Search Results for "aws-cpp-sdk-s3"
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Showing 283 open source projects for "aws-cpp-sdk-s3"
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AWS SDK for pandas
Easy integration with Athena, Glue, Redshift, Timestream, Neptune
aws-sdk-pandas (formerly AWS Data Wrangler) bridges pandas with the AWS analytics stack so DataFrames flow seamlessly to and from cloud services. With a few lines of code, you can read from and write to Amazon S3 in Parquet/CSV/JSON/ORC, register tables in the AWS Glue Data Catalog, and query with Amazon Athena directly into pandas. The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling boilerplate. ... -
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AWS IoT Device SDK for Python
SDK for connecting to AWS IoT from a device using Python
The AWS IoT Device SDK for Python allows developers to write Python script to use their devices to access the AWS IoT platform through MQTT or MQTT over the WebSocket protocol. By connecting their devices to AWS IoT, users can securely work with the message broker, rules, and the device shadow (sometimes referred to as a thing shadow) provided by AWS IoT and with other AWS services like AWS Lambda, Amazon Kinesis, Amazon S3, and more. ... -
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aws-encryption-sdk
AWS Encryption SDK
...With the AWS Encryption SDK, you define a master key provider (Java and Python) or a keyring (C, C#/.NET, and JavaScript) that determines which wrapping keys you use to protect your data. Then you encrypt and decrypt your data using straightforward methods provided by the AWS Encryption SDK. The AWS Encryption SDK does the rest. Without the AWS Encryption SDK, you might spend more effort on building an encryption solution than on the core functionality of your application. -
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AWS Data Wrangler
Pandas on AWS, easy integration with Athena, Glue, Redshift, etc.
An AWS Professional Service open-source python initiative that extends the power of Pandas library to AWS connecting DataFrames and AWS data-related services. Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON, and EXCEL). -
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AWS IoT Device SDK v2 for Python
Next generation AWS IoT Client SDK for Python
Next-generation AWS IoT Client SDK for Python using the AWS Common Runtime. This document provides information about the AWS IoT Device SDK v2 for Python. This SDK is built on the AWS Common Runtime, a collection of libraries (aws-c-common, aws-c-io, aws-c-mqtt, aws-c-compression, aws-c-http, aws-c-cal, aws-c-auth, s2n ...) written in C to be cross-platform, high-performance, secure, and reliable. ... -
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aws-encryption-sdk-cli
CLI wrapper around aws-encryption-sdk-python
This command line tool can be used to encrypt and decrypt files and directories using the AWS Encryption SDK. If you have not already installed cryptography, you might need to install additional prerequisites as detailed in the cryptography installation guide for your operating system. Installation using a python virtual environment is recommended to avoid conflicts between system packages and user-installed packages. For the most part, the behavior of aws-encryption-cli in handling files is based on that of GNU CLIs such as cp. ... -
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AWS X-Ray SDK for Python
AWS X-Ray SDK for the Python programming language
AWS X-Ray SDK for the Python programming language. The AWS X-Ray SDK for Python is compatible with Python 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, and 3.9. X-Ray Python SDK will by default generate no-op trace and entity id for unsampled requests and secure random trace and entity id for sampled requests. If customer wants to enable generating secure random trace and entity id for all the (sampled/unsampled) requests (this is applicable for trace id injection into logs use case) then they should set the AWS_XRAY_NOOP_ID environment variable as False. ... -
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Amazon Braket Python SDK
A python SDK for interacting with quantum devices on Amazon Braket
...As a managed service, Amazon Braket performs operations on your behalf on the AWS hardware that is managed by Amazon Braket. Amazon Braket can perform only operations that the user permits. You can read more about which permissions are necessary in the AWS Documentation. The Braket Python SDK should not require any additional permissions aside from what is required for using Braket. However, if you are using an IAM role with a path in it, you should grant permission for iam:GetRole. -
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AWS Secrets Manager Python caching
Enables in-process caching of secrets for Python applications
...Follow the instructions to create an AWS account. To create a secret in AWS Secrets Manager, go to Creating Secrets and follow the instructions on that page. This library makes use of botocore, the low-level core functionality of the boto3 SDK. For more information on boto3 and botocore, please review the AWS SDK for Python and Botocore documentation. -
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s3-client
Sample python script to work with Amazon S3
Example Python script to work with S3. -
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aws-devops-zero-to-hero
AWS zero to hero repo for devops engineers to learn AWS in 30 Days
aws-devops-zero-to-hero is a 30-day AWS learning roadmap aimed squarely at DevOps engineers who want both conceptual understanding and hands-on projects. The README is structured as a day-by-day syllabus, starting with “Day 1: Introduction to AWS” and moving through IAM, EC2, VPC networking, security, DNS (Route 53), storage (S3), and many other core services. -
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AWS Chalice
Python Serverless Microframework for AWS
