Use Starlette-Babel for localization
mainStarlette-Babel provides support for translations, localization, and timezones by integrating with the Babel library.
Starlette
repository·main·Indexed 11 days ago
https://github.com/kludex/starletteA lightweight, high-performance ASGI framework and toolkit for building asynchronous web services in Python. It supports WebSockets, background tasks, and multiple async backends including asyncio and trio. Starlette can be used as a complete framework or a modular toolkit for implementing raw ASGI applications.
What's inside Starlette
Use Starlette-StaticResources for package resources
mainStarlette-StaticResources allows you to mount package resources for static data, providing functionality similar to Starlette's built-inStaticFiles.Use Responder for async web services
mainResponder is an asynchronous web service framework that offers several features including:
- Flask-style route expressions
- YAML support
- OpenAPI schema generation
- Background tasks
- GraphQL support
Integrate Sentry for error tracking and performance
mainSentry integrates with Starlette to provide software error detection and actionable insights. Key capabilities include:
- Error tracking
- Performance insights
- Contextual information for debugging
- Alerts and notifications
Use Ellar for scalable REST APIs
mainEllar is an ASGI web framework inspired by NestJS. It is designed for building fast, efficient, and scalable REST APIs and server-side applications by combining Object-Oriented Programming (OOP) and Functional Programming (FP) elements. It is built on three core libraries: Starlette, Pydantic, and injector.Integrate Apiman for Swagger/OpenAPI documentation
mainUse Flama for machine learning API deployment
mainFlama is a data-science oriented framework designed to rapidly build and deploy modern machine learning (ML) APIs. It allows data scientists to turn ML models into asynchronous, auto-documented APIs quickly. It supports GraphQL, REST, and ML APIs and provides an intuitive CLI for automatic deployment of ML models.Use Xpresso for flexible web frameworks
mainXpresso is a flexible and extendable web framework built by combining Starlette, Pydantic, and thedidependency injection library.Use Greppo for geospatial dashboards
mainGreppo is a Python framework specifically for building geospatial dashboards and web applications. It provides a toolkit to integrate data, algorithms, visualizations, and UI. It includes APIs for updating backend variables, recomputing logic, and reflecting changes in the frontend via a data mutation hook.Use Dark Star for HTML-centric development
mainDark Star is a framework designed to minimize the code required to serve HTML. It automatically converts file paths into Starlette routes and places view code adjacent to templates. It includes built-in support for htmx to enhance frontend interactivity.Explore Starlette third-party plugins and integrations
mainStarlette has a large ecosystem of community-maintained tools. These include plugins for authentication, monitoring, API documentation, and serverless deployment. Use these third-party packages to extend Starlette's core functionality without building everything from scratch.Use Shiny for reactive Python web applications
mainShiny leverages Starlette andasyncioto allow developers to create web applications using reactive programming. It automates state management and determines the best execution path at runtime to minimize re-rendering, supporting everything from simple dashboards to full-featured web apps.