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Software development
fromInfoQ
1 day ago

Dynamic Languages Faster and Cheaper in 13-Language Claude Code Benchmark

Dynamic languages like Ruby, Python, and JavaScript are faster and cheaper for AI coding tasks compared to statically typed languages.
fromZDNET
3 days ago

Is increasing VRAM finally worth it? I ran the numbers on my Windows 11 PC

Rising RAM prices have made upgrading your PC more expensive. Virtual RAM is a less expensive way of boosting an older computer's performance, but it has limited use cases because it can't match the speed of physical RAM.
Gadgets
JavaScript
fromPythonSpeed
6 days ago

Timesliced reservoir sampling: a new(?) algorithm for profilers

Random sampling from an unknown-length event stream can effectively identify relevant information without storing all data.
#python
Python
fromInfoWorld
1 week ago

Speed boost your Python programs with new lazy imports

Lazy imports in Python create a proxy object that delays the actual import until the module is needed.
Python
fromInfoWorld
1 week ago

Speed boost your Python programs with new lazy imports

Lazy imports in Python create a proxy object that delays the actual import until the module is needed.
more#python
Software development
fromInfoWorld
2 weeks ago

I ran Qwen3.5 locally instead of Claude Code. Here's what happened.

Smaller, efficient LLMs like Qwen3.5 can run on consumer-grade PCs for local development, but setup complexity and IDE integration remain challenging barriers to widespread adoption.
Python
fromRealpython
3 weeks ago

Threading in Python Quiz - Real Python

An interactive 10-question quiz assesses understanding of Python threading concepts including thread creation, ThreadPoolExecutor, locks for race condition prevention, and queue-based producer-consumer patterns.
fromMedium
4 weeks ago

Scala Profiling Under Fire

While the codebase is fresh and grows fast under the umbrella of the local environment, we tend to rely on debugging tools, which were created specifically for that purpose. The app is half-baked, and the code is split open. We observe it through the lens of our IDE and with the speed of our brain. Everything is possible; we may pause execution for minutes, and the whole system is a white box - an open book for us.
Software development
fromTheregister
3 weeks ago

RAM is getting expensive, so squeeze the most from it

Both work with Linux's existing swapping mechanism. Swapping (called paging in Windows) is a way for the kernel to handle running low on available RAM. It chooses pages of memory that aren't in use right now and copies them to disk, then those blocks can be marked as free and reused for something else.
Software development
DevOps
fromMedium
4 months ago

What is swap memory in linux? What It Really Is, Why It Exists, and How to Actually Use It

Swap uses disk space to extend RAM by storing rarely used memory pages as a slower backup when physical memory fills.
Python
fromInfoWorld
2 months ago

CPython vs. PyPy: Which Python runtime has the better JIT?

PyPy remains far faster for raw numerical workloads, but CPython's new native JIT and no-GIL builds close the gap in other workloads and enable threading.
Java
fromMedium
2 months ago

Java Is Slow-Until You Use It Like This

Deep JVM knowledge and disciplined practices—clear module boundaries, immutable domain models, simple services, careful stream use, and higher-level concurrency—enable scalable, maintainable Java systems.
Gadgets
fromZDNET
2 months ago

RAM too expensive? Here's how to speed up your Linux system anyway - for free

Use ZRAM to improve Linux performance by providing compressed in-memory swap when adding physical RAM is too expensive.
fromPythonSpeed
2 months ago

Unit testing your code's performance, part 1: Big-O scaling

If you're trying to make sure your software is fast, or at least doesn't get slower, automated tests for performance would also be useful. But where should you start? My suggestion: start by testing big-O scaling. It's a critical aspect of your software's speed, and it doesn't require a complex benchmarking setup. In this article I'll cover: A reminder of what big-O scaling means for algorithms. Why this is such a critical performance property.
Software development
Python
fromPythonSpeed
1 month ago

Speeding up NumPy with parallelism

Combine CPU-core parallelism and algorithmic optimization (e.g., Numba) to substantially speed up NumPy computations and reduce memory usage.
Software development
fromZDNET
2 months ago

I used GPT-5.2-Codex to find a mystery bug and hosting nightmare - it was beyond fast

A $20 ChatGPT Plus plan with Codex can diagnose and fix real-world WordPress plugin bugs and hosting issues, saving developer time.
fromNedbatchelder
2 months ago

Testing: exceptions and caches

Kacper Borucki blogged about parameterizing exception testing, and linked to pytest docs and a StackOverflow answer with similar approaches. The common way to test exceptions is to use pytest.raises as a context manager, and have separate tests for the cases that succeed and those that fail. Instead, this approach lets you unify them. I tweaked it to this, which I think reads nicely: One parameterized test that covers both good and bad outcomes. Nice.
Software development
fromPybites
1 month ago

How To Automate Python Performance Benchmarking In Your CI/CD Pipeline - Pybites

Treat performance as a quality gate: use deterministic benchmarks, enforce PR performance limits, and add AI-aware guardrails to prevent regressions.
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