Category: Advanced Concepts

The Python Immutable data structures are the data structures that once created, cannot be changed. This means that any attempt to modify the data structure will result in a new instance being created rather than altering the original. Immutable data structures are useful for ensuring that data remains constant throughout the execution of a program which can…

Memory leaks occur when a program incorrectly manages memory allocations which resulting in reduced available memory and potentially causing the program to slow down or crash. In Python, memory management is generally handled by the interpreter but memory leaks can still happen especially in long-running applications. Diagnosing and fixing memory leaks in Python involves understanding how memory is allocated, identifying problematic areas and applying…

Python Descriptors Python Descriptors are a way to customize the access, assignment and deletion of object attributes. They provide a powerful mechanism for managing the behavior of attributes by defining methods that get, set and delete their values. Descriptors are often used to implement properties, methods and attribute validation. A descriptor is any object that implements at least…

Python Coroutines are a fundamental concept in programming that extend the capabilities of traditional functions. They are particularly useful for asynchronous programming and complex data processing pipelines. Coroutines are an extension of the concept of functions and generators. They are designed to perform cooperative multitasking and manage asynchronous operations. In traditional functions i.e. subroutines which have a single…

Context managers in Python provide a powerful way to manage resources efficiently and safely. A context manager in Python is an object that defines a runtime context for use with the with statement. It ensures that setup and cleanup operations are performed automatically. For instance, when working with file operations, context managers handle the opening and closing of files, ensuring…

The Humanize Package in Python is a library which is specifically designed to convert numerical values, dates, times and file sizes into formats that are more easily understood by humans. Although computers and databases excel at processing raw numerical data but these formats can be challenging for humans to quickly grasp. The Humanize Package tackles this issue by converting…

Automation using Python Automation with Python involves using programming techniques to perform tasks automatically, typically without human intervention. Python provides various libraries to make it a powerful tool for automating different types of repetitive tasks including, task scheduling, web scraping, GUI automation and many more. Utilizing the Python’s extensive libraries, can create automation solutions to…

Python type hints were introduced in PEP 484 to bring the benefits of static typing to a dynamically typed language. Although type hints do not enforce type checking at runtime, they provide a way to specify the expected types of variables, function parameters, and return values, which can be checked by static analysis tools such as mypy. This…

Signal handling in Python allows you to define custom handlers for managing asynchronous events such as interrupts or termination requests from keyboard, alarms, and even system signals. You can control how your program responds to various signals by defining custom handlers. The signal module in Python provides mechanisms to set and manage signal handlers. A signal handler is a function…

Monkey patching in Python refers to the practice of dynamically modifying or extending code at runtime typically replacing or adding new functionalities to existing modules, classes or methods without altering their original source code. This technique is often used for quick fixes, debugging or adding temporary features. The term “monkey patching” originates from the idea of making changes in…