web development

Quick Guide to GraphQL for BackEnd & FrontEnd

GraphQL is one of those technologies which is constantly on my radar, just waiting for the right time and project to try it on. For now, I’m just slowly moving to that target, collecting links to resources in the meantime.

“Introduction & Quick Guide to GraphQL for BackEnd & FrontEnd” is a new addition to my collection. This article, much like many others, provides a brief introduction to the technology. And it also shows a practical example of how to design and implement GraphQL API both on the front and back ends. I give it extra credits for mentioning GraphiQL in-browser IDE for exploring GraphQL.

PHP Internals

Here’s a new addition to all the web resources dedicated to the PHP programming language – PHP Internals.

This website is dedicated to providing resources on PHP’s internals. All content covers PHP 7+, with the documentation typically targeting the current master branch of php-src.

idg – document image generator

idg is a very handy tool for programmatically generating images which look like documents and web page templates. It’s built on top of the ImageMagick and will come native to anyone familiar with the modern grid-based web design.

Carbon – beautiful screenshots of your source code

Carbon – is a very simple, but very useful web tool for creating beautiful screenshots of the source code. And yes, before you start correcting me, I know that source code is always more useful as a listing, which can be copy-pasted, searched, and so on, rather than an image. But there are still plenty of scenarios when you just need it fixed and frozen.

Carbon provides plenty of flexibility in a very friendly user interface – code highlighting for a variety of programming languages and configuration files, editor themes, window controls, fonts, and more. There’s also a very simple way to tweet the screenshot directly from Carbon, if that’s what you want to do.

How to Analyze Tweet Sentiments with PHP Machine Learning

Machine learning is rarely mentioned in the same sentence (or article, for that matter) with PHP, so each time this happens, I’m all ears. Here’s one that I came across recently – How to Analyze Tweet Sentiments with PHP Machine Learning.

Unlike many other “hello world” kind of examples, this article examines a real and quite common problem, which can be easily adopted to other similar problems – SPAM filtering, marketing segmentation, fraud detection, etc.