I have various functions and I want to call each function with the same value. For instance,
I have these functions:
(defun OP1 (arg) ( + 1 arg) )
(defun OP2 (arg) ( + 2 arg) )
(defun OP3 (arg) ( + 3 arg) )
And a list containing the name of each function:
(defconstant *OPERATORS* '(OP1 OP2 OP3))
So far, I'm trying:
(defun TEST (argument) (dolist (n *OPERATORS*) (n argument) ) )
I've tried using eval, mapcar, and apply, but these haven't worked.
This is just a simplified example; the program that I'm writing has eight functions that are needed to expand nodes in a search tree, but for the moment, this example should suffice.
Other answers have provided some idiomatic solutions with mapcar. One pointed out that you might want a list of functions (which *operators* isn't) instead of a list of symbols (which *operators* is), but it's OK in Common Lisp to funcall a symbol. It's probably more common to use some kind of mapping construction (e.g., mapcar) for this, but since you've provided code using dolist, I think it's worth looking at how you can do this iteratively, too. Let's cover the (probably more idiomatic) solution with mapping first, though.
Mapping
You have a fixed argument, argument, and you want to be able to take a function function and call it with that `argument. We can abstract this as a function:
(lambda (function)
(funcall function argument))
Now, we want to call this function with each of the operations that you've defined. This is simple to do with mapcar:
(defun test (argument)
(mapcar (lambda (function)
(funcall function argument))
*operators*))
Instead of operators, you could also write '(op1 op2 op3) or (list 'op1 'op2 'op3), which are lists of symbols, or (list #'op1 #'op2 #'op3) which is a list of functions. All of these work because funcall takes a function designator as its first argument, and a function designator is
an object that denotes a function and that is one of: a symbol (denoting the function named by that symbol in the global environment), or a function (denoting itself).
Iteratively
You can do this using dolist. The [documentation for actually shows that dolist has a few more tricks up its sleeve. The full syntax is from the documentation
dolist (var list-form [result-form]) declaration* {tag | statement}*
We don't need to worry about declarations here, and we won't be using any tags, but notice that optional result-form. You can specify a form to produce the value that dolist returns; you don't have to accept its default nil. The common idiom for collecting values into a list in an iterative loop is to push each value into a new list, and then return the reverse of that list. Since the new list doesn't share structure with anything else, we usually reverse it destructively using nreverse. Your loop would become
(defun test (argument)
(let ((results '()))
(dolist (op *operators* (nreverse results))
(push (funcall op argument) results))))
Stylistically, I don't like that let that just introduces a single value, and would probably use an &aux variable in the function (but this is a matter of taste, not correctness):
(defun test (argument &aux (results '()))
(dolist (op *operators* (nreverse results))
(push (funcall op argument) results)))
You could also conveniently use loop for this:
(defun test2 (argument)
(loop for op in *operators*
collect (funcall op argument)))
You can also do somewhat succinctly, but perhaps less readably, using do:
(defun test3a (argument)
(do ((results '() (list* (funcall (first operators) argument) results))
(operators *operators* (rest operators)))
((endp operators) (nreverse results))))
This says that on the first iteration, results and operators are initialized with '() and *operators*, respectively. The loop terminates when operators is the empty list, and whenever it terminates, the return value is (nreverse results). On successive iterations, results is a assigned new value, (list* (funcall (first operators) argument) results), which is just like pushing the next value onto results, and operators is updated to (rest operators).
FUNCALL works with symbols.
From the department of silly tricks.
(defconstant *operators* '(op1 op2 o3))
(defun test (&rest arg)
(setf (cdr arg) arg)
(mapcar #'funcall *operators* arg))
There's a library, which is almost mandatory in any anywhat complex project: Alexandria. It has many useful functions, and there's also something that would make your code prettier / less verbose and more conscious.
