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Roman Baumer (Freenode: rba #raku or ##raku-infra) / 2020-07-06T17:19:19


gfldex: Spinning up sort

Published by gfldex on 2020-07-06T17:00:56

My Linux box is transcoding from mp4 to av1 like a boss. I figured that shrinking the space hogs to halve is cheaper then doubling disk space. Running with a load of 20.29 for a few days helped to uncover a bug and a ENODOCish.

I wanted the following code to DWIM.

my $obj = class AnonClass {
    has @.a;
    method push(\e) { self.a.push: e; self }
    method list { self.a.list }
}.new;
my $sort = Proc::Async.new('/usr/bin/sort');
{ (‚a‘..‚z‘).roll(10) } |> $sort |> $obj;

Have a block that returns a list (that’s the small one that might be lazy) and feed it’s values into sort. Not overly helpful to have a blocking shell command with a lazy list but blocking did help to uncover a thinko of mine before. The result is then fed into something I call an Arrayish, a not-quite-type defined by a subset.

subset Arrayish of Any where { .^can(‚push‘) && .^can(‚list‘) }

Used in a Signature it basicly means: “If you give me an object that got .push and .list with the semantics of the buildin types, I will gladly take it.” The pipe operator handling this case looks as follows.

my multi infix:«|>»(Arrayish:D \a, Proc::Async:D $in) {
    my $pipe = Shell::Pipe.new;

    $pipe.pipees.push: a;
    $pipe.pipees.push: $in;
    # FIXME workaround R#3778
    $in.^attributes.grep(*.name eq '$!w')[0].set_value($in, True);
    $pipe.starters.push: -> {
        | $in.start, start {
            LEAVE try $in.close-stdin;
            await $in.ready;
            $in.write: „$_\n“.encode for a.list;
        }
    }

    $pipe
}

At first I did not have the blocking await $in.ready what caused the block to spit text in the direction of sort before the latter was properly started and ready to read on its STDIN. The docs mention .write and .ready but don’t explain that you need to use them together. If my system would have been idle I might not have spotted it. So I can conclude that porn is useful, so long as it is made smaller. A surprising thought because it’s usually used to make things bigger.

If you are using async behaviour it might help to run stress -c 32 in the background to push your heisenbugs over the edge. While you are on it, please push my bug over the edge too. I don’t really want to have them.

Rakudo Weekly: 2020.27 Advanced Beginning

Published by liztormato on 2020-07-06T14:52:40

Vadim Belman has kicked off a series of blog posts about advanced Raku subjects, but for beginners! And what a kick off it was! With already three blog posts to savour:

Looking forward to future instalments!

RakuOps

Alexey Melezhik has also started a series of blog posts, called RakuOps, about how you can use Raku in daily DevOps tasks. The first episode is called: How to Build Docker Containers Using Raku and Sparrow (/r/rakulang comments).

Grant Extension Request

Jonathan Worthington has requested an extension of the Raku Performance and Reliability Engineering grant. Please leave your thoughts about this requests with that request (/r/rakulang comments).

A Thousand Times Faster

Timo Paulssen has published a blog post about their grant work called: How would you like a 1000x speed increase. It’s about how tracking allocations in the profiler can be done much better (/r/rakulang comments).

Grammar Hinting

Mark Carter returns for another week with a blog post that’s about grammar hints about creating a templating system (/r/rakulang comments).

Close, But Yet Another Two

Wenzel P. P. Peppmeyer almost didn’t make it to publish 2 blog posts this week, but the second one appeared just for the Rakudo Weekly News’ deadline. As usual, each addressing some feature or quirk of the Raku Programming Language.

Jeff Goff’s Blog Posts

Andrew Shitov took to the Wayback Machine, and managed to recreate the blogs that Jeff Goff (aka DrForr) has written in the period 2015-2019 (/r/rakulang announcement).

Weekly Challenge

The entries for Challenge #67 that have Raku solutions:

Andrew Shitov provided a complete index of solutions they made to previous challenges. And Challenge #68 is up for your perusal!

Core Developments

Most of the work of the past week has been done behind the scenes in branches again: Stefan Seifert worked on in-process pre-compilation, Jonathan Worthington and Timo Paulssen worked on the new dispatch mechanism and the RakuAST grant, Elizabeth Mattijsen abandoned (at least for now) their work on refactoring the way Match objects are populated.

Questions about Raku

Meanwhile on Twitter

Meanwhile on perl6-users

Comments about Raku

New Raku Modules

Updated Raku Modules

Winding down

Fortunately, a lot less happened in the world of the Raku Programming Language than last week. Quite a cool crop of blog posts, and promises of many more. In these interesting times, don’t forget to keep healthy and keep safe. Hope to see you next week for yet another instalment of the Rakudo Weekly News!

gfldex: Unrecursing

Published by gfldex on 2020-07-06T09:45:51

Moritz was unhappy with the power Raku gave him to wrestle with lists. And he is right. If easy things are easy, no wrestling is required. That made me think about the data structure I build in my last blog post. It’s a list of pairs of a list and a Proc::Async.

[[[Proc::Async],Proc::Async],Proc::Async]

Whereby the list has the method .start mixed in. That allows me to connect the shell commands in order and start them in reverse order without special casing to get .start called. After all I need to connect STDOUT and STDIN before I start a pair of shell commands. However, any form of introspection becomes a burden. And I need to check if an Array is not at the start or end of a pipe chain.

@a |> $grep |> $sort; # this is fine
$find |> $sort |> @a; # this too
$find |> @a |> $sort; this can not work

An Array is not a concurrent data structure. The left and right side of the chain are. So we can’t mix them. (I believe I can make this work when R#3778 is fixed.)

So I rewrote what I had so far. As a side effect we can store a pipe and start it later by hand and provide a nice gist.

my $find = Proc::Async.new('/usr/bin/find', '/tmp');
my $sort = Proc::Async.new('/usr/bin/sort');
my @a;
my $p = $find |> $sort |> @a;
say $p;
#OUTPUT: find ↦ sort ↦ @a

Whereby $p contains a Shell::Pipe which has @.pipees. So we can do something like this.

for $p.pipees -> $p { $p.stderr.tap(-> {}) if $p ~~ Proc::Async}; # silence is golden
$p.start;

I want to support Supplies, Channels and Callables as start and end of a pipe. Maybe even in between. Then I can move on to tackle error handling.

It is very tempting to build elaborate data structures because Raku is so good at deconstructing them. This seams to be an option best to be avoided. Elegance might just be the solution with the least moving parts.

gfldex: Piping made easy

Published by gfldex on 2020-07-04T14:55:12

Pied Piper of Hamelin is one of the most powerful superheros ever to walk the earth. He could lead large groups of children away by playing a tune on his pipe. Most parents struggle to lead a single child away from the telly. I’m quite sure that’s why |is called a pipe on *nix. This also means that super hero movies are just fairy tales.

It’s a very powerful tool indeed, allowing to compose programs that can handle data in the form of lines of text. If your program lacks the ability to filter its output you can just pipe to grep. You might even reuse a program you have written for a different purpose to do so.

A pipe is actually a very simple construct. We start two programs and connect STDOUT of the first with STDIN of the second. From the stand point of the programs they are writing to filehandles that where opened without a filename. Raku allows us to do so by using Proc::Async.

my $find = Proc::Async.new('/usr/bin/find', '/usr');
my $grep = Proc::Async.new('/bin/grep', 'lib');

$grep.bind-stdin: $find.stdout;

await $find.start, $grep.start;

That’s a lot more wordy than how Bash is doing it.

find /usr | grep lib

We wont get as dense as Bash. Raku is not a shell scripting language. However, in a operator oriented language we should be able to define an operator that does the binding of STDOUT and STDIN. Preferably, with starting the threads and waiting for them to finish. We want to be able to chain that operator too.

role Shell::Pipe {
    method sink {
        say [self[0].command, self[1].command, "sinking"];
        await self[1].start, self[0].start;
    }
}
my multi infix:«|>»(Proc::Async:D $out, Proc::Async:D $in) {
    $in.bind-stdin: $out.stdout;
    [$out, $in] does Shell::Pipe
}

$find |> $grep
# OUTPUT: [(/usr/bin/find /usr) (/bin/grep lib) sinking]
#         <lots of lines found by find containing 'lib'>

The chaining is the tricky part. We want to handle two cases here. Sink context and list context. Raku allows us to handle a list that is not assigned to anything or has a method called. The runtime will call the method .sink on a bare list. We can use that to tell that we have to start processing the pipe. By defining another operator we can capture the output of the whole pipe as lines of text in an Array.

my multi infix:«|>»(@pipe where @pipe ~~ Shell::Pipe, @array) {
    @pipe[1].stdout.lines.tap: -> $line is raw { @array.push: $line };
    @pipe.sink;
}
my @a;
$find |> $grep |> @a;

In this case we call .sink by hand. Chaining pipes needs a little more work. To use sink context a single pipe returns an Array with a role mixed in. We can use that to write a multi candidate that expects just that as its left operand and a Proc::Async on the right. The tricky part is that I want to be able to handle any odd Proc::Async objects. Both for connecting two of them and one of them to an Array to feed data from. I tried a custom IO::Handle but that failed because Proc::Async.bind-stdin wants to call .native-descriptor. If I feed data from an Array I don’t got that. I believe that’s a Rakudobug because if we call Proc::Async.write it just works. So it clearly don’t really need that native descriptor. I got help finding a workaround. As long as Proc::Async.w is changed befor .start-internal is called, the callback is setup properly. Sadly, that attribute does not have a public write accessor. With the help of the MOP we can write a workaround.

my multi infix:«|>»(@array where @array !~~ Shell::Pipe, Proc::Async:D $in) {
    my $h = Shell::ArrayHandle.new(:@array);
    # HERE BE DRAGONS!
    $in.^attributes.grep(*.name eq '$!w')[0].set_value($in, True);
    my $out = class {
        method command { @array.WHAT.gist ~ ' ↦ ' ~ $in.command }
        method start {
            my $p_out = start {
                LEAVE $in.close-stdin;
                $in.write: ($_ ~ "\n").encode for @array;
            }
            slip $p_out
        }
    }
    # $in.bind-stdin: $h;
    [$out, $in] does Shell::Pipe
}

my $sort = Proc::Async.new('/usr/bin/sort');
my @a;
$find |> $grep |> @a;
# fiddle-with(@a);
@a |> $sort;

If you follow my blog you likely spotted already that this is another quest item in my Bag of Holding. Looks like I got quite close to a module that makes Raku a nice replacement for Bash.

When I started to think of how to implement easy Unix pipes in Raku I expected it to be a daunting task. It wasn’t. I have come to the conclusion that “Raku” is actually a verb with the meaning “making things fall into place”.

my Timotimo \this: How would you like a 1000x speed increase

Published by Timo Paulssen on 2020-07-01T20:09:08

How would you like a 1000x speed increase

Good, that's the click-baity title out of the way. Sorry for taking such a long time to write again! There really has been everything going on.

To get back into blogging, I've decided to quickly write about a change I made some time ago already.

This change was for the "instrumented profiler", i.e. the one that will at run-time change all the code of the user's program, in order to measure execution times and count up calls and allocations.

In order to get everything right, the instrumented profiler keeps an entire call graph in memory. If you haven't seen something like it yet, imagine taking stack traces at every point in your program's life, and all these stack traces put together make all the paths in the tree that point at the root.

This means, among other things, that the same function can come up multiple times. With recursion, the same function can in fact come up a few hundred times "in a row". In general, if your call tree can become both deep and wide, you can end up with a whole truckload of nodes in your tree.

How would you like a 1000x speed increase
Photo by Gabriel Garcia Marengo / Unsplash

Is it a bad thing to have many nodes? Of course, it uses up memory. Only a single path on the tree is ever interesting at any one moment, though. Memory that's not read from or written to is not quite as "expensive". It never has to go into the CPU cache, and is even free to be swapped out to disk and/or compressed. But hold on, is this really actually the case?

It turns out that when you're compiling the Core Setting, which is a code file almost 2½ megabytes big with about 71½ thousand lines, and you're profiling during the parsing process, the tree gets enormous. At the same time, the parsing process slows to a crawl. What on earth is wrong here?

Well, looking at what MoarVM spends most of its time doing while the profiler runs gives you a good hint: It's spending almost all of its time going through the entirety of the tree for garbage collection purposes. Why would it do that, you ask? Well, in order to count allocated objects at every node, you have to match the count with the type you're allocating, and that means you need to hold on to a pointer to the type, and that in turn has to be kept up to date if anything moves (which the GC does to recently-born things) and to make sure types aren't considered unused and thrown out.

That's bad, right? Isn't there anything we can do? Well, we have to know at every node which counter belongs to which type, and we need to give all the types we have to the garbage collector to manage. But nothing forces us to have the types right next to the counter. And that's already the solution to the problem:

Holding on to all types is now the job of a little array kept just once per tree, and next to every counter there's just a little number that tells you where in the array to look.

This increases the cost of recording an allocation, as you'll now have to go to a separate memory location to match types to counters. On the other hand, the "little number" can be much smaller than before, and that saves memory in every node of the tree.

More importantly, the time cost of going through the profiler data is now independent of how big the tree is, since the individual nodes don't have to be looked at at all.

With a task as big as parsing the core setting, which is where almost every type, exception, operator, or sub lives, the difference is a factor of at least a thousand. Well, to be honest I didn't actually calculate the difference, but I'm sure it's somewhere between 100x faster and 10000x faster, and going from "ten microseconds per tree node" to "ten microseconds per tree" isn't a matter of a single factor increase, it's a complexity improvement from O(n) to O(1). As long as you can find a bigger tree, you can come up with a higher improvement factor. Very useful for writing that blog post you've always wanted to put at the center of a heated discussion about dishonest article titles!

Anyway, on testing my patch, esteemed colleague MasterDuke had this to say on IRC:

timotimo: hot damn, what did you do?!?! stage parse only took almost twice as long (i.e., 60s instead of the normal 37s) instead of the 930s last time i did the profile

(psst, don't check what 930 divided by 60 is, or else you'll expose my blog post title for the fraud that it is!)

Well, that's already all I had for this post. Thanks for your attention, stay safe, wear a mask (if by the time you're reading this the covid19 pandemic is still A Thing, or maybe something new has come up), and stay safe!

How would you like a 1000x speed increase
Photo by Macau Photo Agency / Unsplash

Rakudo Weekly: 2020.26 Cloud Gone

Published by liztormato on 2020-06-29T21:17:05

The Conference in the Cloud is over. All that’s left is a number of videos (and some slides):

The Elephant in the Room

At the Conference in the Cloud, Sawyer X (the Perl pumpkin) dropped a bit of a bombshell when they announced Perl 7 (skip to the part where they go into Perl’s relation to Raku). This caused quite bit of reactions, news articles, blog posts and discussions. These are the ones that relate to Raku:

Itertools reprised

Tyler Limkemann continued their blogging, this time about Python’s itertools in pure Raku. This incited quite a few comments on /r/rakulang. Which inspired a follow-up blog post: Explaining Raku using Python’s itertools (/r/rakulang comments).

Prodigals returning

After a long absence, John Haltiwanger has returned with a blog post on how they used Raku to thwart the system in Raku to the Rescue: APL Keyboard Setting Keeper (/r/rakulang comments).

Joshua Yeshouroun has also returned with a small blog post: Pick and Choose (Part N), announcing the first upload of their Math::Combinatorics module.

Mark Carter returns with a blog post about An assembler for a virtual machine (/r/rakulang comments).

Perl, Haskell & Raku

Wim Vanderbauwheide continues their blogging with an extensive blog about List-based parser combinators in Haskell and Raku (/r/rakulang comments), which basically requires having read their previous blog post about Roles as Algebraic Data Types. Recommended!

Yet Another Two Still

Wenzel P. P. Peppmeyer continues to publish 2 blog posts a week, each addressing some feature or quirk of the Raku Programming Language.

External Dependency Management

Alexey Melezhik published a blog post about Managing External Raku Dependencies using Sparrow (/r/rakulang comments).

Weekly Challenge

The entries for Challenge #66 that have Raku solutions:

Andrew Shitov provided an overview of their solutions to previous challenges. And the next Challenge #67 is up for your perusal!

Core Developments

Most of the work of the past week has been done behind the scenes in branches: Stefan Seifert worked on in-process pre-compilation, Jonathan Worthington and Timo Paulssen worked on the new dispatch mechanism, Elizabeth Mattijsen worked on a refactoring of the way Match objects are populated.

Questions about Raku

Meanwhile on Twitter

Meanwhile on perl6-users

Comments about Raku

New Raku Modules

Updated Raku Modules

Winding down

Wow, what a week. Yours truly hopes that this week’s news about the Raku Programming Language will not be too much of a time sink. Meanwhile, one can only keep saying: keep healthy, keep safe and see you next week for yet another instalment of the Rakudo Weekly News!

p6steve: perl7 vs. raku: Sibling Rivalry?

Published by p6steve on 2020-06-27T11:24:01

It was an emotional moment to see the keynote talk at TPRCiC from Sawyer X announcing that perl 7.00 === 5.32. Elation because of the ability of the hardcore perl community to finally break free of the frustrating perl6 roadblock. Pleasure in seeing how the risky decision to rename perl6 to raku has paid off and hopefully is beginning to defuse the tensions between the two rival communities. And Fear that improvements to perl7 will undermine the reasons for many to try out raku and may cannibalise raku usage. (Kudos to Sawyer to recognising that usage is an important design goal).

Then the left side of my brain kicked in. Raku took 15 years of total commitment of genius linguists to ingest 361 RFCs and then synthesise a new kind of programming language. If perl7 seeks the same level of completeness and perfection as raku, surely that will take the same amount of effort. And I do not see the perl community going for the same level of breaking changes that raku did. (OK maybe they could steal some stuff from raku to speed things up…)

And that brought me to Sadness. To reflect that perl Osborned sometime around 2005. That broke the community in two – let’s say the visionaries and the practical-cats. And it drove a mass emigration to Python. Ancient history.

So now we have two sister languages, and each will find a niche in the programming ecosystem via a process of Darwinism. They both inherit the traits (https://en.wikipedia.org/wiki/Perl#Design) that made perl great in the first place….

The design of Perl can be understood as a response to three broad trends in the computer industry: falling hardware costs, rising labor costs, and improvements in compiler technology. Many earlier computer languages, such as Fortran and C, aimed to make efficient use of expensive computer hardware. In contrast, Perl was designed so that computer programmers could write programs more quickly and easily.

Perl has many features that ease the task of the programmer at the expense of greater CPU and memory requirements. These include automatic memory management; dynamic typing; strings, lists, and hashes; regular expressions; introspection; and an eval() function. Perl follows the theory of “no built-in limits,” an idea similar to the Zero One Infinity rule.

Wall was trained as a linguist, and the design of Perl is very much informed by linguistic principles. Examples include Huffman coding(common constructions should be short), good end-weighting (the important information should come first), and a large collection of language primitives. Perl favours language constructs that are concise and natural for humans to write.

Perl’s syntax reflects the idea that “things that are different should look different.” For example, scalars, arrays, and hashes have different leading sigils. Array indices and hash keys use different kinds of braces. Strings and regular expressions have different standard delimiters. This approach can be contrasted with a language such as Lisp, where the same basic syntax, composed of simple and universal symbolic expressions, is used for all purposes.

Perl does not enforce any particular programming paradigm (proceduralobject-orientedfunctional, or others) or even require the programmer to choose among them.

But perl7 and raku serve distinct interests & needs:

Thingperl7raku
compilationstatic parserone pass compiler
compile speedsuper fastrelies on pre-c0mp
executioninterpretedvirtual machine
execution speedsuper fastrelies on jit
module libraryCPAN nativeCPAN import
closuresyesyes
OO philosophyCor not modulepervasive
OO inheritanceRoles + IsRoles + Is + multiple
method invocation->.
type checkingnogradual
sigilsidiosyncratic consistent
referencesmanualautomatic
unicodefeature guardcore
signaturesfeature guardcore
lazy executionnopecore
Junctionsnopecore
Rat mathnopecore
Sets & Mixesnopecore
Complex mathnopecore
Grammarsnopecore
mutabilitynopecore
concurrencynopecore
variable scope“notched”cleaner
operatorsC-likecleaner (e.g. for ->)
switchnogather/when
regexenclassiccleaner
evalyesshell
AST macroshuh?
…and so on

A long list and perhaps a little harsh on perl since many things may be got from CPAN – but when you use raku in anger, you do see the benefit if having a large core language. Only when I made this table, did I truly realise just what a comprehensive language raku is, and that perl will genuinely be the lean and mean option.

Ariel Atom 3.5 review, price, specs and video | Evo
perl7
Model X | Tesla
raku

And, lest we forget our strengths:

When I first saw Python code, I thought that using indents to define the scope seemed like a good idea. However, there’s a huge downside. Deep nesting is permitted, but lines can get so wide that they wrap lines in the text editor. Long functions and long conditional actions may make it hard to match the start to the end. And I pity anyone who miscounts spaces and accidentally puts in three spaces instead of four somewhere — this can take hours to debug and track down. [Source: here]

gfldex: We can do more

Published by gfldex on 2020-06-26T11:38:15

DataKinds proceeds with his educational translations of the way of the Python to the way of the butterfly. His quest is to show how to do stuff in Raku that is done in Python. As always TIMTOWTDI applies.

Looking at the examples one can see that Raku lacks nothing Python can provide. That’s nice to know but why would you want to switch if you can’t do more? So lets explore what Raku can do better.

For a Positional container we want to switch each even element with each uneven element. Flip element 1 with 2, then 3 with 4 and so on. We also want to provide a sensible error message for the case where this is not possible. Rakudo is providing and using the X::Parameter namespace. So that’s a natural place for our custom exception.

class X::Parameter::UnevenElementList is Exception {
    method message {
        'Positional with uneven elements in where clause.'
    }
}

Now we need a sub that takes one Positional in a positional parameter and does a type check on it. We shall move that type check into an aptly named sub. We don’t need to reduce readability if we don’t have to. Using a Callable container in a where clause is not in the docs. I will check Roast later and file an issue if needed.

sub swap-each-pair(@a is raw where &check-for-even-elements ) {
    sub check-for-even-elements {
        .elems %% 2
        || X::Parameter::UnevenElementList.new.throw
    }

    for @a <-> $a, $b {
        ($a, $b) = ($b, $a)
    }
}

my @l = 1..6;
@l.&swap-each-pair;
say @l;

I put the where clause sub into the main sub to not pollute the global namespace of my script. In a module we could stick it outside and reuse it. The argument Array is marked as is raw. That’s a bit redundant because @-sigiled arguments are call-by-reference anyway. By doing so I make it clear that this sub is meant to be a mutator. If you are a Haskell lubber, you may want to look away now. The <-> pointer is applying is rw to all arguments. That allows us to modify elements of @a with a destructuring assignment.

Using a good name for the where clause sub and throwing an exception we get a helpful error message with a stacktrace. We must do so or fear the LTA tag.

Positional with uneven elements in where clause.
  in sub check-for-even-elements at /home/dex/tmp/tmp.raku line 28
  in sub swap-each-pair at /home/dex/tmp/tmp.raku line 26
  in block <unit> at /home/dex/tmp/tmp.raku line 38

Both languages are late bound and don’t have strict type checks. In a large code base that can bite you. In that case it can be very helpful to do type and value checks on strategic points and provide error messages that actually help with debugging.

Raku got lots of features that make the life of module authors easier who want to make the life of module users easier. One might think that the language designers have written CPAN modules before.

gfldex: A Raku riddle

Published by gfldex on 2020-06-24T19:59:37

While thinking about DataKinds blog post I came up with a most peculiar riddle. It goes as follows:

Name something that when removed is still defined but never existed.

The answer is an Array element whereby the Array got default values.

my @a is default('fill') = 1,2,3;
say @a[5]:exists; # False
@a = @a[5]:delete;
say @a[5].defined; # True
say @a[5]:exists; # False

How many elements got such an Array and when will iteration end?

say @a.elems; # 3
.print for @a; # 123

It has 3 elements and we can iterate over them. What makes perfect sense. However, if we judge by definedness for looping it will be infinite.

while @a[$++] -> $_ { .say } # will not stop

Is this an infinite list then? It can not run out of elements so if we believe the docs about infix:<Z> it should never stop the zipping.

use v6;

my @a is default('‽') = 1,2,3;
my @b = <a b c d e>;

say @a Z @b;
# OUTPUT: ((1 a) (2 b) (3 c))

I tried to convince Z to behave as desired to no avail. In the process I learned how to set the default value of a container long after its declaration.

my @a := Array.new;
{
    use nqp;
    my $descriptor = nqp::getattr(@a.VAR, Array, '$!descriptor');
    my $a = $descriptor.set_default('‽');
}
say @a[1];
# OUTPUT: ‽

Rakudo does a lot with iterators. Since they are an implementation detail, we can’t easily build our own. That’s not really a problem because the zip operator is clever enough to DWIM.

my @a = 1,2,3;
my @b = <a b c d e>;
say ((|@a, |('‽' xx *)) Z (|@b, |('‽' xx *)))[^(@a.elems max @b.elems)];
# OUTPUT: ((1 a) (2 b) (3 c) (‽ d) (‽ e))

I believe that is what DataKinds was looking for.

Rakudo Weekly: 2020.25 On Time

Published by liztormato on 2020-06-22T14:30:02

Alexander Kiryuhin announced the Rakudo 2020.06 Compiler Release at the expected date! The associated binary packages are available at the expected locations.

Conference in the Cloud

A last minute addition to the program of the Conference in the Cloud: Lock-Less Concurrent Programming in Raku by Vadim Belman, only a few days away! If you want to experience that interactively, you can still sign up, tickets are only 10 US$! You can even join the Hallway Track! These are the other presentations with Raku content:

On Raku’s Progress

Tyler Limkemann, after a hiatus of about a year, is back with a very nice blog post on Raku in June 2020: Speed, Usability, and Politics. The takeaway? “I’m deeply pleased with the state of Raku right now.” (/r/rakulang comments).

Still Yet Another Two

Wenzel P. P. Peppmeyer continues to publish 2 blog posts a week, each addressing some feature or quirk of the Raku Programming Language.

Three in one

Patrick Spek reports on what they’ve been doing in Raku lately (/r/rakulang comments).

Grant Progress

Not one, but two grant progress reports by Jonathan Worthington this week:

If you wonder why not a lot is happening on the Core Developments section, this is one of the reasons: things only get reported when they’re actually merged in the main branch.

Spazure

Alexey Melezhik announces an Azure DevOps toolset to automate CRUD operations that does not require PowerShell.

Weekly Challenge

The entries for Challenge #65 that have Raku solutions:

Challenge #66 is up for your perusal!

Core Developments

Questions about Raku

Meanwhile on Twitter

Meanwhile on perl6-users

Comments about Raku

New Raku Modules

Updated Raku Modules

Winding down

One can only say: keep healthy, keep safe and see you next week for yet another instalment of the Rakudo Weekly News!

Rakudo Weekly: 2020.24 Cloud Approaching

Published by liztormato on 2020-06-15T15:10:08

In 10 days the Conference in the Cloud will start! If you want to experience that interactively, you can still sign up, tickets are only 10 US$! You can even join the Hallway Track! These are the presentations with Raku content:

Yet Another Two

Wenzel P. P. Peppmeyer has written yet another two blog posts in the past week, each addressing some feature or quirk of the Raku Programming Language.

Discussions

Alexey Melezhik started up two discussions: one about RakuDist/Whateverable/Alpine and one about black box testing for ake runs.

Weekly Challenge

The entries for Challenge #64 that have Raku solutions:

Mohammad S Anwar has created two videos on how they created this week’s solutions: Challenge #1 and Challenge #2. And Challenge #65 is up for your perusal!

