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Large IT company, office 404. Interview for the position of Python developer. Participants: department head, senior developer, HR manager. And I’m the candidate. Department head: — We’ve covered everything. Looks out into the hallway. — Oh, Jamie! Would you like to ask the candidate one last question? Jamie works in a neighboring department, does something completely different, and has never programmed in Python but once read something. Jamie sits down at the table. He wasn’t there last time, but today, his presence will decide my fate. Jamie: — What is the maximum list size in Python? I instantly turn pale. While this question touches on the basics of the language, it rarely affects a developer’s day-to-day work. But, to my shame, I find it difficult to give a precise answer. The department head and the senior developer exchange glances. Department head (to the senior developer): — Hmm, let’s look at other candidates. And just like that, after an hour of discussing technically complex issues, one unexpected and impractical question from a random person in the office can dash the hopes of joining the team. In this interview, as in many others, technical expertise was not the deciding factor. Sometimes, a question completely unrelated to the developer’s daily tasks determines everything.

В этой статье я, Евгений Бартенев, техлид и автор курса «Python-разработчик» , возьму и рассмотрю не только те «банановые шкурки», которые периодически разбрасываю сам на собеседованиях, но и те, на которых поскальзывались мои коллеги, некоторые наши студенты, да и я сам.

Привет! Это команда курса «Python-разработчик» . Недавно мы провели рефакторинг — большое обновление программы. Для этого мы изучили фидбек студентов, выявили точки роста и актуализировали набор технологий исходя из запросов рынка. В этом материале мы расскажем, какие изменения внесли, почему рефакторинг никогда не заканчивается и какая работа нам ещё предстоит впереди. Материал может быть полезен тем, кто хочет узнать больше о том, как устроено онлайн-образование в IT, и всем, кто думает об обучении Python в Практикуме.

There are several significant paradigms in programming — approaches that determine how programmers structure and organize their code. For example, procedural programming is the most straightforward approach. Programs are organized as chains of commands or procedures that are executed sequentially. For example, a culinary recipe is similar to a program written in the procedural programming paradigm. A recipe is a set of instructions that must be executed strictly to get the finished dish. There is functional programming. This approach is based on the concept of mathematical functions that take input data and return a result. Suppose you have written a letter and want to translate it into another language, check it for grammar and spelling, and then print it out. In functional programming, each step can be a function, and each function always returns the same result given the same input data. One of the most popular approaches is object-oriented programming, OOP, where code is organized around objects and classes. Many programming uses the object-oriented approach, and beginners should understand in detail what the scary words “polymorphism,” “encapsulation,” and other terms used in this paradigm mean in practice. In this article, I will talk about the key concepts related to OOP. In the example of Python code, I will analyze how the same task can be successfully solved using procedural and object approaches. But let’s start, traditionally, with the basics, and the fictional hockey player Ivan will help me with this.

Algorithms are the fundamental building blocks in programming and have a pivotal role in today’s technology-driven world. They comprise instructions designed to perform tasks efficiently, such as sorting data, searching databases, and making predictions. By automating these tasks, algorithms save time and reduce errors, enabling informed decisions. They form the foundation of many technologies we rely on daily, from social media to e-commerce, and significantly influence industries from finance to healthcare. For instance, almost every graphics editor equips users with valuable and convenient tools. One notable tool is the function that allows filling an area with a specified color. Its operation is straightforward: you select the desired fill color and click on the intended area of the image. Consequently, the selected region changes to the chosen color. This function is driven by a specific algorithm known as the Flood Fill.

Всем привет! Собрали для вас подборку вспомогательных материалов для изучения Python — они помогут разработчикам решать более сложные задачи и чувствовать себя увереннее в работе. Нам помогали авторы курсов по Python-разработке в Яндекс Практикуме: Рома Володин, Женя Бартенев и Миша Николаев.