Say, you wanted to call a number of functions with the same value. Here's how you'd do it:
(ql:quickload "alexandria")
(use-package :alexandria)
(defun example-rcurry (value)
"Calls `listp', `string' and `numberp' with VALUE and returns
a list of results"
(let ((predicates '(listp stringp numberp)))
(mapcar (rcurry #'funcall value) predicates)))
(example-rcurry 42) ;; (NIL NIL T)
(example-rcurry "42") ;; (NIL T NIL)
(defun example-compose (value)
"Calls `complexp' with the result of calling `sqrt'
with the result of calling `parse-integer' on VALUE"
(let ((predicates '(complexp sqrt parse-integer)))
(funcall (apply #'compose predicates) value)))
(example-compose "0") ;; NIL
(example-compose "-1") ;; T
Functions rcurry and compose are from Alexandria package.
Related
Prelude
In Raku there's a notion called infinite list AKA lazy list which is defined and used like:
my #inf = (1,2,3 ... Inf);
for #inf { say $_;
exit if $_ == 7 }
# => OUTPUT
1
2
3
4
5
6
7
I'd like to implement this sort of thing in Common Lisp, specifically an infinite list of consecutive integers like:
(defun inf (n)
("the implementation"))
such that
(inf 5)
=> (5 6 7 8 9 10 .... infinity)
;; hypothetical output just for the demo purposes. It won't be used in reality
Then I'll use it for lazy evaluation like this:
(defun try () ;; catch and dolist
(catch 'foo ;; are just for demo purposes
(dolist (n (inf 1) 'done)
(format t "~A~%" n)
(when (= n 7)
(throw 'foo x)))))
CL-USER> (try)
1
2
3
4
5
6
7
; Evaluation aborted.
How can I implement such an infinite list in CL in the most practical way?
A good pedagogical approach to this is to define things which are sometimes called 'streams'. The single best introduction to doing this that I know of is in Structure and Interpretation of Computer Programs. Streams are introduced in section 3.5, but don't just read that: read the book, seriously: it is a book everyone interested in programming should read.
SICP uses Scheme, and this sort of thing is more natural in Scheme. But it can be done in CL reasonably easily. What I've written below is rather 'Schemy' CL: in particular I just assume tail calls are optimised. That's not a safe assumption in CL, but it's good enough to see how you can build these concepts into a language which does not already have them, if your language is competent.
First of all we need a construct which supports lazy evaluation: we need to be able to 'delay' something to create a 'promise' which will be evaluated only when it needs to be. Well, what functions do is evaluate their body only when they are asked to, so we'll use them:
(defmacro delay (form)
(let ((stashn (make-symbol "STASH"))
(forcedn (make-symbol "FORCED")))
`(let ((,stashn nil)
(,forcedn nil))
(lambda ()
(if ,forcedn
,stashn
(setf ,forcedn t
,stashn ,form))))))
(defun force (thing)
(funcall thing))
delay is mildly fiddly, it wants to make sure that a promise is forced only once, and it also wants to make sure that the form being delayed doesn't get infected by the state it uses to do that. You can trace the expansion of delay to see what it makes:
(delay (print 1))
-> (let ((#:stash nil) (#:forced nil))
(lambda ()
(if #:forced #:stash (setf #:forced t #:stash (print 1)))))
This is fine.
So now, we'll invent streams: streams are like conses (they are conses!) but their cdrs are delayed:
(defmacro cons-stream (car cdr)
`(cons ,car (delay ,cdr)))
(defun stream-car (s)
(car s))
(defun stream-cdr (s)
(force (cdr s)))
OK, let's write a function to get the nth element of a stream:
(defun stream-nth (n s)
(cond ((null s)
nil)
((= n 0) (stream-car s))
(t
(stream-nth (1- n) (stream-cdr s)))))
And we can test this:
> (stream-nth 2
(cons-stream 0 (cons-stream 1 (cons-stream 2 nil))))
2
And now we can write a function to enumerate an interval in the naturals, which by default will be an half-infinite interval:
(defun stream-enumerate-interval (low &optional (high nil))
(if (and high (> low high))
nil
(cons-stream
low
(stream-enumerate-interval (1+ low) high))))
And now:
> (stream-nth 1000 (stream-enumerate-interval 0))
1000
And so on.
Well, we'd like some kind of macro which lets us traverse a stream: something like dolist, but for streams. Well we can do this by first writing a function which will call a function for each element in the stream (this is not the way I'd do this in production CL code, but it's fine here):
(defun call/stream-elements (f s)
;; Call f on the elements of s, returning NIL
(if (null s)
nil
(progn
(funcall f (stream-car s))
(call/stream-elements f (stream-cdr s)))))
And now
(defmacro do-stream ((e s &optional (r 'nil)) &body forms)
`(progn
(call/stream-elements (lambda (,e)
,#forms)
,s)
,r))
And now, for instance
(defun look-for (v s)
;; look for an element of S which is EQL to V
(do-stream (e s (values nil nil))
(when (eql e v)
(return-from look-for (values e t)))))
And we can then say
> (look-for 100 (stream-enumerate-interval 0))
100
t
Well, there is a lot more mechanism you need to make streams really useful: you need to be able to combine them, append them and so on. SICP has many of these functions, and they're generally easy to turn into CL, but too long here.
For practical purposes it would be wise to use existing libraries, but since the question is about how to implemented lazy lists, we will do it from scratch.
Closures
Lazy iteration is a matter of producing an object that can generate the new value of a lazy sequence each time it is asked to do so.
A simple approach for this is to return a closure, i.e. a function that closes over variables, which produces values while updating its state by side-effect.
If you evaluate:
(let ((a 0))
(lambda () (incf a)))
You obtain a function object that has a local state, namely here the variable named a.
This is a lexical binding to a location that is exclusive to this function, if you evaluate a second time the same expression, you'll obtain a different anonymous function that has its own local state.
When you call the closure, the value stored in a in incremented and its value is returned.
Let's bind this closure to a variable named counter, call it multiple times and store the successive results in a list:
(let ((counter (let ((a 0))
(lambda () (incf a)))))
(list (funcall counter)
(funcall counter)
(funcall counter)
(funcall counter)))
The resulting list is:
(1 2 3 4)
Simple iterator
In your case, you want to have an iterator that starts counting from 5 when writing:
(inf 5)
This can implemented as follows:
(defun inf (n)
(lambda ()
(shiftf n (1+ n))))
Here is there is no need to add a let, the lexical binding of an argument to n is done when calling the function.
We assign n to a different value within the body over time.
More precisely, SHIFTF assigns n to (1+ n), but returns the previous value of n.
For example:
(let ((it (inf 5)))
(list (funcall it)
(funcall it)
(funcall it)
(funcall it)))
Which gives:
(5 6 7 8)
Generic iterator
The standard dolist expects a proper list as an input, there is no way you can put another kind of data and expect it to work (or maybe in an implementation-specific way).
We need a similar macro to iterate over all the values in an arbitrary iterator.
We also need to specify when iteration stops.
There are multiple possibilities here, let's define a basic iteration protocol as follows:
we can call make-iterator on any object, along with arbitrary arguments, to obtain an iterator
we can call next on an iterator to obtain the next value.
More precisely, if there is a value, next returns the value and T as a secondary value; otherwise, next returns NIL.
Let's define two generic functions:
(defgeneric make-iterator (object &key)
(:documentation "create an iterator for OBJECT and arguments ARGS"))
(defgeneric next (iterator)
(:documentation "returns the next value and T as a secondary value, or NIL"))
Using generic functions allows the user to define custom iterators, as long as they respect the specified behaviour above.
Instead of using dolist, which only works with eager sequences, we define our own macro: for.
It hides calls to make-iterator and next from the user.
In other words, for takes an object and iterates over it.
We can skip iteration with (return v) since for is implemented with loop.
(defmacro for ((value object &rest args) &body body)
(let ((it (gensym)) (exists (gensym)))
`(let ((,it (make-iterator ,object ,#args)))
(loop
(multiple-value-bind (,value ,exists) (next ,it)
(unless ,exists
(return))
,#body)))))
We assume any function object can act as an iterator, so we specialize next for values f of class function, so that the function f gets called:
(defmethod next ((f function))
"A closure is an interator"
(funcall f))
Also, we can also specialize make-iterator to make closures their own iterators (I see no other good default behaviour to provide for closures):
(defmethod make-iterator ((function function) &key)
function)
Vector iterator
For example, we can built an iterator for vectors as follows. We specialize make-iterator for values (here named vec) of class vector.
The returned iterator is a closure, so we will be able to call next on it.
The method accepts a :start argument defaulting to zero:
(defmethod make-iterator ((vec vector) &key (start 0))
"Vector iterator"
(let ((index start))
(lambda ()
(when (array-in-bounds-p vec index)
(values (aref vec (shiftf index (1+ index))) t)))))
You can now write:
(for (v "abcdefg" :start 2)
(print v))
And this prints the following characters:
#\c
#\d
#\e
#\f
#\g
List iterator
Likewise, we can build a list iterator.
Here to demonstrate other kind of iterators, let's have a custom cursor type.
(defstruct list-cursor head)
The cursor is an object which keeps a reference to the current cons-cell in the list being visited, or NIL.
(defmethod make-iterator ((list list) &key)
"List iterator"
(make-list-cursor :head list))
And we define next as follows, specializeing on list-cursor:
(defmethod next ((cursor list-cursor))
(when (list-cursor-head cursor)
(values (pop (list-cursor-head cursor)) t)))
Ranges
Common Lisp also allows methods to be specialized with EQL specializers, which means the object we give to for might be a specific keyword, for example :range.
(defmethod make-iterator ((_ (eql :range)) &key (from 0) (to :infinity) (by 1))
(check-type from number)
(check-type to (or number (eql :infinity)))
(check-type by number)
(let ((counter from))
(case to
(:infinity
(lambda () (values (incf counter by) t)))
(t
(lambda ()
(when (< counter to)
(values (incf counter by) T)))))))
A possible call for make-iterator would be:
(make-iterator :range :from 0 :to 10 :by 2)
This also returns a closure.
Here, for example, you would iterate over a range as follows:
(for (v :range :from 0 :to 10 :by 2)
(print v))
The above expands as:
(let ((#:g1463 (make-iterator :range :from 0 :to 10 :by 2)))
(loop
(multiple-value-bind (v #:g1464)
(next #:g1463)
(unless #:g1464 (return))
(print v))))
Finally, if we add small modification to inf (adding secondary value):
(defun inf (n)
(lambda ()
(values (shiftf n (1+ n)) T)))
We can write:
(for (v (inf 5))
(print v)
(when (= v 7)
(return)))
Which prints:
5
6
7
I'll show it with a library:
How to create and consume an infinite list of integers with the GTWIWTG generators library
This library, called "Generators The Way I Want Them Generated", allows to do three things:
create generators (iterators)
combine them
consume them (once).
It is not unsimilar to the nearly-classic Series.
Install the lib with (ql:quickload "gtwiwtg"). I will work in its package: (in-package :gtwiwtg).
Create a generator for an infinite list of integers, start from 0:
GTWIWTG> (range)
#<RANGE-BACKED-GENERATOR! {10042B4D83}>
We can also specify its :from, :to, :by and :inclusive parameters.
Combine this generator with others: not needed here.
Iterate over it and stop:
GTWIWTG> (for x *
(print x)
(when (= x 7)
(return)))
0
1
2
3
4
5
6
7
T
This solution is very practical :)
I am working on problem to get the occurence of Prime in a list in lisp.
Input:
Write a function (OccurencesOfPrimes < list >) which counts the number of primes in a (possibly nested) list.
Output: Example: (OccurencesOfPrimes (((1)(2))(5)(3)((8)3)) returns 4.
I am using the below code but getting the error like:
(
defun OccurencesOfPrimes (list)
(loop for i from 2 to 100
do ( setq isPrime t)
(loop for j from 2 to i
never (zerop (mod i j))
(setq isPrime f)
(break)
)
)
(if (setq isPrime t)
(append list i)
)
)
)
LOOP: illegal syntax near (SETQ ISPRIME F) in
(LOOP FOR J FROM 2 TO I NEVER (ZEROP (MOD I J)) (SETQ ISPRIME F) (BREAK)
)
Any help.
It is important to keep the format consistent with the expected conventions of the language. It helps when reading the code (in particular with other programmers), and can help you see errors.
Also, you should use an editor which, at the minimum, keep tracks of parentheses. In Emacs, when you put the cursor in the first opening parenthesis, the matching parenthesis is highlighted. You can spot that you have one additional parenthesis that serves no purpose.