Core Developments

Questions about Raku

Meanwhile on Twitter

Meanwhile on perl6-users

Comments about Raku

New Raku Modules

Updated Raku Modules

Winding down

With a pandemic, worldwide protesting and the climate becoming more and more erratic, we live in interesting times indeed. Long time contributor and creator of Panda, Tadeusz Sośnierz, has written a blog post about the LGBT situation in Poland, which really hit home for yours truly. So in closing, one can only say: keep healthy, keep safe and see you next week for yet another instalment of the Rakudo Weekly News!

Rakudo Weekly: 2020.23 500+ Rakoons

Published by liztormato on 2020-06-08T12:57:26

In just over 7 months, the /r/rakulang subreddit has had more than 500 people join it. Although this is still a lot less than the 1631 people that joined the now closed /r/perl6 subreddit, that number was achieved in 8.5 years. It’s good to see interest in Raku growing!

Totally Natural

Herbert Breunung has written a multi-page article in a Heise Magazine special edition about programming languages (German), which apparently also includes an interview with Jonathan Worthington. It is behind a paywall, and supposedly you can get a free trial subscription, but yours truly has not been able to make that work.

Algebraic Data Types

Wim Vanderbauwhede, a former lambdacamel, has written an extensive blog post about using roles as algebraic data types in Raku. Specifically on how you can parameterize roles and mixin roles into other roles. You may find this article interesting if you are curious about functional-style static typing or if your would like an alternative to object-oriented programming.

Another Two

Wenzel P. P. Peppmeyer has written another two blog posts in the past week, each addressing some feature or quirk of the Raku Programming Language.

Easy CLI testing

Alexey Melezhik explains how you, as a Raku module author, simply need to add a .tomty directory with Tomty scenarios to run, to test your CLI programs that your distribution provides. A great tool just got better!

Tips for working with hashes

Andrew Shitov elaborates on the different ways one can work with hashes in Raku, explaining that a Pair can be considered a single element element Hash, and that a list of Pairs is not the same as a Hash.

Weekly Challenge

The champion of the month of May is Shahed Nooshmand, known for their excellent Raku one-liner solutions! The entries for Challenge #63 that have Raku solutions:

Challenge #64 is up for your perusal!

Core Developments

Questions about Raku

Meanwhile on Twitter

Meanwhile on perl6-users

Comments about Raku

New Raku Modules

Updated Raku Modules

Winding down

Sorry to bother you all again after only a week :-). Again a very nice batch of new and updated modules, blog posts and some very nice speedups. Keep healthy, keep safe and see you next week for yet another instalment of the Rakudo Weekly News!

p6steve: Raku Objects: Confusing or What?

Published by p6steve on 2020-05-07T21:51:52

Chapter 1: The Convenience Seeker

Coming from Python, the Raku object model is recognizable, but brings a tad more structure:

Screenshot 2020-05-07 22.36.37

What works for me, as a convenience seeker, is:

These are the things you want if you are writing in a more procedural or functional style and using class as a means to define a record type.

Chapter 2: The Control Freak

Here’s the rub…

When we describe OO, terms like “encapsulation” and “data hiding” often come up. The key idea here is that the state model inside the object – that is, the way it chooses to represent the data it needs in order to implement its behaviours (the methods) – is free to evolve, for example to handle new requirements. The more complex the object, the more liberating this becomes.

However, getters and setters are methods that have an implicit connection with the state. While we might claim we’re achieving data hiding because we’re calling a method, not accessing state directly, my experience is that we quickly end up at a place where outside code is making sequences of setter calls to achieve an operation – which is a form of the feature envy anti-pattern. And if we’re doing that, it’s pretty certain we’ll end up with logic outside of the object that does a mix of getter and setter operations to achieve an operation. Really, these operations should have been exposed as methods with a names that describes what is being achieved. This becomes even more important if we’re in a concurrent setting; a well-designed object is often fairly easy to protect at the method boundary.

(source jnthn https://stackoverflow.com/questions/59671027/mixing-private-and-public-attributes-and-accessors-in-raku)

Let’s fix that:

Screenshot 2020-05-07 22.38.41
Now, I had to do a bit more lifting, but here’s what I got:

And, in contrast to Chapter 1:

Chapter 3: Who Got the Colon in the End?

I also discovered Larry’s First Law of Language Redesign: Everyone wants the colon

Apocalypse 1: The Ugly, the Bad, and the Good https://www.perl.com/pub/2001/04/02/wall.html/

I conclude that Larry’s decision was to confer the colon on the method syntax,  subtly tilting the balance towards the strict model: by preferring $p.y: 3 over $p.y = 2.

p6steve: Raku vs. Perl – save 70%

Published by p6steve on 2020-04-17T17:36:39

Having hit rock bottom with an ‘I can’t understand my own code sufficiently enough to extend/maintain it’, I have been on a journey to review the perl5 Physics::Unit design and to use this to cut through my self made mess of raku Physics::Unit version 0.0.2.

Now I bring the perspective of a couple of years of regular raku coding to bear, so I am hoping that the bastard child of mature perl5 and raku version one will surpass both in the spirit of David Bowie’s “Pretty Things”.

One of the reasons I chose Physics::Units as a project was that, on the face of it, it seemed to have an aspect that could be approached by raku Grammars – helping me learn them. Here’s a sample of the perl5 version:

Screenshot 2020-04-17 18.40.05

Yes – a recursive descent parser written from scratch in perl5 – pay dirt! There are 215 source code lines dedicated to the parse function. 5 more screens like this…

So I took out my newly sharpened raku tools and here’s my entire port: 

Screenshot 2020-04-17 18.42.08

Instead of ranging over 215 lines, raku has refined this down to a total of 58 lines (incl. the 11 blank ones I kept in for readability) – that’s a space saving of over 70%. Partly removal of parser boilerplate code, partly the raku Grammar constructs and partly an increased focus on the program logic as opposed to the mechanism.

For my coding style, this represents a greater than a two-thirds improvement – by getting the whole parser onto a single screen, I find that I can get the whole problem into my brain’s working memory and avoid burning cycles scrolling up and down to pin down butterflies bugs.

Attentive students will have noted that the Grammar / code integration provides a very natural paradigm for loading real-world data into an OO system, the UnitAction class starts with a stub object and populates ‘has’ attributes as it goes.

Oh and the raku code does a whole lot more such as support for unicode superscripts (up to +/-4), type assignment and type checking, offsets (such as 0 K = 273.15 °C), wider tolerance of user input and so on. Most importantly Real values are kept as Rats as much as possible which helps greatly for example, when round tripping 38.5 °C to  °F and back it is still equals 38.5 °C!

One final remark – use Grammar::Tracer is a fantastic debugging tool for finding and fixing the subtle bugs that can come in and contributing to quickly getting to the optimum solution.

rakudo.org: Rakudo Star Release 2020.01

Published on 2020-02-24T00:00:00

p6steve: Raku: the firkin challenge

Published by p6steve on 2020-01-20T22:40:01

For anyone wondering where my occasional blog on raku has been for a couple of months – sorry. I have been busy wrestling with, and losing to, the first released version of my Physics::Measure module.

Of course, this is all a bit overshadowed by the name change from perl6 to raku. I was skeptical on this, but did not have a strong opinion either way. So kudos to the folks who thrashed this out and I am looking forward to a naissance. For now, I have decided to keep my nickname ‘p6steve’ – I enjoy the resonance between P6 and P–sics and that is my niche. No offence intended to either camp.

My stated aim (blogs passim) is to create a set of physical units that makes sense for high school education. To me, inspired by the perl5 Physics::Unit module, that means not just core SI units for science class, but also old style units like sea miles, furlongs/fortnight and so on for geography and even history. As I started to roll out v0.0.3 of raku Physics::Unit, I thought it would be worthwhile to track a real-world high school education resource, namely OpenStax CNX. As I came upon this passage, I had to take the firkin challenge on:

While there are numerous types of units that we are all familiar with, there are others that are much more obscure. For example, a firkin is a unit of volume that was once used to measure beer. One firkin equals about 34 liters. To learn more about nonstandard units, use a dictionary or encyclopedia to research different “weights and measures.” Take note of any unusual units, such as a barleycorn, that are not listed in the text. Think about how the unit is defined and state its relationship to SI units.

Disaster – I went back to the code for Physics::Unit and, blow me, could I figure out how to drop in a new Unit: the firkin??…. nope!! Why not? Well Physics::Unit v:0.0.3 was impenetrable even to me, the author. Statistically it has 638 lines of code alongside 380 lines of heredoc data. Practically, while it passes all the tests 100%, it is not a practical, maintainable code base.

How did we get here? Well I plead guilty to being an average perl5 coder who really loves the expressivity that Larry offers … but a newbie to raku. I wanted to take on Physics::Measure to learn raku. Finally, I have started to get raku – but it has taken me a couple of years to get to this point!

My best step now – bin the code. I have dumped my original effort, gone back to the original perl5 Physics::Unit module source and transposed it to raku. The result: 296 lines of tight code alongside the same 380 lines of heredoc – a reduction of 53%! And a new found respect for the design skill of my perl5 forbears.

I am aiming to release as v0.0.7 in April 2020.

Raku Advent Calendar: Happy new year!

Published by jjmerelo on 2019-12-26T18:48:44

This year’s advent calendar is over, and it leaves us lots of articles on metaprogramming, applications, useful Raku modules, how to migrate from Perl, programming techniques and even how to work with Raku inside containers.

No more articles until next year, and the call is already open: if you want to tell something about Raku and its surroundings, add your name to the list with possible title, and you’re in!

Meanwhile, you’ve got raku.org and docs.raku.org for all your Raku needs.

Raku means enjoyment. So we wish you all a lot of Raku for next year!

Raku Advent Calendar: Day 24: The Grinch of Raku, Part 2: Hold Your Horses

Published by kaiepi on 2019-12-24T00:01:00

In 2017, the Grinch ruined Christmas by showing off some of the naughty things you can do with Raku’s features. Unfortunately, while his heart grew by three sizes that year, there’s more than one Grinch! This Grinch will be doing something extra naughty this year, taking some inspiration from the JavaScript community.

You may have heard of JSFuck, which is a tool that allows you to write any JavaScript code using only the characters [, ], (, ), +, and !. This is something you’d only expect to be possible in a language like JavaScript, right? That’s not entirely true! To prove this, let’s port it to Raku. Since this can’t be implemented using the exact same set of characters, our restrictions will be that only non-alphanumeric ASCII characters may be used in the translated code, and string literals must not be used.

Generating Primitives

The first thing we’ll need to do is find a way to generate some primitives. The ones from JavaScript that are of interest to us are booleans, numbers, and strings; any other type of primitive can be represented through other means. These are generated mainly through type coercion on empty arrays, which also happens to be possible to do in Raku.

True and False can be generated in Raku using the ! prefix operator, similarly to how you can in JavaScript:

say ![];  # OUTPUT: True
say !![]: # OUTPUT: False

Using this in combination with the + prefix operator, we can generate any whole number, which is also the case in JavaScript:

say +[];         # OUTPUT: 0
say +![];        # OUTPUT: 1
say +![] + +![]; # OUTPUT: 2

In JavaScript, + also happens to be used to concatenate strings. When used with two empty arrays, + will coerce both to strings and concatenate them, which results in an empty string. + doesn’t behave like this in Raku, so we’ll need to use the ~ operator instead:

say (~[]).perl; # OUTPUT: ""

What about strings that aren’t empty though? In JavaScript, strings are iterable, which allows for certain characters to be used when stringifying values other than empty arrays. This isn’t the case in Raku! It’s time to start getting creative.

String bitwise operators allow you to perform the same bitwise operations you can perform on numbers on codepoints in strings. Using the ~^ infix operator, we can generate a null character given 0 and 0:

say ord +[] ~^ +[]; # OUTPUT: 0

We can’t generate the characters we need very easily with the ~+, ~|, and ~^ operators alone though. There is a way to do this using that null character, but we need a lowercase letter of some sort first. We can grab the letter "e" from "True" if we use a regex:

say ~(![] ~~ /...(.)/)[+[]]; # OUTPUT: e

Using an infinite sequence with these two characters, we can generate most of the characters in ASCII:

my Str:D @chars = (+[] ~^ +[]...~(![] ~~ /...(.)/)[+[]]...*);
say @chars[65..90];  # OUTPUT: (A B C D E F G H I J K L M N O P Q R S T U V W X Y Z)
say @chars[97..122]; # OUTPUT: (a b c d e f g h i j k l m n o p q r s t u v w x y z)

Now that we can generate the characters in the string "&chr", we’ll be able to generate any Unicode string after the next step.

Evaluating Code

Most of the JavaScript code that can be generated depends on the Function constructor in order to work. Using it, you can arbitrarily generate a function at runtime. As far as I know, it’s not possible to generate code like this in Raku without using &EVAL. There’s a problem we need to solve if we are to use it, though.

We can use string literals with &EVAL just fine:

say EVAL "'Hello, world!'"; # OUTPUT: Hello, world!

But if we try to use a value that is unknown at compile-time with it, we’ll get an exception warning about the security implications of what we’re doing, telling us to use the MONKEY-SEE-NO-EVAL pragma:

say EVAL my $ = "'Hello, world!'"; # Throws X::SecurityPolicy::Eval

That’s not good in our case! We can’t set this pragma without alphanumeric characters. It’s time to get naughty. What happens if we try to use &EVAL using an indirect symbol lookup?

say ::('&EVAL')(my $ = "'Hello world!'"); # OUTPUT: Hello, world!

Perfect! Along with this, using indirect symbol lookup we can also call the &chr routine to generate a string for any Unicode codepoint. In combination, this allows us to translate any valid Raku code.

Hold Your Horses

We’re ready to start writing code for our port of JSFuck. This will simply be a script that takes some Raku code as input and outputs its translation. All of the subroutines used (apart from &MAIN) will be pure. Now, let’s give this port a bit of a nicer name than the obvious choice and call it Hold Your Horses instead.

