In true newline-fashion, we'll get *rolling* with a practical application right away. We're creating a fully functional, dice-rolling chat bot for Slack!

Create a Serverless Slack Bot with AWS Lambda and Python

Introduction

There's no `AWS Lambda` without `AWS`. That means we'll need a few AWS resources created and configured on the AWS side of things to develop and effectively.

How to Setup a Free AWS Developer Environment

Here, we'll configure an `AWS Workspace` or `AWS EC2 Instance` as the development environment to use for developing for AWS Lambda.

How to Configure EC2 and AWS Workspaces Local Credentials

Configuring Your AWS Environment

We can comfortably develop for AWS Lambda with python on any modern Operating System

Setup a Local Python AWS Lambda Development Environment

We will be using the AWS Lambda runtime for the latest stable version of Python 3 - `python3.7`.

Installing Python 3 and Pyenv on MacOS, Windows, and Linux

The easiest way to configure our local development with our credentials is to run the command `aws configure`

How to Login to AWS CLI and Configure Default Region

Configuring Your Local Machine

How Our Slack Bot "Dicebot" Will Work

How to Create an AWS S3 Bucket for Lambda Artifacts

How to Code a Lambda Hello World Function with AWS SAM

How to Test AWS Lambda Functions Locally With Docker

The Beginner Guide to AWS Lambda Deployment

Creating Hello-world Lambda

How to Create a Slack Bot

How to Code a Python Dice Rolling Simulator Program

How to Turn Serverless Python Lambda Code Into a Slack Bot

Testing Our Serverless Slack Dicebot with Docker Locally

Cleaning Up Our Serverless Dicebot Deployment

Creating Dicebot Lambda

*Serverless Computing* may sound like a scary topic, but with the rise of AWS Lambda and mature tools supporting it - it's more approachable than ever. In this newline course, we're going to learn what serverless technology is and isn't, and why it belongs in your developer toolbox. We'll see that for certain common projects - like custom chat bot creation - AWS Lambda really shines for it's simplicity, affordability, and ability to integrate with the wider AWS ecosystem. 

Some developers love using serverless tech because it helps them save money, scale quickly, and deliver on reliability goals. While all of those things are possible with Lambda (especially cost savings which are common - but certainly not guaranteed), it's the development agility and reduction of operations overhead that drives my love for the service. It's a relief to be able to get right into the code, without worrying about configuring operating systems, deploying containers, or scaling clusters. Serverless on Lambda gives developers the resources needed to write, deploy, and _maintain_ production-ready software - all without significant operational overhead.

In true newline-fashion, we'll get *rolling* with a practical application right away. RPG players rejoice - we're creating a fully functional, dice-rolling chat bot for Slack! While the example bot will be for Slack, the same idea can be easily adapted to create a bot for Telegram, Discord, or nearly any other chat service with a bot API. 

We will be using Python 3 for this project, but it's worth noting that [AWS Lambda works with other common languages and runtimes](https://docs.aws.amazon.com/lambda/latest/dg/lambda-runtimes.html), including NodeJS, Java, ruby, go, and .NET. The basic mechanisms of creating, testing, and deploying your Lambda do not vary significantly based on your runtime choice.

By the end of this course you'll:

* Deploy a Slack Bot that runs on AWS Lambda
* Understand how to keep your AWS account secure
* Be able to deploy custom Lambda functions
* Understand serverless architecture and how it works

In this course we'll build and deploy a Serverless Slack Bot using AWS Lambda and Python. Along the way you'll learn about proper security, how lambda works, and how to deploy your service.

Create a Serverless Slackbot with AWS Lambda and Python

How to deploy a serverless bot into production

Turning Our Hello-World Serverless Function into A Slack Dicebot

 directory to modify the core lambda code.

First, we'll want to add two import statements to top of 

 to support our bot. Add these lines at line 4, underneath the imports already in place.

import dicebot  # used to import dicebot functionality
from urllib.parse import parse_qs  # used to parse slack input

 import allows us to handle dice rolling like we did in our interactive shell.

