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Clojure Programming Language Cheat Sheet

Clojure Programming Language Cheat Sheet

Back to Programming Languages
Updated 2026-05-16
Next Topic: Concurrency Models and Patterns Across Languages Cheat Sheet

Clojure is a modern functional Lisp dialect that runs on the Java Virtual Machine, JavaScript engines (ClojureScript), and the .NET CLR. Unlike traditional object-oriented languages, Clojure treats immutable, persistent data structures as first-class citizens and provides powerful concurrency primitives that eliminate the need for explicit locking. The language embraces a REPL-driven development workflow where code is iteratively built and tested in a live environment, dramatically shortening the feedback loop. One key mental model: in Clojure, functions compose data transformations rather than mutating stateβ€”this shift from "place-oriented programming" to "value-oriented programming" makes parallel execution safe by default and greatly simplifies reasoning about program behavior.

What This Cheat Sheet Covers

This topic spans 29 focused tables and 259 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Core Data StructuresTable 2: Collection OperationsTable 3: Higher-Order FunctionsTable 4: Sequences and Lazy EvaluationTable 5: DestructuringTable 6: Functions and Anonymous FunctionsTable 7: Macros and MetaprogrammingTable 8: Threading MacrosTable 9: Control FlowTable 10: Recursion and LoopingTable 11: State ManagementTable 12: Concurrency with core.asyncTable 13: Multimethods and ProtocolsTable 14: Java InteroperabilityTable 15: Namespaces and DependenciesTable 16: Reduce and TransducersTable 17: Sequence OperationsTable 18: String OperationsTable 19: Testing with clojure.testTable 20: Error HandlingTable 21: Regular ExpressionsTable 22: Type Checking and PredicatesTable 23: MetadataTable 24: clojure.specTable 25: REPL and DevelopmentTable 26: Compilation and PerformanceTable 27: ZippersTable 28: ClojureScript SpecificsTable 29: Tools and Build

Table 1: Core Data Structures

StructureExampleDescription
Vector
[1 2 3]
(vector 1 2 3)
β€’ Indexed collection with fast random access at any position
β€’ conj adds to end.
List
'(1 2 3)
(list 1 2 3)
β€’ Linked list optimized for sequential access from head
β€’ conj adds to front.
Map
{:a 1 :b 2}
(hash-map :a 1 :b 2)
β€’ Key-value pairs with fast lookup
β€’ keys are typically keywords

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