(
defun OccurencesOfPrimes (list)
(loop for i from 2 to 100
do ( setq isPrime t)
(loop for j from 2 to i
never (zerop (mod i j))
(setq isPrime f)
(break)
)
)
(if (setq isPrime t)
(append list i)
)
) ;; <- end of defun
) ;; <- closes nothing
In Lisp, parentheses are for the computer, whereas indentation is for humans. Tools can automatically indent the code according to the structure (the parenthesis), and any discrepancy between what indentation you expect and the one being computed is a hint that your code is badly formed. If you look at the indentation of your expressions, you can see how deep you are in the form, and that alone helps you understand the code.
Symbol names are dash-separated, not camlCased.
Your code, with remarks:
(defun occurences-of-primes (list)
;; You argument is likely to be a LIST, given its name and the way
;; you call APPEND below. But you never iterate over the list. This
;; is suspicious.
(loop
for i from 2 to 100
do
(setq is-prime t) ;; setting an undeclared variable
(loop
for j from 2 to i
never (zerop (mod i j))
;; the following two forms are not expected here according
;; to LOOP's grammar; setting IS-PRIME to F, but F is not
;; an existing variable. If you want to set to false, use
;; NIL instead.
(setq is-prime f)
;; BREAK enters the debugger, maybe you wanted to use
;; LOOP-FINISH instead, but the NEVER clause above should
;; already be enough to exit the loop as soon as its
;; sub-expression evaluates to NIL.
(break)))
;; The return value of (SETQ X V) is V, so here your test would
;; always succeed.
(if (setq is-prime t)
;; Append RETURNS a new list, without modifying its
;; arguments. In particular, LIST is not modified. Note that "I"
;; is unknown at this point, because the bindings effective
;; inside the LOOP are not visible in this scope. Besides, "I"
;; is a number, not a list.
(append list i)))
Original question
Write one function which counts all the occurrences of a prime number in a (possibly nested) list.
Even though the homework questions says "write one function", it does not say that you should write one big function that compute everything at once. You could write one such big function, but if you split your problem into sub-problems, you will end with different auxiliary functions, which:
are simpler to understand (they do one thing)
can be reused to build other functions
The sub-problems are, for example: how to determine if a number is a prime? how to iterate over a tree (a.k.a. a possibly nested list)? how to count
the occurrences?
The basic idea is to write an "is-prime" function, iterate over the tree and call "is-prime" on each element; if the element is prime and was never seen before, add 1 to a counter, local to your function.
You can also flatten the input tree, to obtain a list, then sort the resulting
list; you iterate over the list while keeping track of the last
value seen: if the value is the same as the previous one, you
already know if the number is prime; if the previous number differs, then
you have to test if the number is prime first.
You could also abstract things a little more, and define a higher-order tree-walker function, which calls a function on each leaf of the tree. And write another higher-order function which "memoizes" calls: it wraps around a
function F so that if you call F with the same arguments as before,
it returns the result that was stored instead of recomputing it.
Example
I'll combine the above ideas because if you give that answer to a teacher you are likely to have to carefully explain what each part does (and if you can, great for you); this is not necessarily the "best" answer, but it covers a lot of things.
(defun tree-walk-leaves (tree function)
(typecase tree
(null nil)
(cons
(tree-walk-leaves (car tree) function)
(tree-walk-leaves (cdr tree) function))
(t (funcall function tree))))
(defun flatten (tree &optional keep-order-p)
(let ((flat nil))
(tree-walk-leaves tree (lambda (leaf) (push leaf flat)))
(if keep-order-p
(nreverse flat)
flat)))
(defun prime-p (n)
(or (= n 2)
(and (> n 2)
(oddp n)
(loop
for d from 3 upto (isqrt n) by 2
never (zerop (mod n d))))))
(defun count-occurences-of-prime (tree)
(count-if #'prime-p (remove-duplicates (flatten tree))))
(count-occurences-of-prime '(((1)(2))(5)(3)((8)3)))
=> 4
If, instead, you don't want to remove duplicates but count the multiple times a prime number occurs, you can do:
(count-if (memoize #'prime-p) (flatten tree))
... where memoize is:
(defun memoize (function &key (test #'equalp) (key #'identity))
(let ((hash (make-hash-table :test test)))
(lambda (&rest args)
(let ((args (funcall key args)))
(multiple-value-bind (result exists-p) (gethash args hash)
(values-list
(if exists-p
result
(setf (gethash args hash)
(multiple-value-list (apply function args))))))))))
(memoize is useless if there are no duplicates)
I'm trying to write a macro that will let me streamline the definition of multiple top-level variables in one single expression.
