py-shiny
d3
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py-shiny | d3 | |
---|---|---|
29 | 276 | |
903 | 107,465 | |
8.0% | 0.3% | |
9.7 | 8.4 | |
6 days ago | 3 days ago | |
Python | Shell | |
MIT License | ISC 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.
py-shiny
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Designing a Pure Python Web Framework
I really like this idea of using Python to create both the frontend and backend. Another lib doing this is https://solara.dev/ . Something I particularly like about Solara is that you can interactively build your app in a Jupyter Notebook, since behind the scenes it's using ipywidgets.
Has anyone compared Solara and Reflex and can comment on pros/cons? Are there other options in this space? Maybe https://shiny.posit.co/py/ ?
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FastUI: Build Better UIs Faster
Would you consider giving Shiny (for Python) a try? https://shiny.posit.co/py/ It's (I hope) pretty close to Streamlit in ease of use for getting started, but reactive programming runs all the way through it. The kind of app you're talking about are extremely natural to write in Shiny, you don't have to keep track of state yourself at all.
If you decide to give it a try and have trouble, please email me (email in profile) or drop by the Discord (https://discord.gg/yMGCamUMnS).
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py-shiny VS solara - a user suggested alternative
2 projects | 13 Oct 2023
- Show HN: Mercury – convert Jupyter Notebooks to Web Apps without code rewriting
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Tidyverse 2.0.0
I'm not sure how usable it is, but Shiny for Python exists: https://shiny.rstudio.com/py/
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Graphs in Python web app
There's Shiny for Python - originally for R - but it's only Alpha status: https://shiny.rstudio.com/py/
- Warning, Streamlit collects a lot of data!
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Company project : Django/React, Streamlit or non-web based GUI?
Shiny for python https://shiny.rstudio.com/py/ This is a great Python implementation of the popular R library and lets you build performant applications without all of the caching problems that Streamlit requires. It's got a lot of energy and funding behind it, and there's also a rich suite of pro and open source products around publishing and securely hosting applications which is nice. The main difference between it and Streamlit is reactive execution which means that components minimally re-render without hitting a cache.
- When would you use R instead of Python?
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What tools do I need to create a web based application that shows detailed graphs based on user input?
R Shiny has worked well for me. Admittedly, the R language itself is a bit more obscure, but there is a Python version in Alpha.
d3
- Ask HN: Tips to get started on my own server
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Full Stack Web Development Concept map
d3 - very power visualization library enabling dynamic visualizations. docs
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Observable 2.0, a static site generator for data apps
Yep, Evidence is doing good work. We were most directly inspired by VitePress; we spent months rewriting both D3’s docs (https://d3js.org) and Observable Plot’s docs (https://observablehq.com/plot) in VitePress, and absolutely loved the experience. But we wanted a tool focused on data apps, dashboards, reports — observability and business intelligence use cases rather than documentation. Compared to Evidence, I’d say we’re trying to target data app developers more than data analysts; we offer a lot of power and expressiveness, and emphasize custom visualizations and interaction (leaning on Observable Plot or D3), as well as polyglot programming with data loaders written in any language (Python, R, not just SQL).
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Using Deno with Jupyter Notebook to build a data dashboard
D3.js: A robust library to visualize your data and create interactive data-driven visualizations.
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What is the technology stack used to create these live charts?
They are images so it could be any number of things, datawrapper, charts.js, d3.js to name a few options.
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How do you implement library types?
When I go to the homepage of types/d3 the only hint for any kind of documentation is what seems to be the main github page of d3. It's highly possible I'm missing something here, so sorry if I am but I can't find any documentation of how you are supposed to type these library objects.
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The top 11 React chart libraries for data visualization
Website: D3.js official site
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Frontend development roadmap
D3js
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How to use Next.js and Recharts to build an information dashboard
Recharts is a composable charting library built on React components and D3.js. It contains API’s which allow you to easily add 11 different highly configurable chart types to your React application. Recharts is one of the most popular React.js charting libraries with over 20k likes on GitHub.
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Best heatmap libraries for React (with demos)
D3.js: The advanced option
What are some alternatives?
echarts - Apache ECharts is a powerful, interactive charting and data visualization library for browser
GoJS, a JavaScript Library for HTML Diagrams - JavaScript diagramming library for interactive flowcharts, org charts, design tools, planning tools, visual languages.
vis
d4 - A friendly reusable charts DSL for D3
svg.js - The lightweight library for manipulating and animating SVG
sigma.js - A JavaScript library aimed at visualizing graphs of thousands of nodes and edges
paper.js - The Swiss Army Knife of Vector Graphics Scripting – Scriptographer ported to JavaScript and the browser, using HTML5 Canvas. Created by @lehni & @puckey
fabric.js - Javascript Canvas Library, SVG-to-Canvas (& canvas-to-SVG) Parser
visx - 🐯 visx | visualization components
vega - A visualization grammar.
Cytoscape.js - Graph theory (network) library for visualisation and analysis
Snap.svg - The JavaScript library for modern SVG graphics.