Instance Variables Instance variables are variables defined within a class but outside of any method. They are unique to each instance (object) of a class. This means that if you create multiple objects from the same class, each object will have its own separate copy of the instance variables. They are used to store the…
In Python classes, you can have different types of variables and methods, each with a specific scope and purpose. They are primarily categorized based on whether they belong to the class itself or to an object (instance) of the class. 1. Types of Variables Variables in a class are called attributes. a. Instance Variables 🧑💻…
🟥 Rectangle Properties Properties are the nouns that describe a rectangle. They are the characteristics that define a specific rectangle’s dimensions and position. Examples: 📐 Rectangle Methods Methods are the verbs that describe what a rectangle can do or what can be done to it. They are the actions that allow you to calculate information…
🚗 Car Properties ⚙️ Car Methods 🚗 Car Properties Properties are the nouns that describe a car. They are the characteristics or attributes that define a specific car’s state. Think of them as the data associated with a car object. Examples: ⚙️ Car Methods Methods are the verbs that describe what a car can do….
OOP in Python is a programming paradigm that uses objects and classes to structure code. It’s a way of organizing code into reusable and logical blocks, making programs easier to manage, understand, and scale. Instead of focusing on functions, OOP focuses on data and the behavior associated with that data. Core Concepts of OOP 1….
The regular expression r’;\s*(.*?);’ is used to find and extract text that is located between two semicolons. In summary, this expression finds a semicolon, then non-greedily captures all characters up to the next semicolon. This is an effective way to extract the middle value from a semicolon-separated string. Title 1 to 25 chars The regular…
A negative lookbehind assertion in Python’s re module is a zero-width assertion that checks if a pattern is not present immediately before the current position. It is written as (?<!…). It’s the opposite of a positive lookbehind and allows you to exclude matches based on what precedes them. Similar to the positive lookbehind, the pattern…
A positive lookbehind assertion in Python’s re module is a zero-width assertion that checks if the pattern that precedes it is present, without including that pattern in the overall match. It’s the opposite of a lookahead. It is written as (?<=…). The key constraint for lookbehind assertions in Python is that the pattern inside the…
A positive lookahead assertion in Python’s re module is a zero-width assertion that checks if the pattern that follows it is present, without including that pattern in the overall match. It is written as (?=…). The key is that it’s a “lookahead”—the regex engine looks ahead in the string to see if the pattern inside…
To create a non-capturing group in Python’s re module, you use the syntax (?:…). This groups a part of a regular expression together without creating a backreference for that group. A capturing group (…) saves the matched text. You can then access this captured text using methods like group(1), group(2), etc. A non-capturing group (?:…)…