How many spaces is a tab in Java, Rust, C++, Python, C#, Powershell, Golang, Javascript

Java cuenta con Collection Framework, que define cómo se almacenan los datos y qué reglas deben cumplir las distintas estructuras…Continue reading on Medium »

I recently built Segmented Timer, a simple iOS app that lets you create a sequence of timed segments for workouts, study sessions, meditation, or anything that needs structured timing. Why this project was technically challenging Most timer apps just do one countdown — but I wanted something that could run multiple segments in a row automatically, without needing the user to tap “next” every time. That meant I had to handle: Segment scheduling: Ensuring the app correctly transitions between segments, even if the user leaves the app or locks the screen. Background execution: iOS often pauses apps in the background, so I had to build a timer system that still works reliably without draining battery. State persistence: Saving routines so users can close the app and reopen it later without losing progress. What made it interesting The most interesting part was designing the timer system to be both accurate and efficient. I didn’t just want a simple countdown — I wanted the app to feel reliable, even when interrupted by phone calls, notifications, or screen locks. To solve this, I: Used a timestamp-based system instead of relying only on repeated intervals. Stored start times and segment end times in a way that could be recalculated when the app reopened. Ensured the UI always reflected the correct remaining time, even after interruptions. What I learned This project taught me a lot about: iOS app lifecycle and background tasks Managing app state (especially when the user closes or switches apps) Creating clean UI workflows for multi-step processes Final result Segmented Timer is a clean, simple app that works exactly how I needed it to: reliable, fast, and easy to use. If you have any tips on how to make this better that would help a lot. submitted by /u/StationPersonal4902 [link] [comments]

In an era where data has become the world’s most valuable resource, web scraping has emerged as one of the most powerful — and…Continue reading on Medium »

Asinxron proqramlaşdırma — uzun çəkən işləri gözləyərkən proqramın işləməyə davam etməsidir.yani proqramın bloklanmırContinue reading on Medium »

Hi there folks!Continue reading on Level Up Coding »

The verifiability threshold explains why AI excels at computing tasks humans can’t specify but struggles with simple common senseContinue reading on Level Up Coding »

Learn How Guards and Providers Work at the Heart of Laravel’s Authentication SystemContinue reading on Level Up Coding »

Fix this one thing, and your salary could change dramatically.Continue reading on Level Up Coding »

Master These Everyday Tools to Clean, Format, and Supercharge Your StringsContinue reading on Level Up Coding »

I thought I was a Senior Engineer. Then I realized I didn’t understand how a Python list actually worked.Continue reading on Level Up Coding »

Every few weeks, the same fear comes back.Continue reading on Level Up Coding »

I am building an open source project in the AI agents space and I am currently in the phase of stabilizing it toward a first solid release. The project already has a clear vision, real code, and a concrete roadmap. I am working on it as a side project until it reaches a stable baseline, then I plan to do a larger announcement and push for wider adoption. I believe it can have a meaningful impact in its domain. My question is more about process than promotion. What are the best ways you have found to attract serious contributors or long-term partners for an open source project? For example: - Where do you usually look for collaborators? - What signals make you personally want to join a project? - Is it better to wait until things are very polished, or invite people earlier? Any advice or lessons learned would be really appreciated. submitted by /u/nirberko [link] [comments]

Private Rust project for building with any compiler language Release to Windows and Mac for now submitted by /u/roussov [link] [comments]

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Why writing a custom programming language as part of your app is like going up against a Sicilian when death is on the line submitted by /u/me_again [link] [comments]

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Hey everyone! I've been working on Rustrak, an open-source error tracking system that works as a drop-in replacement for Sentry. Why I built this: - Sentry is great but can be expensive or overkill for smaller projects - Self-hosted Sentry requires a lot of resources - I wanted something minimal that just works What makes it different: - Works with any existing Sentry SDK (Python, JS, Go, Rust, etc.) - no code changes needed - ~50MB memory footprint (vs. 16GB+ for self-hosted Sentry) - Single binary + PostgreSQL, no Redis or complex infrastructure - <50ms ingestion latency Tech stack: - Backend: Rust + Actix-web - Frontend: Next.js - Database: PostgreSQL It's still early but fully functional. You can be up and running in minutes with Docker. Links: - GitHub: https://github.com/AbianS/rustrak - Docs: https://abians.github.io/rustrak Would love feedback, bug reports, or feature suggestions. Happy to answer any questions! submitted by /u/Zukonsio [link] [comments]

Since 2022, users have been asking Grafana for market depth chart visualization support. More than three years later, there is still no built-in solution or third-party plugins. If you want to see order book depth in real-time, you're out of luck. So I built one. In the blog post I tell the basics of a Market Depth chart, and I show the javascript I wrote for the Plotly plugin to render it. The full code is available on Github. submitted by /u/supercoco9 [link] [comments]

https://devforum.play.date/t/playdate-supports-go-language-compiler-sdk-bindings-tools-and-examples/24919 submitted by /u/AmorBielyi [link] [comments]

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Hey Programmers, As we know, most systems do not need Microservices - wisely designed Modular Monolith covers it all; but then, the question arises: How do you communicate and exchange data between different modules? In the post, I describe in more detail a few good ways in which modules might communicate with each other. Most notably: Clients/APIs - simple, in-memory method calls of dedicated interfaces Application Events - in-memory events published between modules, which can introduce coupling at the database level Outbox Pattern - in-memory events with more sophisticated sending process that does not introduce coupling at the database level, thus making it easier to separate modules physically Background Data Synchronization - does not allow modules to communicate with each other during external requests processing, which forces them to be more self-contained, independent and resilient You can go very far with properly modularized monolith and clear communication conventions of these kind. And if you ever find yourself needing to move one or two modules into separate services - that is quite straightforward as well! submitted by /u/BinaryIgor [link] [comments]

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Wrote up my experience optimizing audio preprocessing in Mojo. Went from 476ms down to 27ms for 30s audio through 9 optimization passes. Some techniques worked great (sparse filterbanks, twiddle caching), others didn't (bit-reversal LUTs, cache blocking). The interesting part was competing against librosa's Intel MKL backend. Managed 1.5-3.6x speedup depending on audio length, with better consistency too. submitted by /u/DevCoffee_ [link] [comments]

We have created some good interactive examples to understand high cardinality in the context of monitoring systems. For a better experience, check out in desktop. If you want more topics explained like this, please leave a comment. submitted by /u/ankit01-oss [link] [comments]

No matter how they’re designed—manager discretion, calibration committees, or opaque algorithms—performance reviews in big tech reliably produce results that are neither meritocratic nor humane. In practice, compensation and promotions still hinge on a single decision-maker. I wrote a dark, deliberately cynical essay comparing Apple and Roblox, two companies where I managed teams, that tried very different approaches to performance evaluation and failed in different ways. Even if we could make these systems “fair,” I’m not convinced that’s the right goal. What people actually want isn’t better algorithms, but humane treatment and rational judgment when it matters. Originally posted in r/ExperiencedDevs. Sharing here for a broader perspective. submitted by /u/NoVibeCoding [link] [comments]

That "30-40% productivity gain" claim for GitHub Copilot? Independent research from Uplevel found a 41% increase in bugs introduced into codebases. The code got written faster. It also broke more often. I fact-checked 8 claims from Nadella's Davos interview. Only 1 held up. submitted by /u/jpcaparas [link] [comments]

Both incidents involve smart people doing reasonable things and systems behaving exactly as designed. Mars Climate Orbiter (1999): lost because one team used Imperial units and the other used Metric. Citibank $500M error (2020): a routine interest payment turned into a principal transfer due to ambiguous UI labels. The problem wasn’t complexity but "meaning" that existed only in people’s heads. This is a breakdown of how assumptions turn into catastrophic technical debt. submitted by /u/Vast-Drawing-98 [link] [comments]

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