Tag: frontend

JavaScript for R — ebook

The R programming language has seen the integration of many languages; C, C++, Python, to name a few, can be seamlessly embedded into R so one can conveniently call code written in other languages from the R console. Little known to many, R works just as well with JavaScript—this book delves into the various ways both languages can work together.
https://book.javascript-for-r.com/

John Coene is an well-known R and JavaScript developer. He recently wrote a book on JavaScript for R users, of which he published an online version free to access here.

The book is definitely worth your while if you want to better learn how to develop front-end applications (in JavaScript) on top of your statistical R programs. Think of better understanding, and building, yourself Shiny modules or advanced data visualizations integrated right into webpages.

A nice step on your development path towards becoming a full stack developer by combining R and JavaScript!

Yet most R developers are not familiar with one of web browsers’ core technology: JavaScript. This book aims to remedy that by revealing how much JavaScript can greatly enhance various stages of data science pipelines from the analysis to the communication of results.
https://book.javascript-for-r.com/

Want to learn more about JavaScript in general, then I recommend this book:

Learn to style HTML using CSS — Tutorials by Mozilla

Cascading Stylesheets — or CSS — is the first technology you should start learning after HTML. While HTML is used to define the structure and semantics of your content, CSS is used to style it and lay it out. For example, you can use CSS to alter the font, color, size, and spacing of your content, split it into multiple columns, or add animations and other decorative features.
https://developer.mozilla.org/en-US/docs/Learn/CSS

I was personally encoutered CSS in multiple stages of my Data Science career:

When I started using (R) markdown (see here, or here), I could present my data science projects as HTML pages, styled through CSS.
When I got more acustomed to building web applications (e.g., Shiny) on top of my data science models, I had to use CSS to build more beautiful dashboard layouts.
When I was scraping data from Ebay, Amazon, WordPress, and Goodreads, my prior experiences with CSS & HTML helped greatly to identify and interpret the elements when you look under the hood of a webpage (try pressing CTRL + SHIFT + C).

I know others agree with me when I say that the small investment in learning the basics behind HTML & CSS pay off big time:

ok listen……. i finally took a few hours to learn some CSS basics and big time recommend to any and all #rstats people who have always felt absolutely clueless looking up CSS stuff on stack overflow
— Sharla Gelfand (@sharlagelfand) June 30, 2020

I read that Mozilla offers some great tutorials for those interested in learning more about “the web”, so here are some quicklinks to their free tutorials:

Screenshot via developer.mozilla.org/en-US/docs/Learn/CSS/CSS_layout/Introduction

17 Principles of (Unix) Software Design

I came across this 1999-2003 e-book by Eric Raymond, on the Art of Unix Programming. It contains several relevant overviews of the basic principles behind the Unix philosophy, which are probably useful for anybody working in hardware, software, or other algoritmic design.

First up, is a great list of 17 design rules, explained in more detail in the original article:

Rule of Modularity: Write simple parts connected by clean interfaces.
Rule of Clarity: Clarity is better than cleverness.
Rule of Composition: Design programs to be connected to other programs.
Rule of Separation: Separate policy from mechanism; separate interfaces from engines.
Rule of Simplicity: Design for simplicity; add complexity only where you must.
Rule of Parsimony: Write a big program only when it is clear by demonstration that nothing else will do.
Rule of Transparency: Design for visibility to make inspection and debugging easier.
Rule of Robustness: Robustness is the child of transparency and simplicity.
Rule of Representation: Fold knowledge into data so program logic can be stupid and robust.
Rule of Least Surprise: In interface design, always do the least surprising thing.
Rule of Silence: When a program has nothing surprising to say, it should say nothing.
Rule of Repair: When you must fail, fail noisily and as soon as possible.
Rule of Economy: Programmer time is expensive; conserve it in preference to machine time.
Rule of Generation: Avoid hand-hacking; write programs to write programs when you can.
Rule of Optimization: Prototype before polishing. Get it working before you optimize it.
Rule of Diversity: Distrust all claims for “one true way”.
Rule of Extensibility: Design for the future, because it will be here sooner than you think.

Moreover, the book contains a shortlist of some of the philosophical principles behind Unix (and software design in general):

Everything that can be a source- and destination-independent filter should be one.
Data streams should if at all possible be textual (so they can be viewed and filtered with standard tools).
Database layouts and application protocols should if at all possible be textual (human-readable and human-editable).
Complex front ends (user interfaces) should be cleanly separated from complex back ends.
Whenever possible, prototype in an interpreted language before coding C.
Mixing languages is better than writing everything in one, if and only if using only that one is likely to overcomplicate the program.
Be generous in what you accept, rigorous in what you emit.
When filtering, never throw away information you don’t need to.
Small is beautiful. Write programs that do as little as is consistent with getting the job done.

If you want to read the real book, or if you just want to support the original author, you can buy the book here: