Python

In Python, the main thread is the initial thread that starts when the Python interpreter is executed. It is the default thread within a Python process, responsible for managing the program and creating additional threads. Every Python program has at least one thread of execution called the main thread. The main thread by default is a non-daemon […]

A thread pool is a mechanism that automatically manages multiple threads efficiently, allowing tasks to be executed concurrently. Python does not provide thread pooling directly through the threading module. Instead, it offers thread-based pooling through the multiprocessing.dummy module and the concurrent.futures module. These modules provide convenient interfaces for creating and managing thread pools, making it easier to perform concurrent task execution. […]

Thread scheduling in Python is a process of deciding which thread runs at any given time. In a multi-threaded program, multiple threads are executed independently, allowing for parallel execution of tasks. However, Python does not have built-in support for controlling thread priorities or scheduling policies directly. Instead, it relies on the operating system’s thread scheduler. […]

In Python, naming a thread involves assigning a string as an identifier to the thread object. Thread names in Python are primarily used for identification purposes only and do not affect the thread’s behavior or semantics. Multiple threads can share the same name, and names can be specified during the thread’s initialization or changed dynamically. […]

In Python, joining the threads means using the join() method to wait for one thread to finish before moving on to others. This is useful in multithreaded programming to make sure some threads are completed before starting or continuing with other threads. By using the join() method, you can make sure that one thread has finished running before another […]

In Python, starting a thread involves using the start() method provided by the Thread class in the threading module. This method initiates the thread’s activity and automatically calls its run() method in a separate thread of execution. Meaning that, when you call start() on each thread object (for example., thread1, thread2, thread3) to initiate their execution. Python to launch separate threads […]

Creating a thread in Python involves initiating a separate flow of execution within a program, allowing multiple operations to run concurrently. This is particularly useful for performing tasks simultaneously, such as handling various I/O operations in parallel. Python provides multiple ways to create and manage threads. In this tutorial, you will learn the basics of […]

A thread object goes through different stages during its life cycle. When a new thread object is created, it must be started, which calls the run() method of thread class. This method contains the logic of the process to be performed by the new thread. The thread completes its task as the run() method is […]

In Python, multithreading allows you to run multiple threads concurrently within a single process, which is also known as thread-based parallelism. This means a program can perform multiple tasks at the same time, enhancing its efficiency and responsiveness. Multithreading in Python is especially useful for multiple I/O-bound operations, rather than for tasks that require heavy […]

Built-in exceptions are pre-defined error classes in Python that handle errors and exceptional conditions in programs. They are derived from the base class “BaseException” and are part of the standard library. Standard Built-in Exceptions in Python Here is a list of Standard Exceptions available in Python − Sr.No. Exception Name & Description 1 ExceptionBase class […]