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Clojure Programming

Cover of Clojure Programming by Chas Emerick... Published by O'Reilly Media, Inc.
  1. Clojure Programming
  2. SPECIAL OFFER: Upgrade this ebook with O’Reilly
  3. Preface
    1. Who Is This Book For?
      1. Engaged Java Developers
      2. Ruby, Python, and Other Developers
    2. How to Read This Book
      1. Start with Practical Applications of Clojure
      2. Start from the Ground Up with Clojure’s Foundational Concepts
    3. Who’s “We”?
      1. Chas Emerick
      2. Brian Carper
      3. Christophe Grand
    4. Acknowledgments
      1. And Last, but Certainly Far from Least
    5. Conventions Used in This Book
    6. Using Code Examples
    7. Safari® Books Online
    8. How to Contact Us
  4. 1. Down the Rabbit Hole
    1. Why Clojure?
    2. Obtaining Clojure
    3. The Clojure REPL
    4. No, Parentheses Actually Won’t Make You Go Blind
    5. Expressions, Operators, Syntax, and Precedence
    6. Homoiconicity
    7. The Reader
      1. Scalar Literals
      3. Whitespace and Commas
      4. Collection Literals
      5. Miscellaneous Reader Sugar
    8. Namespaces
    9. Symbol Evaluation
    10. Special Forms
      1. Suppressing Evaluation: quote
      2. Code Blocks: do
      3. Defining Vars: def
      4. Local Bindings: let
      5. Destructuring (let, Part 2)
      6. Creating Functions: fn
      7. Conditionals: if
      8. Looping: loop and recur
      9. Referring to Vars: var
      10. Java Interop: . and new
      11. Exception Handling: try and throw
      12. Specialized Mutation: set!
      13. Primitive Locking: monitor-enter and monitor-exit
    11. Putting It All Together
      1. eval
    12. This Is Just the Beginning
  5. I. Functional Programming and Concurrency
    1. 2. Functional Programming
      1. What Does Functional Programming Mean?
      2. On the Importance of Values
      3. First-Class and Higher-Order Functions
      4. Composition of Function(ality)
      5. Pure Functions
      6. Functional Programming in the Real World
    2. 3. Collections and Data Structures
      1. Abstractions over Implementations
      2. Concise Collection Access
      3. Data Structure Types
      4. Immutability and Persistence
      5. Metadata
      6. Putting Clojure’s Collections to Work
      7. In Summary
    3. 4. Concurrency and Parallelism
      1. Shifting Computation Through Time and Space
      2. Parallelism on the Cheap
      3. State and Identity
      4. Clojure Reference Types
      5. Classifying Concurrent Operations
      6. Atoms
      7. Notifications and Constraints
      8. Refs
      9. Vars
      10. Agents
      11. Using Java’s Concurrency Primitives
      12. Final Thoughts
  6. II. Building Abstractions
    1. 5. Macros
      1. What Is a Macro?
      2. Writing Your First Macro
      3. Debugging Macros
      4. Syntax
      5. When to Use Macros
      6. Hygiene
      7. Common Macro Idioms and Patterns
      8. The Implicit Arguments: &env and &form
      9. In Detail: -> and ->>
      10. Final Thoughts
    2. 6. Datatypes and Protocols
      1. Protocols
      2. Extending to Existing Types
      3. Defining Your Own Types
      4. Implementing Protocols
      5. Protocol Introspection
      6. Protocol Dispatch Edge Cases
      7. Participating in Clojure’s Collection Abstractions
      8. Final Thoughts
    3. 7. Multimethods
      1. Multimethods Basics
      2. Toward Hierarchies
      3. Hierarchies
      4. Making It Really Multiple!
      5. A Few More Things
      6. Final Thoughts
  7. III. Tools, Platform, and Projects
    1. 8. Organizing and Building Clojure Projects
      1. Project Geography
      2. Build
      3. Final Thoughts
    2. 9. Java and JVM Interoperability
      1. The JVM Is Clojure’s Foundation
      2. Using Java Classes, Methods, and Fields
      3. Handy Interop Utilities
      4. Exceptions and Error Handling
      5. Type Hinting for Performance
      6. Arrays
      7. Defining Classes and Implementing Interfaces
      8. Using Clojure from Java
      9. Collaborating Partners
    3. 10. REPL-Oriented Programming
      1. Interactive Development
      2. Tooling
      3. Debugging, Monitoring, and Patching Production in the REPL
      4. Limitations to Redefining Constructs
      5. In Summary
  8. IV. Practicums
    1. 11. Numerics and Mathematics
      1. Clojure Numerics
      2. Clojure Mathematics
      3. Equality and Equivalence
      4. Optimizing Numeric Performance
      5. Visualizing the Mandelbrot Set in Clojure
    2. 12. Design Patterns
      1. Dependency Injection
      2. Strategy Pattern
      3. Chain of Responsibility
      4. Aspect-Oriented Programming
      5. Final Thoughts
    3. 13. Testing
      1. Immutable Values and Pure Functions
      2. clojure.test
      3. Growing an HTML DSL
      4. Relying upon Assertions
    4. 14. Using Relational Databases
      2. Korma
      3. Hibernate
      4. Final Thoughts
    5. 15. Using Nonrelational Databases
      1. Getting Set Up with CouchDB and Clutch
      2. Basic CRUD Operations
      4. _changes: Abusing CouchDB as a Message Queue
      5. À la Carte Message Queues
      6. Final Thoughts
    6. 16. Clojure and the Web
      1. The “Clojure Stack”
      2. The Foundation: Ring
      3. Routing Requests with Compojure
      4. Templating
      5. Final Thoughts
    7. 17. Deploying Clojure Web Applications
      1. Java and Clojure Web Architecture
      2. Running Web Apps Locally
      3. Web Application Deployment
      4. Going Beyond Simple Web Application Deployment
  9. V. Miscellanea
    1. 18. Choosing Clojure Type Definition Forms Wisely
    2. 19. Introducing Clojure into Your Workplace
      1. Just the Facts…
      2. Emphasize Productivity
      3. Emphasize Community
      4. Be Prudent
    3. 20. What’s Next?
      1. (dissoc Clojure 'JVM)
      2. 4Clojure
      3. Overtone
      4. core.logic
      5. Pallet
      6. Avout
      7. Clojure on Heroku
  10. Index
  11. About the Authors
  12. Colophon
  13. SPECIAL OFFER: Upgrade this ebook with O’Reilly
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Expressions, Operators, Syntax, and Precedence

