Developing with S3: AWS with Python and Boto3 Series

Explore the tools and environment for developing with S3 using Python and Boto3, configure credentials and region, and set up PyCharm across macOS, Windows, or Linux.

Create an AWS account via the AWS console, complete sign-up with personal details, billing, and phone verification. Explore 12 months of free tier for EC2, S3, and DynamoDB.

Sign in to the AWS management console, switch regions, and navigate account details, billing, and organizations. Explore services, pin favorites, and use cost explorer for resources, including EC2 and VPC.

Create an IAM user for programmatic access, generate an access key and secret key, attach administrator policies, enable multifactor authentication, and securely manage credentials for AWS resources.

Install Python 3.6.5 on Windows from python.org, customize the installation to include documentation and pip, add Python to PATH, and verify by typing python in Command Prompt.

Install the AWS CLI on Windows 10 (64-bit) and verify the setup by correcting the PATH and environment variables. Run AWS in the command prompt to confirm it works.

Configure the AWS CLI with your access key and secret key, set eu-central-1 as the region, and choose json output to enable Python boto3 access to AWS resources.

Install the boto3 library with pip to begin using AWS resources in Python. Pip collects dependencies like the core S3 transfer, documentation, and utils, preparing boto3 for use.

Verify your AWS credentials with aws configure, confirm the access key, secret key, and region, then check Python installation and confirm boto3 is installed with pip show.

Install python 3 and the pip package manager on macOS from python.org, then verify python3 and pip3 in the terminal to prepare for boto3 development.

Install the AWS CLI on macOS with Homebrew to easily configure access keys and secret keys for use across command lines, applications, and languages, then verify by running aws.

Configure the AWS CLI with your access key and secret key using AWS configure, and set the default region to eu central one. Install Boto3 for Python.

Install the boto3 library for your Python project using pip, verify Python 3.6 is in use, and start working with AWS APIs through your Python code.

Verify Python 3.6 is installed, AWS CLI is configured, and the AWS SDK for Python is ready, then prepare to work with AWS resources like VPC and EC2.

Set up a PyCharm project for S3 operations by creating a source package and a Python file, import boto3, and instantiate a global S3 client without a region.

Create an s3 bucket with boto3 by defining a create_bucket method that accepts a bucket name, sets a region location constraint, prints the AWS response including http status 200.

Create and apply an S3 bucket policy using a Python dictionary and JSON, specifying version, statement, sid, effect, principal, action, and resource for public access to all objects.

Learn how to list s3 buckets in aws with a python boto3 s3 client, retrieving bucket details and printing the response to enable bulk operations and policies.

Learn how to retrieve S3 bucket properties and configurations, including policy and encryption status, and explore additional settings like ACL, analytics, and lifecycle using boto3.

define and apply an updated bucket policy with a json document to allow delete, get, and put object actions on all objects in the bucket.

Enable server-side encryption on your S3 bucket by configuring a default encryption rule using AES-256, and apply bucket encryption with boto3.

Delete an S3 bucket on AWS using boto3 by calling the delete_bucket operation on the S3 client with your bucket name, and verify the 204 response and deletion.

Learn how to upload small files to S3 using Python and boto3, including configuring the bucket, key, and verification, and contrast with multipart large-file uploads.

Learn to upload large files to S3 using transfer config for parallel multipart uploads, configuring threshold, chunk size, and max concurrency, while tracking progress with a callback.

Demonstrate implementing a progress percentage tracker and callback for multi-part uploads to AWS S3 with Python and Boto3, using threading and transfer config.

Learn to read objects from S3 with get object by specifying bucket and key, and inspect metadata like last modified, ETag, content length, and content type.

Enable versioning on S3 buckets to prevent accidental deletes by using delete markers and preserved versions. The video shows enabling versioning with boto3 and a versioning configuration status.

Upload a new version of readme.txt to an S3 bucket using boto3's upload file method. View and download the latest version and access previous versions through the console.

Define S3 lifecycle policies to transition objects to Glacier or delete them after set days, using JSON rules with prefixes and enabled statuses, then apply with put bucket lifecycle configuration.

Discover hosting a static website on S3 by creating and configuring an eu central one bucket, enabling static website hosting, and setting index and error documents for Route 53 routing.

Create index.html and error.html, upload them to an S3 bucket, enable static website hosting, make objects public, and access your site via the S3 endpoint, with Route 53 later.

Bind Route 53 DNS to an S3 hosted website by creating a change batch payload with upserted A records and a www redirect.

Master Amazon S3 operations, from uploading small and large files with multi-part uploads and threading to hosting websites with Route 53, and updating bucket policies and versioning.