. That function allows us to parse the slack slash command data from the default value of 

Update code under lambda_handler function in app.py

Next, we'll add some modifications to the 

. We will remove all of the default code underneath the considerably huge default docstring, and replace it with the code below. Delete the 

Ensure all code is properly indented throughout! Since this code is underneath the 

 each line must have at least 4 spaces before any text.

    dice_input = None
    status_code = 500 # fallback value
    result_output = {} # fallback
    print(event) # ensure event input is logged
    if "body" in event:
        dice_input = event["body"]
    try:
        dice_query = parse_qs(event["body"])
        print(dice_query) # log parsed message from slack
        if "text" in dice_query:
            dice_input = dice_query["text"][0] # The text field is an array
        else:
            dice_input = "" # default to empty string if missing
        parsed_input = dicebot.parse_text(dice_input)
    except Exception as e:
        status_code = 400
        result_output = {"text": str(e)}
    else:
        dice_results = dicebot.roll_dice(**parsed_input)
        print(dice_results)
        result_output = dicebot.format_slack_response(dice_results)
        status_code = 200
    finally:
        return {
            "statusCode": status_code,
            "body": json.dumps(result_output)
        }

Save these changes, and if you are tracking your project in a git repo, go ahead and commit now.

---
title: How to Turn Serverless Python Lambda Code Into a Slack Bot
isPublicLesson: false
code: https://gitlab.com/fullstackio/books/newline-course-apps/stephanie-prime-create-a-serverless-slack-bot-with-aws-lambda-and-python-app/-/tree/main/code/dicebot
---

# Turning Our Hello-World Serverless Function into A Slack Dicebot

## Modify app.py to use dicebot

Open up the `app.py` file, in the `first_function` directory to modify the core lambda code.

### Add imports to app.py

First, we'll want to add two import statements to top of `app.py` to support our bot. Add these lines at line 4, underneath the imports already in place.

```python
import dicebot  # used to import dicebot functionality
from urllib.parse import parse_qs  # used to parse slack input
```

The `dicebot` import allows us to handle dice rolling like we did in our interactive shell.

The line `from urllib.parse import parse_qs` will give us access to the `parse_qs` library from [`urllib.parse`](https://docs.python.org/2/library/urlparse.html#urlparse.parse_qsl). That function allows us to parse the slack slash command data from the default value of `x-www-form-urlencoded` into a python dict.

### Update code under lambda_handler function in app.py

Next, we'll add some modifications to the `lambda_handler` function in `app.py`. We will remove all of the default code underneath the considerably huge default docstring, and replace it with the code below. Delete the `get_message` function as well. 

Ensure all code is properly indented throughout! Since this code is underneath the `lambda_function` each line must have at least 4 spaces before any text.

```python
    dice_input = None
    status_code = 500 # fallback value
    result_output = {} # fallback
    print(event) # ensure event input is logged
    if "body" in event:
        dice_input = event["body"]
    try:
        dice_query = parse_qs(event["body"])
        print(dice_query) # log parsed message from slack
        if "text" in dice_query:
            dice_input = dice_query["text"][0] # The text field is an array
        else:
            dice_input = "" # default to empty string if missing
        parsed_input = dicebot.parse_text(dice_input)
    except Exception as e:
        status_code = 400
        result_output = {"text": str(e)}
    else:
        dice_results = dicebot.roll_dice(**parsed_input)
        print(dice_results)
        result_output = dicebot.format_slack_response(dice_results)
        status_code = 200
    finally:
        return {
            "statusCode": status_code,
            "body": json.dumps(result_output)
        }
```

Save these changes, and if you are tracking your project in a git repo, go ahead and commit now.

Most of that code is just there for error handling, which we will explain in-depth in chapter 2. The core bot logic works as follows: