I'm trying to emulate a stack in scheme. I'm using DrScheme and I select the language R5RS. I need to create functions that pop, push, and peek. But i'm having trouble figuring out how to pass by reference. I've read some information about boxes, but they are not supported in R5RS. Is there any other way to pass by reference?
Short answer: don't use r5rs; just use the native language. In current versions of DrRacket, that language is called "racket". Here's a program that uses boxes:
#lang racket
(define b (box 234))
(set-box! b 333)
(unbox b)
FWIW: Greg's answer is more purely functional than mine, but it would be a mistake to believe that mutable structures are not available in DrRacket (nee DrScheme).
Finally finally, you're misusing the term "call by reference". Boxes are just mutable structures, and a call-by-value language (such as racket, r5rs, java, etc.) can mutate these structures just fine.
Instead of passing "by reference", which is something you might do in an imperative language, Scheme encourages you to think in a functional sense. This means that your push operation, for example, would take two parameters:
a stack
a new element
and return a new stack that contains the new element in combination with the rest of the existing stack. Similarly, the pop operation would take a stack and return one with the top element gone, and peek would return the value of the top element.
As it turns out, lists in Scheme work almost exactly like stacks. The following mappings will help you get started:
push - cons
pop - rest
peek - first
Related
By function-call/procedure-call pairs, I mean pairs of functions that do the same thing, except one returns it's result whereas the other alters it's argument(s) to be the result. For example the pair List/Apply.
List(list, func) Returns the list resulting from applying the function func to every value of list.
Apply(list, func) Applies the function func to every value of a mutable list list, changing list.
I've become annoyed of writing my own functions to find that GAP already had a built in version I should be using, so it'd help to know these pairs. Like, does Filtered have a procedural counterpart I don't know about? Or do I need to write my own? If a function does have a counterpart will it necessarily be listed in the documentation for that function? The only other such pair that I can think of right now is Concatenation/Append. What are other such pairs of functions/procedures in GAP?
Although this may be of little help, as Alexander Hulpke explained in https://math.stackexchange.com/questions/3704518, "The general language convention is that verbs do something to an object, while nouns create a new object with the desired characteristics." GAP naming conventions are described in the GAP Reference Manual here.
So, a counterpart to Filtered would likely be called Filter - but there is no such function (and Filter has another meaning in GAP). We do try to mention counterparts in corresponding manual sections - if you find them missing, then please suggest improvements to the GAP documentation, preferably at the GAP repository on GitHub.
I'm browsing the swift tensorflow code, and stumbled upon instances of
var result = #tfop("Mul", a, b)
#tfop is well explained in the doc here, in the sense of 'what it does' but I'm also interested in what is actually is from a language standpoint, or as a function implementation.
What does #tfop represent, beside a handle to the computation graph? why the '#'? Where can I find tfop implementation if I want to? (I browsed the code, but no luck, although I can't guarantee that I didn't miss anything).
per Chris Lattner:
#tfop is a “well known” representation used for tensor operations.
It is an internal implementation detail of our stack that isn’t meant
to be user visible, and is likely to change over time.
In Swift, "#foo(bar: 42)” is the general syntax used for “macro like”
and “compiler magic” operations. For example C things like FILE
are spelled as #file in swift:
https://github.com/apple/swift-evolution/blob/master/proposals/0034-disambiguating-line.md
And the “#line 42” syntax used by the C preprocesser is represented
with arguments like this: #sourceLocation(file: "foo", line: 42)
In the case of #tfop specifically, this is represented in the Swift
AST as an ObjectLiteralExpr, which is the normal AST node for this
sort of thing:
https://github.com/google/swift/blob/tensorflow/include/swift/AST/Expr.h#L1097
We use special lowering magic to turn it into a SIL builtin
instruction in SILGen, which are prefixed with "__tfop_"
https://github.com/google/swift/blob/tensorflow/lib/SILGen/SILGenExpr.cpp#L3009
I’d like to move away from using builtin instructions for this, and
introduce a first-class sil instruction instead, that’s tracked by:
https://github.com/google/swift/issues/16
These instructions are specially recognized by the partitioning pass
of GPE:
https://github.com/google/swift/blob/tensorflow/lib/SILOptimizer/Mandatory/TFUtilities.cpp#L715
source here
True or False?
