Tidier.jl VS Genie.jl

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

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.

“Tidier.jl is a 100% Julia implementation of the R tidyverse mini-language in Julia.”

https://github.com/TidierOrg/Tidier.jl

A recent package, Tidier.jl, is coming from a R package developer: https://github.com/kdpsingh/Tidier.jl

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/

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!

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 :)

Have you checked https://genieframework.com/? It's the most popular web dev framework in Julia.

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.

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/

Check Genie. They're working on an app builder called Genie Cloud.