Clojure is a dynamic, functional programming language that runs on the Java Virtual Machine (JVM). It emphasizes immutability and provides robust concurrency primitives.
Clojure Anti-Patterns Overview
Clojure, despite being a well-designed functional language, has several common anti-patterns that can lead to performance issues, maintainability problems, and bugs. Here are the most important anti-patterns to avoid when writing Clojure code.
Using Mutable State Unnecessarily
Avoid using mutable state (atoms, refs, agents) when pure functions would suffice. Embrace Clojure’s functional programming paradigm and use immutable data structures by default.
Not Using Threading Macros
Use threading macros (->
, ->>
, as->
, etc.) to make code more readable by avoiding deeply nested function calls. Threading macros make the data flow explicit and easier to follow.
Using Java Collections Instead of Clojure Ones
Prefer Clojure’s persistent collections over Java’s mutable collections. Clojure’s collections are immutable, thread-safe, and work seamlessly with the rest of the language.
Using recur Instead of Higher-Order Functions
Prefer higher-order functions like map
, filter
, reduce
, etc., over manual recursion with loop
/recur
. Higher-order functions are more declarative and often more readable.
Not Using Destructuring
Use destructuring to extract values from data structures. It makes code more concise and expressive, especially when working with nested data structures.
Using Reflection
Avoid reflection by using type hints when working with Java interop or performance-critical code. Reflection is slow and can cause unexpected performance issues.
Not Using Transducers for Composition
Use transducers when composing multiple transformations on a collection. Transducers avoid creating intermediate collections and can be more efficient.
Using Dynamic Vars Unnecessarily
Avoid using dynamic vars (^:dynamic
) for configuration or state that could be passed explicitly. Dynamic vars make code harder to reason about and test.
Not Using Proper Exception Handling
Use proper exception handling with try
/catch
/finally
for operations that might fail, especially I/O operations. Consider using libraries like ex-info
and ex-data
for structured error handling.
Not Using Specs for Validation
Use clojure.spec
for data validation and documentation. Specs provide a declarative way to define the shape and constraints of your data.
Using Keywords as Functions Excessively
While using keywords as functions (e.g., :name user
) is idiomatic in Clojure, excessive use can make code less readable. Consider using destructuring for clarity.
Not Using Proper Namespaces
Organize your code into logical namespaces with clear responsibilities. Follow the principle of cohesion: each namespace should have a single, well-defined purpose.
Using nil Punning
Be careful with nil punning (relying on nil to propagate through a chain of operations). While it can be convenient, it can also hide bugs and make code harder to debug.
Not Using Proper Testing
Write proper tests using clojure.test
or other testing libraries. Tests help ensure your code works as expected and catch regressions.
Not Using Proper Documentation
Document your functions and namespaces with docstrings. Include descriptions of arguments, return values, and usage examples.
Not Using Component Lifecycle Management
Use a component lifecycle management library like Component, Mount, or Integrant for managing stateful resources. These libraries help with initialization, shutdown, and dependency injection.
Not Using Proper Error Messages
Provide descriptive error messages and use ex-info
to include structured data with exceptions. This makes debugging easier and allows for programmatic handling of specific error conditions.
Using def Inside Functions
Avoid using def
inside functions to create or modify global variables. This leads to side effects and makes code harder to reason about and test.
Not Using Proper Dependency Management
Use dependency injection or a component system to manage dependencies between parts of your application. This makes your code more modular, testable, and flexible.
Not Using Proper Concurrency Primitives
Use the appropriate concurrency primitives for your use case. Atoms are good for independent values, refs for coordinated changes, agents for asynchronous updates, and Java’s concurrency utilities for more complex coordination.
Not Using Proper Performance Optimization
Avoid premature optimization. Start with clear, simple code, then profile to identify actual bottlenecks. Use tools like criterium
for benchmarking and YourKit or VisualVM for profiling.