Michael Fogus - The Joy of Clojure

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ISBN 9781617291418

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To Timothy Harta hacker of the highest order. Rest in peace.

The authors blaze through many of the classics of both functional programming and industry programming in a whirlwind tour of Clojure that feels at times more like a class-five tropical storm. Youll learn fast!

From the Foreword by Steve Yegge, Google

The Joy of Clojure wants to make you a better programmer, not just a better Clojure programmer. I would absolutely recommend this to anyone I know who had an interest in Clojure and/or functional programming.

Rob Friesel Dealer.com Websystems

Teaches the Tao of Clojure and, oh boy, its such a joy! Simply unputdownable!

Baishampayan Ghose (BG) Cofounder & CTO, Qotd, Inc.

The Clojure community, present and future, will be grateful for this book.

Andrew Oswald Chariot Solutions

Discover the why not just the how of Clojure

Federico Tomassetti Politecnico di Torino

The Joy of Clojure really lives up to its name! Every page oozes with the excitement @fogus and @chrishouser have for the language and its community. This is exactly what makes this book such an enjoyable read, its hard not to get drawn into the beauty of Clojure when you have two convinced developers sharing their passion with you.

Amazon Reader M.K.

What Irma Rombauer did for cooking, Fogus and Houser have done for Clojure! By going beyond the basics, this book equips the reader to think like a native speaker in Clojure-land.

Phil Hagelberg Creator of the Leiningen build tool, Heroku

A fun exploration of functional programming and Lisp.

Matt Revelle Cofounder, Woven, Inc.

In this second edition of The Joy of Clojure, Michael Fogus and Chris Houser present a cornucopia of programming concepts, including many of the topics from the programming languages course we taught together for many years. Fundamental programming languages concepts close to our hearts that appear in this book include higher-order functions, lexical scope, closures, tail recursion, mutual recursion, continuations and continuation-passing style, trampolining, lazy sequences, macros, and relational programming. Most important, Fogus and Houser teach you how to define your own little languages.

Alan J. Perlis, brilliant language designer and inaugural Turing Award recipient, famously wrote, There will always be things we wish to say in our programs that in all known languages can only be said poorly. No existing programming language can express precisely those concepts and abstractions needed for your specific application. The only person who can design a language to solve your exact problem is you.

Creating a little language to solve a specific problem is the most effective technique yet devised for reducing complexity in software.[] Two well-known examples are database query languages and the formula languages of spreadsheet applications. These examples are as notable for what they exclude as for what they include, illustrating another of Perliss epigrams: A programming language is low level when its programs require attention to the irrelevant. By only including features relevant to the problem, a well-designed little language is inherently high level.

Jon Bentley popularized the concept of little languages in his article Programming Pearls: Little Languages, Communications of the ACM 29, no. 8 (1986):711-21.

Database query languages illustrate another fundamental aspect of little languages: writing a complete application requires addressing problems in more than one domain. An application that performs database queries will also make use of other languages. A single little language cant address the exact needs of a nontrivial application any more than can a single general-purpose language.

For this reason, little languages work best in concert. The ideal technique for writing a complex program is to slice it into multiple problem-specific pieces and then define a language for each problem slice. If we slice the program vertically, the result is a tower of languages, layered atop one another. Regardless of how we slice the overall problem, we can use the right language, and the right paradigm, for each subproblem.

As with recursion, the art of defining little languages encouragesand rewardswishful thinking. You might think to yourself, If only I had a language for expressing the rules for legal passwords for my login system. A more involved examplea story, reallystarted several years ago, when we thought to ourselves, If only we had the right relational language, we could write a Lisp interpreter that runs backward.[] What does this mean?

We use Lisp to refer to any member of a large family of languages that includes Scheme, Racket, Common Lisp, Dylan, and, of course, Clojure. To us, a Lisp must be homoiconic, have first-class functions, and have some form of macros. (All three concepts are described in this book.)

An interpreter can be thought of as a function that maps an input expression, such as (+ 5 1), onto a valuein this case, 6. We wanted to write an interpreter in the style of a relational database, in which either the expression being interpreted or the value of that expression, or both, can be treated as unknown variables. We can run the interpreter forward using the query (interpret '(+ 5 1) x), which associates the query variable x with the value 6. Better yet, we can run the interpreter