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Mastering Clojure

Mastering Clojure

By : Wali
3.5 (2)
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Mastering Clojure

Mastering Clojure

3.5 (2)
By: Wali

Overview of this book

Clojure is a general-purpose language from the Lisp family with an emphasis on functional programming. It has some interesting concepts and features such as immutability, gradual typing, thread-safe concurrency primitives, and macro-based metaprogramming, which makes it a great choice to create modern, performant, and scalable applications. Mastering Clojure gives you an insight into the nitty-gritty details and more advanced features of the Clojure programming language to create more scalable, maintainable, and elegant applications. You’ll start off by learning the details of sequences, concurrency primitives, and macros. Packed with a lot of examples, you’ll get a walkthrough on orchestrating concurrency and parallelism, which will help you understand Clojure reducers, and we’ll walk through composing transducers so you know about functional composition and process transformation inside out. We also explain how reducers and transducers can be used to handle data in a more performant manner. Later on, we describe how Clojure also supports other programming paradigms such as pure functional programming and logic programming. Furthermore, you’ll level up your skills by taking advantage of Clojure's powerful macro system. Parallel, asynchronous, and reactive programming techniques are also described in detail. Lastly, we’ll show you how to test and troubleshoot your code to speed up your development cycles and allow you to deploy the code faster.
Table of Contents (14 chapters)
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12
A. References
13
Index

Using reduce to transform collections

Sequences and functions that operate on sequences preserve the sequential ordering between elements. Lazy sequences avoid the unnecessary realization of elements in a collection until they are required for a computation, but the realization of these values is still performed in a sequential manner. However, this characteristic of sequential ordering may not be desirable for all computations performed over it. For example, it's not possible to map a function over a vector and then lazily realize values in the resulting collection out of order; since the map function converts the supplied collection into a sequence. Also, functions such as map and filter are lazy, but still sequential by nature.

What's wrong with sequences?

One of the limitations of sequences is that they are realized in chunks. Let's study a simple example to illustrate what this means. Consider a unary function, as shown in Example 3.1, which we intend to map over a given...

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