Create a Serverless Slack Bot with AWS Lambda and Python

Introduction

How to Setup a Free AWS Developer Environment

How to Configure EC2 and AWS Workspaces Local Credentials

Configuring Your AWS Environment

Setup a Local Python AWS Lambda Development Environment

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

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

Creating A Basic Hello-World Lambda from SAM Cookiecutter Template

 project directory, we will clone a sample project that AWS provides for Python and SAM.

git clone https://github.com/aws-samples/cookiecutter-aws-sam-python.git

sam init --location cookiecutter-aws-sam-python

 to create our dicebot lambda directory. We will be prompted for certain parameters after sending this command, so fill them in according to the example shown below.

$ sam init --location cookiecutter-aws-sam-python
[+] Initializing project structure...
project_name [Name of the project]: dice_bot
project_short_description [A short description of the project]: A bot that rolls dice
include_apigw [y]: y
include_xray [y]: n
include_safe_deployment [y]: n
include_experimental_make [n]: n
 [INFO]: Removing Makefile from project due to chosen options...
 [SUCCESS]: Project initialized successfully! You can now jump to dice_bot folder
 [INFO]: dice_bot/README.md contains instructions on how to proceed.
[*] Project initialization is now complete

 directory will contain all of the important code for this project. So go ahead and navigate into that directory and init a git project there, as shown below.

 to open VSCode with the explorer already pointing to this directory.

Poke around the directory structure a bit to see the basic scaffolding created by 

. We won't need to touch most of these files yet, but there are a few essential files we need to review, and modify. 

The main files we will be concerned with are:

 file provided by AWS is almost ready to use as-is. It has defined a generic lambda resource and an API Gateway that we can use with slack. We need to just make a few minor tweaks to make it ready to go.

---
title: How to Code a Lambda Hello World Function with AWS SAM
isPublicLesson: false
---

## Creating A Basic Hello-World Lambda from SAM Cookiecutter Template

From the `chap1` project directory, we will clone a sample project that AWS provides for Python and SAM.

```bash
git clone https://github.com/aws-samples/cookiecutter-aws-sam-python.git
```

From that same directory, we will use `sam init --location cookiecutter-aws-sam-python` to create our dicebot lambda directory. We will be prompted for certain parameters after sending this command, so fill them in according to the example shown below.

```bash
$ sam init --location cookiecutter-aws-sam-python
[+] Initializing project structure...
project_name [Name of the project]: dice_bot
project_short_description [A short description of the project]: A bot that rolls dice
include_apigw [y]: y
include_xray [y]: n
include_safe_deployment [y]: n
include_experimental_make [n]: n
 [INFO]: Removing Makefile from project due to chosen options...
 [SUCCESS]: Project initialized successfully! You can now jump to dice_bot folder
 [INFO]: dice_bot/README.md contains instructions on how to proceed.
[*] Project initialization is now complete
```

We should now see a directory called `dice_bot` created within our `chap1` directory. This `dice_bot` directory will contain all of the important code for this project. So go ahead and navigate into that directory and init a git project there, as shown below.

```bash
cd dice_bot
git init .
```

If we have `VSCode` installed, we can use the command `code .` to open VSCode with the explorer already pointing to this directory.

Poke around the directory structure a bit to see the basic scaffolding created by `cookiecutter`. We won't need to touch most of these files yet, but there are a few essential files we need to review, and modify. 

The main files we will be concerned with are:

-   `README.md` - Always write useful instructions into the README.md file. In `VSCode`, we this file and do `Ctrl+Shift+V` to preview it.
-   `template.yaml` - This is a SAM infrastructure template that defines resources being deployed to AWS
-   `first_function/app.py` - Python application code that AWS Lambda will execute
-   `events/first_function.json` - Sample event that will be used when testing the Lambda locally. This will simulate the slack slash command.

## Update the SAM template

The SAM `template.yaml` file provided by AWS is almost ready to use as-is. It has defined a generic lambda resource and an API Gateway that we can use with slack. We need to just make a few minor tweaks to make it ready to go.

Learn

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Amelia Wattenberger

Author of Fullstack D3

Community

Create a Serverless Slackbot with AWS Lambda and Python

Module 1: Introduction

Introduction:

Start Here

Introduction:

Create a Serverless Slack Bot with AWS Lambda and Python

Module 2: Configuring Your AWS Environment

Lesson 1:

How to Setup a Free AWS Developer Environment

Lesson 2:

How to Configure EC2 and AWS Workspaces Local Credentials

Module 3: Configuring Your Local Machine

Lesson 1:

Setup a Local Python AWS Lambda Development Environment

Lesson 2:

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

Lesson 3:

How to Login to AWS CLI and Configure Default Region

Module 4: Creating Hello-world Lambda

Lesson 1:

How Our Slack Bot "Dicebot" Will Work

Lesson 2:

How to Create an AWS S3 Bucket for Lambda Artifacts

Lesson 3:

How to Code a Lambda Hello World Function with AWS SAM

Lesson 4:

How to Test AWS Lambda Functions Locally With Docker

Lesson 5:

The Beginner Guide to AWS Lambda Deployment

Module 5: Creating Dicebot Lambda

Lesson 1:

How to Create a Slack Bot

Lesson 2:

How to Code a Python Dice Rolling Simulator Program

Lesson 3:

How to Turn Serverless Python Lambda Code Into a Slack Bot

Lesson 4:

Testing Our Serverless Slack Dicebot with Docker Locally

Lesson 5:

Cleaning Up Our Serverless Dicebot Deployment

How to Code a Lambda Hello World Function with AWS SAM