Intro to Clojure

Brief introduction to Clojure presented at the Budapest Clojure User Group.

Transcript

1. Intro to Clojure Balint Erdi twitter: @baaz http://github.com/balinterdi http://codigoergosum.com => http://balinterdi.com
2. • Elevator pitch • Rationale • 10-minute crash course • REPL playtime
3. Clojure is a dynamic programming language that targets the JVM and is a dialect of Lisp with a strong focus on concurrency.
4. Clojure is a dynamic programming language that targets the JVM and is a dialect of Lisp with a strong focus on concurrency.
5. Rich Hickey http://www.tbray.org/ongoing/When/200x/2008/09/25/-big/R0010774.jpg.html
6. Rich Hickey (RH): Why did I write yet another programming language? Basically because I wanted: • A Lisp • for Functional Programming • symbiotic with an established platform • designed for concurrency • ... and couldn’t find one
7. History • Rich Hickey sends an email to Common Lisp friends in 2007 • After working on it for 2.5 years • Gets picked up, now at 1.4 (Apr 2012) • Targets other platforms, too (Javascript, CLR, Python)
8. Rationale (http://clojure.org/rationale) • Lisp is a good thing • Functional programming is a good thing • Languages and platforms • Object Orientation is overrated • Polymorphism is a good thing • Concurrency and the multi-core future
9. 10-minute crash course
10. Atomic types • Number (3, 3.14, 1e6) • Character (\a, \b, \c) • String (“foo”) • Symbol (‘a, ‘b, ‘c) • Keywords • for very fast equality test (:cool, :bad) • Regex (#”clo[s|j]ure”) • Boolean (true, false) • Only nil and false are falsey
11. Collections • A handful (list, vector, map, set) • Sequential, counted, associative • A large number of functions that operate on them • All of them are immutable • Extensible: deftype, defrecord, reify
12. Vectors • Like an array • Fast random access by index • Sequential, counted and associative (by index) • [:a :b :a :c :c :d] • or (vector :a :b :a :c :c :d)
13. Maps • Hash, dictionary, “associative” array • Fast access by key • Counted and associative, not sequential • {“bob” 35, “alice” 28, “charlie” 19} • (hash-map “bob” 35, “alice” 28, “charlie” 19)
14. Sets • Distinct collection of elements • Fast lookup for containment • Counted, not sequential, not associative • #{“alice” “bob” “charlie”} • (set '("alice" "bob" "charlie"))
15. Lists • First and rest (car and cdr in Lisp) • Counted and sequential, not associative • Fast access to first and rest • ‘(:apple :banana :cherry) • (list :apple :banana :cherry)
16. Functions • First class citizens (no surprise there) • Defined by (defn fn-name [...] body) • Anonymous functions • (fn [...] body) • (map #(+ % 2) collection)
17. Laziness • Only gets evaluated when the result is needed • Makes for elegant, readable programming • Enables working with infinite sequences • Most functions are lazy (map, filter, for, take, drop, partition, etc.) • Use eager functions if you need side effects
18. Prefix notation • Function is always the first argument • Needs some getting used to • Makes variable-length arg functions simple • e.g (+ 1 -7 3 15) • Operator precedence is done away with
19. Homoiconicity • Clojure programs are written in Clojure data structures • Makes macros “easy”
20. Java interop • The whole Java ecosystem at your fingertips • A few succinct forms to reach them (. .. new doto) • Enterprise-ready :)
21. Polymorphism • Multimethods • dispatch on type • Protocols • if you need more flexibility
22. Namespaces • Encapsulation • See packages in other languages
23. Concurrency • Data structures are immutable • Mechanisms • Refs/Transactions (STM) • Atoms (thread isolation) • Agents (independent/asynchronous change)
24. Parallelism • pmap • Reducers (1.5) • e.g ideal for map-reduce tasks
25. REPL session
26. Thank you. Questions? @baaz