Our first subroutine will be &from-uint, which will translate numbers. We could just add 1 to 0 repeatedly until we get the number we’re looking for, but this will generate huge amounts of code for larger codepoints. One way we can shorten the code this generates is if we represent numbers as being products of prime numbers. This can be further shortened by representing prime numbers greater than 5 as being a sum of products of prime numbers:

use Prime::Factor;

sub from-uint(UInt:D $x, Int:D $remainder = 0 --> Str:D) is pure {
    proto sub translate(UInt:D --> Str:D) is pure {*}
    multi sub translate(0 --> '+[]') { }
    multi sub translate(1 --> '+![]') { }
    multi sub translate(UInt:D $x --> Str:D) {
        join ' + ', '+![]' xx $x
    }

    if $x <= 5 {
        my Str:D $translation = $x.&translate;
        $translation ~= ' + ' ~ $remainder.&from-uint if $remainder;
        $translation
    } elsif $x.is-prime {
        from-uint $x - 1, $remainder + 1
    } else {
        my Str:D $translation = $x.&prime-factors».&from-uint.fmt: '(%s)', ' * ';
        $translation ~= ' + ' ~ $remainder.&from-uint if $remainder;
        $translation
    }
}

Now we can implement &from-str, which will parse code input by the user. This needs to map each codepoint in the given code to a Hold Your Horses number, which can be done by looking up a character in the sequence of characters from earlier if it is within its range, otherwise &chr can be called. Since we’re using this sequence every time we see a character that is included by it, this will be stored in $_ by our next subroutine. Since translating a single codepoint can be quite intensive, let’s use the experimental is cached trait with our helper subroutine that handles this to avoid having to do it more than once for any given codepoint:

use experimental :cached;

sub from-str(Str:D $code --> Str:D) is pure {
    my Int:D constant LIMIT = 'z'.ord.succ;

    proto sub translate(UInt:D --> Str:D) is pure is cached {*}
    multi sub translate(UInt:D $codepoint where 0..^LIMIT --> Str:D) {
        sprintf '.[%s]', $codepoint.&from-uint
    }
    multi sub translate(UInt:D $codepoint where LIMIT..* --> Str:D) {
        sprintf '::(%s)(%s)',
                '&chr'.ords».&translate.join(' ~ '),
                $codepoint.&from-uint
    }

    sprintf '::(%s)(%s)',
            '&EVAL'.ords».&translate.join(' ~ '),
            $code.ords».&translate.join(' ~ ')
}

Now we can implement &hold-your-horses, which will handle the full translation of code input by the user. All this needs to do is store the sequence from earlier in $_ before calling &from-str:

sub hold-your-horses(Str:D $code --> Str:D) is pure {
    Qc:to/TRANSLATION/.chomp
    $_ := (+[] ~^ +[]...~(![] ~~ /...(.)/)[+[]]...*);
    {$code.&from-str};
    TRANSLATION
}

With &MAIN added, our script is now complete:

use v6.d;
use experimental :cached;
use Prime::Factor;
unit sub MAIN(Str:D $code) {
    say hold-your-horses $code
}

sub from-uint(UInt:D $x, Int:D $remainder = 0 --> Str:D) is pure {
    proto sub translate(UInt:D --> Str:D) is pure {*}
    multi sub translate(0 --> '+[]') { }
    multi sub translate(1 --> '+![]') { }
    multi sub translate(UInt:D $x --> Str:D) {
        join ' + ', '+![]' xx $x
    }

    if $x <= 5 {
        my Str:D $translation = $x.&translate;
        $translation ~= ' + ' ~ $remainder.&from-uint if $remainder;
        $translation
    } elsif $x.is-prime {
        from-uint $x - 1, $remainder + 1
    } else {
        my Str:D $translation = $x.&prime-factors».&from-uint.fmt: '(%s)', ' * ';
        $translation ~= ' + ' ~ $remainder.&from-uint if $remainder;
        $translation
    }
}

sub from-str(Str:D $code --> Str:D) is pure {
    my Int:D constant LIMIT = 'z'.ord.succ;

    proto sub translate(UInt:D --> Str:D) is pure is cached {*}
    multi sub translate(UInt:D $codepoint where 0..^LIMIT --> Str:D) {
        sprintf '.[%s]', $codepoint.&from-uint
    }
    multi sub translate(UInt:D $codepoint where LIMIT..* --> Str:D) {
        sprintf '::(%s)(%s)',
                '&chr'.ords».&translate.join(' ~ '),
                $codepoint.&from-uint
    }

    sprintf '::(%s)(%s)',
            '&EVAL'.ords».&translate.join(' ~ '),
            $code.ords».&translate.join(' ~ ')
}

sub hold-your-horses(Str:D $code --> Str:D) is pure {
    Qc:to/TRANSLATION/.chomp
    $_ := (+[] ~^ +[]...~(![] ~~ /...(.)/)[+[]]...*);
    {$code.&from-str};
    TRANSLATION
}

Now, does this actually work? For brevity’s sake, let’s say it works as intended if say "Hello, world! 👋" can be translated and run:

bastille% raku hold-your-horses.raku 'say "Hello, world! 👋"' > hello-world.raku
bastille% raku hello-world.raku
Hello, world! 👋

Perfect! This is the script’s output:

$_ := (+[] ~^ +[]...~(![] ~~ /...(.)/)[+[]]...*);
::(.[(+![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) + +![])] ~ .[(+![] + +![] + +![]) * ((+![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![] + +![] + +![]) + +![]) + +![])] ~ .[(+![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![]) + +![]) + +![])] ~ .[(+![] + +![] + +![] + +![] + +![]) * ((+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) + +![])])(.[(+![] + +![] + +![] + +![] + +![]) * ((+![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![] + +![] + +![]) + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![]) + +![]] ~ .[((+![] + +![]) * (+![] + +![] + +![] + +![] + +![]) + +![]) * ((+![] + +![]) * (+![] + +![] + +![] + +![] + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![])] ~ .[(+![] + +![]) * ((+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![] + +![] + +![]) * (+![] + +![] + +![] + +![] + +![]) + +![]] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![])] ~ .[(+![] + +![] + +![]) * ((+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![] + +![] + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![])] ~ .[((+![] + +![]) * (+![] + +![] + +![]) + +![]) * ((+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![]) + +![])] ~ .[(+![] + +![] + +![]) * ((+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![] + +![] + +![]) * (+![] + +![] + +![] + +![] + +![])] ~ .[(+![] + +![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![] + +![] + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![])] ~ ::(.[(+![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) + +![])] ~ .[(+![] + +![] + +![]) * (+![] + +![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![] + +![] + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![]) * (+![] + +![]) * ((+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![]) + +![])] ~ .[(+![] + +![]) * (+![] + +![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) + +![])])((+![] + +![] + +![] + +![] + +![]) * (+![] + +![] + +![] + +![] + +![]) * ((+![] + +![]) * ((+![] + +![]) * ((+![] + +![]) * (+![] + +![] + +![] + +![] + +![]) + +![]) + +![]) + +![]) * ((+![] + +![]) * (+![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) * (+![] + +![] + +![]) + +![])) ~ .[(+![] + +![]) * ((+![] + +![]) * (+![] + +![]) * (+![] + +![]) * (+![] + +![]) + +![])]);

Wrapping Up

Raku is quite a large language with an extensive set of features. These can be combined in some very interesting ways! Here, using a combination of type coercion, string bitwise operators, regexen, sequences, indirect symbol lookup, and a loophole with &EVAL, we were able to be naughty Grinches again this year and port JSFuck from JavaScript. If you’re tempted to say something is impossible to write in Raku, hold your horses; it may very well be possible to do with the right tools.

Raku Advent Calendar: Day 23 – A Raku Advent Helper

Published by Tom Browder (@tbrowder) on 2019-12-23T00:01:00

Introduction

I have been writing Raku Advent articles annually since 2016, and it’s always been a struggle for me to get a reliable transformation of my source file into the Raku Advent WordPress (WP) website without something getting changed by WP. Then, the menus are terrible and editing can be troublesome. In this article I hope to show how the situation can be improved.

Background

The great name change to Raku this year unfortunately happened late in the year and there was not a lot of time to get a new Raku Advent website ready. Consequently, theme selection and tweaking, confusion over the actual Raku Advent website link, and unfortunate article cancellations were wrinkles in the normally smoother process. However, we plan to improve the website before the 2020 Advent season, and also get commitments earlier with concrete drafts available sooner. In the meantime, in this hastily prepared stand-in article, I will go into a bit of detail on some help we hope to offer.

Article creation

Since my first experience with WordPress, I have found these things that make it awkward for me to use WP:

I’m sure most of my problems with WP are self-induced, but I do prefer a more TeX-like document production work flow.

Prior years

In past years I’ve created the articles in Gihub-flavored markdown, manually (with the assistance of my Emacs editor) converted each paragraph to single, long lines, and then posted it in a Github gist. After that, I used the tool p6advent-md2html.p6, developed by @zoffix [Note 2] and modified by @SimonProctor, to extract the html from Github’s representation of the markdown which results in a nice highlighting of code blocks. Finally, that html is copied and pasted into WP and a publishing schedule set up. That original process is outlined here:

  1. Write the post in Github-favored Markdown text
  2. Collapse each paragraph to one long line
  3. Paste the source into a Github gist
  4. Use the existing Advent tool to extract the resulting html representation to one’s local computer
  5. Copy the html and paste it into the blank, html view of the selected WP editor
  6. View the finished product and check for errors

If errors are found:

  1. Correct the errors in the WP editor

OR

  1. Correct the errors in the source
  2. Repeat steps 2 through 6 again

That process is not so bad the first time through it, but when, inevitably, errors are found, one has the choice of either manually editing it on WP or modifying the source and going through the entire process again! Neither choice is very good.

2019’s Advent goal: reduce WP pain

I decided this year to help my article-creation situation so I created a Raku tool to eliminate some of the problems. It’s available to the public as of today:

$ zef install RakuAdvent::WordPress

That module provides the tool make-wp-input. So my new steps as of this year:

  1. Write the post in raw html
  2. Run my new Advent tool (make-wp-input) to format the source into WP-acceptable html
  3. Copy the html and paste it into the blank, html view of the selected WP editor
  4. View the finished product and check and correct for errors

If errors are found:

  1. Correct the errors in the WP editor

OR, preferably,

  1. Correct the errors in the source
  2. Repeat steps 2 through 4 again

Thus, in my new process, I’ve eliminated a couple of steps, but I still have to copy/paste my clean WP source into the WordPress editor—but that’s because I have not taken advantage of the available APIs from WordPress and Github to do the drudge work.

However, in spite of other limitations, the new tool has been a huge help in easing the use of live code examples in an article. In my sandbox where I write my article, I create the code samples in their own files and then add the

<!-- insert file-name lang -->

lines as needed in the location needed. That way, I can edit the live code and test it to make sure it works, but don’t have to change the source using that code.

Tips for Raku authors

Here are some ideas I’ve found helpful while developing articles for the Raku Advent:

Wish lists

Here are some things I hope to do with make-wp-input in the New Year:

  1. Convert html source to Github-flavored markdown
  2. Handle html tables
  3. Allow paragraphs in the source html to be recognized by either blank lines above and below the text or a line with a closing tag on the line before the text or an opening tag on the line following the text
  4. Use Github’s APIs [Ref. 2] to manipulate markdown source to a Github gist and get html results back from it
  5. Use WordPress’s APIs [Ref. 3] to manipulate one’s article on WordPress (including setting or updating the publication schedule)

And here are some things I hope the community can do (or at least agree upon) for the Raku Advent website:

  1. Improve the theme and code styling.
  2. Use the old Perl 6 Advent theme?
  3. Sign up for article slots earlier in the year, and start the article (at least in skeleton form) as a scheduled one on the Raku Advent website.

Summary

This year has seen a lot of changes in the Raku community, especially with the name change, and not all are done yet. One area that still needs work is improving the new Raku Advent website. We also hope to make it easier to create and post Raku Advent articles as well as get more participation. Note the 2020 schedule is open now, so you can get your slot early and avoid last minute shopping, er, Raku Adventing!

I ❤ Raku! 😊

Merry Christmas and a Happy, Blessed New Year to all!


APPENDIX


Notes

  1. I have filed an issue with WordPress to help with time zone identification in the scheduling calendar.
  2. Names preceded by @ are IRC or Github aliases.

References

  1. wkhtmltopdf (available as a Debian package)
  2. Github API
  3. WordPress API

Raku modules used

Raku Advent Calendar: Day 22: Off Course

Published by arnesom on 2019-12-22T01:01:00

You may not have heard about my Perl 6 Courses, and I don’t blame you.

It has been quite a journey.

It started in September 2018 with my Perl6 In 45+45 Minutes introduction to Perl 6 at the Nordic Perl Workshop in Oslo. The very first time a held a presentation at a conference…

I got positive feedback, and wondered if I could build on it. The idea of a full blown course matured, and I started working on the accompanying textbook first.

The book and course is meant as an introduction to Raku, for people already familiar with programming.

I pitched the course to PerlCon 2019 in Riga, and they accepted it. The organiser asked me to promote it, and the result was my Perl 6 blog Perl 6 Musings (at the absolutely fantastic address «perl6.eu»).

Unfortunately that didn’t work out, and the course was cancelled due to too few participants.

  Beginning Raku, 1. Edition (December 2019)  

Pages: 370

File size: ~ 11 Mbyte (pdf)


arnesom.github.io/Beginning-v1.00.pdf

I am giving away this first version of the book for free. I do reserve the right to print the book and sell it. You are free to distribute the pdf file or print it. You are also free to distribute printed copies, but you may not get paid for it.

Feel free to use the code samples, either as they are or as inspiration for your own work. Atribution would be nice, but isn’t required.

I will be grateful for feedback, and do so at the Github page for the book – or by email to the address shown in the book. I intend to publish a revised version of the book if I receive feedback that warrants an update.

Not Complete

The next course, «Advanced Raku» continues where this one ends. As the book is meant as a reference, I have chosen to make a combined book for both courses, called «Raku Explained». The second half (the «Advanced Raku» part) is unfinished, but I have published a preliminary Table of Contents and Index so that you can see what the whole book intends to cover.


