py-shiny
Tidier.jl
py-shiny | Tidier.jl | |
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29 | 5 | |
968 | 489 | |
5.8% | 4.1% | |
9.7 | 8.5 | |
5 days ago | 6 days ago | |
Python | Julia | |
MIT License | MIT License |
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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
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Duckdb + Shiny for Python example
Code is here: https://github.com/rstudio/py-shiny/tree/duckdb-example/examples/duckdb
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Transitioning from R to Python - any tips?
The equivalent of shiny in python is shiny for python: https://shiny.posit.co/py/
- Show HN: Mercury – convert Jupyter Notebooks to Web Apps without code rewriting
- Shiny for Python – building interactive web apps from Python
- Shiny – Web Pages in Python
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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/
Tidier.jl
- Tidier.jl: Meta-package for data analysis in Julia, modeled after R tidyverse
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Julia 1.10 Released
btw, there has been a pretty nice effort of reimplementing the tidyverse in julia with https://github.com/TidierOrg/Tidier.jl and it seems to be quite nice to work with, if you were missing that from R at least
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Pandas vs. Julia – cheat sheet and comparison
Indeed DataFrames.jl isn't and won't be the fastest way to do many things. It makes a lot of trade offs in performance for flexibility. The columns of the dataframe can be any indexable array, so while most examples use 64-bit floating point numbers, strings, and categorical arrays, the nice thing about DataFrames.jl is that using arbitrary precision floats, pointers to binaries, etc. are all fine inside of a DataFrame without any modification. This is compared to things like the Pandas allowed datatypes (https://pbpython.com/pandas_dtypes.html). I'm quite impressed by the DataFrames.jl developers given how they've kept it dynamic yet seem to have achieved pretty good performance. Most of it is smart use of function barriers to avoid the dynamism in the core algorithms. But from that knowledge it's very clear that systems should be able to exist that outperform it even with the same algorithms, in some cases just by tens of nanoseconds but in theory that bump is always there.
In the Julia world the one which optimizes to be fully non-dynamic is TypedTables (https://github.com/JuliaData/TypedTables.jl) where all column types are known at compile time, removing the dynamic dispatch overhead. But in Julia the minor performance gain of using TypedTables vs the major flexibility loss is the reason why you pretty much never hear about it. Probably not even worth mentioning but it's a fun tidbit.
> For what it's worth, data.table is my favourite to use and I believe it has the nicest ergonomics of the three I spoke about.
I would be interested to hear what about the ergonomics of data.table you find useful. if there are some ideas that would be helpful for DataFrames.jl to learn from data.table directly I'd be happy to share it with the devs. Generally when I hear about R people talk about tidyverse. Tidier (https://github.com/TidierOrg/Tidier.jl) is making some big strides in bringing a tidy syntax to Julia and I hear that it has had some rapid adoption and happy users, so there are some ongoing efforts to use the learnings of R API's but I'm not sure if someone is looking directly at the data.table parts.
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Tidyverse 2.0.0
“Tidier.jl is a 100% Julia implementation of the R tidyverse mini-language in Julia.”
https://github.com/TidierOrg/Tidier.jl
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What's Julia's biggest weakness?
A recent package, Tidier.jl, is coming from a R package developer: https://github.com/kdpsingh/Tidier.jl
What are some alternatives?
Solara - A Pure Python, React-style Framework for Scaling Your Jupyter and Web Apps
Julia-DataFrames-Tutorial - A tutorial on Julia DataFrames package
pyvibe - Generate styled HTML pages from Python
tidytable - Tidy interface to 'data.table'
Genie.jl - 🧞The highly productive Julia web framework
DataFramesMeta.jl - Metaprogramming tools for DataFrames
React - The library for web and native user interfaces.
julia - The Julia Programming Language
streamlit - Streamlit — A faster way to build and share data apps.
db-benchmark - reproducible benchmark of database-like ops
pyodide - Pyodide is a Python distribution for the browser and Node.js based on WebAssembly