#3896 Application of LISP & Scheme in 2025

#3896 Describe LISP and how it is still useful in 2025

LISP (List Processing) is one of the oldest high-level programming languages, second only to Fortran. Invented by John McCarthy in 1958, it was created for symbolic reasoning and artificial intelligence rather than simple number crunching.

Despite its age, LISP remains useful in 2025 because it is arguably the most adaptable programming language ever made. Its unique "code-as-data" philosophy allows it to rewrite itself to solve new problems, finding homes in cutting-edge fields like quantum computing and neuro-symbolic AI.

Core Concepts: What Makes LISP Special?

At its heart, LISP is defined by homoiconicity (code and data share the same structure).

S-Expressions: Everything in LISP is a list enclosed in parentheses. For example, (+ 1 2) is a list of three elements: the function + and the numbers 1 and 2.
Macros: Because code is just a list, you can write programs that write other programs. While other languages have "macros" (like C++), LISP macros allow you to alter the language's compiler on the fly, creating new syntax or "Domain Specific Languages" (DSLs) tailored exactly to your problem.
The "Repl": LISP pioneered the Read-Eval-Print Loop (REPL), allowing developers to modify a running program without stopping or recompiling it—a feature that remains a gold standard for rapid prototyping.

Why LISP is Still Useful in 2025

While it is no longer the default for general application development, LISP has evolved into a "secret weapon" for solving hard, non-standard engineering problems.

1. Quantum Computing

LISP has found a surprising niche in the quantum revolution.

Rigetti Computing: Their quantum compiler, Quilc, and Quantum Virtual Machine (QVM) are largely written in Common Lisp.
Coalton: In 2025, Coalton is a key tool in this space. It is a statically typed, functional language embedded entirely within Common Lisp. It allows engineers to write type-safe, high-performance code for quantum compilers while keeping the dynamic flexibility of LISP for the rest of the system.

2. The Neuro-Symbolic AI Resurgence

For the last decade, AI was dominated by "Deep Learning" (neural networks)—black boxes that are great at pattern recognition but poor at logic. In 2025, there is a push for Neuro-symbolic AI, which combines neural nets with logical reasoning to make AI "explainable."

LISP’s original strength—symbolic processing—makes it ideal for the "logic" half of this equation.
Researchers use LISP to parse complex logical rules that guide or constrain the output of neural networks, ensuring AI behaves within safety bounds.

3. Industrial Automation (AutoCAD)

AutoLISP remains the standard scripting language for AutoCAD 2025.

Engineers and architects use it to automate repetitive drafting tasks.
In the 2025 release, Autodesk continued to update the language (e.g., adding Unicode support and new function libraries like acet-load-expresstools), proving it is not just "legacy" but actively maintained for daily industrial use.

4. Modern Web & Data (Clojure)

Clojure is the most widely used modern LISP dialect. It runs on the Java Virtual Machine (JVM), giving it access to the entire Java ecosystem while keeping LISP's elegance.

Immutability: Clojure forces data to be immutable (unchangeable) by default, which eliminates huge classes of bugs in multi-threaded cloud applications.
Data Science: Through the "Scicloj" community, Clojure is used for data cleaning and processing pipelines where its ability to treat code as data simplifies complex transformations.

The Three Main Dialects in 2025

Dialect	Primary Use Case in 2025	Philosophy
Common Lisp	Quantum computing, heavy industry, scientific simulation.	"The Kitchen Sink": Multi-paradigm, powerful object system (CLOS), compiles to fast native code.
Clojure	Web backends, distributed systems, big data processing.	"The Modernist": Runs on JVM/JavaScript, emphasizes functional programming and immutable data.
Scheme	Computer science education, research, embedded scripting (e.g., GIMP).	"The Minimalist": Extremely small core, clean mathematical elegance.

Next Step

Would you like me to show you a simple example of a LISP Macro to demonstrate how it can create new language features that don't exist in the base language?

Why You Should Learn Lisp In 2025

This video provides a recent perspective on why LISP's unique features, such as its powerful macro system and "code as data" philosophy, remain relevant and advantageous for programmers today.

Compare Scheme to LISP

In the Lisp family, the two giants are Scheme and Common Lisp (often referred to simply as "Lisp").

If Common Lisp is a factory filled with heavy machinery, Scheme is a pristine mathematical theorem.

