Python’s popularity has surged with the rise of AI/machine learning, due to its extensive libraries. The language is easy to learn but has some strange behaviors. The article discusses five such peculiarities: improper use of ‘is’ for comparisons, initializing 2D arrays, mutable default arguments, duck typing issues, and the Global Interpreter Lock (GIL).
ForkJoinPool and ThreadPoolExecutor are essential tools in Java concurrency. ForkJoinPool excels at handling recursive, CPU-intensive tasks using a divide-and-conquer approach, while ThreadPoolExecutor is versatile for managing general-purpose, mixed workloads, including IO-bound tasks. This article explores their differences, usage scenarios, and how to maximize their performance.
This article explores creating a custom resource pool in Java, a reusable collection of resources like database connections, shared among multiple consumers. It explains the need for resource pools to manage scarce resources efficiently and provides a guide to implementing one using classes like Resource and ResourcePool.
Golang offers a unique error handling approach, bypassing traditional try-catch in favor of explicit error returns. This article explains how to use the ‘errors’ package for custom error messages, while also detailing the panic and recover mechanisms for handling exceptional runtime errors, with clear, practical code examples.
Have you ever wanted to monitor your NVIDIA GPU directly from your Python code? I’ve been there, and I’m going to show you exactly how to do it. I first discovered NVML Python when I participated in Google Summer of Code several years back, working on Ganglia’s GPU monitoring module. Trust me, once you learn […]
