The shortest introduction to Lisp

Lisp isn’t as inaccessible, alien, or irrelevant as you might believe

Four pedestrians waiting for a green light

Lisp is one of the oldest programming languages in computing. John McCarthy and his team implemented the first Lisp interpreter in 1960. They wanted a programming language for AI research. Since then, he and many others discovered amazing things about how Lisp can make computers do surprising, interesting things.

Most people acknowledge Lisp’s influence without knowing what it is exactly. Many are turned off by Lisp’s weirdness. It doesn’t look like most other programming languages. And yet Lisp continues to influence programming languages today. It’s not as inaccessible, alien, or irrelevant as you might believe.


Lisp is an acronym for LISt Processor. A list is a sequence of items. To specify a list, we start with an opening parenthesis, continue with the things in the list, and end with a closing parenthesis. For example, here’s a list of ingredients for a salad:

(lettuce tomato oil vinegar)

We can use extra spaces to clarify what we type but Lisp doesn’t care about excessive white space between list items, as long as there is some. And there’s no need to put white space around parentheses. Here are some lists that look different to us but mean the same to Lisp:

(lettuce  tomato   oil         vinegar     )


A list may itself also contain lists. Here’s a list that is different from our previous list:

((lettuce tomato) (oil vinegar))

While it contains the same items, they are arranged into two sub-lists. The first for the vegetables (lettuce tomato), the second for the dressing (oil vinegar).

Here’s an empty list:



The empty list comes up so much that Lisp has a symbol for it: nil. A symbol is just a name that represents something. What the symbol represents depends on you, the programmer. In our list above, lettuce, tomato, oil, and vinegar are symbols for salad ingredients. We sometimes refer to symbols as atoms.

Unlike lists, atoms are not composed of parts. To Lisp, a symbol is only the same as the same symbol. But a symbol is not the same as its parts. For example oil and oil are the same symbol. But oil and o i l are not. In fact, they’re 4 different symbols, oil, o, i, and l.

Functions manipulate S-expressions

In Lisp, lists and atoms are called S-expressions, where the S means “symbolic”. We also use just “expression” to mean the same thing. The Processor part of LISt Processor means that we program a Lisp interpreter to manipulate S-expressions. We manipulate them with functions that accept S-expression arguments.

Here’s a cool thing about Lisp: functions are also written as S-expressions. In other words, data and programs have the same form.

To see how functions work, let’s take a closer look at nil and the empty list. To verify that they are the same, we enter this expression in Lisp:

(eq nil () )

The first item in the list of our expression is eq, which is a symbol that represents a function. A function tells Lisp what needs to be done: we want to determine equality. The remaining items in the list, nil and (), specify the data that we want the eq function to process.

Lisp responds with:


The t symobl means that the result of this expression is true: nil and () are indeed equal. Using the t symbol to represent true is a Lisp convention, while nil is the conventional value for false.

In Lisp, we say function application to mean applying a function to arguments. In our example, we apply eq to two arguments. The function compares them for equality, then returns a t for true or nil for false.

Before Lisp applies a function to its arguments, it first evaluates them. For example, let’s look at a more complicated expression:

 (eq nil ())
 (eq () nil))

In this expression, we give the first eq these arguments: (eq nil ()) and (eq () nil).

We can’t determine how to compute the value of the first eq application until we know the values of its arguments. Behind the scenes, that’s what Lisp does. If we could watch the internal computation of our S-expression, we would see Lisp first compute then substitute the values of the arguments.

Inside Lisp, this substitution renders our expression from this:

 (eq nil ())
 (eq () nil))

To this:

 (eq () nil))

Then this:


And finally:


Lisp evaluates expressions recursively by computing the values of the deepest argument expressions before computing arguments that are higher up.

Built-in functions

Lisp has some useful built-in functions. One of these functions is quote. It’s pretty important. It takes a single argument and returns it unevaluated. It might seem funny that a so-called “important” function does nothing. This importance comes from its necessity.

For example, when we type our salad list into Lisp:

(lettuce tomato oil vinegar)

Lisp returns an error about lettuce not being a function.

To make it clear that our salad list is a list and not an applicaton of the lettuce function, we enter:

(quote (lettuce tomato oil vinegar))

Lisp responds with:

(lettuce tomato oil vinegar)

Lisp wouldn’t be useful if we couldn’t create our own functions. To describe a function, we use a lambda expression. A lambda function takes a list of parameters then a sequence of S-expressions to evaluate. Here’s an example of a lambda function that accepts a single parameter to compute its equality with nil:

(lambda (x) (eq nil x))

Each parameter in the parameter list is a symbol that represents an argument at application time. The sequence of S-expressions in the lambda may refer to these parameters. In fact, it’s good practice to make sure that the S-expressions in a lambda refer only to the lambda parameters.

Lisp treats the last S-expression in the lambda specially. Its value is the value that the lambda returns when Lisp applies it.

In our lambda above, (x) is the list of parameters. In this case, we have a single parameter, x. The S-expression (eq nil x) is the only expression in our lambda. It’s also the last expression, so the lambda returns the value of this expression when we apply the lambda.

When you enter a lambda by itself:

(lambda (x) (eq nil x))

Lisp returns the lambda, unapplied:

(lambda (x) (eq nil x))

If we want to apply our lambda to an argument, we need to use the same form as a function application: (function argument ...)

We just need to replace function with a lambda expression.

