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Mastering Functional Programming. Functional techniques for sequential and parallel programming with Scala

Język publikacji: angielskim
Mastering Functional Programming. Functional techniques for sequential and parallel programming with Scala Anatolii Kmetiuk - okladka książki

Mastering Functional Programming. Functional techniques for sequential and parallel programming with Scala Anatolii Kmetiuk - okladka książki

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380
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Functional programming is a paradigm specifically designed to deal with the complexity of software development in large projects. It helps developers to keep track of the interdependencies in the code base and changes in its state in runtime. Mastering Functional Programming provides detailed coverage of how to apply the right abstractions to reduce code complexity, so that it is easy to read and understand.

Complete with explanations of essential concepts, practical examples, and self-assessment questions, the book begins by covering the basics such as what lambdas are and how to write declarative code with the help of functions. It then moves on to concepts such as pure functions and type classes, the problems they aim to solve, and how to use them in real-world scenarios. You’ll also explore some of the more advanced patterns in the world of functional programming such as monad transformers and Tagless Final. In the concluding chapters, you’ll be introduced to the actor model, which you can implement in modern functional languages, and delve into parallel programming.

By the end of the book, you will be able to apply the concepts of functional programming and object-oriented programming (OOP)in order to build robust applications.

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O autorze książki

Anatolii Kmetiuk is a Functional Programming and Data Science Freelance Developer. During his programming career, he has worked on Scala projects involving parallel computing, web APIs, SaaS, and data engineering. His areas of expertise include using applications of pure functional programming to build fault-tolerant, reactive systems, as well as parallel computing. Another area of his focus is machine learning and natural language processing.

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