:

And I responded

I didn't really have anymore time now than I did over the holiday, but Bob asking and me answering pushed me to actually write the darned thing.

I think one of the problems I encountered was what backend / tech stack to use. I'm familiar with Django, but going from 0 to something in production has a few steps and although I know how to do them ... I just felt ~overwhelmed~ by the prospect.

I felt equally ~overwhelmed~ by the prospect of trying FastAPI to create the API or Flask, because I am not as familiar with their deployment story.

Another thing that was different now than before was that I had worked on a Django Cookie Cutter to use and that was 'good enough' to try it out. So I did.

I ran into a few problems while working with my Django Cookie Cutter but I fixed them and then dove head first into writing the Slack Bot

The model

The initial implementation of the model was very simple ... just 2 fields:

class Acronym(models.Model):
    acronym = models.CharField(max_length=8)
    definition = models.TextField()

    def save(self, *args, **kwargs):
        self.acronym = self.acronym.lower()
        super(Acronym, self).save(*args, **kwargs)

    class Meta:
        unique_together = ("acronym", "definition")
        ordering = ["acronym"]

    def __str__(self) -> str:
        return self.acronym

Next I created the API using Django Rest Framework using a single serializer

class AcronymSerializer(serializers.ModelSerializer):
    class Meta:
        model = Acronym
        fields = [
            "id",
            "acronym",
            "definition",
        ]

which is used by a single view

class AcronymViewSet(viewsets.ReadOnlyModelViewSet):
    serializer_class = AcronymSerializer
    queryset = Acronym.objects.all()

    def get_object(self):
        queryset = self.filter_queryset(self.get_queryset())
        print(self.kwargs["acronym"])
        acronym = self.kwargs["acronym"]
        obj = get_object_or_404(queryset, acronym__iexact=acronym)

        return obj

and exposed on 2 end points:

from django.urls import include, path

from .views import AcronymViewSet, AddAcronym, CountAcronyms, Events

app_name = "api"

user_list = AcronymViewSet.as_view({"get": "list"})
user_detail = AcronymViewSet.as_view({"get": "retrieve"})

urlpatterns = [
    path("", AcronymViewSet.as_view({"get": "list"}), name="acronym-list"),
    path("<acronym>/", AcronymViewSet.as_view({"get": "retrieve"}), name="acronym-detail"),
    path("api-auth/", include("rest_framework.urls", namespace="rest_framework")),
]

Getting the data

At my joby-job we use Jira and Confluence. In one of our Confluence spaces we have a Glossary page which includes nearly 200 acronyms. I had two choices:

  1. Copy and Paste the acronym and definition for each item
  2. Use Python to get the data

I used Python to get the data, via a Jupyter Notebook, but I didn't seem to save the code anywhere (🤦🏻), so I can't include it here. But trust me, it was 💯.

Setting up the Slack Bot

Although I had watched Mason's video, since I was building this with Django I used this article as a guide in the development of the code below.

The code from my views.py is below:

ssl_context = ssl.create_default_context()
ssl_context.check_hostname = False
ssl_context.verify_mode = ssl.CERT_NONE

SLACK_VERIFICATION_TOKEN = getattr(settings, "SLACK_VERIFICATION_TOKEN", None)
SLACK_BOT_USER_TOKEN = getattr(settings, "SLACK_BOT_USER_TOKEN", None)
CONFLUENCE_LINK = getattr(settings, "CONFLUENCE_LINK", None)
client = slack.WebClient(SLACK_BOT_USER_TOKEN, ssl=ssl_context)

class Events(APIView):
    def post(self, request, *args, **kwargs):

        slack_message = request.data

        if slack_message.get("token") != SLACK_VERIFICATION_TOKEN:
            return Response(status=status.HTTP_403_FORBIDDEN)

        # verification challenge
        if slack_message.get("type") == "url_verification":
            return Response(data=slack_message, status=status.HTTP_200_OK)
        # greet bot
        if "event" in slack_message:
            event_message = slack_message.get("event")

            # ignore bot's own message
            if event_message.get("subtype"):
                return Response(status=status.HTTP_200_OK)

            # process user's message
            user = event_message.get("user")
            text = event_message.get("text")
            channel = event_message.get("channel")
            url = f"https://slackbot.ryancheley.com/api/{text}/"
            response = requests.get(url).json()
            definition = response.get("definition")
            if definition:
                message = f"The acronym '{text.upper()}' means: {definition}"
            else:
                confluence = CONFLUENCE_LINK + f'/dosearchsite.action?cql=siteSearch+~+"{text}"'
                confluence_link = f"<{confluence}|Confluence>"
                message = f"I'm sorry <@{user}> I don't know what *{text.upper()}* is :shrug:. Try checking {confluence_link}."

            if user != "U031T0UHLH1":
                client.chat_postMessage(
                    blocks=[{"type": "section", "text": {"type": "mrkdwn", "text": message}}], channel=channel
                )
                return Response(status=status.HTTP_200_OK)
        return Response(status=status.HTTP_200_OK)

Essentially what the Slack Bot does is takes in the request.data['text'] and checks it against the DRF API end point to see if there is a matching Acronym.

If there is, then it returns the acronym and it's definition.

If it's not, you get a message that it's not sure what you're looking for, but that maybe Confluence1 can help, and gives a link to our Confluence Search page.

The last thing you'll notice is that if the User has a specific ID it won't respond with a message. That's because in my initial testing I just had the Slack Bot replying to the user saying 'Hi' with a 'Hi' back to the user.

I had a missing bit of logic though, so once you said hi to the Slack Bot, it would reply back 'Hi' and then keep replying 'Hi' because it was talking to itself. It was comical to see in real time 😂.

Using ngrok to test it locally

ngrok is a great tool for taking a local url, like localhost:8000/api/entpoint, and exposing it on the internet with a url like https://a123-45-678-901-234.ngrok.io/api/entpoint. This allows you to test your local code and see any issues that might arise when pushed to production.

As I mentioned above the Slack Bot continually said "Hi" to itself in my initial testing. Since I was running ngrok to serve up my local Server I was able to stop the infinite loop by stopping my local web server. This would have been a little more challenging if I had to push my code to an actual web server first and then tested.

Conclusion

This was such a fun project to work on, and I'm really glad that Bob tweeted asking what Slack Bot we would build.

That gave me the final push to actually build it.

  1. You'll notice that I'm using an environment variable to define the Confluence Link and may wonder why. It's mostly to keep the actual Confluence Link used at work non-public and not for any other reason 🤷🏻 ↩

tags: django, drf, slack