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# S3 Directory Buckets code examples for the SDK for Python
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## Overview
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Shows how to use the AWS SDK for Python (Boto3) to work with Amazon S3 Directory Buckets.
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_S3 Directory Buckets are designed to store data within a single AWS Zone. Directory buckets organize data hierarchically into directories, providing a structure similar to a file system._
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## ⚠ Important
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* Running this code might result in charges to your AWS account. For more details, see [AWS Pricing](https://aws.amazon.com/pricing/) and [Free Tier](https://aws.amazon.com/free/).
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* Running the tests might result in charges to your AWS account.
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* We recommend that you grant your code least privilege. At most, grant only the minimum permissions required to perform the task. For more information, see [Grant least privilege](https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html#grant-least-privilege).
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* This code is not tested in every AWS Region. For more information, see [AWS Regional Services](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services).
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## Code examples
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### Prerequisites
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For prerequisites, see the [README](../../README.md#Prerequisites) in the `python` folder.
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Install the packages required by these examples by running the following in a virtual environment:
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```
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python -m pip install -r requirements.txt
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```
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### Basics
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Code examples that show you how to perform the essential operations within a service.
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-[Learn the basics](s3_express_getting_started.py)
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## Run the examples
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### Instructions
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#### Learn the basics
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This example shows you how to do the following:
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- Set up a VPC and VPC Endpoint.
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- Set up the Policies, Roles, and User to work with S3 directory buckets and the S3 Express One Zone storage class.
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- Create two S3 Clients.
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- Create two buckets.
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- Create an object and copy it over.
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- Demonstrate performance difference.
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- Populate the buckets to show the lexicographical difference.
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- Prompt the user to see if they want to clean up the resources.
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