Code examples that show how to use Boto3 to access Amazon Web Services (AWS).
- You must have an AWS account, and have your default credentials and AWS Region configured as described in the AWS Tools and SDKs Shared Configuration and Credentials Reference Guide.
- Python 3.6 or later
- Boto3 1.11.10 or later
- PyTest 5.3.5 or later (to run unit tests)
For Boto3 and AWS documentation, see the following:
Shows how to use the AWS SDK for Python (Boto3) with AWS Certificate Manager (ACM) to request, import, and manage certificates.
- Request a new certificate from ACM.
- Import a self-signed certificate.
- Retrieve certificate data.
- Add custom tags to certificates.
Shows how to use the AWS SDK for Python (Boto3) with Amazon CloudWatch to accomplish the following tasks:
- Create a custom metric.
- Create an alarm that watches a metric.
- Send data to CloudWatch for a metric.
- Get statistics for a metric.
- Trigger an alarm and get its state.
Shows how to use the AWS SDK for Python (Boto3) to write and retrieve Amazon DynamoDB data using batch functions.
Boto3 features a batch_writer function that handles all of the necessary intricacies of the Amazon DynamoDB batch API on your behalf. This includes buffering, removing duplicates, and retrying unprocessed items.
Shows how to use the AWS SDK for Python (Boto3) to create an Amazon DynamoDB table for storing movies, load movies into the table from a JSON-formatted file, and update and query movies in various ways.
Shows how to use the AWS SDK for Python (Boto3) and the Amazon DAX Client for
Python to read items from an Amazon DynamoDB table. Retrieval, query, and scan speeds
are measured for both Boto3 and DAX clients to show some of the performance
advantages of using DAX.
DAX is a DynamoDB-compatible caching service that provides fast in-memory performance and high availability for applications that demand microsecond latency. For more information, see In-Memory Acceleration with DynamoDB Accelerator (DAX).
Shows how to use the AWS SDK for Python (Boto3) to manage Amazon Compute Cloud (Amazon EC2) resources. Learn to accomplish the following tasks:
- Create security keys, groups, and instances.
- Start and stop instances, use Elastic IP addresses, and update security groups.
- Clean up security keys and security groups.
- Permanently terminate instances.
Shows how to use the AWS SDK for Python (Boto3) with the Amazon EMR API to create and manage clusters and job steps. Learn to accomplish the following tasks:
- Create a short-lived cluster that estimates the value of pi using Apache Spark to parallelize a large number of calculations, writes output to Amazon S3, and terminates itself after completing the job.
- Create a long-lived cluster that uses Apache Spark to query historical Amazon review data to discover the top products in various categories with certain keywords in their product titles.
- Create security roles and groups to let Amazon EMR manage cluster instances and to let the instances access additional AWS resources.
- Run commands on cluster instances, such as EMRFS configuration and shell scripts to install additional libraries.
- Query clusters for status and terminate them using the API.
Shows how to use the AWS IoT Greengrass Core SDK to create AWS Lambda functions that publish MQTT messages, implement connectors, and retrieve secrets.
These code examples are primarily code snippets that are used in the AWS Iot Greengrass developer guide and are not intended to be used out of context.
Shows how to use the AWS SDK for Python (Boto3) to manage AWS Identity and Access Management (IAM) resources. Learn to accomplish the following tasks:
- Create and manage IAM user access keys.
- Manage the alias of an account.
- Acquire reports about account usage.
- Create and manage IAM policies, including versioned policies.
- Create and manage IAM roles, including how to attach and detach policies.
- Create and manage IAM users, including how to attach a policy to a user.
Shows how to use the AWS SDK for Python (Boto3) with Amazon Kinesis and version 2 of the Amazon Kinesis Data Analytics API to create an application that reads data from an input stream, uses SQL code to transform the data, and writes it to an output stream.
- Create and manage Kinesis streams.
- Create and manage Kinesis Data Analytics applications.
- Create an AWS Identity and Access Management (IAM) role and policy that lets an application read from an input stream and write to an output stream.
- Add input and output streams to an application.
- Upload SQL code that runs in an application and transforms data from an input stream to data in an output stream.
- Run a data generator that puts records into an input stream.
- Read transformed records from an output stream.
Shows how to use the AWS SDK for Python (Boto3) to create, deploy, and invoke AWS Lambda functions. Learn to accomplish the following tasks:
- Create and deploy Lambda functions that can be invoked in different ways:
- By an invoke call through Boto3
- By Amazon API Gateway as the target of a REST request
- By Amazon EventBridge on a schedule
- Create and deploy a REST API on Amazon API Gateway. The REST API targets an AWS Lambda function to handle REST requests.
- Create a schedule rule on Amazon EventBridge that targets an AWS Lambda function.
These examples show how to use the low-level Boto3 client APIs to accomplish tasks like creating a REST API and setting an event schedule. You can also use AWS Chalice to achieve similar results more easily and with additional features.
