Genie.jl VS TidyverseSkeptic

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.

I just don't get these to be honest -- besides the fact that author missed simple things like `df.groupby('var',as_index=False)`, isn't this obviously arbitrary "this is easier my way" complaints? (I did R before all the chaining stuff was popular, and I wouldn't stuff everything into a single command like that even now. It isn't like you get lazy evaluation or any special data processing magic.)

So I get people love chaining and tidyverse, good for you, I don't. But at least I can acknowledge that my way (or this way) people have different preferences and one is not intrinsically easier.

Norm Matloff has a blog where he essentially just argues the opposite of all the tidyverse stuff, https://github.com/matloff/TidyverseSkeptic, but it is the same idea in reverse to me (one is not obviously easier to learn than the other IMO).

On the other hand, there is also a more traditional universe outside of the of the newer tidyverse approach. See the criticism of the tidyverse ecosystem by Prof Norm Matloff (of UC Davis). He provides a freely available introductory course in base R.

Whenever I hear tidyverse, I just feel the need to leave this: TidyverseSceptic

Yeah, I had never heard of him before, but I followed the link in the article above to his GitHub page and think he made some really great points about conciseness and clarity in base R code, and, I admittedly had no idea tapply() was so useful and easy to use, because I almost never see it used in any examples online. Although I agree with others here that he's misrepresenting why package developers use base R (which is to avoid dependences in their packages, which is very important), I also find myself agreeing with him that future R programmers not being taught base R is worrisome (I'm thinking of dependencies in future package development).

I was in an R group meeting. One of the members mentioned Prof. Norm Matloff and said he has comments about tidyverse. I searched and found Matloff's explanation here. What are your thoughts on tidyverse and Matloff's comments about it? As I read it, I found myself agreeing with certain points. I do not have a computer science background; I'm someone trying to learn coding because I see uses for it in my work. I started my learning, about a year ago, with tidyverse tutorials. My patchwork jumping around, maybe in addition to some of the gaps Matloff indicates, show me that I know very little about base R.

There are good arguments against tidyverse, especially for beginners. It doesn't lead to a growth in understanding the language fundamentals and requires to learn many functions, paradigms, and syntaxes not shared by base R, which can easily be overwhelming and lead to a learn-by-heart approach more than to a learn-by-understanding. There are many good articles on the topic, such as this one or a more in-depth one, suggesting to consider tidyverse a more advanced application for specific use cases, if you like the dialect. I don't, so I might be biased.

I would discourage you to get into the tidyverse, at least in the first stages of your R training. It's like trying to learn english AND scottish together as a foreigner. You can read some better worded discussions here https://github.com/matloff/TidyverseSkeptic and here https://towardsdatascience.com/a-thousand-gadgets-my-thoughts-on-the-r-tidyverse-2441d8504433?gi=1b0a3648b6e6

My opinions are largely in agreement with Norm Matloff on the subject actually.