streamlit
fastapi
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streamlit | fastapi | |
---|---|---|
254 | 465 | |
31,506 | 70,779 | |
3.6% | - | |
9.8 | 9.8 | |
2 days ago | 3 days ago | |
Python | Python | |
Apache License 2.0 | 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.
streamlit
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Creating a Sales Analysis Application with Streamlit: A Practical Approach to Business Intelligence
2.-Go to https://streamlit.io, log in, and create a new app from your GitHub repository.
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🦙 Llama-2-GGML-CSV-Chatbot 🤖
Developed using Langchain and Streamlit technologies for enhanced performance.
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Python dev considering Electron vs. Kivy for desktop app UI
Hello,
Have you ever seen the https://streamlit.io/ ? I think this is what you are looking for.
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Show HN: Buefy Web Components for Streamlit
While building dashboards in Streamlit, I found myself really missing Buefy's (Bulma) modern web components.
Specially due to the inability to add new values to Streamlit's multiselect [1], some missing controls like a polished image carousel [2] or a highly customizable data table.
Long story short, we put together streamfy (Streamlit + Buefy) as an MIT licensed project in GitHub to bring Buefy to Streamlit.
Demo: https://streamfy.streamlit.app
All the form components are implemented, missing half of other non-form UX components. There is plenty of room for PRs, testing, feedback, documentation, example, etc.
Please send issues and contributions to GitHub project [3] and general feedback to X / Twitter [4]
Thanks!
[1] https://github.com/streamlit/streamlit/issues/5348
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Simplify Web App Development: Code Lite, Create Big!
Here's your savior, let's welcome Streamlit.
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Show HN: Hyperdiv – Reactive, immediate-mode web UI framework for Python
Looks cool. How do you see this differing from streamlit? https://streamlit.io/
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Revolutionizing Real-Time Alerts with AI, NATs and Streamlit
Imagine you have an AI-powered personal alerting chat assistant that interacts using up-to-date data. Whether it's a big move in the stock market that affects your investments, any significant change on your shared SharePoint documents, or discounts on Amazon you were waiting for, the application is designed to keep you informed and alert you about any significant changes based on the criteria you set in advance using your natural language. In this post, we will learn how to build a full-stack event-driven weather alert chat application in Python using pretty cool tools: Streamlit, NATS, and OpenAI. The app can collect real-time weather information, understand your criteria for alerts using AI, and deliver these alerts to the user interface.
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Using LangServe to build REST APIs for LangChain Applications
In this tutorial, you'll construct a fully functional Streamlit application from the ground up. Streamlit lets you turn simple data scripts into web applications without traditional front-end tools. This application will be capable of downloading audio from any YouTube video, transcribing it using Deepgram, and then summarizing the content with the assistance of Mistral 7B, all streamlined through the capabilities of Langchain.
- Ask HN: Can I create a mobile and Web App using Python/Python Framework?
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Creating Videos with Stable Video Diffusion
Install the Stable Diffusion tools and checkpoints, and run it all with Streamlit.
fastapi
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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:
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Building Fast APIs with FastAPI: A Comprehensive Guide
FastAPI is a modern, fast, web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed to be easy to use, fast to run, and secure. In this blog post, we’ll explore the key features of FastAPI and walk through the process of creating a simple API using this powerful framework.
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Effortless API Documentation: Accelerating Development with FastAPI, Swagger, and ReDoc
FastAPI is a modern, fast web framework for building APIs with Python 3.7+ that automatically generates OpenAPI and JSON Schema documentation. While FastAPI simplifies API development, manually creating and updating API documentation can still be a time-consuming task. In this blog post, we’ll explore how to leverage FastAPI’s automatic documentation generation capabilities, specifically focusing on Swagger and ReDoc, and how to streamline the process of documenting your APIs.
What are some alternatives?
PyWebIO - Write interactive web app in script way.
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
gradio - Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
nicegui - Create web-based user interfaces with Python. The nice way.
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
superset - Apache Superset is a Data Visualization and Data Exploration Platform
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
reflex - 🕸️ Web apps in pure Python 🐍
Flask - The Python micro framework for building web applications.
PySimpleGUI - Python GUIs for Humans! PySimpleGUI is the top-rated Python application development environment. Launched in 2018 and actively developed, maintained, and supported in 2024. Transforms tkinter, Qt, WxPython, and Remi into a simple, intuitive, and fun experience for both hobbyists and expert users.
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.