Common Lisp has a mountain of functions. All of those functions are built (or could be built) using this small set of core functions: CAR, CDR, CONS, ATOM, EQ, QUOTE, COND, LAMBDA, LABEL, NULL.
If the answer is False, can you provide an example of a function that cannot be implemented using the core functions? Perhaps the list of core functions is incomplete, and another or two additional core functions are required?
[..] All of those functions are built (or could be built) using [..]
The important part is the could, which you already figured out yourself. That (almost*) all of (a) Lisp could be built using that small set of core functions (forms) is part of the beauty of Lisp. In practice, though, the set of functions (forms) not implemented in Lisp is a lot larger.
Why do implementations then bother to implement that much, when they only could implement that minimal core? As a small example, think of this expression:
(+ 1 2)
You could implement a Lisp that uses only the small set of core functions and it would be able (given an appropriate parser for the numbers) to evaluate this expression. But it would be painfully slow! The systems (CPUs) that are available to us mostly provide a lot of different instructions which Lisp implementations (especially the compiling ones) try to leverage as much as possible in order to allow fast execution of Lisp programs. And, to get back to the example, that also means that one wouldn't do actual calculations using peano arithmetic but rather use the "boolean logic arithmetic" implemented in hardware.
If the answer is False, can you provide an example of a function that cannot be implemented using the core functions?
That's easy, how'd you implement format? Anything that's not part of the "algorithmic" nature of a programming language, i.e. the stuff interfacing with the "outside world", is often not implemented in itself but - being dependent on the underlying system - most often in C or assembly.
False. Any function which deals with a datatype other than conses can not be implemented from your proposed core set: for instance important types such as NUMBER and SYMBOL can not be dealt with at all. Any function which does I/O likewise, and probably other vast reaches of the language.
Your list sounds like it came from some incomplete description of a proposed core of Lisp 1.5.
I have been reading a lot about Haskell lately, and the benefits that it derives from being a purely functional language. (I'm not interested in discussing monads for Lisp) It makes sense to me to (at least logically) isolate functions with side-effects as much as possible. I have used setf and other destructive functions plenty, and I recognize the need for them in Lisp and (most of) its derivatives.
Here we go:
Would something like (declare pure) potentially help an optimizing compiler? Or is this a moot point because it already knows?
Would the declaration help in proving a function or program, or at least a subset that was declared as pure? Or is this again something that is unnecessary because it's already obvious to the programmer and compiler and prover?
If for nothing else, would it be useful to a programmer for the compiler to enforce purity for functions with this declaration and add to the readability/maintainablity of Lisp programs?
Does any of this make any sense? Or am I too tired to even think right now?
I'd appreciate any insights here. Info on compiler implementation or provability is welcome.
EDIT
To clarify, I didn't intend to restrict this question to Common Lisp. It clearly (I think) doesn't apply to certain derivative languages, but I'm also curious if some features of other Lisps may tend to support (or not) this kind of facility.
You have two answers but neither touch on the real problem.
First, yes, it would obviously be good to know that a function is pure. There's a ton of compiler level things that would like to know that, as well as user level things. Given that lisp languages are so flexible, you could twist things a bit: instead of a "pure" declaration that asks the compiler to try harder or something, you just make the declaration restrict the code in the definition. This way you can guarantee that the function is pure.
You can even do that with additional supporting facilities -- I mentioned two of them in a comment I made to johanbev's answer: add the notion of immutable bindings and immutable data structures. I know that in Common Lisp these are very problematic, especially immutable bindings (since CL loads code by "side-effecting" it into place). But such features will help simplifying things, and they're not inconceivable (see for example the Racket implementation that has immutable pairs and other data structures, and has immutable bindings.
