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Ask the right questions to secure the right Clojure talent among an increasingly shrinking pool of talent.
Clojure is a dynamic, general-purpose programming language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. It was created by Rich Hickey and first released in 2007, with its development funded by the company Cognitect. Clojure is a dialect of the Lisp programming language and runs on the Java Virtual Machine, JavaScript engines, and Common Language Runtime. It emphasizes functional programming, offering immutable data structures and encouraging developers to write pure functions. The language's design allows it to handle concurrent processing, making it a popular choice for multi-core processing tasks.
The next 20 minutes of the interview should attempt to focus more specifically on the development questions used, and the level of depth and skill the engineer possesses.
Macros in Clojure are a way to define reusable chunks of code. They are functions that are executed at compile time and can generate and include code in the program.
In Clojure, exceptions can be handled using the 'try'/'catch'/'finally' construct, similar to Java. The 'try' block contains the code that might throw an exception, the 'catch' block contains the code to handle the exception, and the 'finally' block contains the code that will be executed regardless of whether an exception was thrown or not.
In Clojure, vectors and lists are both sequences, but they have different performance characteristics. Vectors have constant-time access and update for elements at any position, while lists have constant-time access and update only for the first element.
The core data structures in Clojure are lists, vectors, maps, and sets.
You can define a function in Clojure using the 'defn' keyword. For example: (defn add [a b] (+ a b)). This defines a function named 'add' that takes two parameters, a and b, and returns their sum.
Testing is an important part of software development. The candidate should be familiar with Clojure's testing libraries and practices.
Clojure runs on the JVM and has excellent Java interop capabilities. The candidate should be comfortable working with Java libraries and classes in Clojure.
Macros are a powerful feature of Clojure that allow for code generation and metaprogramming. The candidate should understand how to use them.
One of Clojure's strengths is its support for concurrent and parallel programming, so the candidate should be able to use features like atoms, futures, and promises.
Clojure has a unique syntax and data structures like vectors, lists, sets, and maps. The candidate should be able to work with these effectively.
Clojure is a functional programming language, so the candidate should be comfortable with concepts like immutability, first-class functions, and higher-order functions.
The next 20 minutes of the interview should attempt to focus more specifically on the development questions used, and the level of depth and skill the engineer possesses.
Clojure provides several constructs for handling concurrency, including atoms, agents, refs, and vars. These constructs provide a way to manage mutable state in a safe and consistent way in a concurrent program.
'apply' takes a function and a sequence of arguments, and calls the function with those arguments. 'map' takes a function and one or more sequences, and applies the function to each element of the sequences, returning a sequence of results.
Multimethods in Clojure provide a way to define a function that can have different implementations depending on the type or value of its arguments. This is done using the 'defmulti' and 'defmethod' forms.
In Clojure, you can implement a loop using the 'loop'/'recur' construct. The 'loop' expression initializes the loop variables, and the 'recur' expression updates the loop variables and jumps back to the 'loop' expression.
'def' is used to define a global variable, while 'let' is used to define local variables. Variables defined with 'let' are only accessible within the 'let' block, while variables defined with 'def' are accessible throughout the program.
A skilled Clojure engineer should demonstrate strong problem-solving skills, a deep understanding of functional programming principles and extensive experience with Clojure's ecosystem and libraries. Red flags include an inability to explain complex concepts or code, lack of real-world project experience, or over-reliance on other programming paradigms.
(defn hello-world [] (println "Hello, World!"))(defn add-numbers [a b] (+ a b)) (add-numbers 5 10)(defn filter-even [coll] (filter even? coll))(defn run-in-thread [f] (Thread. f))(defrecord Person [name age])(defn factorial [n] (if (<= n 1) 1 (* n (factorial (- n 1))))) (factorial 5)The final few interview questions for a Clojure candidate should typically focus on a combination of technical skills, personal goals, growth potential, team dynamics, and company culture.
'cons' takes an element and a sequence, and returns a new sequence with the element prepended. 'lazy-seq' takes a body of code and returns a sequence that is realized lazily, i.e., the elements are computed only when needed.
Protocols in Clojure provide a way to define polymorphic functions. A protocol is a set of function signatures, and types can be extended to implement these functions. This allows you to write code that can operate on different types in a generic way.
In Clojure, you can implement memoization using the 'memoize' function. This function takes a function as an argument and returns a new function that caches the results of the original function for each set of arguments.
'reduce' takes a function and a sequence, and applies the function to the elements of the sequence in a pairwise way, accumulating a single result. 'fold' is similar, but it can split the sequence into chunks and process them in parallel, which can be more efficient for large sequences.
Transducers in Clojure are a way to define and compose transformations on data. A transducer is a function that takes a reducing function as an argument and returns a new reducing function that incorporates the transformation.
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