  Raku Explained, v0.01 (December 2019)  

Pages: 30 (Table of Contents & Index only)

File size: ~ 5 Mbyte (pdf)


arnesom.github.io/Explained-v0.01.pdf

I am also interested in feedback on the topics in the second part (chapter 18 – 32).

Raku Advent Calendar: Day 21: Searching for a Red gift

Published by SmokeMachine on 2019-12-21T00:00:00

Alabaster Snowball, the elf, was searching for a gift for the person he had drawn on the North Pole’s Secret Santa. He had the great honour to draw Santa! What to give for the one who gives everyone’s presents? So he was searching on the internet for some keywords he knew Santa would like:

Wait a minute! Is Red going to :api<2>?!! Alabaster Snowball has already read about that ORM for Raku. But it seems this new :api<2> version is taking it to the next level.

That’s it! I’ll give Santa a Red:api<2> PoC as gift! I know he has been playing with Raku, and I think it would be great to change all that collection of SQL strings on the NiceList model to a well made set of ORM classes.

Reading the documentation, Snowball learned that it would be very easy to create it’s first model:

use Red:api<2>;

unit model Child;

has UInt $!id              is id;
has Str  $.name            is column;
has Str  $.country         is column;

He started using Red:api<2> and creating a new model that represents a table child with 3 columns (id, name and country). As easy as that.

Alabaster could now just connect into a database, create the table, and start inserting children:

use Red:api<2>;
red-defaults default => database "SQLite";

Child.^create-table: :unless-exists;

Child.^create: :name<Fernanda>, :country<England> ;
Child.^create: :name<Sophia>,   :country<England> ;
Child.^create: :name<Dudu>,     :country<Scotland>;
Child.^create: :name<Rafinha>,  :country<Scotland>;
Child.^create: :name<Maricota>, :country<Brazil>  ;
Child.^create: :name<Lulu>,     :country<Brazil>  ;

And to list all children created:

.say for Child.^all.sort: *.name;

And that would run this query:

SELECT
   child.id, child.name, child.country 
FROM
   child
ORDER BY
   child.name

And prints:

Child.new(name => "Dudu", country => "Scotland")
Child.new(name => "Fernanda", country => "England")
Child.new(name => "Lulu", country => "Brazil")
Child.new(name => "Maricota", country => "Brazil")
Child.new(name => "Rafinha", country => "Scotland")
Child.new(name => "Sophia", country => "England")

If it’s needed, Santa can classify children by country:

my %by-country := Child.^all.classify: *.country;

And to discover what countries have children registered:

say %by-country.keys;

That would run:

SELECT
   DISTINCT(child.country) as "data_1"
FROM
   child

And that would return:

(England Scotland Brazil)

If he needs to get all children from England:

.say for %by-country<England>;

That would run:

SELECT
   child.id, child.name, child.country 
FROM
   child
WHERE
   child.country = ?

-- BIND: ["England"]

That would return:

Child.new(name => "Fernanda", country => "England")
Child.new(name => "Sophia", country => "England")

It’s working great! How about storing the gifts? Is there a way to store what a child asked by year?

# Gift.pm6
use Red:api<2>;

unit model Gift;

has UInt $!id            is serial;
has Str  $.name          is column{ :unique };

has      @.asked-by-year is relationship( *.gift-id, :model<ChildAskedOnYear> );

method child-asked-on-year(UInt $year = Date.today.year) {
    @!asked-by-year.grep(*.year == $year)
}

method asked-by(UInt $year) {
    self.child-asked-on-year(|($_ with $year)).map: *.child
} 
# Child.pm6
use Red:api<2>;

unit model Child;

has UInt $!id              is id;
has Str  $.name            is column;
has Str  $.country         is column;

has      @.asked-by-year   is relationship( *.child-id, :model<ChildAskedOnYear> );

method asked(UInt $year = Date.today.year) {
    @!asked-by-year.grep: *.year == $year
}
# ChildAskedOnYear.pm6
use Red:api<2>;

unit model ChildAskedOnYear;

has UInt $!id       is serial;
has UInt $.year     is column = Date.today.year;
has UInt $!child-id is referencing(*.id, :model<Child>);
has UInt $!gift-id  is referencing(*.id, :model<Gift>);

has      $.child    is relationship( *.child-id, :model<Child> );
has      $.gift     is relationship( *.gift-id,  :model<Gift>  );

Alabaster Snowball thought that way he could get all information he would need. Creating new gifts is easy!

for <doll ball car pokemon> -> $name {
    Gift.^create: :$name;
}

How about searching? Alabaster Snowball writes a new line:

.say for Gift.^all

And it returns all the gifts. But what if we want only the gifts that end with “ll”?

.say for Gift.^all.grep: *.name.ends-with: "ll"

That will run a query like:

SELECT
   gift.id, gift.name 
FROM
   gift
WHERE
   gift.name like '%ll'

Snowball wondered if it is possible to find what a child has asked:

.say for Child.^find(:name<Fernanda>).asked.map: *.gift

That runs:

SELECT
   child_asked_on_year_gift.id, child_asked_on_year_gift.name 
FROM
   child_asked_on_year
    LEFT JOIN gift as child_asked_on_year_gift ON child_asked_on_year.gift_id = child_asked_on_year_gift.id
WHERE
   child_asked_on_year.child_id = ? AND child_asked_on_year.year = 2019

And what if we want to know the last year’s gift?

.say for Child.^find(:name<Fernanda>).asked(2018).map: *.gift
SELECT
   child_asked_on_year_gift.id, child_asked_on_year_gift.name 
FROM
   child_asked_on_year
    LEFT JOIN gift as child_asked_on_year_gift ON child_asked_on_year.gift_id = child_asked_on_year_gift.id
WHERE
   child_asked_on_year.child_id = ? AND child_asked_on_year.year = '2018'

How do we know how many of each gift should be built?

say ChildAskedOnYear.^all.map(*.gift.name).Bag
SELECT
   child_asked_on_year_gift.name as "data_1", COUNT('*') as "data_2"
FROM
   child_asked_on_year
    LEFT JOIN gift as child_asked_on_year_gift ON child_asked_on_year.gift_id = child_asked_on_year_gift.id
GROUP BY
   child_asked_on_year_gift.name

The documentation for Red is on https://fco.github.io/Red/ and some examples used here can be found on https://github.com/FCO/Red/blob/join/examples/xmas/index.p6

Jo Christian Oterhals: By the way, you could replace … * with Inf or the unicode infinity symbol ∞ to make it more…

Published by Jo Christian Oterhals on 2019-11-24T19:25:11

By the way, you could replace … * with Inf or the unicode infinity symbol ∞ to make it more readable, i.e.

my @a = 1, 1, * + * … ∞;

— — or — —

my @a = 1, 1, * + * … Inf;

Jo Christian Oterhals: As I understand this, * + * … * means the following:

Published by Jo Christian Oterhals on 2019-11-24T10:20:11

As I understand this, * + * … * means the following:

First— * + * sums the two previous elements in the list. … * tells this to do this an infinite number of times; i.e.

1, 1, (1 + 1)

1, 1, 2, (1 + 2)

1, 1, 2, 3, (2 + 3)

1, 1, 2, 3, 5, (3 + 5)

1, 1, 2, 3, 5, 8, (5 + 8), etc.

… three dots means that it does it lazy, i.e. that it does not generate an element before you call it. This can be good for large lists that are computationally heavy.

my Timotimo \this: Introducing: The Heap Snapshot UI

Published by Timo Paulssen on 2019-10-25T23:12:36

Introducing: The Heap Snapshot UI

Hello everyone! In the last report I said that just a little bit of work on the heap snapshot portion of the UI should result in a useful tool.

Introducing: The Heap Snapshot UI
Photo by Sticker Mule / Unsplash

Here's my report for the first useful pieces of the Heap Snapshot UI!

Last time you already saw the graphs showing how the number of instances of a given type or frame grow and shrink over the course of multiple snapshots, and how new snapshots can be requested from the UI.

The latter now looks a little bit different:

Introducing: The Heap Snapshot UI

Each snapshot now has a little button for itself, they are in one line instead of each snapshot having its own line, and the progress bar has been replaced with a percentage and a little "spinner".

There are multiple ways to get started navigating the heap snapshot. Everything is reachable from the "Root" object (this is the norm for reachability-based garbage collection schemes). You can just click through from there and see what you can find.

Another way is to look at the Type & Frame Lists, which show every type or frame along with the number of instances that exist in the heap snapshot, and the total size taken up by those objects.

Type & Frame Lists

Introducing: The Heap Snapshot UI

Clicking on a type, or the name or filename of a frame leads you to a list of all objects of that type, all frames with the given name, or all frames from the given file. They are grouped by size, and each object shows up as a little button with the ID:

Introducing: The Heap Snapshot UI

Clicking any of these buttons leads you to the Explorer.

Explorer

Here's a screenshot of the explorer to give you an idea of how the parts go together that I explain next:

Introducing: The Heap Snapshot UI

The explorer is split into two identical panels, which allows you to compare two objects, or to explore in multiple directions from one given object.

There's an "Arrow to the Right" button on the left pane and an "Arrow to the Left" button on the right pane. These buttons make the other pane show the same object that the one pane currently shows.

On the left of each pane there's a "Path" display. Clicking the "Path" button in the explorer will calculate the shortest path to reach the object from the root. This is useful when you've got an object that you would expect to have already been deleted by the garbage collector, but for some reason is still around. The path can give the critical hint to figure out why it's still around. Maybe one phase of the program has ended, but something is still holding on to a cache that was put in as an optimization, and that still has your object in it? That cache in question would be on the path for your object.

The other half of each panel shows information about the object: Displayed at the very top is whether it is an object, a type object, an STable, or a frame.

Below that there is an input field where you can enter any ID belonging to a Collectable (the general term encompassing types, type objects, stables, and frames) to have a look.

The "Kind" field needs to have the number values replaced with human-readable text, but it's not the most interesting thing anyway.

The "Size" of the Collectable is split into two parts. One is the fixed size that every instance of the given type has. The other is any extra data an instance of this type may have attached to it, that's not a Collectable itself. This would be the case for arrays and hashes, as well as buffers and many "internal" objects.

Finally, the "References" field shows how many Collectables are referred to by the Collectable in question (outgoing references) and how many Collectables reference this object in question.

Below that there are two buttons, Path and Network. The former was explained further above, and the latter will get its own little section in this blog post.

Finally, the bottom of the panel is dedicated to a list of all references - outgoing or incoming - grouped by what the reference means, and what type it references.

Introducing: The Heap Snapshot UI

In this example you see that the frame of the function display from elementary2d.p6 on line 87 references a couple of variables ($_, $tv, &inv), the frame that called this frame (step), an outer frame (MAIN), and a code object. The right pane shows the incoming references. For incoming references, the name of the reference isn't available (yet), but you can see that 7 different objects are holding a reference to this frame.

Network View

The newest part of the heap snapshot UI is the Network View. It allows the user to get a "bird's eye" view of many objects and their relations to each other.

Here's a screenshot of the network view in action:

Introducing: The Heap Snapshot UI

The network view is split into two panes. The pane on the left lists all types present in the network currently. It allows you to give every type a different symbol, a different color, or optionally make it invisible. In addition, it shows how many of each type are currently in the network display.

The right pane shows the objects, sorted by how far they are from the root (object 0, the one in Layer 0, with the frog icon).

Each object has one three-piece button. On the left of the button is the icon representing the type, in the middle is the object ID for this particular object, and on the right is an icon for the "relation" this object has to the "selected" object:

This view was generated for object 46011 (in layer 4, with a hamburger as the icon). This object gets the little "map marker pin" icon to show that it's the "center" of the network. In layers for distances 3, 2, and 1 there is one object each with a little icon showing two map marker pins connected with a squiggly line. This means that the object is part of the shortest path to the root. The third kind of icon is an arrow pointing from the left into a square that's on the right. Those are objects that refer to the selected object.

There is also an icon that's the same but the arrow goes outwards from the square instead of inwards. Those are objects that are referenced by the selected object. However, there is currently no button to have every object referenced by the selected object put into the network view. This is one of the next steps I'll be working on.

Customizing the colors and visibility of different types can give you a view like this:

Introducing: The Heap Snapshot UI

And here's a view with more objects in it:

Introducing: The Heap Snapshot UI

Interesting observations from this image:

Next Steps

You have no doubt noticed that the buttons for collectables are very different between the network view and the type/frame lists and the explorer. The reason for that is that I only just started with the network view and wanted to display more info for each collectable (namely the icons to the left and right) and wanted them to look nicer. In the explorer there are sometimes thousands of objects in the reference list, and having big buttons like in the network view could be difficult to work with. There'll probably have to be a solution for that, or maybe it'll just work out fine in real-world use cases.

On the other hand, I want the colors and icons for types to be available everywhere, so that it's easier to spot common patterns across different views and to mark things you're interested in so they stand out in lists of many objects. I was also thinking of a "bookmark this object" feature for similar purposes.

Before most of that, the network viewer will have to become "navigable", i.e. clicking on an object should put it in the center, grab the path to the root, grab incoming references, etc.

There also need to be ways to handle references you're not (or no longer) interested in, especially when you come across an object that has thousands of them.

But until then, all of this should already be very useful!

Here's the section about the heap snapshot profiler from the original grant proposal:

Looking at the list, it seems like the majority of intended features are already available or will be very soon!

Easier Installation

Until now the user had to download nodejs and npm along with a whole load of javascript libraries in order to compile and bundle the javascript code that powers the frontend of moarperf.

Fortunately, it was relatively easy to get travis-ci to do the work automatically and upload a package with the finished javascript code and the backend code to github.

You can now visit the releases page on github to grab a tarball with all the files you need! Just install all backend dependencies with zef install --deps-only . and run service.p6!

And with that I'm already done for this report!

It looks like the heap snapshot portion of the grant is quite a bit smaller than the profiler part, although a lot of work happened in moarvm rather than the UI. I'm glad to see rapid progress on this.

I hope you enjoyed this quick look at the newest pieces of moarperf!
  - Timo

Weekly changes in and around Perl 6: 2019.42 Question

Published by liztormato on 2019-10-21T14:14:51

The Perl 6 Weekly has been renamed to the Rakudo Weekly and can be found at: https://rakudoweekly.blog.