Shows how to use AWS Chalice with the AWS SDK for Python (Boto3) to create a serverless REST API that uses Amazon API Gateway, AWS Lambda, and Amazon DynamoDB. The REST API simulates a system that tracks daily cases of COVID-19 in the United States, using fictional data. Learn how to:
- Use AWS Chalice to define routes in AWS Lambda functions that are called to handle REST requests that come through Amazon API Gateway.
- Use AWS Lambda functions to retrieve and store data in an Amazon DynamoDB table to serve REST requests.
- Define table structure and security role resources in an AWS CloudFormation template.
- Use AWS Chalice and AWS CloudFormation to package and deploy all necessary resources.
- Use AWS CloudFormation to clean up all created resources.
This example brings together some of the same information you can find in the tutorials in the AWS Chalice GitHub repository.
Shows how to use the AWS SDK for Python (Boto3) to create and manage AWS Organizations policies.
Shows how to use the AWS SDK for Python (Boto3) with the Amazon Relational Database Service (Amazon RDS) API and AWS Chalice to create a REST API backed by an Amazon Aurora database. The web service is fully serverless and represents a simple lending library where patrons can borrow and return books. Learn how to:
- Create and manage a serverless Amazon Aurora database cluster.
- Use AWS Secrets Manager to manage database credentials.
- Implement a data storage layer that uses Amazon RDS Data Service to move data into and out of the database.
- Use AWS Chalice to deploy a serverless REST API to Amazon API Gateway and AWS Lambda.
- Use the Requests package to send requests to the web service.
Shows how to use the AWS SDK for Python (Boto3) with Amazon Rekognition to recognize people, objects, and text in images and videos.
- Detect faces, celebrities, objects, and text in an image.
- Create a collection of indexed faces and search for faces in your collection that match a reference image.
- Detect faces, celebrities, and objects in a video.
- Create a notification channel so your code can determine when a video detection job has completed.
Shows how to use the AWS SDK for Python (Boto3) transfer manager to manage multipart uploads to and downloads from an Amazon Simple Storage Service (Amazon S3) bucket.
When the file to transfer is larger than the specified threshold, the transfer manager automatically uses multipart uploads or downloads. This example shows how to use several of the available transfer manager settings, and reports thread usage and time to transfer.
Shows how to use the AWS SDK for Python (Boto3) to get started using bucket and object operations in Amazon Simple Storage Service (Amazon S3). Learn to create, get, remove, and configure buckets and objects.
Shows how to use the AWS SDK for Python (Boto3) to set up an Amazon S3 bucket for versioning, and how to perform tasks on a version-enabled bucket. Learn to accomplish the following tasks:
- Create a version-enabled bucket and apply revisions to its objects.
- Get a full series of object versions.
- Roll back to a previous version.
- Revive a deleted object.
- Permanently delete all versions of an object.
Shows how to manipulate Amazon S3 versioned objects in batches by creating jobs that call AWS Lambda functions to perform processing. Learn to accomplish the following tasks:
- Create Lambda functions that operate on versioned objects.
- Create a manifest of objects to update.
- Create batch jobs that invoke Lambda functions to update objects.
- Delete Lambda functions.
- Empty and delete a versioned bucket.
Shows how to use the AWS SDK for Python (Boto3) with Amazon Simple Email Service (Amazon SES) to verify identities, send emails, and manage rules and templates.
- Verify email address and domain identities.
- Create and manage email templates that contain replaceable tags.
- Send email by using the Amazon SES API or an Amazon SES SMTP server.
- Create and manage rules to block, allow, or handle incoming emails.
- Copy email and domain identity configuration from one AWS Region to another.
Shows how to use the AWS SDK for Python (Boto3) to get started using queue and message operations in Amazon Simple Queue Service (Amazon SQS). Learn how to create, get, and remove standard, FIFO, and dead-letter queues. Learn how to send, receive, and delete messages from a queue.
Shows how to use the AWS Python SDK (Boto3) to access the AWS Security Token Service (AWS STS) to acquire temporary credentials that grant specific permissions. Also demonstrates how to set up and use a multi-factor authentication (MFA) device. Learn to accomplish the following tasks:
- Assume a role that grants specific permissions, and use those credentials to perform permitted actions.
- Add a new MFA device to a user.
- Assume a role that requires MFA to be present.
- Construct a URL that gives federated users direct access to an account through the AWS Management Console.
- Get a session token that can be used to call an API function that requires MFA.
Shows how to use the AWS SDK for Python (Boto3) with the Amazon Transcribe API to transcribe an audio file to a text file. Learn how to:
- Run a transcription job against an audio file in an Amazon S3 bucket.
- Create and refine a custom vocabulary to improve the accuracy of the transcription.
- List and manage transcription jobs and custom vocabularies.
Centralizes PyTest fixtures and specialized stubbers based on the botocore Stubber that Python code examples can use for unit tests.
- As an AWS best practice, grant this code least privilege, or only the permissions required to perform a task. For more information, see Grant Least Privilege in the AWS Identity and Access Management User Guide.
- This code has not been tested in all AWS Regions. Some AWS services are available only in specific Regions. For more information, see the AWS Regional Table
- Running this code might result in charges to your AWS account.
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SPDX-License-Identifier: Apache-2.0