Here is the comparison of how they differ in philosophy, mechanics, and usage in 2025.

1. The Philosophical Divide

Feature	Scheme	Common Lisp
Philosophy	Minimalism. Created to be small, clean, and mathematically perfect. The goal is to define as few core rules as possible and derive everything else from them.	Maximalism. Created to unify fragmented dialects into an industrial-strength standard. It includes everything a developer might need (the "kitchen sink" approach).
Nickname	"The Jewel" (Small and flawless).	"The Mudball" (Big, messy, but it sticks together).
Standard Size	~50 pages (R5RS).	~1100 pages (ANSI Standard).

2. Technical Differences

Lisp-1 vs. Lisp-2 (The Namespace Debate)

This is the most famous technical distinction.

Scheme is a "Lisp-1": It shares one namespace for variables and functions.¹ If you define a variable named list, you overwrite the list function. This makes "functional programming" (passing functions as arguments) extremely natural.
;; Scheme (define (apply-twice f x) (f (f x))) ;; simpler syntax
Common Lisp is a "Lisp-2": It has two namespaces—one for variables and one for functions.² You can have a variable named list and the function list existing simultaneously without conflict. However, you must explicitly tell Lisp when you want to use a function as a value using #' (sharp-quote) and funcall.
;; Common Lisp (defun apply-twice (f x) (funcall f (funcall f x))) ;; explicit calling required

Macros: Hygiene vs. Power

Scheme (Hygienic Macros):³ Scheme’s macros (using syntax-rules) are "hygienic" by default.⁴ The compiler guarantees that variables inside your macro won't accidentally clash with variables in the code where the macro is used. It is safer but sometimes considered more rigid.
Common Lisp (Defmacro): CL uses "unhygienic" text-substitution macros.⁵ They are incredibly powerful and allow you to rewrite the language entirely, but you must manually manage variable names (using gensym) to prevent bugs.

Recursion vs. Iteration

Scheme: Mandates Tail Call Optimization (TCO).⁶ The standard requires that compilers optimize recursion. In Scheme, you rarely write loops; you write recursive functions that run as efficiently as loops.⁷
Common Lisp: Does not mandate TCO (though many implementations have it). Instead, CL provides a powerful LOOP macro—a mini-language within Lisp for complex iteration.⁸

3. The State of the Ecosystem in 2025

Scheme in 2025

Scheme is still the dominant choice for Computer Science education and language research.

Racket: While technically a descendant of Scheme, Racket has grown into its own massive ecosystem. It is the "batteries-included" version of Scheme, widely used for creating new programming languages (Language Oriented Programming).
Embedded Scripting: Scheme (via Guile) remains the extension language for the GNU project (e.g., GIMP, Make).
WebAssembly: Scheme’s small footprint makes it popular for compiling to WASM for browser-based apps.

Common Lisp in 2025

Common Lisp remains the choice for heavy industry and high-performance systems.

Performance: The SBCL (Steel Bank Common Lisp) compiler produces machine code that rivals C++ in speed.
Quantum Computing: As noted previously, the quantum ecosystem (like Rigetti’s forest) relies heavily on Common Lisp.
Coalton: A major 2020s innovation, Coalton is a statically typed, Haskell-like language embedded inside Common Lisp, bringing modern type safety to the industrial stability of CL.

Summary: Which should you choose?

Choose Scheme (or Racket) if you want to learn the "Tao of Lisp," are interested in language design, or prefer functional purity and recursion over iteration.
Choose Common Lisp if you want to build a high-performance standalone binary, need access to massive mature libraries (via Quicklisp), or prefer a pragmatic, multi-paradigm approach (OOP, functional, and procedural mixed together).⁹

#3896 Application of LISP & Scheme in 2025

Here is a complete, runnable Scheme script to calculate and display the first 25 prime numbers.

I have included a helper function prime? to check for primality and a recursive loop in first-n-primes to collect the results.

;;; -------------------------------------------------------------------------

;;; Scheme Script: First 25 Prime Numbers

;;; -------------------------------------------------------------------------

;;; This script defines a primality test and a generator function to find

;;; the first N prime numbers, then prints the result to the console.

;; Predicate: Returns #t if n is prime, #f otherwise.

;; We handle small base cases and then check odd divisors up to sqrt(n).

