Python Tutorial: Intro to AWS and Boto3

Want to learn more? Take the full course at https://learn.datacamp.com/courses/introduction-to-aws-boto-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Welcome to Introduction to AWS and Boto in Python! Amazon Web Services is the backbone of the internet. Boto3 lets us harness the power of AWS to use as an extension of our laptops. We can build automated reports, perform sentiment analysis, send alerts and more. Let's get started! Our house needs water, electricity, trash service, and cable TV. Our project needs storage, compute resources, and alerts to be successful. We buy utilities for the home. We buy AWS services for our project. AWS services are granular, so they work together or on their own. To interact with AWS in Python, we use the Boto3 library. Let's look at an example. We import boto3. We initialize the client with an AWS service name, region, key and secret. The service name can be any of the 100+ available AWS services. The region is the geo region where our resources are located. Key and secret are like a username and password to an AWS account. We'll make our own next. Creating an account at aws.amazon.com gives us access to the AWS Console. Anything we do here to manage our web services, we can do in Boto3 in Python. To log into the console, we use the username/password we signed up with. This is the root user. To create the key/secret for Boto3, we are going to use IAM or Identity Access Management Service. We create IAM sub-users to control access to AWS resources in our account. Credentials - or the key / secret combo are what authenticate IAM users. In the console, type IAM in the Find Services Section. At the IAM Screen, click "Users" Click "Add User" Enter a username and select "programmatic access". Select "Attach Existing Policies Directly" to add pre-made permission sets to our new user. Give the user the AmazonS3FullAccess policy, AmazonSNSFullA