The idea was to make it work similar to how let works:
(defparameters ((*foo* 42)
(*bar* 31)
(*baz* 99)))
I tried using the following, but it doesn't seem to do anything.
(defmacro defparameters (exprs)
(dolist (expr exprs)
(let ((name (car expr))
(exp (cadr expr)))
`(defparameter ,name ,exp))))
I've tried using macroexpand but it doesn't seem to expand at all.
What am I doing wrong? and how can I fix it?
The return value of a dolist is given by its optional third argument, so your macro returns the default of nil.
Macros only return one form, so when you have multiple things, such as your series of defparameters, you need to wrap them all in some form and return that. progn will be suitable here. For Example:
(defmacro defparameters (exprs)
`(progn ,#(loop for (name exp) in exprs
collect `(defparameter ,name ,exp))))
Assume that the macro would take the boolean types a and b . If a is nil, then the macro should return nil (without ever evaluating b), otherwise it returns b. How do you do this?
This really depends on what you can use.
E.g., is or available? if? cond?
Here is one example:
(defmacro and (a b)
`(if ,a ,b nil)
EDIT. In response to a comment, or is more complicated because we have to avoid double evaluation:
(defmacro or (a b)
(let ((v (gensym "OR")))
`(let ((,v ,a))
(if ,v ,v ,b))))
sds's answer is nice and concise, but it has two limitations:
It only works with two arguments, whereas the built in and and or take any number of arguments. It's not too hard to update the solution to take any number of arguments, but it would be a bit more complicated.
More importantly, it's based very directly in terms of delayed operations that are already present in the language. I.e., it takes advantage of the fact that if doesn't evaluate the then or else parts until it has first evaluated the condition.
It might be a good exercise, then, to note that when a macro needs to delay evaluation of some forms, it's often the simplest strategy (in terms of implementation, but not necessarily the most efficient) to use a macro that expands to a function call that takes a function. For instance, a naive implementation of with-open-file might be:
(defun %call-with-open-file (pathname function)
(funcall function (open pathname)))
(defmacro my-with-open-file ((var pathname) &body body)
`(%call-with-open-file
,pathname
(lambda (,var)
,#body)))
Using a technique like this, you can easily get a binary and (and or):
(defun %and (a b)
(if (funcall a)
(funcall b)
nil))
(defmacro my-and (a b)
`(%and (lambda () ,a)
(lambda () ,b)))
CL-USER> (my-and t (print "hello"))
"hello" ; printed output
"hello" ; return value
CL-USER> (my-and nil (print "hello"))
NIL
or is similar:
(defun %or (a b)
(let ((aa (funcall a)))
(if aa
aa
(funcall b))))
(defmacro my-or (a b)
`(%or (lambda () ,a)
(lambda () ,b)))
To handle the n-ary case (since and and or actually take any number of arguments), you could write a function that takes a list of lambda functions and calls each of them until you get to one that would short circuit (or else reaches the end). Common Lisp actually already has functions like that: every and some. With this approach, you could implement and in terms of every by wrapping all the arguments in lambda functions:
(defmacro my-and (&rest args)
`(every #'funcall
(list ,#(mapcar #'(lambda (form)
`(lambda () ,form))
args))))
For instance, with this implementation,
(my-and (listp '()) (evenp 3) (null 'x))
expands to:
(EVERY #'FUNCALL
(LIST (LAMBDA () (LISTP 'NIL))
(LAMBDA () (EVENP 3))
(LAMBDA () (NULL 'X))))
Since all the forms are now wrapped in lambda functions, they won't get called until every gets that far.
The only difference is that and is specially defined to return the value of the last argument if all the preceding ones are true (e.g., (and t t 3) returns 3, not t, whereas the specific return value of every is not specified (except that it would be a true value).
