Understanding Shallow Copy and Deep Copy in Python

Managing objects in Python, especially copying objects, is an essential skill for every Python developer. Python offers two main methods for copying objects: shallow copy and deep copy. These two techniques have different uses and implications, especially when working with complex objects or collections of objects. In this article, we will explore the differences between these two copying methods, their uses, and when to favor one over the other, with concrete examples.

Introduction to regular expressions

Introduction Regular expressions (or regex) are sequences of characters that describe a search pattern in a string of characters. They are used in many programming languages to search for, extract, and manipulate textual data. Regular expressions allow for precise descriptions of complex search patterns, such as email addresses or phone numbers, and can be much faster and more efficient than manually traversing each line of text to extract specific information.

The Slicing in Python: Usage and Examples

1/ Sequences In Python, sequences are data types that represent an ordered collection of elements. The most common sequence types are lists, tuples, and strings. 1 2 3 a_list = ["a", "b", "c", "d"] a_tuple = ("a", "b", "c", "d") a_string = "abcd" 2/ Slicing Slicing in Python is a feature that allows you to extract a sub-sequence from a sequence. This can be very useful for accessing specific parts of a sequence.