FP & Clojure
- Programming Paradigms
- Imperative vs. FP
- Benefits of FP
- Clojure Overview
- Development Setup
- Keywords and Symbols
- Code as Data
Core Concepts
- Values and Expressions
- Data Types
- First-Class Functions
- Immutable Bindings
- Namespaces
- Namespaced Keywords
- Symbolic Programming
- REPL Development
Immutability & State
- Immutability
- Immutable Data
- Atoms
- Refs
- Agents
- STM
- Multithreaded State
Pure Functions
- Defining Pure Functions
- Advantages of Pure Functions
- Avoid Side Effects
- Referential Transparency
- Impure Functions
- Writing Testable Functions
Higher-Order Functions
- Higher-Order Functions
- map/filter/reduce
- Composition Techniques
- Custom HOFs
- HOF Applications
- Currying and Partial Application
- Recursion vs Iteration
Composition Pipelines
- comp
- Threading Macros
- Data Flow
- Function Chains
- Composition Practices
- Transducer Basics
- Transducer Pipelines
- Transducer Examples
Recursion
- Fundamentals of Recursion
- Recursive Functions FP
- Tail Recursion
- Recursive Data
- Optimizing Recursive Solutions
- Mutual Recursion and Trampolining
Lazy Sequences
- Lazy Evaluation
- Lazy Sequence Creation
- Laziness Benefits
- Core Lazy Sequence Functions
- Working with Infinite Sequences
- Laziness Pitfalls
Data Structures
- Persistent Data
- Collections
- Structural Sharing
- Data Manipulation
- Custom Data Structures
- Advanced Collections
- Data-Oriented Design
Polymorphism
- Protocols
- Defining and Implementing Protocols
- Extend Protocols
- Multimethods and Dispatching
- Polymorphic Design
- Records and Types FP
- Protocol Practices
Error Handling
- Functional Errors
- Exceptions
- spec Validation
- Generative Testing
- Resilient Functions
- Structured Logging
- Error Reporting
- Debugging
Effects & Interop
- Side Effects and Purity
- Isolating Effects
- I/O
- State Changes Functionally
- Effect Practices
- Interoperability with Java Libraries
- Java Exceptions FP
- Configuration
Concurrency
- Concurrency Role
- Concurrency Primitives
- Concurrent State
- core.async Tasks
- Agents Atoms Refs
- STM Explained
- Parallel Processing
- Thread Safety
- Shared Resources
Reactive Programming
- Reactive Concepts
- FRP Implementation
- Streams and Observables
- Reactive Systems
- Backpressure
- core.async
- core.async Use Cases
- UI State
Design Patterns
- Pattern Basics
- Strategy Pattern
- Decorator Pattern
- Factory Pattern
- Observer Pattern
- Memoization
- Domain Modeling
- Currying Techniques
- core.match
Macros
- Macros FP
- Writing Basic Macros
- Macro Expansion and Debugging
- Advanced Macro Techniques
- Creating Domain-Specific Languages
- Macro Practices
- Quote & Unquote
Performance
- Performance Basics
- Profiling
- Recursion Optimization
- Efficient Data Processing Strategies
- Compiler Optimizations and Hints
- Memory and Garbage Collection
- Lazy Performance
- Transients for Performance
Testing
- Testing Benefits
- Unit Tests
- test.check
- Testing Pure Functions Effectively
- Effect Testing
- Integration Testing Strategies
- Test Automation
- Mocks & Stubs
Refactoring
- Imperative Code Patterns
- Refactoring Loops into Recursions
- Eliminating Mutable State Variables
- HOF Refactoring
- Enhancing Readability and Maintainability
- Techniques for Code Transformation
- Java Refactoring
Best Practices
- Readable Code
- Project Organization
- Documentation
- Common Pitfalls
- Community Learning
- Environment Awareness
- Secure Code
- Security Pitfalls
- Observability
Case Studies
- Functional Web App
- Data Pipelines
- DSL Case Study
- Functional GUI
- Functional Design Examples
- Large-Scale Architecture
- Microservices vs Monoliths
- Deployment Automation
- Containers
Libraries
- Library Overview
- Async Data
- Ring & Compojure
- JDBC Libraries
- Liberator APIs
- Reagent and re-frame
- Testing Libraries
- JSON and XML
- ClojureScript
Deployment & CI
- CI/CD Pipelines
- Build Automation
- Cloud Deployment
- Monitoring and Scaling
- DevOps Practices
- Docker and Kubernetes
Advanced Concepts
- Monads and Functors
- Lenses
- Composable Transducers
- Category Theory
- FP at Scale
- Distributed Design
- Architecture Patterns
Next Steps
- Concept Recap
- Community Contribution
- Other FP Languages
- Cross-Platform FP
- FP Mindset

Recursion and Recursive Data Structures

Recursion and Recursive Data Structures helps Java engineers apply functional Clojure through explicit data flow, controlled effects, tests, and JVM-aware trade-offs.

Recursion and Recursive Data Structures frames Recursion as a practical design checkpoint for Java engineers writing Clojure. Use these lessons to connect functional concepts to JVM code you can test, review, operate, and evolve without falling back into hidden mutable state.

Checkpoint	What to verify
Concept boundary	You can explain where Recursion changes the design compared with a class-oriented Java implementation.
Clojure shape	You can identify the values, functions, namespaces, and effect boundaries involved.
Production risk	You can name the main review risk: accidental state, lazy resource retention, unclear interop, macro complexity, weak tests, or poor observability.

In this section

Recursion in Clojure
Explore the fundamentals of recursion in Clojure, understand its components, visualize recursive calls, and learn about common recursive algorithms.
Recursive Functions in Clojure for Scalable Applications
Explore the power of recursion in Clojure, learn to define recursive functions, tackle potential issues, and optimize for efficiency.
Tail Recursion and the `recur` Special Form in Clojure
Explore the power of tail recursion and the `recur` special form in Clojure to optimize recursive calls and build efficient, scalable applications.
Recursive Data Structures in Clojure
Explore the power of recursive data structures in Clojure, including trees and nested maps, and learn how to traverse and manipulate them effectively.
Optimizing Recursive Solutions in Clojure: Techniques for Efficient Functional Programming
Explore techniques for optimizing recursive solutions in Clojure, including memoization, iterative alternatives, and understanding tail call optimization limits. Learn how to profile and enhance performance in functional programming.
Mutual Recursion and Trampolining in Clojure
Explore mutual recursion and trampolining in Clojure to optimize recursive functions and manage stack growth efficiently.

Revised on Saturday, May 23, 2026

Composition Pipelines

Lazy Sequences

Browse Functional Programming with Clojure

Recursion and Recursive Data Structures

In this section