Effective Testing in JavaScript
Some surprising ways to be more effective at testing in JavaScript. »
Some surprising ways to be more effective at testing in JavaScript. »
In this article, learn how to add a natural language interface to your application and then extend the chatbot to voice commands. »
There is no one size fits all answer. Monoliths and microservices are not your only two choices. Find the balance that works for you. »
Learn how to create separate CI/CD pipelines for microservices in a monorepo. So you can keep using the monorepo for much longer, but still have the flexiblity of independent deployment pipelines for your microservices. »
For when you need a cloud-based Kubernetes cluster quickly! »
Why create a Kubernetes cluster when you probably already have one locally. If you installed Docker Desktop you most likely have a local version of Kubernetes that you can simply switch on and start using! »
A three part series with techniques and tips on automated testing for Algorand smart contracts. »
A three part series with techniques and tips on automated testing for Algorand smart contracts. »
A three part series with techniques and tips on automated testing for Algorand smart contracts. »
pnpm. What’s all the fuss about? Learn how you can use to share code between backend and frontend in a fullstack monorepo. »
Live reload: What it is, why you need it, and how to do it across your entire stack »
Exploring effective ways to share TypeScript code between different projects. »
Developers make mistakes — we're human. In this post, you'll learn how to improve your review process and write better, mistake-free code. »
Learn where singletons came from, where it all went wrong, and how you can best use singletons to reap their benefits. »
Why is it so difficult to implement video streaming for Safari? What does it take to make it work for Safari? The answers to these questions are revealed in this blog post. »
In this blog post, I’d like to introduce you to my new open-source project called MiniQL. We’ll also talk about why I reinvented the wheel and when it’s OK to do that. »
How to roll your own dependency injection with TypeScript decorators and the JavaScript Proxy class — it’s easier than you think. »
The how-to guide to microservices for startups, small teams and solo developers. »
Startups can use microservices. Sortal is living proof. In this blog post I describe the microservices architecture behind Sortal, why we couldn't do without microservices and how as a startup we bootstrapped microservices in a cost effective way. »
Building useful debugging tools from the Node.js async hooks API »
This blog post shows how to compute percent volatility for time series data. »
The simplest possible starting point for scalable logging on your Kubernetes cluster »
For when you need a new Kubernetes cluster quickly! »
The microservices architecture is an increasingly popular alternative to monolithic application development. But what is a monolith and what exactly is wrong with it? »
Learn how you can use a multi-stage Docker build for your Node.js application. »
I've announced my new book! Bootstrapping microservices is a practical and project-based guide to building microservices applications. »
After a whole year of development I'm very proud to announce the launch of Data-Forge Notebook version 1! »
A new update on my progress with Data-Forge Plot - the plot function for Data-Forge! »
JavaScript can be used to do many things, including quantitative trading. In this post I show how to backtest a quantitative trading strategy with JavaScript. »
The world of data is big and it can be difficult to navigate it on your own. With data all around us growing at an ever-increasing rate, it's more important than ever that we can deal with data effectively and efficiently to support our businesses and our customers, to be able to monitor and understand our processes and enable faster and better decision-making. »
Node.js has memory limitations that you can hit quite easily in production. You'll know this if you ever tried to load a large data file into your Node.js application. But where exactly are the limits of memory in Node.js? In this short post we'll push Node.js to it's limits to figure out where those limits are. We'll also cover some practical techniques you can use to work around the memory limitations and get your data to fit into memory. »
Another quick update on my progress developing Data-Forge Plot (DFP). The API has recently evolved but is remains relatively stable, although there are still features I must add to it. I'm sure it will continue to evolve as I integrate new visualization libraries and expand the API. The main thing I have done recently is to extract and restructure the export and capture code, which I talk about in this post. »
Today I'm announcing my new product for data analysis, transformation and visualization in JavaScript! »
Just a quick update of my progress developing Data-Forge Plot. The API has evolved a little bit and so has my thinking around it. I've also started adding examples and unit tests. »
This is the transcript of a conversation I had recently with Athan Reines, co-creator of the JavaScript stdlib library. We talked about why Athan created the library, why he needs to do scientific computing in JavaScript and the difficulties he has encountered. We also discussed the state of data science in the JavaScript ecosystem and how far off we are from equalling Python and what it would take for us to catch up. »
Over the past couple of weeks I've prototyped a new API for plotting in JavaScript. You might rightly wonder why I've done this? Surely there's already enough JavaScript visualization libraries in the wild? »
I have some big news. I've just published Data-Forge version 1 to npm! After over 2.5 years, 1,148 commits and 2 Github repositories it's finally here, and now rewritten in TypeScript no less! This software has been in gestation for sometime. »
I work with JavaScript quite a lot and it shows in this blog, so you won't be surprised to hear that I've been putting together a book that teaches how to do data wrangling in JavaScript. »
I've been doing a lot of data analysis in JavaScript. It makes sense for me to work in JavaScript, because I already use it and that's where my visualizations normally end up. JavaScript has a very rich ecosystem of visualization libraries so that's not surprising. All these visualization libraries are browser based... which is great if that's where you want your visualization to be. It's not so great if you just want to render a chart to an image, say to store for later or to include in some kind of report. »
As a stock trader I need a ready of supply stock market data for analysis and visualisation. That data is needed for decision making and I often render it to a chart to better understand it. »
This is a revisit with various improvements to my original post on The Data Wrangler. In this post I show how to visualise stock data using Data-Forge and Highstock. I also demonstrate how to apply a simple moving average to the price data. »
Are you interested in stock trading but don't have time to watch prices all day? Why stare at the screen for hours on end when you can automate this kind of thing. This post talks about a small app I created to continuously and automatically detect when the price of particular companies have risen to specified levels. »
Do you have a slow internet? Need to visualize your internet speed over time? Do you want to know when outages are happening? »
Linear regression is a technique that is very useful when analysing the trajectory of a stock. In this post I'll show how to compute and render a linear regression trend line. »
Average true range is an indicator that is useful for judging the volatility of a stock. I use this to set the level for my stop loss orders. In this post I'm going to show how to calculate and visualise average true range in JavaScript. »
In this first post on The Data Wrangler I show how to visualise financial data from the Yahoo API using Data-Forge and Highstock. I also demonstrate how to apply a simple moving average to the price data. »