With this approach, implementing or (using some) is no more complicated than implementing and:
(defmacro my-or (&rest args)
`(some #'funcall ,#(mapcar #'(lambda (form)
`(lambda () ,form))
args)))
I'm reading Peter Norvig's Paradigms of AI. In chapter 6.2, the author uses code like below (not the original code, I picked out the troubling part):
Code Snippet:
(progv '(op arg) '(1+ 1)
(eval '(op arg)))
As the author's original intent, this code should return 2, but in sbcl 1.1.1, the interpreter is apparently not looking up op in the environment, throwing out op: undefined function.
Is this implementation specific? Since the code must have been tested on some other lisp.
p.s Original code
You probably mean
(progv '(op arg) '(1+ 1)
(eval '(funcall op arg)))
Edit(2013-08-21):
PAIP was written in pre-ANSI-Common-Lisp era, so it's possible the code
there contains a few noncompliances wrt the standard. We can make
the examples work with the following revision:
(defun match-if (pattern input bindings)
"Test an arbitrary expression involving variables.
The pattern looks like ((?if code) . rest)."
(and (eval (reduce (lambda (code binding)
(destructuring-bind (var . val) binding
(subst val var code)))
bindings :initial-value (second (first pattern))))
(pat-match (rest pattern) input bindings)))
;; CL-USER> (pat-match '(?x ?op ?y is ?z (?if (eql (?op ?x ?y) ?z))) '(3 + 4 is 7))
;; ((?Z . 7) (?Y . 4) (?OP . +) (?X . 3) (T . T))
;; CL-USER> (pat-match '(?x ?op ?y (?if (?op ?x ?y))) '(3 > 4))
;; NIL
Elements in first positions are not looked up as values, but as functions and there is no concept of dynamic binding in the function namespace.
I'd say after a quick look that the original code was designed to evaluate in a context like
(progv '(x y) '(12 34)
(eval '(> (+ x y) 99)))
i.e. evaluating a formula providing substitution for variables, not for function names.
The other answers so far are right, in that the actual form being evaluated is not the variables being bound by progv (simply (op arg)), but none have mentioned what is being evaluated. In fact, the comments in the code you linked to provide a (very) short explanation (this is the only code in that file that uses progv):
(defun match-if (pattern input bindings)
"Test an arbitrary expression involving variables.
The pattern looks like ((?if code) . rest)."
;; *** fix, rjf 10/1/92 (used to eval binding values)
(and (progv (mapcar #'car bindings)
(mapcar #'cdr bindings)
(eval (second (first pattern))))
(pat-match (rest pattern) input bindings)))
The idea is that a call to match-if gets called like
(match-if '((?if code) . rest) input ((v1 val1) (v2 val2) ...))
and eval is called with (second (first pattern)), which the value of code. However, eval is called within the progv that binds v1, v2, &c., to the corresponding val1, val2, &c., so that if any of those variables appear free in code, then they are bound when code is evaluated.
Problem
The problem that I see here is that, by the code we can't tell if the value is to be saved as the variable's symbol-value or symbol-function. Thus when you put a + as a value to some corresponding variable, say v, then it'll always be saved as the symbol-value of var, not it's symbol-function.
Therefore when you'll try to use it as, say (v 1 2) , it won't work. Because there is no function named v in the functions' namespace(see this).
So, what to do?
A probable solution can be explicit checking for the value that is to be bound to a variable. If the value is a function, then it should be bound to the variable's function value. This checking can be done via fboundp.
So, we can make a macro functioner and a modified version of match-if. functioner checks if the value is a function, and sets it aptly. match-if does the dynamic local bindings, and allows other code in the scope of the bound variables.
(defmacro functioner (var val)
`(if (and (symbolp ',val)
(fboundp ',val))
(setf (symbol-function ',var) #',val)
(setf ,var ,val)))
(defun match-if (pattern input bindings)
(eval `(and (let ,(mapcar #'(lambda (x) (list (car x))) bindings)
(declare (special ,# (mapcar #'car bindings)))
(loop for i in ',bindings
do (eval `(functioner ,(first i) ,(rest i))))
(eval (second (first ',pattern))))
(pat-match (rest ',pattern) ',input ',bindings))))