Genie.jl
fastapi
Genie.jl | fastapi | |
---|---|---|
21 | 467 | |
2,185 | 71,023 | |
0.5% | - | |
8.7 | 9.8 | |
3 days ago | 5 days ago | |
Julia | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Genie.jl
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Tidyverse 2.0.0
Julia seems to be doing a better job catching up to R in this space than Python. I haven't used it personally, but the demos of Genie Framework are impressive: https://github.com/GenieFramework/Genie.jl / https://genieframework.com/
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Show HN: Genie Cloud – no-code platform to build and deploy Julia web apps
Hi everyone! I’m Adrian, co-founder of Genie Cloud. Genie Cloud is the no-code platform to quickly build & deploy Julia web apps. It is designed for R&D and data science teams using Julia, who need to share their work with interactive web apps.
Genie Cloud is very simple: import (or write) the Julia code, build the GUI with the drag & drop editor, and deploy the apps in one-click. No frontend code, server stack or hosting to worry about. With Genie Cloud you can build anything, from interactive dashboards to ML demos to production-grade apps.
Genie Cloud is built on top of the open source Genie Framework (https://genieframework.com/), the most popular Julia web framework (I’m also the creator and maintainer of Genie Framework).
At the moment we are in private beta. You can learn more and sign up to get access here: https://www.geniecloud.io/. Looking forward to your thoughts and questions!
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Julia outside of academia?
I used Julia through my PhD but then started working at a consulting company and had to use Python except for few proof of concepts I built in Julia. Luckily for me, now I'm working at Genie so I finally get to use Julia professionally :)
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GUI library suggestion for school project
Have you checked https://genieframework.com/? It's the most popular web dev framework in Julia.
- Help With Next Language Decision
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Show HN: Genie Builder, no-code UI plugin for building data apps
Hi! Genie Builder is a free VSCode plugin that makes it easy to build web GUIs for Julia applications (and in future, Python apps too). Users can simply drag & drop UI elements to create interactive dashboards and data apps, without writing any frontend code.
The tool is designed for data scientists and researchers who need to expose their data models to business users with an interactive web application, but lack the software development skills to build one.
Genie Builder completely eliminates the need to learn frontend development to code the UI. And very soon, we’re also going to support one-click cloud deployments to make it easy to build AND deploy data apps - no frontend nor devops skills required.
I’m Adrian, the creator of the open-source Genie web framework ([https://genieframework.com/](https://genieframework.com/)). Genie offers low-code libraries for building data applications - just like Streamlit or Dash, but for JuliaLang. We developed Genie Builder because of feedback from our open source community who needs more productive data tooling.
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Beginner's Series to Rust
Yep, I'm a PHP dev and often do simple JS/jQuery to support my backend code. I have a very general interest in data science and embedded programming, meaning one day I might start doing something with them, but for now, I'm interested in those languages for web development. The following frameworks were especially interesting
Go: https://github.com/gin-gonic/gin
Rust: https://rocket.rs/
Julia: https://genieframework.com/
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Plotting in a GUI with Julia
Check Genie. They're working on an app builder called Genie Cloud.
- GenieFramework – Build web applications with Julia
fastapi
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FastAPI Best Practices: A Condensed Guide with Examples
FastAPI is a modern, high-performance web framework for building APIs with Python, based on standard Python type hints.
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Building an Email Assistant Application with Burr
In this tutorial, I will demonstrate how to use Burr, an open source framework (disclosure: I helped create it), using simple OpenAI client calls to GPT4, and FastAPI to create a custom email assistant agent. We’ll describe the challenge one faces and then how you can solve for them. For the application frontend we provide a reference implementation but won’t dive into details for it.
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FastAPI Got Me an OpenAPI Spec Really... Fast
That’s when I found FastAPI.
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How to Deploy a Fast API Application to a Kubernetes Cluster using Podman and Minikube
FastAPI & Uvicorn
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Analysing FastAPI Middleware Performance
Discussion at FastAPI GitHub: https://github.com/tiangolo/fastapi/issues/2696
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LangChain, Python, and Heroku
An API application framework (such as FastAPI)
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Litestar – powerful, flexible, and highly performant Python ASGI framework
It’s been my experience that async Python frameworks tend to turn IO bound problems into CPU bound problems with a high enough request rate, because due to their nature they act as unbounded queues.
This ends up made worse if you’re using sync routes.
If you’re constrained on a resource such as a database connection pool, your framework will continue to pull http requests off the wire that a sane client will cancel and retry due to timeouts because it takes too long to get a connection out of the pool. Since there isn’t a straightforward way to cancel the execution of a route handler in every Python http framework I’ve seen exhibit this problem, the problem quickly snowballs.
This is an issue with fastapi, too- https://github.com/tiangolo/fastapi/issues/5759
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AI-Powered Image Search with CLIP, pgvector, and Fast API
Fast API.
- Ask HN: What is your go-to stack for the web?
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Fun with Avatars: Crafting the core engine | Part. 1
We will create our API using FastAPI, a modern high-performance web framework for building fast APIs with Python. It is designed to be easy to use, efficient, and highly scalable. Some key features of FastAPI include:
What are some alternatives?
Dash.jl - Dash for Julia - A Julia interface to the Dash ecosystem for creating analytic web applications in Julia. No JavaScript required.
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
PlutoSliderServer.jl - Web server to run just the `@bind` parts of a Pluto.jl notebook
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
Visual Studio Code - Visual Studio Code
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
PackageCompiler.jl - Compile your Julia Package
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
Chain.jl - A Julia package for piping a value through a series of transformation expressions using a more convenient syntax than Julia's native piping functionality.
Flask - The Python micro framework for building web applications.
Revise.jl - Automatically update function definitions in a running Julia session
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.