This document provides an introduction to the Clojure programming language. Clojure is a dynamic, functional programming language for the Java Virtual Machine (JVM). The document discusses Clojure's fundamentals including being dynamic, functional, hosted on the JVM, and supporting concurrency. It also covers Clojure's syntax, data types, Java integration, functional programming features, and concurrency model using immutable persistent data structures and software transactional memory.

1. Clojure
A Dynamic Programming Language for the JVM
An Introduction for Java Programmers
Rich Hickey

2. Introduction
• Who are you?
• Know/use Lisp?
• Java/C#/Scala?
• ML/Haskell?
• Python, Ruby, Groovy?
• Clojure?
• Any multithreaded programming?

3. Agenda
• Fundamentals
• Syntax and evaluation model
• Sequences
• Java Integration
• Concurrency
• Q&A

4. Clojure Fundamentals
• Dynamic
• a new Lisp, not Common Lisp or Scheme
• Functional
• emphasis on immutability
• Hosted on the JVM
• Supporting Concurrency
• Open Source

5. Why use a dynamic
language?
• Flexibility
• Interactivity
• Concision
• Exploration
• Focus on your problem

6. Which dynamic language?
• Many options on the JVM
• allow you to leverage your existing
knowledge and code
• Ports to JVM
• JRuby
• Jython
• Native to JVM
• Groovy
• Clojure

7. Why Clojure?
• Expressive, elegant
• Good performance
• Useful for the same tasks Java is
• Wrapper-free Java access
• Powerful extensibility
• Functional programming and concurrency

8. Clojure is a Lisp
• Dynamic
• Code as data
• Reader
• Small core
• Sequences
• Syntactic abstraction

9. Dynamic development
• REPL - Read-eval-print-loop
• Define functions on the fly
• Load and compile code at runtime
• Introspection
• Interactive environment

10. Atomic Data Types
• Arbitrary precision integers -12345678987654
• Doubles , BigDecimals
1.234 1.234M
• Ratios -22/7
• Strings -“fred”, Characters -a b c
• Symbols - fred ethel , Keywords - :fred :ethel
• Booleans - true false , Null -
nil
• Regex patterns #“a*b”

11. Data Structures
• Lists - singly linked, grow at front
• (1 2 3 4 5), (fred ethel lucy), (list 1 2 3)
• Vectors - indexed access, grow at end
• [1 2 3 4 5], [fred ethel lucy]
• Maps - key/value associations
• {:a 1, :b 2, :c 3}, {1 “ethel” 2 “fred”}
• Sets #{fred ethel lucy}
• Everything Nests

12. Syntax
• You’ve just seen it
• Data structures are the code
• Homoiconicity
• No more text-based syntax
• Actually, syntax is in the interpretation of
data structures

13. Traditional evaluation
Code
Text
characters
Effect
Compiler
bytecode
Executable
JVM
.class/.jar
Run java

14. Clojure Evaluation
Code
Text
characters
Effect
Reader
data structures
evaluator/
bytecode JVM
compiler

15. Interactivity
Code
Text
characters
Effect
Reader
data structures
characters
evaluator/
bytecode JVM
compiler
You

16. Programs writing Programs
Code
Text
characters
Effect
Reader
data structures
characters
evaluator/
bytecode JVM
compiler
data structures
You
Program

17. Syntactic Abstraction
Code
Text
characters
Effect
Reader
data structures
characters
evaluator/
bytecode JVM
compiler
data structures
You
Program data structures
Program
(macro)

18. Expressions
• Everything is an expression
• All data literals represent themselves
• Except:
• Symbols
• looks for binding to value, locally,
then globally
• Lists
• An operation form

19. Operation forms
• (op ...)
• op can be either:
• one of very few special ops
• macro
• expression which yields a function

20. Special ops
• Can have non-normal evaluation of arguments
• (def name value-expr)
• establishes a global variable
• (if test-expr then-expr else-expr)
• conditional, evaluates only one of then/
else
• fn let loop recur do new . throw try
set! quote var

21. Macros
• Supplied with Clojure, and defined by user
• Argument forms are passed as data to the
macro function, which returns a new data
structure as a replacement for the macro call
• (or x y)
(let [or__158 x]
• becomes: (if or__158 or__158 y))
• Many things that are ‘built-in’ to other languages
are just macros in Clojure

22. Functions
• First-class values
(def five 5)
(def sqr (fn [x] (* x x)))
(sqr five)
25
• Maps are functions of their keys
(def m {:fred :ethel :ricky :lucy})
(m :fred)
:ethel

23. Syntax Summary
• Things that would be declarations, control
structures, function calls, operators, are all
just lists with op at front:
Java Clojure
int i = 5; (def i 5)
if(x == 0) (if (zero? x)
return y; y
else z)
return z;
x* y * z; (* x y z)
foo(x, y, z); (foo x y z)
foo.bar(x); (. foo bar x)

24. Sequences
• Abstraction of traditional Lisp lists
• (seq coll)
• if collection is non-empty, return seq
object on it, else nil
• (first seq)
• returns the first element
• (rest seq)
• returns a seq of the rest of the elements,
or nil if no more

25. Sequence Library
(drop 2 [1 2 3 4 5]) -> (3 4 5)
(take 9 (cycle [1 2 3 4]))
-> (1 2 3 4 1 2 3 4 1)
(interleave [:a :b :c :d :e] [1 2 3 4 5])
-> (:a 1 :b 2 :c 3 :d 4 :e 5)
(partition 3 [1 2 3 4 5 6 7 8 9])
-> ((1 2 3) (4 5 6) (7 8 9))
(map vector [:a :b :c :d :e] [1 2 3 4 5])
-> ([:a 1] [:b 2] [:c 3] [:d 4] [:e 5])
(apply str (interpose , "asdf"))
-> "a,s,d,f"
(reduce + (range 100)) -> 4950

