Programming becomes interesting when you can work with sets of elements.
There are just a few examples where they appear:
- Paginated data output on the website
- Calculate the order total based on the price of each item
- Displaying a list of friends, messages, movies, and the like
- Processing a set of DOM nodes (HTML, frontend development)
Every list we encounter in a real or virtual world is, from a programmer's point of view, a collection of items. Python uses lists, a data structure that allows you to work with the set as a single entity:
// Defining a friends list
friends = ['petya', 'vasya', 'ivan']
Unlike primitive data types, lists can change in Python, both the contents and the size of the list itself. It affects how we handle them, adding more power but also responsibility.
With lists, we can solve the problem in many different ways. Only some will be good, while the rest will be inefficient and difficult to debug and analyze.
It is why we devote an entire course to lists, not just a few lessons.
This course covers many cases where programmers commonly use lists. The knowledge gained in this course will be the foundation for all future learning.
The main topics of this course are
- Operations on lists
- Working with lists in loops
- Working with nested lists using nested loops
- Sorting lists
- Working with strings through lists
In addition to lists, we'll also cover algorithms and data structures in this course. We will discuss the concept of algorithmic complexity and learn how to implement some basic algorithms, which will help in job interviews. Knowledge of these topics is essential to writing effective code.
How to prepare for this course
Before learning about lists, you need to master the basic syntax of the programming language:
For the correct sequence of courses, see the Python Developer.
Are there any more questions? Ask them in the Discussion section.
The Hexlet support team or other students will answer you.
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