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Image credit: Саша Алалыкин via Pexels Boston and Stockholm just swapped a very expensive piece of digital Lego, as private equity heavyweight Abry Partners has officially agreed to hand over the keys to Confirma Software to Main Capital Partners after a cozy seven-year run. From Thesis to Treasure Chest Back in 2017, the folks at Abry looked at the sprawling, picturesque Nordic region and decided that what it really needed wasn't just more heavy metal bands or artisanal meatballs, but a powerhouse of mission-critical vertical software. Fast forward seven years, and that little thesis has matured into Confirma Software—a veritable digital empire of niche enterprise apps. Selling a massive software platform is a bit like finally upgrading from Python to R—wait, let me rephrase that, because nobody actually enjoys wrestling with R unless they are a sadomasochistic data scientist. Let's call it more like parting with a trusty, tangle-free pair of wired earbuds: you k...

Image credit: Brett Sayles via Pexels It is a truth universally acknowledged in the tech world that if you build a self-driving car in your garage, the universe will test your code in the most comically unforgiving way possible. Case in point: a viral video circulating out of Pakistan, where a hopeful innovator’s DIY autonomous vehicle skipped the gentle test-track phase and opted instead to target a parked police van with surgical, irony-laced precision. A Demonstration Gone Spectacularly Wrong The clip begins like many hopeful tech demos on the internet. A creator enthusiastically showcases a vehicle modified to steer itself, promising a glimpse into the future of automated transit. But much like trying to perform data science in R when you could be using the sheer perfection of Python, the execution devolved into unnecessary pain very quickly. The vehicle suddenly veered off its path, ignored the open street entirely, and slammed directly into a stationary police cruise...

Performance – how fast a program runs – matters a great deal in computing. In tasks like heavy numerical simulation, processing large files, or running many concurrent operations, a few extra seconds (or minutes) can make a big difference. At one end of the spectrum are low-level compiled languages like C++ that give programmers direct control of the hardware, and at the other end are high-level languages like Python that prioritize ease of use but may incur overhead. Java sits in the middle as a managed language with a sophisticated runtime, while Julia is a newer language explicitly designed for scientific and numerical computing with high performance in mind. In this article, we compare how Python, C++, Java, and Julia typically perform on three kinds of tasks – numerical computation, file I/O, and concurrency – and explain what language features and architectures cause the differences. Illustration: The speed of code Numerical Computation Python: Pure Python code (e...

Images now make up nearly 50% of a typical website's total page weight . In an era where both  user experience and search engine rankings are tied to page speed , optimizing images is no longer a luxury—it's a necessity. This article will guide you through two powerful techniques to address this: implementing responsive images with srcset and converting your entire library to the modern WebP format . Illustration: A webP image Why Your Website Needs Responsive Images The "one-size-fits-all" approach to images is broken. Serving a massive, high-resolution desktop image to a mobile user wastes bandwidth and slows loading times . Conversely, stretching a small image on a high-resolution screen makes it look blurry or pixelated . Responsive image technologies solve two main problems: The Art Direction Problem : Delivering a differently cropped or composed image depending on the display size. For example, a wide header image on desktop might be cropp...

Want to glue Python to the rest of your system  -  call a compiled program, run a shell script, invoke Node.js, call Java, or pipe data to/from R? Enter subprocess . It’s Python’s standard way to start external programs, control their input/output, check return codes, set environments and timeouts — all with a solid API. Below is a practical, friendly guide: what subprocess is, why you’d use it, examples, best practices, pitfalls, and which languages/tools you can call from it. What is subprocess ? subprocess is a standard Python module that lets your Python program spawn new processes, connect to their input/output/error pipes, and obtain their return codes. It replaces older modules like os.system , popen and friends with a unified, safer interface. Key high-level primitives: subprocess.run() — simple, recommended for most cases (Python 3.5+). subprocess.Popen — lower-level, use when you need streaming IO, advanced control, or long-lived processes...

In user interfaces, transparent elements are fully see-through (like clear glass), while translucent elements are semi-see-through (like frosted glass) that often blur or soften whatever is behind them. Both techniques let background content show through, but translucent layers typically add blur or tint to create depth. In code, transparency and translucency are controlled by opacity or alpha values and, for blurring effects, by special APIs (like backdrop filters or blur effects). We’ll explore how to make UI components transparent or translucent in HTML/CSS , Android ( Jetpack Compose and XML), and iOS (SwiftUI and UIKit), with examples and technical details. Finally, we’ll look at iOS 26’s new Liquid Glass material – Apple’s latest adaptive translucency effect – and how it builds on these concepts. Web (HTML/CSS) On the web, CSS offers simple ways to make elements transparent or translucent: Opacity and RGBA/HSLA : You can set an element’s opacity (0.0 = f...

Data visualization is a key part of data analysis in science, engineering, and business. Among the popular tools for creating plots are Python’s Matplotlib ( matplotlib.pyplot ), Microsoft Excel , and R (especially with the ggplot2 package). Each has its strengths and trade-offs in ease of use, customizability, and performance. Below we compare their plotting capabilities and suggest which is best for different tasks. Matplotlib (Python) Plotting Capabilities Matplotlib is a versatile Python library for 2D (and limited 3D) plotting. Its pyplot interface provides functions like plot() , scatter() , bar() , hist() , etc., covering virtually all standard chart types. For example, one can easily draw line plots, bar charts, pie charts, heatmaps, and even 3D surface or scatter plots (via mpl_toolkits ). Because it is code-based, Matplotlib integrates tightly with NumPy and Pandas: data from Python arrays or dataframes can be plotted directly. Matplotlib also supports subplots and fi...

Starting to code can feel like stepping into a completely new world—one filled with unfamiliar terms, tools, and decisions. But don’t worry: every expert coder once stood where you are now. The key to success? Start small. Stay curious. Practice regularly. In this guide, we’ll walk you through how to begin coding, how to choose your first programming language, and how to build the skills that will turn you into a confident developer. Illustration: The beginning of coding What Is Coding? Coding is the process of writing instructions a computer can understand. These instructions, written in programming languages, tell machines how to perform specific tasks—from calculating numbers to displaying websites and even controlling spacecraft. In short, coding is a way to solve problems and create things using logic and creativity. Step 1: Set Up Your Workspace Before diving into your first line of code, you need a workspace—think of it like a carpenter’s workbench. Here’s what you’l...

Floating-point arithmetic is the backbone of modern computation—but it’s not without its caveats. Programmers frequently encounter precision errors when performing numerical operations, especially in high-stakes domains like scientific computing, finance, or cryptography. This article dives deep into the concept of machine precision (also known as machine epsilon), explains how Python stores numbers, compares precision across programming languages, and shows how Python’s fractions module can be a powerful tool for exact calculations. Not exactly the same precision of machines I meant Understanding Floating‑Point Precision in Python Python’s native float type adheres to the IEEE 754 standard for binary64 (double precision) floating-point numbers. It utilizes 64 bits as follows: 1 bit for the sign 11 bits for the exponent 52 bits for the mantissa (or fraction) This representation provides around 15 to 17 decimal digits of precision. However, due to binary enc...