Chalice is a Python microframework for writing and deploying serverless applications on AWS with minimal ceremony. You define routes, event handlers, and background tasks in plain Python, and Chalice turns them into AWS Lambda functions wired to API Gateway, Amazon EventBridge schedulers, S3/SNS/SQS triggers, and more. A single command builds your app, bundles dependencies, generates infrastructure templates, and deploys to your account with sensible defaults. ... -
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AWS Neuron
Powering Amazon custom machine learning chips
AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. ... -
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AWS Agent Skills
AWS Skills for Agents
...The skills cover critical AWS services such as IAM, Lambda, DynamoDB, S3, API Gateway, EKS, and many more, letting agents offer actionable advice on infrastructure as code, debugging, security configurations, and architectural workflows. Skills are kept up to date with weekly documentation checks, ensuring they reflect current AWS patterns and service changes. -
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aws-cli
Universal Command Line Interface for Amazon Web Services
The AWS CLI is the universal command-line interface for managing AWS services, automating tasks, and scripting cloud workflows. It exposes nearly every public API from EC2 and S3 to IAM, Lambda, and beyond, providing parity with the service SDKs in a tool you can run anywhere. Profiles, regions, single-sign-on, and credential helpers make it straightforward to switch contexts securely across accounts and environments. -
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Amazon Braket Python Schemas
A library that contains schemas for Amazon Braket
Amazon Braket Python Schemas is an open source library that contains the schemas for Braket, including intermediate representations (IR) for Amazon Braket quantum tasks and offers serialization and deserialization of those IR payloads. Think of the IR as the contract between the Amazon Braket SDK and Amazon Braket API for quantum programs. Schemas for the S3 results of each quantum task. Schemas for the device capabilities of each device. The preferred way to get Amazon Braket Python Schemas is by installing the Amazon Braket Python SDK, which will pull in the schemas. You can install from source by cloning this repository and running a pip install command in the root directory of the repository. ... -
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Nexa SDK
Nexa SDK is a comprehensive toolkit for supporting ONNX and GGML
...Users can run Nexa SDK in any device with Python environment, and GPU acceleration is supported, including CUDA, Metal, and ROCm. An executable version is also available. -
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AWS SAM CLI
CLI tool to build, test, debug, and deploy Serverless applications
The AWS Serverless Application Model (SAM) CLI is an open-source CLI tool that helps you develop serverless applications containing Lambda functions, Step Functions, API Gateway, EventBridge, SQS, SNS and more. The AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications. It provides shorthand syntax to express functions, APIs, databases, and event source mappings. -
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AWS MCP Servers
Helping you get the most out of AWS, wherever you use MCP
AWS MCP Servers are a collection of remotely hosted, fully-managed Model Context Protocol (MCP) servers by AWS, providing AI applications with real-time access to AWS documentation, API references, best practices, and infrastructure-management capabilities via natural-language workflows. An MCP Server is a lightweight program that exposes specific capabilities through the standardized Model Context Protocol. -
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AWS ParallelCluster Node
Python package installed on the Amazon EC2 instances
aws-parallelcluster-node is the python package installed on the Amazon EC2 instances launched as part of AWS ParallelCluster. AWS ParallelCluster is an AWS-supported Open Source cluster management tool that makes it easy for you to deploy and manage High-Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. ... -
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OpenAI Agents SDK
A lightweight, powerful framework for multi-agent workflows
The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management. -
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Google Antigravity SDK
Python library for building agents that leverages Google Antigravity
Google Antigravity SDK for Python is a Python library for building AI agents powered by Antigravity and Gemini. It provides a secure, scalable, and stateful infrastructure layer so developers can focus on agent behavior instead of manually implementing the full agent loop. The SDK includes a high-level Agent class for quick setup, as well as lower-level conversation and connection abstractions for more controlled workflows. -
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Docker SDK for Python
A Python library for the Docker Engine API
A Python library for the Docker Engine API. It lets you do anything the docker command does, but from within Python apps, run containers, manage containers, manage Swarms, etc. The latest stable version is available on PyPI. Either add docker to your requirements.txt file or install with pip. To communicate with the Docker daemon, you first need to instantiate a client. The easiest way to do that is by calling the function from_env(). It can also be configured manually by instantiating a... -
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troposphere
Python library to create AWS CloudFormation descriptions
The troposphere library allows for easier creation of the AWS CloudFormation JSON by writing Python code to describe the AWS resources. troposphere also includes some basic support for OpenStack resources via Heat. To facilitate catching CloudFormation or JSON errors early the library has property and type checking built into the classes. -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
...The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. This project is licensed under the Apache-2.0 License. Ensure you have access to an AWS account i.e. setup your environment such that awscli can access your account via either an IAM user or an IAM role.