All Clojure code is made up of expressions, each of which evaluates to a single value. This is in contrast to many languages that rely upon valueless statements—such as if, for, and continue—to control program flow imperatively. Clojure’s corollaries to these statements are all expressions that evaluate to a value.

You’ve already seen a few examples of expressions in Clojure:

  • 60

  • [60 80 100 400]

  • (average [60 80 100 400])

  • (+ 1 2)

These expressions all evaluate to a single value. The rules for that evaluation are extraordinarily simple compared to other languages:

  1. Lists (denoted by parentheses) are calls, where the first value in the list is the operator and the rest of the values are parameters. The first element in a list is often referred to as being in function position (as that’s where one provides the function or symbol naming the function to be called). Call expressions evaluate to the value returned by the call.

  2. Symbols (such as average or +) evaluate to the named value in the current scope—which can be a function, a named local like numbers in our average function, a Java class, a macro, or a special form. We’ll learn about macros and special forms in a little bit; for now, just think of them as functions.

  3. All other expressions evaluate to the literal values they describe.


Lists in Lisps are often called s-expressions or sexprs—short for symbolic expressions due to the significance of symbols in identifying the values to be used in calls denoted by such lists. Generally, valid s-expressions that can be successfully evaluated are often referred to as forms: e.g., (if condition then else) is an if form, [60 80 100 400] is a vector form. Not all s-expressions are forms: (1 2 3) is a valid s-expression—a list of three integers—but evaluating it will produce an error because the first value in the list is an integer, which is not callable.

The second and third points are roughly equivalent to most other languages (although Clojure’s literals are more expressive, as we’ll see shortly). However, an examination of how calls work in other languages quickly reveals the complexity of their syntax.

Table 1-1. Comparison of call syntax between Clojure, Java, Python, and Ruby

Clojure expressionJava equivalentPython equivalentRuby equivalent

(not k)


not k

not k or ! k

(inc a)

a++, ++a, a += 1, a + 1[a]

a += 1, a + 1

a += 1

(/ (+ x y) 2)

(x + y) / 2

(x + y) / 2

(x + y) / 2

(instance? java.util.List al)

al instanceof java.util.List

isinstance(al, list)

al.is_a? Array

(if (not a) (inc b) (dec b)) [b]

!a ? b + 1 : b - 1

b + 1 if not a else b - 1

!a ? b + 1 : b - 1

(Math/pow 2 10) [c]

Math.pow(2, 10)

pow(2, 10)

2 ** 10

(.someMethod someObj "foo" (.otherMethod otherObj 0))

someObj.someMethod("foo", otherObj.otherMethod(0))

someObj.someMethod("foo", otherObj.otherMethod(0))

someObj.someMethod("foo", otherObj.otherMethod(0))

[a] In-place increment and decrement operations have no direct corollary in Clojure, because unfettered mutability isn’t available. See Chapter 2, particularly On the Importance of Values for a complete discussion of why this is a good thing.

[b] Remember, even forms that influence control flow in Clojure evaluate to values just like any other expression, including if and when. Here, the value of the if expression will be either (inc b) or (dec b), depending on the value of (not a).

[c] Here’s your first taste of what it looks like to call Java libraries from Clojure. For details, see Chapter 9.

Notice that call syntax is all over the map (we’re picking on Java here the most, but Python and Ruby aren’t so different):

  • Infix operators are available (e.g., a + 1, al instanceof List), but any nontrivial code ends up having to use often-significant numbers of parentheses to override default precedence rules and make evaluation order explicit.

  • Unary operators are seemingly arbitrary in regard to whether they use prefix (e.g., !k and ++a) or postfix position (e.g., a++).

  • Static method calls have prefix position, such as Math.pow(2, 10), but…

  • Instance method calls use an unusual variety of infix positions, where the target of the method (which will be assigned to this within the body of the method being called) is specified first, with the formal parameters to the method coming after the method name.[5]

In contrast, Clojure call expressions follow one simple rule: the first value in a list is the operator, the remainder are parameters to that operator. There are no call expressions that use infix or postfix position, and there are no difficult-to-remember precedence rules. This simplification helps make Clojure’s syntax very easy to learn and internalize, and helps make Clojure code very easy to read.

[5] Python uses the same sort of infix position for its instance methods, but varies from Algol-family brethren by requiring that methods explicitly name their first parameter, usually self.

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