Thank you for visiting the Perl 6 Weekly the past years. It was a blast!

Please adjust your RSS readers, email notifications. Thank you!

Hope to see you there!

Weekly changes in and around Perl 6: 2019.41 New Wineskins

Published by liztormato on 2019-10-15T16:46:05

Larry Wall emerged, almost like a deus ex machina, to give his approval of changing the name of the Perl 6 Programming Language to “Raku”. This stirred up quite some reactions on the interwebs:

Also see quite some reactions on Twitter below.

London Perl Workshop

Next weekend, on Saturday 19 October, it’s time for the London Perl Workshop again. The following presentations with Perl 6 content appear to have been planned:

An excellent opportunity to learn more about Perl 6 / Raku. And possibly the last time for a pre-Brexit visit to the UK!

Even More Video Tutorials

Yanzhan Yang, a serial tech video uploader, yet again has posted more Perl 6 introductory videos on YouTube:

Getting more amazing every week!

Andrew Shitov

It was a stressful week for Andrew Shitov: at first he was worried about the future of his Perl 6 compiler book. Then, after Larry Wall showed his approval of the renaming, he suggested having a RakuCon in May 2020 on Cyprus at the venue previously intended for the 2020 Perl Conference. Quickly followed by a blog post explaining how he sees the future of Raku, including building a new, faster Raku compiler (/r/perl6 comments). Followed by the publication of the first Raku book: Using Raku and making that available for free download (/r/perl6 comments). And to top it off, produced a little tutorial about the difference between is rw and is raw. Yours truly can only hope that future weeks will be less stressful.

Perl Weekly Challenge #29

Blog posts with Perl 6 solutions for Challenge #29:

Challenge #30 is up for your perusal.

Questions about Perl 6

Meanwhile on Twitter

Meanwhile on Facebook

Thanks to the quickly unrepairable actions of a certain individual outside of the Perl 6 community, the Perl 6 Facebook group has changed all of its URLs and/or is only accessible to people with Facebook logins. And since it is the intention of changing back to the original URLs (which will most likely take a month thanks to Facebook policies), it doesn’t seem to make sense to put deep links here now.

So, if you’re interested in happenings on Facebook, check out the Perl 6 Group, and navigate from there.

Meanwhile on perl6-users

Perl 6 in comments

Perl 6 Modules

New modules:

Updated modules:

Winding Down

The past year has been very stressful for yours truly. And the past week even more so. Some stress will remain in the near future, but it looks like stress levels will be allowed to go down in the further future, with “Perl” and “Raku” each going their own way.

This is the last Perl 6 Weekly that yours truly will write. Next week I will just announce the location of the new Rakudo Weekly blog here.

Why “Rakudo” and not “Raku”, you might ask? Well, originally the “Perl 6 Weekly” was about all implementations of Perl 6. But for the past 4 years, it has effectively been only about the “Rakudo” implementation. Now that “Perl 6” is being renamed to “Raku”, it seems like a good opportunity to not squat on the language name in a blog that is effectively dedicated to a single implementation of the Raku Programming Language.

So see you next week for directions to the new blog!

Weekly changes in and around Perl 6: 2019.40 Quick Syntaxing

Published by liztormato on 2019-10-07T14:23:14

JJ Merelo is the proud writer of the latest Perl 6 book: Perl 6 Quick Syntax Reference: A Pocket Guide to the Language, the Core Modules, and the Community. A book packed with useful information and a must-have for any developer new to Perl 6. Highly recommended! (Safari).

Sub as method

Sterling Hanenkamp shows how to use a sub as a method (/r/perl6 comments).

Perspective and FALLBACK

Greg Donald has published two blog posts in the past week: a personal one about his perspective as an outsider, and a technical one about adding an attribute to a class at runtime.

Even More Video Tutorials

Yanzhan Yang, a serial tech video uploader, yet again has posted more Perl 6 introductory videos on YouTube:

Getting more amazing every week!

Perl Weekly Challenge #28

Blog posts with Perl 6 solutions for Challenge #28:

Challenge #29 is up for your perusal.

Core Developments

Questions about Perl 6

Meanwhile on Twitter

Meanwhile on Facebook

Perl 6 in comments

Perl 6 Modules

New modules:

Updated modules:

Winding Down

A quiet week, with one more week to go on voting on the rename of Perl 6. See you all next week with more news about the Perl 6 Programming Language!

Weekly changes in and around Perl 6: 2019.39 With A Lump

Published by liztormato on 2019-09-30T18:56:54

Jonathan Worthington explains why he got a lump in his throat when he approved changing the name of “Perl 6” to “Raku”. Feelings that yours truly (like many others) only can share. (/r/perl, /r/perl6 comments). Andrew Shitov also shared his feelings about renaming the Perl 6 Programming Language (/r/perl6, Facebook comments).

Video Tutorials

Yanzhan Yang, a serial tech video uploader, has posted some more Perl 6 introductory videos on YouTube:

Amazing!

Faster Continuous Integration

Tony O’Dell has created a walk through on how to do Continuous Integration with Circle CI and Travis CI, using a Docker image.

The power of base

Shred_Alert describes the magic of base.

Perl Weekly Challenge #27

Blog posts with Perl 6 solutions for Challenge #27:

Simon Proctor is the champion of week 27! And as usual, Challenge #28 is up for your perusal.

Core Developments

Questions about Perl 6

Meanwhile on Twitter

Meanwhile on Facebook

Meanwhile on perl6-users

Perl 6 in comments

Perl 6 Modules

New modules:

Updated modules:

Winding Down

It appears there will be no Rakudo 2019.09 compiler release. Which makes sense since it’s almost October. Check out the Perl 6 Weekly next week for more news about this and many other things!

Weekly changes in and around Perl 6: 2019.38 For Else Itch

Published by liztormato on 2019-09-23T15:27:14

Damian Conway had an itch, and he scratched it in “Itch.scratch()“. An extensive treatise on how to extend the Perl 6 Programming Language, giving the for loop an else block to be executed only if no iterations were done in the for loop. In less than 25 lines! (Reddit comments).

Video Tutorials

Yanzhan Yang has posted a number of Perl 6 introductory videos on YouTube, maybe the first of many to come:

Yanzhan Yang appears to be a serial tech video uploader (Reddit comments).

Atomic Units

Steve Roe explains his thoughts on seamlessly supporting atomic units in the Physics::Measure Perl 6 module.

Perl 6 at LPW

These presentations about Perl 6 are currently planned to be given at the next London Perl Workshop:

It’s not too late to submit your presentation!

Perl Foundation News

The Perl Foundation is nominating Pete Krawczyk as Treasurer. Many thanks to Dan Wright for having filled this position for so many years.

And there is a grant proposal for curating the Perl 6 documentation, a continuation of earlier work by JJ Merelo.

Please leave your comments, if you have any of course!

What’s in a name?

Sven Gregori investigated several open source projects with naming issues, Perl 6 just being one of them (/r/perl, /r/perl6 comments).

Perl Weekly Challenge #26

Blog posts with Perl 6 solutions for Challenge #26:

Yet Ebreo is the champion of week 25! And as usual, Challenge #27 is up for your perusal.

Core Developments

Questions about Perl 6

Meanwhile on Twitter

Meanwhile on Facebook

Meanwhile on perl6-users

Perl 6 in comments

Perl 6 Modules

New modules (some of them were missed previously because of not having been uploaded to CPAN):

Updated modules:

Winding Down

A quiet week yet again, while work has started on finalizing the next Rakudo compiler release. Hope to be able to report on that next week. Until then, program safely and have fun!

p6steve: Atomic Units?

Published by p6steve on 2019-09-17T20:49:39

One of the most exciting parts of blogging about and hacking on perl6* is that there’s a community out there and there’s (always) more than one way to do it!

For Physics::Measure I have been working on a design for a ‘nano-slang’ that can provide a shortcut for the usual new Class declaration… quite long winded for my target audience of physics undergraduates and high school students.

#Instances the usual way

my Unit $u .=new(name => ‘m’, unitsof => ‘Distance’); #Unit m

my Distance $a .=new(value => 10, units => $u);           #Distance 10 m

So, duly inspired by Rakudo perl6 going atomic ⚛ applying unicode to some threading constructs, I started with the notion of the ‘libra’ operator ♎ as shorthand to declare and load Measure instances.

#Introducing the libra operator ♎ as shorthand to declare and load

my $b ♎ ’50 m’;   #Distance 50 m

$b ♎ ‘3 yards’;     #Distance 3 yards

As you can see, the gap created between ♎ and ; is a slang zone that can consume strings and numeric literals. Here’s something a bit more elaborate:

#Normalization with the .norm method

my $p ♎ ’27 kg m^2 / s^3′;   #Power 27 kg m^2 / s^3

$p .= norm;                              #Power 27 W

A few design ideas drew me in this direction:

# Resistance

[‘Ω’, ‘Ohm:s’,],       ’kg m^2 / A^2 s^3′,

[‘kilohm:s’,],          ’kilo Ohm’,

[‘megohm:s’,],       ’mega Ohm’,

HOWEVER!!

Others have proposed a much more direct approach to generate and combine Measure objects – by the use of a simple postfix syntax – thank you!

Something like:

say 500g; # –> Weight.new(grams => 500, prefix => “”)

say 2kg;  # –> Weight.new(grams => 2000, prefix => “kg”)

Watch this space! Or even better zef Physics::Measure and give it a try…

~p6steve

* soon to be Rakudo?!

my Timotimo \this: Progressing with progress.

Published by Timo Paulssen on 2019-09-12T19:50:18

Progressing with progress.

It has been a while since the last progress report, hasn't it?

Over the last few months I've been focusing on the MoarVM Heap Snapshot Profiler. The new format that I explained in the last post, "Intermediate Progress Report: Heap Snapshots", is available in the master branch of MoarVM, and it has learned a few new tricks, too.

The first thing I usually did when opening a Heap Snapshot in the heapanalyzer (the older command-line based one) was to select a Snapshot, ask for the summary, and then for the top objects by size, top objects by count, top frames by size, and/or top frames by count to see if anything immediately catches my eye. In order to make more sense of the results, I would repeat those commands for one or more other Snapshots.

Snapshot  Heap Size          Objects  Type Objects  STables  Frames  References  
========  =================  =======  ============  =======  ======  ==========  
0         46,229,818 bytes   331,212  686           687      1,285   1,146,426   
25        63,471,658 bytes   475,587  995           996      2,832   1,889,612   
50        82,407,275 bytes   625,958  1,320         1,321    6,176   2,741,066   
75        97,860,712 bytes   754,075  1,415         1,416    6,967   3,436,141   
100       113,398,840 bytes  883,405  1,507         1,508    7,837   4,187,184   

Snapshot  Heap Size          Objects    Type Objects  STables  Frames  References  
========  =================  =========  ============  =======  ======  ==========  
125       130,799,241 bytes  1,028,928  1,631         1,632    9,254   5,036,284   
150       145,781,617 bytes  1,155,887  1,684         1,685    9,774   5,809,084   
175       162,018,588 bytes  1,293,439  1,791         1,792    10,887  6,602,449 

Realizing that the most common use case should be simple to achieve, I first implemented a command summary all and later a command summary every 10 to get the heapanalyzer to give the summaries of multiple Snapshots at once, and to be able to get summaries (relatively) quickly even if there's multiple hundreds of snapshots in one file.

Sadly, this still requires the parser to go through the entire file to do the counting and adding up. That's obviously not optimal, even though this is an Embarrassingly Parallel task, and it can use every CPU core in the machine you have, it's still a whole lot of work just for the summary.

For this reason I decided to shift the responsibility for this task to MoarVM itself, to be done while the snapshot is taken. In order to record everything that goes into the Snapshot, MoarVM already differentiates between Object, Type Object, STable, and Frame, and it stores all references anyway. I figured it shouldn't have a performance impact to just add up the numbers and make them available in the file.

The result is that the summary table as shown further above is available only milliseconds after loading the heap snapshot file, rather than after an explicit request and sometimes a lengthy wait period.

The next step was to see if top objects by size and friends could be made faster in a similar way.

I decided that adding an optional "statistics collection" feature inside of MoarVM's heap snapshot profiler would be worthwhile. If it turns out that the performance impact of summing up sizes and counts on a per-type and per-frame basis makes capturing a snapshot too slow, it could be turned off.

Frontend work

> snapshot 50
Loading that snapshot. Carry on...
> top frames by size
Wait a moment, while I finish loading the snapshot...

Name                                  Total Bytes    
====================================  =============  
finish_code_object (World.nqp:2532)   201,960 bytes  
moarop_mapper (QAST.nqp:1764)         136,512 bytes  
!protoregex (QRegex.nqp:1625)         71,760 bytes   
new_type (Metamodel.nqp:1345)         40,704 bytes   
statement (Perl6-Grammar.nqp:951)     35,640 bytes   
termish (Perl6-Grammar.nqp:3641)      34,720 bytes   
<anon> (Perl6-BOOTSTRAP.c.nqp:1382)   29,960 bytes   
EXPR (Perl6-Grammar.nqp:3677)         27,200 bytes   
<mainline> (Perl6-BOOTSTRAP.c.nqp:1)  26,496 bytes   
<mainline> (NQPCORE.setting:1)        25,896 bytes   
EXPR (NQPHLL.nqp:1186)                25,760 bytes   
<anon> (<null>:1)                     25,272 bytes   
declarator (Perl6-Grammar.nqp:2189)   23,520 bytes   
<anon> (<null>:1)                     22,464 bytes   
<anon> (<null>:1)                     22,464 bytes   

Showing the top objects or frame for a single snapshot is fairly straight-forward in the commandline based UI, but how would you display how a type or frame develops its value across many snapshots?

Instead of figuring out the best way to display this data in the commandline, I switched focus to the Moarperf Web Frontend. The most obvious way to display data like this is a Line Graph, I believe. So that's what we have now!

Progressing with progress.

And of course you also get to see the data from each snapshot's Summary in graph format:

Progressing with progress.