But the real question is what can you do in such restricted functions. Even a very simple looking problem would be infested with issues. (I'm using Scheme-like syntax for this.)
(define-pure (foo x)
(cons (+ x 1) (bar)))
Seems easy enough to tell that this function is indeed pure, it doesn't do anything . Also, seems that having define-pure restrict the body and allow only pure code would work fine in this case, and will allow this definition.
Now start with the problems:
It's calling cons, so it assumes that it is also known to be pure. In addition, as I mentioned above, it should rely on cons being what it is, so assume that the cons binding is immutable. Easy, since it's a known builtin. Do the same with bar, of course.
But cons does have a side effect (even if you're talking about Racket's immutable pairs): it allocates a new pair. This seems like a minor and ignorable point, but, for example, if you allow such things to appear in pure functions, then you won't be able to auto-memoize them. The problem is that someone might rely on every foo call returning a new pair -- one that is not-eq to any other existing pair. Seems that to make it fine you need to further restrict pure functions to deal not only with immutable values, but also values where the constructor doesn't always create a new value (eg, it could hash-cons instead of allocate).
But that code also calls bar -- so no you need to make the same assumptions on bar: it must be known as a pure function, with an immutable binding. Note specifically that bar receives no arguments -- so in that case the compiler could not only require that bar is a pure function, it could also use that information and pre-compute its value. After all, a pure function with no inputs could be reduced to a plain value. (Note BTW that Haskell doesn't have zero-argument functions.)
And that brings another big issue in. What if bar is a function of one input? In that case you'd have an error, and some exception will get thrown ... and that's no longer pure. Exceptions are side-effects. You now need to know the arity of bar in addition to everything else, and you need to avoid other exceptions. Now, how about that input x -- what happens if it isn't a number? That will throw an exception too, so you need to avoid it too. This means that you now need a type system.
Change that (+ x 1) to (/ 1 x) and you can see that not only do you need a type system, you need one that is sophisticated enough to distinguish 0s.
Alternatively, you could re-think the whole thing and have new pure arithmetic operations that never throw exceptions -- but with all the other restrictions you're now quite a long way from home, with a language that is radically different.
Finally, there's one more side-effect that remains a PITA: what if the definition of bar is (define-pure (bar) (bar))? It certainly is pure according to all of the above restrictions... But diverging is a form of a side effect, so even this is no longer kosher. (For example, if you did make your compiler optimize nullary functions to values, then for this example the compiler itself would get stuck in an infinite loop.) (And yes, Haskell doesn't deal with that, it doesn't make it less of an issue.)
Given a Lisp function, knowing if it is pure or not is undecidable in general. Of course, necessary conditions and sufficient conditions can be tested at compile time. (If there are no impure operations at all, then the function must be pure; if an impure operation gets executed unconditionally, then the function must be impure; for more complicated cases, the compiler could try to prove that the function is pure or impure, but it will not succeed in all cases.)
If the user can manually annotate a function as pure, then the compiler could either (a.) try harder to prove that the function is pure, ie. spend more time before giving up, or (b.) assume that it is and add optimizations which would not be correct for impure functions (like, say, memoizing results). So, yes, annotating functions as pure could help the compiler if the annotations are assumed to be correct.
Apart from heuristics like the "trying harder" idea above, the annotation would not help to prove stuff, because it's not giving any information to the prover. (In other words, the prover could just assume that the annotation is always there before trying.) However, it could make sense to attach to pure functions a proof of their purity.
The compiler could either (a.) check if pure functions are indeed pure at compile time, but this is undecidable in general, or (b.) add code to try to catch side effects in pure functions at runtime and report those as an error. (a.) would probably be helpful with simple heuristics (like "an impure operation gets executed unconditionally), (b.) would be useful for debug.
