serverless-python-requirements
serverless-plugin-warmup
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serverless-python-requirements | serverless-plugin-warmup | |
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2 | 1 | |
1,083 | 951 | |
0.8% | - | |
6.7 | 8.0 | |
22 days ago | about 2 years ago | |
JavaScript | JavaScript | |
MIT License | MIT License |
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serverless-python-requirements
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A Guide to Starting a FastAPI + Poetry + Serverless Project
"Error: poetry not found! Install it according to the poetry docs." on Windows 10 #609
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Serverless Proxy with AWS API Gateway and AWS Lambda
serverless-python-requirements: to automatically bundle Python dependencies from requirements.txt
serverless-plugin-warmup
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Structuring a Real-World Serverless App
We use the package.json at the project root to install the dependencies that will be shared across all the services. For example, if you are using serverless-bundle to optimally package the Lambda functions, or using the serverless-plugin-warmup to reduce cold starts, they should be installed at the root level. It doesn’t make sense to install them in each and every single service.
What are some alternatives?
serverless-dotenv-plugin - Preload Environment Variables with Dotenv into Serverless
serverless-bundle - Optimized packages for ES6 and TypeScript Node.js Lambda functions without any configuration.
serverless-layers - Serverless.js plugin implementing AWS Lambda Layers, reducing lambda size, warm-up, and deployment time.
serverless-chrome - 🌐 Run headless Chrome/Chromium on AWS Lambda
serverless-export-env - Serverless plugin to export environment variables into a .env file
homepage - Seed Homepage
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
serverless-plugin-warmup - Keep your lambdas warm during winter. ♨
lerna - :dragon: Lerna is a fast, modern build system for managing and publishing multiple JavaScript/TypeScript packages from the same repository.
aws-lambda-power-tuning - AWS Lambda Power Tuning is an open-source tool that can help you visualize and fine-tune the memory/power configuration of Lambda functions. It runs in your own AWS account - powered by AWS Step Functions - and it supports three optimization strategies: cost, speed, and balanced.