And now for the reason behind this blog post's Title.

Progress Notifications

Using Jonathan's module Concurrent::Progress (with a slight modification) I sprinkled the code to parse a snapshot with matching calls of .increment-target and .increment. The resulting progress reports (throttled to at most one per second) are then forwarded to the browser via the WebSocket connection that already delivers many other bits of data.

The result can be seen in this tiny screencast:

Progressing with progress.

The recording is rather choppy because the heapanalyzer code was using every last drop of performance out of my CPU while it was trying to capture my screen.

There's obviously a lot still missing from the heap snapshot analyzer frontend GUI, but I feel like this is a good start, and even provides useful features already. The graphs for the summary data are nicer to read than the table in the commandline UI, and it's only in this UI that you can get a graphical representation of the "highscore" lists.

I think a lot of the remaining features will already be useful after just the initial pieces are in place, so a little work should go a long way.

Bits and Bobs

I didn't spend the whole time between the last progress report and now to work directly on the features shown here. Apart from Life Intervening™, I worked on fixing many frustrating bugs related to both of the profilers in MoarVM. I added a small subsystem I call VMEvents that allows user code to be notified when GC runs happen and other interesting bits from inside MoarVM itself. And of course I've been assisting other developers by answering questions and looking over their contributions. And of course there's the occasional video-game-development related experiment, for example with the GTK Live Coding Tool.

Finally, here's a nice little screencap of that same tool displaying a hilbert curve:

Progressing with progress.

That's already everything I have for this time. A lot has (had to) happen behind the scenes to get to this point, but now there was finally something to look at (and touch, if you grab the source code and go through the needlessly complicated build process yourself).

Thank you for reading and I hope to see you in the next one!
  - Timo

Jo Christian Oterhals: You’re right.

Published by Jo Christian Oterhals on 2019-08-25T18:51:13

You’re right. I’ll let the article stand as it is and reflect my ignorance as it was when I wrote it :-)

Jo Christian Oterhals: Perl 6 small stuff #21: it’s a date! …or: learn from an overly complex solution to a simple task

Published by Jo Christian Oterhals on 2019-07-31T13:23:17

Perl 6 small stuff #21: it’s a date! …or: learn from an overly complex solution to a simple task

This week’s Perl Weekly Challenge (#19) has two tasks. The first is to find all months with five weekends in the years from 1900 through 2019. The second is to program an implementation of word wrap using the greedy algorithm.

Both are pretty straight-forward tasks, and the solutions to them can (and should) be as well. This time, however, I’m also going to do the opposite and incrementally turn the easy solution into an unnecessarily complex one. Because in this particular case we can learn more by doing things the unnecessarily hard way. So this post will take a look at Dates and date manipulation in Perl 6, using PWC #19 task 1 as an example:

Write a script to display months from the year 1900 to 2019 where you find 5 weekends i.e. 5 Friday, 5 Saturday and 5 Sunday.

Let’s start by finding five-weekend months the easy way:

#!/usr/bin/env perl6
say join "\n", grep *.day-of-week == 5, map { Date.new: |$_, 1 }, do 1900..2019 X 1,3,5,7,8,10,12;

The algorithm for figuring this out is simple. Given the prerequisite that there must be five occurrences of not only Saturday and Sunday but also Friday, you A) *must* have 31 days to cram five weekends into. And when you know that you’ll also see that B) the last day of the month MUST be a Sunday and C) the first day of the month MUST be a Friday (you don’t have to check for both; if A is true and B is true, C is automatically true too).

The code above implements B and employs a few tricks. You read it from right to left (unless you write it from left to right, like this… say do 1900..2019 X 1,3,5,7,8,10,12 ==> map { Date.new: |$_, 1 } ==> grep *.day-of-week == 5 ==> join “\n”; )

Using the X operator I create a cross product of all the years in the range 1900–2019 and the months 1, 3, 5, 7, 8, 10, 12 (31-day months). In return I get a sequence containing all year-month pairs of the period.

The map function iterates through the Seq. There it instantiates a Date object. A little song and dance is necessary: As Date.new takes three unnamed integer parameters, year, month and day, I have to do something to what I have — a Pair with year and month. I therefore use the | operator to “explode” the pair into two integer parameters for year and month.

You can always use this for calling a sub routine with fixed parameters, using an array with parameter values rather than having separate variables for each parameter. The code below exemplifies usage:

my @list = 1, 2, 3;
sub explode-parameters($one, $two, $three) { 
…do something…
}
#traditional call 
explode-parameters(@list[0], @list[1], @list[2]);
# …or using | 
explode-parameters(|@list);

Back to the business at hand — the .grep filters out the months where the 1st is a Friday, and those are our 5 weekend months. So the output of the one-liner above looks something like this:

...
1997-08-01
1998-05-01
1999-01-01
...

This is a solution as good as any, and if a solution was all we wanted, we could have stopped here. But using this task as an example I want to explore ways to utilise the Date class. Example: The one-liner above does the job, but strictly speaking it doesn’t output the months but the first day of those months. Correcting this is easy, because the Date class supports something called formatters and use the sprintf syntax. To do this you utilise the named parameter “formatter” when instantiating the object.

say join "\n", grep *.day-of-week == 5, map { Date.new: |$_, 1, formatter => { sprintf "%04d/%02d", .year, .month } }, do 1900..2019 X 1,3,5,7,8,10,12;

Every time a routine pulls a stringified version of the date, the formatter object is invoked. In our case the output has been changed to…

...
1997/08
1998/05
1999/01
...

Formatters are powerful. Look into them.

Now to the overly complex solution. This is the unthinking programmer’s solution, as we don’t suppose anything. The program isn’t told that 5 weekend months only can occur on 31 day months. It doesn’t know that the 1st of such months must be a Friday. All it knows is that if the last day of the month is not Sunday, it figures out the date of the last Sunday (this is not very relevant when counting three-day weekends, but could be if you want to find Saturday+Sunday weekends, or only Sundays).

#!/usr/bin/env perl6
my $format-it = sub ($self) {
sprintf "%04d month %02d", .year, .month given $self;
}
sub MAIN(Int :$from-year = 1900, Int :$to-year where * > $from-year = 2019, Int :$weekend-length where * ~~ 1..3 = 3) {
my $date-loop = Date.new($from-year, 1, 1, formatter => $format-it);
while ($date-loop.year <= $to-year) {
my $date = $date-loop.later(day => $date-loop.days-in-month);
$date = $date.truncated-to('week').pred if $date.day-of-week != 7;
my @weekend = do for 0..^$weekend-length -> $w {
$date.earlier(day => $w).weekday-of-month;
};
say $date-loop if ([+] @weekend) / @weekend == 5;
$date-loop = $date-loop.later(:1month);
}
}

This code can solve the task both for three day weekends, but also for weekends consisting of Saturday + Sunday, as well as only Sundays. You control that with the command line parameter weekend-length=[1..3].

This code finds the last Sunday of each month and counts whether it has occured five times that month. It does the same for Saturday (if weekend-length=2) and Friday (if weekend-length=3). Like this:

my @weekend = do for 0..^$weekend-length -> $w { 
$date.earlier(day => $w).weekday-of-month;
};

The code then calculcates the average weekday-of-month for these three days like this:

say $date-loop if ([+] @weekend) / @weekend == 5;

This line uses the reduction operator [+] on the @weekend list to find the sum of all elements. That sum is divided by the number of elements. If the result is 5, then you have a five day weekend.

As for fun stuff to do with the Date object:

.later(day|month|year => Int) — adds the given number of time units to the current date. There’s also an earlier method for subtracting.

.days-in-months — tells you how many days there are in the current month of the Date object. The value may be 31, 30, 29 (february, leap year) or 28 (february).

.truncated-to(week|month|day|year) — rolls the date back to the first day of the week, month, day or year.

.weekday-of-month — figures out what day of week the current date is and calculates how many of that day there has been so far in that month.

Apart from this you’ll see that I added the formatter in a different way this time. This is probably cleaner looking and easier to maintain.

In the end this post maybe isn’t about dates and date manipulation at all, but rather is a call for all of us to use the documentation even more. It’s often I think that Perl 6 should have a function for x, y or z — .weekday-of-month is one such example — and the documentation tells me that it actually does!

It’s very easy to pick up Perl 6 and program it as you would have programmed Perl 5 or other languages you know well. But the documentation has lots of info of things you didn’t have before and that will make programming easier and more fun when you’ve learnt about them.

I guess you don’t need and excuse to delve into the docs, but if you do the Perl Weekly Challenge is an excellent excuse for spending time in the docs!

Jo Christian Oterhals: You have several options besides do. You could use parenthesises instead, like this:

Published by Jo Christian Oterhals on 2019-08-01T07:34:44

You have several options besides do. You could use parenthesises instead, like this:

say join "\n", grep *.day-of-week == 5, map { Date.new: |$_, 1 }, (1900..2019 X 1,3,5,7,8,10,12);

In this case I just thought the code looked better without parenthesises, so I chose to use do instead. The docs has a couple of sentences about this option here.

BTW, I chose the form Date.new: blah — the colon variant — instead of Date.new(blah) also because I wanted to avoid parenthesises. This freedom to chose is the essence of Perl’s credo “There’s more than one way to do it” I guess.

Rant: This freedom of choice is the best thing with Perl 6, but it has a downside too. Code can be harder to understand if you’re not familiar with the variants another programmer has made. This is a part of the Perls’s reputation of being write-only languages.

It won’t happen, but personally I’d like to see someone analyse real-world Perl 6 code (public repositories on Github for instance) and figure what forms are used most. The analysis could have been used to clean house — figuring out what forms to keep and which should be removed. Perl 6 would become a smaller — and arguably easier — language while staying just as powerful as it is today.

my Timotimo \this: A Close Look At Controlling The MoarVM Profiler

Published by Timo Paulssen on 2019-05-22T14:41:13

A Close Look At Controlling The MoarVM Profiler

This is slightly tangential to the Rakudo Perl 6 Performance Analysis Tooling grant from The Perl Foundation, but it does interact closely with it, so this is more or less a progress report.

The other day, Jonathan Worthington of Edument approached me with a little paid Job: Profiling very big codebases can be tedious, especially if you're interested in only one specific fraction of the program. That's why I got the assignment to make the profiler "configurable". On top of that, the Comma IDE will get native access to this functionality.

The actual request was just to allow specifying whether individual routines should be included in the profile via a configuration file. That would have been possible with just a simple text file that contains one filename/line number/routine name per line. However, I have been wanting something in MoarVM that allows much more involved configuration for many different parts of the VM, not just the profiler.

A Close Look At Controlling The MoarVM Profiler
Obligatory cat photo.

That's why I quickly developed a small and simple "domain-specific language" for this and similar purposes.

The language had a few requirements:

There's also some things that aren't necessary:

While thinking about what exactly I should build – before I eventually settled on building a "programming language" for this task – I bounced back and forth between the simplest thing that could possibly work (for example, a text file with a list of file/line/name entries) and the most powerful thing that I can implement in a sensible timeframe (for example, allowing a full NQP script). A very important realization was that as long as I require the first line to identify what "version" of configuration program it is, I could completely throw away the current design and put something else instead, if the need ever arises. That allowed me to actually commit to a design that looked at least somewhat promising. And so I got started on what I call confprog.

Here's an example program. It doesn't do very much, but shows what it's about in general:

version = 1
entry profiler_static:
log = sf.name;
profile = sf.name eq "calculate-strawberries"
profile |= sf.cu.filename eq "CustomCode.pm6"

The entry decides which stage of profiling this program is applied to. In this case, the profiler_static means we're seeing a routine for the first time, before it is actually entered. That's why only the information every individual invocation of the frame in question shares is available via the variable sf, which stands for Static Frame. The Static Frame also allows access to the Compilation Unit (cu) that it was compiled into, which lets us find the filename.

The first line that actually does something assigns a value to the special variable log. This will output the name of the routine the program was invoked for.

The next line will turn on profiling only if the name of the routine is "calculate-strawberries". The line after that will also turn on profiling if the filename the routine is from is "CustomCode.pm6".

Apart from profiler_static, there are a couple more entry points available.

The syntax is still subject to change, especially before the whole thing is actually in a released version of MoarVM.

There is a whole lot of other things I could imagine being of interest in the near or far future. One place I'm taking inspiration from is where "extended Berkeley Packet Filter" (eBPF for short) programs are being used in the linux kernel and related pieces of software:

Oversimplifying a bit, BPF was originally meant for tcpdump so that the kernel doesn't have to copy all data over to the userspace process so that the decision what is interesting or not can be made. Instead, the kernel receives a little piece of code in the special BPF language (or bytecode) and can calculate the decision before having to copy anything.

eBPF programs can now also be used as a complex ruleset for sandboxing processes (with "seccomp"), to decide how network packets are to be routed between sockets (that's probably for Software Defined Networks?), what operations a process may perform on a particular device, whether a trace point in the kernel or a user-space program should fire, and so on.

So what's the status of confprog? I've written a parser and compiler that feeds confprog "bytecode" (which is mostly the same as regular moarvm bytecode) to MoarVM. There's also a preliminary validator that ensures the program won't do anything weird, or crash, when run. It is much too lenient at the moment, though. Then there's an interpreter that actually runs the code. It can already take an initial value for the "decision output value" (great name, isn't it) and it will return whatever value the confprog has set when it runs. The heap snapshot profiler is currently the only part of MoarVM that will actually try to run a confprog, and it uses the value to decide whether to take a snapshot or not.

Next up on the list of things to work on:

Apart from improvements to the confprog programming language, the integration with MoarVM lacks almost everything, most importantly installing a confprog for the profiler to decide whether a frame should be profiled (which was the original purpose of this assignment).

After that, and after building a bit of GUI for Comma, the regular grant work can resume: Flame graphs are still not visible on the call graph explorer page, and heap snapshots can't be loaded into moarperf yet, either.

