The book will be useful for everyone who has to deal with programming, including those in the humanities.

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Read this book and learn Python programming with the author’s unique methodology – you can do it too!

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All of them had been hooked on programming since high school. At that time, in the early days of the industry, very few schools offered courses in computer science. Therefore, the future gurus had to conquer professional heights on their own, but all of them are distinguished by creative burning and total dedication to the work they love.

You will learn what they think about the future of programming and how they themselves learned to program, how, in their opinion, software should be designed, how the choice of programming language affects productivity, and whether it is possible to facilitate the detection of hard-to-find bugs.

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Anyone can find in it the material that deals with the topic interesting to him, and presented at the level of complexity and rigor the reader requires.

The description of algorithms in natural language is supplemented by pseudocode, which allows anyone with at least basic programming knowledge and experience to implement an algorithm in the programming language they use. Rigorous mathematical analysis and an abundance of theorems are accompanied by plenty of illustrations, elementary reasoning, and simple approximations. The breadth of the material and the degree of rigor of its presentation make this book one of the best books devoted to algorithm development and analysis.

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From the book the reader learns how to use the domain model to give the development of a complex system the desired direction and dynamics. The basic techniques and patterns that form the common language of a group of developers are highlighted. The necessity to refactor not only the code, but also the model at its core is emphasized, which, combined with iterative agile-methodology, leads to a deepening of knowledge about the subject area and increasing the quality of interaction between specialists and programmers. The book’s approach builds on this very foundation, offering models and architectures for systems and organizations of any complexity.

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