No, it seems to make sense. Hopefully this answer also does.
The usual goodies apply when we can assume purity and referential
transparency. We can automatically memoize hotspots. We can
automatically parallelize computation. We can deal away with a lot of
race conditions. We can also use structure sharing with data that we
know cannot be modified, for instance the (quasi) primitive ``cons()''
does not need to copy the cons-cells in the list it's consing to.
These cells are not affected in any way by having another cons-cell
pointing to it. This example is kinda obvious, but compilers are often
good performers in figuring out more complex structure sharing.
However, actually determining if a lambda (a function) is pure or has
referential transparency is very tricky in Common Lisp. Remember that
a funcall (foo bar) start by looking at (symbol-function foo). So in
this case
(defun foo (bar)
(cons 'zot bar))
foo() is pure.
The next lambda is also pure.
(defun quux ()
(mapcar #'foo '(zong ding flop)))
However, later on we can redefine foo:
(let ((accu -1))
(defun foo (bar)
(incf accu)))
The next call to quux() is no longer pure! The old pure foo() has been
redefined to an impure lambda. Yikes. This example is maybe somewhat
contrived but it's not that uncommon to lexically redefine some
functions, for instance with a let block. In that case it's not
possible to know what would happen at compile time.
Common Lisp has a very dynamic semantic, so actually being
able to determine control flow and data flow ahead of time (for
instance when compiling) is very hard, and in most useful cases
entirely undecidable. This is quite typical of languages with dynamic
type systems. There is a lot of common idioms in Lisp you cannot use
if you must use static typing. It's mainly these that fouls any
attempt to do much meaningful static analysis. We can do it for primitives
like cons and friends. But for lambdas involving other things than
primitives we are in much deeper water, especially in the cases where
we need to look at complex interplay between functions. Remember that
a lambda is only pure if all the lambdas it calls are also pure.
On the top of my head, it could be possible, with some deep macrology,
to do away with the redefinition problem. In a sense, each lambda gets
an extra argument which is a monad that represents the entire state of
the lisp image (we can obviously restrict ourselves to what the function
will actually look at). But it's probably more useful to be able do
declare purity ourselves, in the sense that we promise the compiler
that this lambda is indeed pure. The consequences if it isn't is then
undefined, and all sorts of mayhem could ensue...
I want to provide multiple implementations of a message reader/writer. What is the best approach?
Here is some pseudo-code of what I'm currently thinking:
just have a set of functions that all implementations must provide and leave it up to the caller to hold onto the right streams
(ns x-format)
(read-message [stream] ...)
(write-message [stream message] ...)
return a map with two closed functions holding onto the stream
(ns x-format)
(defn make-formatter [socket]
{:read (fn [] (.read (.getInputStream socket))))
:write (fn [message] (.write (.getOutputStream socket) message)))})
something else?
I think the first option is better. It's more extensible, depending how these objects are going to be used. It's easier to add or change a new function that works on an existing object if the functions and objects are separate. In Clojure there usually isn't much reason to bundle functions along with the objects they work on, unless you really want to hide implementation details from users of your code.
If you're writing an interface for which you expect many implementations, consider using multimethods also. You can have the default throw a "not implemented" exception, to force implementors to implement your interface.
As Gutzofter said, if the only reason you're considering the second option is to allow people not to have to type a parameter on every function call, you could consider having all of your functions use some var as the default socket object and writing a with-socket macro which uses binding to set that var's value. See the builtin printing methods which default to using the value of *out* as the output stream, and with-out-str which binds *out* to a string writer, as a Clojure example.
This article may interest you; it compares and contrasts some OOP idioms with Clojure equivalents.
I think that read-message and write-message are utility functions. What you need to do is encapsulate your functions in a with- macro(s). See 'with-output-to-string' in common lisp to see what I mean.
Edit:
When you use a with- macro you can have error handling and resource allocation in the macro expansion.
I'd go with the first option and make all those functions multimethods.