(define (prime? n)

(cond

((<= n 1) #f) ; 1 and below are not prime

((= n 2) #t) ; 2 is the only even prime

((even? n) #f) ; all other evens are not prime

(else

(let loop ((i 3))

(cond

;; If i*i > n, we've checked all factors up to sqrt(n)

((> (* i i) n) #t)

;; If n is divisible by i, it's not prime

((zero? (remainder n i)) #f)

;; Check the next odd number

(else (loop (+ i 2))))))))

;; Generator: Returns a list of the first n prime numbers.

;; It uses a tail-recursive loop to accumulate found primes.

(define (first-n-primes n)

(let loop ((count 0) ; How many primes we've found so far

(current 2) ; The current number we are checking

(primes '())) ; The list of primes found (in reverse order)

(if (= count n)

(reverse primes) ; Return the list in correct order

(if (prime? current)

;; If prime, increment count and add to list

(loop (+ count 1) (+ current 1) (cons current primes))

;; If not prime, just move to next number

(loop count (+ current 1) primes)))))

;; Main entry point

(define (main)

(let ((target 25))

(display "Calculating the first ")

(display target)

(display " prime numbers...")

(newline)

(let ((result (first-n-primes target)))

(display "Result: ")

(display result)

(newline))))

;; Run the main function

(main)

Here is a complete, runnable Scheme script to calculate and display the first 25 prime numbers.

I have included a helper function prime? to check for primality and a recursive loop in first-n-primes to collect the results.

Prime Number Calculator

How it works:

prime?: This function determines if a number is prime. It optimizes the check by immediately discarding even numbers (except 2) and only checking odd divisors up to the square root of the number.
first-n-primes: This uses a recursive let loop (a common Scheme idiom) to iterate through integers starting from 2. It accumulates numbers that pass the prime? check until it reaches the target count (25).
main: Sets the target to 25, runs the calculation, and prints the resulting list to the standard output.

I see a loop. I thought Scheme rarely used loops

You are absolutely right to be suspicious! In most languages (like C, Python, or Java), a "loop" usually implies a specific imperative structure (like while or for) that mutates state.

However, in Scheme, what you are seeing is not an imperative loop. The (let loop ...) syntax is actually recursion in disguise.

Here is the breakdown of why this is considered "functional" rather than "imperative":

1. It's actually a "Named Let"

The construct (let loop ...) is a special Scheme feature called a Named Let. It is syntactic sugar that does two things at once:

It creates a local function named loop.
It calls that function immediately.

It is arguably the most common idiom in Scheme for iteration.

2. It's Recursion, not Iteration

When you see (loop ...) called inside the body, it is calling the function named loop.

In a language like C, a loop jumps back to the top of a block of code.
In Scheme, this "loop" is actually just a function calling itself with new arguments.

3. Proof: The "Long Way"

To prove this isn't a special "looping" keyword, we can rewrite the first-n-primes function using standard function definition. The code below does the exact same thing as the let loop in your file:

;; This helps visualize what 'let loop' is actually doing behind the scenes

(define (collect-primes-helper count current primes target-n)

(if (= count target-n)

(reverse primes)

(if (prime? current)

;; RECURSION: Call self with updated numbers

(collect-primes-helper (+ count 1) (+ current 1) (cons current primes) target-n)

;; RECURSION: Call self with updated numbers

(collect-primes-helper count (+ current 1) primes target-n))))

(define (first-n-primes n)

;; Start the recursion

(collect-primes-helper 0 2 '() n))

Why use `let loop`?

As you can see above, defining a helper function (collect-primes-helper) explicitly is verbose and clutters the global namespace. let loop allows you to define that recursive helper function inside the main function, keeping your code clean.

Why doesn't it crash? (Tail Call Optimization)

In many languages (like Java or Python), if a function calls itself 1,000,000 times, you get a "Stack Overflow" error because the computer memory fills up keeping track of every call.

Scheme is different. It guarantees Tail Call Optimization (TCO). If the recursive call is the last thing the function does (the "tail position"), Scheme simply jumps back to the top of the function and updates the variables, exactly like a C while loop would. This means you can "recurse" infinitely without using any extra memory.

From <https://gemini.google.com/app/> Google Gemini 3.0 Pro (Thinking)

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