For example, if we enter:

((lambda (x) (eq nil x))
 (quote (lettuce tomato oil vinegar)))

Lisp applies our lambda like a regular function application by following these steps:

  1. Evaluate the expressions of the arguments.
  2. Bind each evaluated argument, in the order it appears in the application, to each of the parameters in the order that they appear in lambda parameter list.
  3. Evaluate each expression in the lambda. When an expression refers to a parameter, Lisp evaluates it by substituting its bound value from step 2.
  4. Return the value of the last expression in the lambda and unbind its parameters.

In step 1 above, Lisp first evaluates the lone argument:

(quote (lettuce tomato oil vinegar))

Which gives:

(lettuce tomato oil vinegar)

In step 2, Lisp binds this evaluated argument to the parameter, x.

For step 3, Lisp evaluates the lambda body, replacing occurrences of x with the value it is bound to. This:

(eq nil x)


(eq nil (lettuce tomato oil vinegar))

Our argument, (lettuce tomato oil vinegar), is not the empty list, so eq returns nil. Since this is the only and last expression in the lambda, the lambda application returns nil. Returning nil for a non-nil argument is ironic until you remember that nil means false in this case.

The parameter bindings in a lambda application last only during the application of the lambda. In step 4, Lisp unbinds the lambda’s parameters. The x argument has no value.

So entering this expression after applying our lambda we can try to see what x is bound to:


Is isn’t bound, we get an error about an unbound variable.

Outside of a lambda, we can bind a symbol to a value so that when you enter the symbol, Lisp returns the value. For example this expression binds name to Valerie:

(define name (quote Valerie))

So entering this expression:


Evaluates to what you would expect:


You can also change an existing binding:

(define name (quote Isabelle))

Bindings in a lambda temporarily override outside bindings. For example:

(define name (quote James))
((lambda (name) name) (quote Rose))



Inside the lambda application, name is bound to Rose. When the lambda application returns, the previous binding to name is restored, so that entering this expression:


Returns this:


Of course, you can also bind a lambda to a symbol, which makes the lambda easier to use if you intend to refer to it frequently. For example, comparison with nil is something we see enough that we define a handy function for it:

(define null (lambda (x) (eq x nil)))

Now comparison to nil is more convenient:

(null (quote Gus))



Notice that the define function plays by different rules than a normal function. Instead of evaluating its first argument, define takes it literally, as if it were quoted. Therefore by definition (ahem), define isn’t a true function. In Lisp, we call this a special form. If you paid enough attention earlier, you noticed that quote and lambda are also special forms. Lambda doesn’t evaluate its list of parameters. And Lisp delays the evaluation of a lambda's expressions until it applies the lambda.

Another special form is cond, which is short for “conditional”. It takes a list of clauses:


Each clause is a list of 2 expressions: (test result).

If the test expression is true, then cond returns the value of the corresponding result expression and stops processing subsequent clauses. If the test is false, cond proceeds to the next clause. It continues doing so until it finds a test that returns true or there are no more expressions.

For example, to evaluate this expression:

 ((eq name (quote Valerie))  (quote funny))
 ((eq name (quote James))    (quote silly))
 (t                          (quote goodbye)))

Lisp starts with the first clause:

((eq name (quote Valerie))  (quote funny))

Which has this test expression:

(eq name (quote Valerie))

Given our most recent binding for name, this test evaluates to false. Lisp skips to the next clause:

((eq name (quote James)) (quote silly))

The test expression evaluates to true. So Lisp evaluates the second expression in this clause, which returns:


Which becomes the value of our cond expression. Lisp ignores subsequent clauses, so this clause doesn’t get evaluated:

(t (quote goodbye))

As a matter of good habit, we always put a final clause in a cond that has t for a condition clause’s test. That way we assure ourselves that a cond test returns a value that we specify when all other clause tests are false.

More than special

Lisp isn’t all special forms. In fact, there are only a handful. Most Lisp built-in functions evaluate arguments normally.

For example, the most frequently-used Lisp functions are car and cdr. For now, let’s see how to use them, with full details of their awesomeness later.

The car function returns the first item in a list and cdr returns a list without its first item. Helpful synonyms for these functions are “first” and “rest”, respectively.

For example, let’s define our salad list:

(define salad (quote (lettuce tomato oil vinegar)))

Entering this:

(car salad)

Returns this:



(cdr salad)


(tomato oil vinegar)

Maybe you’re asking how we get individual items after the first item. Easy. We do this by combining car and cdr. Entering:

(car (cdr salad))

Gives us:


This expression:

(car (cdr (cdr salad)))

Gives us:


Note that car` and ``cdr do not modify the list that is bound to salad. So car doesn’t reduce a list to its first item, it only tells you what that first item is. Likewise, cdr doesn’t remove the first item from a list, it only tells you what a list is without its first item. So after applying car and cdr to salad, salad still has its most recent binding. Entering:


Still gives us:

(lettuce tomato oil vinegar)

Functions that don’t modify bindings other than their own are called pure functions. That’s another way of saying that you, the Lisp user, don’t have to worry about unintended consequences when applying a function. Function purity is an important and useful quality in Lisp programming.

So that’s most of the basics of Lisp that we implement in arpilisp. We’ll cover the rest as we go.


McCarthy. “Recursive Functions of Symbolic Expressions and Their Computation by Machine, Part I”. MIT. 1960.

McCarthy, et al. “Lisp I Programmer’s Manual.” MIT. 1960.