Computer Programming

Recursion in Python is when a function calls itself to solve smaller parts of a bigger problem. This technique is useful when a task can be broken into simpler sub-tasks that look just like the original—like counting backwards, breaking down a number, or exploring nested lists and trees. It helps you solve problems by repeating […]

Active threads are the threads that are currently running or still alive in your Python program. Knowing which threads are active can help you monitor your program’s progress, manage resources better, or debug issues when multiple threads are involved. In this article, you will learn how to use Python’s threading.enumerate() to get a list of

In Python, the main thread is the first thread that starts when your program runs. It acts like the boss, controlling the overall flow of your program. Sometimes, when working with multiple threads, you need to know which thread is the main one—for example, to manage thread behavior or to make sure certain code runs

When you write programs with threads, multiple tasks can run at the same time. But inside each task, you might wonder: “Which thread is running this?” That’s where Python gives you a helpful tool. The threading module includes a simple function: current_thread(). This lets you check the identity of the thread currently running your code.

In Python, both processes and threads help you run multiple tasks at the same time. A process is like a separate program running on your computer, each with its own memory. A thread is a smaller task running inside a program, sharing the same memory with other threads. Using processes and threads makes your programs

Threads are great when you want parts of your program to run at the same time. But sometimes, these threads need to talk to each other — like one thread making things and another using them. This is where a Queue comes in. A Queue is a special tool that lets threads pass data to

When working with multiple threads, there are times when you want all threads to pause at a certain point and wait for each other before moving on. This ensures that no thread gets too far ahead, and everyone stays in sync. A Barrier in Python threading acts like a red light on the road. Each

Threads are like busy workers trying to use shared tools or enter a room. But sometimes, only a few workers can use the tool or fit in the room at the same time. Without control, things get messy and confusing. A Semaphore acts like a smart gatekeeper. It counts how many workers are inside and

Sometimes, threads need to pause and wait for something important to happen before moving on. Condition variables act like traffic lights for threads—they tell them when to stop and when it’s safe to go. In this article, we’ll learn how to use condition variables to make threads wait for a signal and then continue safely,

Threads are like busy helpers working together. Sometimes, they need to share the same tools — like a hammer or a paintbrush. If two helpers try to use the same tool at once, things get messy! Locks act like a tool locker that lets only one helper use a tool at a time, keeping things