26. Java Interop
(. Math PI)
3.141592653589793
(.. System getProperties (get "java.version"))
"1.5.0_13"
(new java.util.Date)
Thu Jun 05 12:37:32 EDT 2008
(doto (JFrame.) (add (JLabel. "Hello World")) pack show)
;expands to:
(let* [G__1837 (JFrame.)]
(do (. G__1837 (add (JLabel. "Hello World")))
(. G__1837 pack)
(. G__1837 show))
G__1837)

27. Java Integration
• Clojure strings are Java Strings, numbers are
Numbers, collections implement Collection,
fns implement Callable and Runnable etc.
• Core abstractions, like seq, are Java interfaces
• Clojure seq library works on Java Iterables,
Strings and arrays.
• Implement and extend Java interfaces and
classes
• New primitive arithmetic support equals
Java’s speed.

28. Swing Example
(import '(javax.swing JFrame JLabel JTextField JButton)
'(java.awt.event ActionListener) '(java.awt GridLayout))
(defn celsius []
(let [frame (JFrame. "Celsius Converter")
temp-text (JTextField.)
celsius-label (JLabel. "Celsius")
convert-button (JButton. "Convert")
fahrenheit-label (JLabel. "Fahrenheit")]
(.addActionListener convert-button
(proxy [ActionListener] []
(actionPerformed [evt]
(let [c (. Double parseDouble (.getText temp-text))]
(.setText fahrenheit-label
(str (+ 32 (* 1.8 c)) " Fahrenheit"))))))
(doto frame
(setLayout (GridLayout. 2 2 3 3))
(add temp-text) (add celsius-label)
(add convert-button) (add fahrenheit-label)
(setSize 300 80) (setVisible true))))
(celsius)

29. Functional Programming
• Immutable data + first-class functions
• Functions produce same output given same
input, and are free of side effects
• Could always be done by discipline/convention
• Pure functional languages tend to strongly static
types (ML, Haskell)
• Not for everyone, or every task
• Dynamic functional languages are rarer
• Clojure, Erlang

30. Why Functional Programming?
• Easier to reason about
• Easier to test
• Essential for concurrency (IMO)
• Java Concurrency in Practice - Goetz
• Additional benefits for purely functional
languages (static analysis, proof, program
transformation), but not Clojure

31. Which Functional Language?
• Fewer choices on the JVM
• CAL
• Haskell-like, strong type system
• Scala
• Type system, but immutability optional
• Clojure
• Dynamic types, immutable data

32. Persistent Data Structures
• Immutable, + old version of the collection is
still available after 'changes'
• Collection maintains its performance
guarantees for most operations
• Therefore new versions are not full copies
• All Clojure data structures persistent
• Hash map and vector both based upon
array mapped hash tries (Bagwell)
• Sorted map is red-black tree

33. Structural Sharing
• Key to efficient ‘copies’ and therefore
persistence
• Everything is final so no chance of
interference
• Thread safe
• Iteration safe

34. Path Copying
HashMap
HashMap
int count 16
int count 15
INode root
INode root

35. Concurrency
• Interleaved/simultaneous execution
• Must avoid seeing/yielding inconsistent data
• The more components there are to the data,
the more difficult to keep consistent
• The more steps in a logical change, the more
difficult to keep consistent
• Opportunities for automatic parallelism
• Emphasis here on coordination

36. State - You’re doing it wrong
• Mutable objects are the new spaghetti code
• Hard to understand, test, reason about
• Concurrency disaster
• Terrible default architecture (Java/C#/
Python/Ruby/Groovy/CLOS...)
• Doing the right thing is very difficult
• Languages matter!

37. Concurrency Methods
• Conventional way:
• Direct references to mutable objects
• Lock and worry (manual/convention)
• Clojure way:
• Indirect references to immutable persistent data
structures
• Concurrency semantics for references
• Automatic/enforced
• No locks!

38. Direct references to
Mutable Objects
?
?
42
?
6
Ensuring a consistent Object is on your head

39. Indirect references to
Immutable Objects
"fred"
"ethel"
42
17
6
Never an inconsistent Object

40. Persistent ‘Edit’
"fred"
"ethel"
42
17
6
"ricky"
"lucy"
42
17
6

41. Atomic Update
"fred"
"ethel"
42
17
6
"ricky"
"lucy"
42
17
6

42. Clojure References
• The only things that mutate are references
themselves, in a controlled way
• 3 types of mutable references
• Vars - Isolate changes within threads
• Refs - Share synchronous coordinated
changes between threads
• Agents - Share asynchronous
independent changes between threads

43. Refs and Transactions
• Software transactional memory system (STM)
• Refs can only be changed within a transaction
• All changes are Atomic and Isolated
• Every change to Refs made within a
transaction occurs or none do
• No transaction sees the effects of any
other transaction while it is running
• Transactions are speculative
• Will be retried automatically if conflict
• Must avoid side-effects!

44. Concurrency Demo
• Ant colony simulation
• World populated with food and ants
• Ants find food, bring home, drop pheromones
• Sense pheromones, food, home
• Ants act independently, on multiple real threads
• Model pheromone evaporation
• Animated GUI
• < 250 lines of Clojure

45. And much more!
• Metadata
• Recursive functional looping
• Destructuring binding in let/fn/loop
• List comprehensions (for)
• Relational set algebra
• Multimethods
• Parallel computation
• Namespaces, zippers, XML ...

46. Thanks for listening!
http://clojure.org