Thanks for sticking with me through this perhaps a little dry and technical post. I hope the next one will have a little more excitement! And if there's interest (which you can signal by sending me a message on irc, or posting on reddit, or reaching me via twitter @loltimo, on the Perl 6 discord server etc) I can also write a post on how exactly the compiler was made, and how you can build your own compiler with Perl 6 code. Until then, you can find Andrew Shitov's presentations about making tiny languages in Perl 6 on youtube.

I hope you have a wonderful day; see you in the next one!
  - Timo

PS: I would like to give a special shout-out to Nadim Khemir for the wonderful Data::Dump::Tree module which made it much easier to see what my parser was doing. Here's some example output from another simple confprog program:

[6] @0
0 = .Label .Node @1
│ ├ $.name = heapsnapshot.Str
│ ├ $.type = entrypoint.Str
│ ├ $.position is rw = Nil
│ └ @.children = [0] @2
1 = .Op .Node @3
│ ├ $.op = =.Str
│ ├ $.type is rw = Nil
│ └ @.children = [2] @4
│   ├ 0 = .Var .Node @5
│   │ ├ $.name = log.Str
│   │ └ $.type = CPType String :stringy  @6
│   └ 1 = String Value ("we're in") @7
2 = .Op .Node @8
│ ├ $.op = =.Str
│ ├ $.type is rw = Nil
│ └ @.children = [2] @9
│   ├ 0 = .Var .Node @10
│   │ ├ $.name = log.Str
│   │ └ $.type = CPType String :stringy  §6
│   └ 1 = .Op .Node @12
│     ├ $.op = getattr.Str
│     ├ $.type is rw = CPType String :stringy  §6
│     └ @.children = [2] @14
│       ├ 0 = .Var .Node @15
│       │ ├ $.name = sf.Str
│       │ └ $.type = CPType MVMStaticFrame  @16
│       └ 1 = name.Str
3 = .Op .Node @17
│ ├ $.op = =.Str
│ ├ $.type is rw = Nil
│ └ @.children = [2] @18
│   ├ 0 = .Var .Node @19
│   │ ├ $.name = log.Str
│   │ └ $.type = CPType String :stringy  §6
│   └ 1 = String Value ("i am the confprog and i say:") @21
4 = .Op .Node @22
│ ├ $.op = =.Str
│ ├ $.type is rw = Nil
│ └ @.children = [2] @23
│   ├ 0 = .Var .Node @24
│   │ ├ $.name = log.Str
│   │ └ $.type = CPType String :stringy  §6
│   └ 1 = String Value ("  no heap snapshots for you my friend!") @26
5 = .Op .Node @27
$.op = =.Str
$.type is rw = Nil
@.children = [2] @28
0 = .Var .Node @29
    │ ├ $.name = snapshot.Str
    │ └ $.type = CPType Int :numeric :stringy  @30
1 = Int Value (0) @31

Notice how it shows the type of most things, like name.Str, as well as cross-references for things that appear multiple times, like the CPType String. Particularly useful is giving your own classes methods that specify exactly how they should be displayed by DDT. Love It!

Strangely Consistent: Refactoring the universe

Published by Carl Mäsak

I'm here to share a thing I'm working on, and chew gum; and I'm all out of gum. The purpose of this post is both to break a disagreeable silence that has befallen this blog, and to be able to geek out about a niche topic here in writing, partially sparing friends and family.

I'm currently refactoring 007's type system in a branch. Basically, ever since 007 was created, a type in 007-land has corresponded to a class/role in Perl 6, the host system that's implementing 007.

Here's what the implementation of Int looks like currently:

class Val::Int does Val {
    has Int $.value;

    method truthy {
        ?$.value;
    }
}

And here's what it looks like as I'm doing the refactor:

constant TYPE is export = {};

BEGIN {
    # ...
    TYPE<Int> = make-type "Int", :backed;
    # ...
}

So, instead of corresponding to types on the host level, all the 007 types are about to correspond to values. The former implementation was the one that felt obvious at the time (four-plus years ago), but it's become blindingly, painstakingly obvious that it really needs to be the latter.

Here's why: as soon as you want to implement class declarations in 007, in the former model you also need to bend over backwards and come up with an entirely new type in the host system. The Perl 6 code to do that looks like this:

return $.type.new(:type(EVAL qq[class :: \{
    method attributes \{ () \}
    method ^name(\$) \{ "{$name}" \}
\}]));

Which is... even someone as EVAL-positive as I wishes for a less clunky solution.

In the new model, a new class comes down to calling make-type and dropping the result in that TYPE hash. (Wait. Or not even dropping it in the TYPE hash. That hash is only for things used by 007 itself, not for user types.)

This is a refactor I've tried once before, back in 2017, but I failed back then because the code got too complicated and ran too slow. This time around I have a much better feeling.

By the way, there's also an is-type subroutine, and similarly a make-int and an is-int subroutine, and so on for every registered type. I figure why not wrap those simple things up in very short function names. So far that turns out to have been a very good decision. "Fold the language of your domain model into your code", and so on.

This is one of the things I'm doing better this time around; last time one of the problems was that each line I touched got longer and messier because there were more layers of indirection to dig through. Concerns were scattered all over the place. This time, it feels like the codebase is getting simpler thanks to those named subroutines. Maybe it can be likened to putting all your database-specific code in one place.

I sometimes get slight vertigo due to the bootstrapping aspects of this type system. One example: Object is an instance of Type, but the base class of Type is Object — a circularity. But, it turns out, if you have absolute power over the object graph, you can always bend things to your will:

BEGIN {
    TYPE<Type> = _007::Value.new(:type(__ITSELF__), slots => { name => "Type" });
    TYPE<Object> = make-type "Object";
    {
        # Bootstrap: now that we have Object, let's make it the base of Type and Object
        TYPE<Type>.slots<base> = TYPE<Object>;
        TYPE<Object>.slots<base> = TYPE<Object>;
    }
    # ...
}

I'm slightly reminded of a thing Gilad Bracha wrote once (which I can't find the exact quote for, unfortunately): that if mutual dependencies and recursive definitions are something that stump you, what you need is a healthy dose of letrec. It's twisty, yes, but it's basically a solved problem.

Like last time, I'm tackling the big task in small steps, one type at a time. I feel I've learned this from Martin Fowler's concept of asset capture. The idea is to end up back with a running system with passing tests often. I do this by replacing one old thing at a time by a new thing. Sounds obvious, but I'm actually not sure I would have been sensible enough on my own to tackle it this way, had I not known about asset capture.

One drawback is that you're sort of running the old system and the new system in parallel, as the old one is being phased out. Only once the whole thing has been asset-captured can complexity associated with the old system be completely removed.

It's a pleasant way to work. To me it's been at least a partial answer to the problem of the big rewrite. If we're free to refactor the insides, we can successively arrive at a point where the new better thing has completely replaced the old thing. The way there is allowed to be a little bit more complex (on the inside) than either endpoint. Importantly, you keep a running system throughout.

I don't have a concluding thought, except to say that I just managed to asset-capture arrays. Which is harder than it sounds, because arrays are everywhere in the compiler and the runtime.

rakudo.org: Rakudo Star Release 2019.03

Published on 2019-03-30T00:00:00

my Timotimo \this: Intermediate Progress Report: Heap Snapshots

Published by Timo Paulssen on 2019-03-22T22:22:00

Intermediate Progress Report: Heap Snapshots

Hello dear readers,

this time I don't have something finished to show off, but nevertheless I can tell you all about the work I've recently started.

The very first post on this blog already had a little bit about the heap snapshot profiler. It was about introducing a binary format to the heap snapshot profiler so that snapshots can be written out immediately after they were taken and by moarvm itself rather than by NQP code. This also made it possible to load snapshot data faster: the files contain an index that allows a big chunk of data to be split up exactly in the middle and then read and decoded by two threads in parallel.

The new format also resulted in much smaller output files, and of course reduced memory usage of turning on the profiler while running perl6 code. However, since it still captures one heap snapshot every time the GC runs, every ordinary program that runs for longer than a few minutes will accumulate quite an amount of data. Heap snapshot files (which are actually collections of multiple snapshots) can very easily outgrow a gigabyte. There would have to be another change.

Intermediate Progress Report: Heap Snapshots
Photo by Waldemar Brandt / Unsplash

Enter Compression

The new format already contained the simplest thing that you could call compression. Instead of simply writing every record to the file as it comes, records that have smaller numbers would be stored with a shorter representation. This saved a lot of space already, but not nearly as much as off-the-shelf compression techniques would.

There had to be another way to get compression than just coming up with my own compression scheme! Well, obviously I could have just implemented something that already exists. However, at the time I was discouraged by the specific requirements of the heap snapshot analyzer - the tool that reads the files to let the user interactively explore the data within it:

Normally, compression formats are not built to support easily seeking to any given spot in the uncompressed data. There was of course the possibility to compress each snapshot individually, but that would mean a whole snapshot could either only be read in with a single thread, or the compression would have to go through the whole blob and when the first splittable piece was decompressed, a thread could go off and parse it. I'm not entirely sure why I didn't go with that, perhaps I just didn't think of it back then. After all, it's already been more than a year, and my brain compresses data by forgetting stuff.

Anyway, recently I decided I'd try a regular compression format for the new moarvm heap snapshot file format. There's already a Perl 6 module named Compress::Zlib, which I first wanted to use. Writing the data out from moarvm was trivial once I linked it to zlib. Just replace fopen with gzopen, fwrite with gzwrite, fclose with gzclose and you're almost done! The compression ratio wasn't too shabby either.

When I mentioned this in the #moarvm channel on IRC, I was asked why I use zlib instead of zstd. After all, zstd usually (or always?) outperforms zlib in both compression/decompression speed and output size. The only answer I had for that was that I hadn't used the zstd C library yet, and there was not yet a Perl 6 module for it.

Figuring out zstd didn't go as smoothly as zlib, not by a long shot. But first I'd like to explain how I solved the issue of reading the file with multiple threads.

Restructuring the data

In the current binary format, there are areas for different kinds of objects that occur once per snapshot. Those are collectables and references. On top of that there are objects that are shared across snapshots: Strings that are referenced from all the other kinds of objects (for example filenames, or descriptions for references like "hashtable entry"), static frames (made up of a name like "push", an ID, a filename, and a line number), and types (made up of a repr name like VMArray, P6opaque, or CStruct and a type name like BagHash or Regex).

That resulted in a file format that has one object after the other in the given area. The heap snapshot analyzer itself then goes through these areas and splits the individual values apart, then shoves them off into a queue for another thread to actually store. Storage inside the heap analyzer consists of one array for each part of these objects. For example, there is one array of integers for all the descriptions and one array of integers for all the target collectables. The main benefit of that is not having to go through all the objects when the garbage collector runs.

The new format on the other hand puts every value of each attribute in one long string before continuing with the next attribute.

Here's how the data for static frames was laid out in the file in the previous version:

"sframes", count, name 1, uuid 1, file 1, line 1, name 2, uuid 2, file 2, line 2, name 3, uuid 3, file 3, line 3, … index data

The count at the beginning tells us how many entries we should be expecting. For collectables, types, reprs, and static frames this gives us the exact number of bytes to look for, too, since every entry has the same size. References on the other hand have a simple "compression" applied to them, which doesn't allow us to just figure out the total size by knowing the count. To offset this, the total size lives at the end in a place that can easily be found by the parser. Strings are also variable in length, but there's only a few hundred of them usually. References take up the most space in total; having four to five times as many references as there are collectables is pretty normal.

Here's how the same static frame data is laid out in the upcoming format:

"names", length, zstd(name 1, name 2, name 3, …), index data, "uuids", length, zstd(uuid 1, uuid 2, uuid 3, …), index data, "files", length, zstd(file 1, file 2, file 3, …), index data, "lines", length, zstd(line 1, line 2, line 3, …), index data

As you can see, the values for each attribute now live in the same space. Each attribute blob is compressed individually, each has a little piece of index data at the end and a length field at the start. The length field is actually supposed to hold the total size of the compressed blob, but if the heap snapshot is being output to a destination that doesn't support seeking (moving back in the file and overwriting an earlier piece of data) we'll just leave it zeroed out and rely on zstd's format being able to tell when one blob ends.

There are some benefits to this approach that I'd like to point out:

The last point, in fact, will let me put some extra fun into the files. First of all, I currently start the files with a "plain text comment" that explains what kind of file it is and how it's structured internally. That way, if someone stumbles upon this file in fifty years, they can get started finding out the contents right away!

On a perhaps more serious note, I'll put in summaries of each snapshot that MoarVM itself can just already generate while it's writing out the snapshot itself. Not only things like "total number of collectables", but also "top 25 types by size, top 25 types by count". That will actually make the heapanalyzer not need to touch the actual data until the user is interested in more specific data, like a "top 100" or "give me a thousand objects of type 'Hash'".

On top of that, why not allow the user to "edit" heap snapshots, put some comments in before sharing it to others, or maybe "bookmarking" specific objects?

All of these things will be easier to do with the new format - that's the hope at least!

Did the compression work?

I didn't actually have the patience to exhaustively measure all the details, but here's a rough ratio for comparison: One dataset I've got results in a 1.1 gigabytes big file with the current binary format, a 147 megabytes big file when using gzip and a 99 megabytes big file using zstd (at the maximum "regular" compression level - I haven't checked yet if the cpu usage isn't prohibitive for this, though).

It seems like this is a viable way forward! Allowing capture to run 10x as long is a nice thing for sure.

What comes next?

The profiler view itself in Moarperf isn't done yet, of course. I may not put in more than the simplest of features if I start on the web frontend for the heap analyzer itself.

On the other hand, there's another task that's been waiting: Packaging moarperf for simpler usage. Recently we got support for a relocatable perl6 binary merged into master. That should make it possible to create an AppImage of moarperf. A docker container should also be relatively easy to build.

We'll see what my actual next steps will be - or will have been I suppose - when I post the next update!

Thanks for reading and take care
  - Timo

brrt to the future: Reverse Linear Scan Allocation is probably a good idea

Published by Bart Wiegmans on 2019-03-21T15:52:00

Hi hackers! Today First of all, I want to thank everybody who gave such useful feedback on my last post.  For instance, I found out that the similarity between the expression JIT IR and the Testarossa Trees IR is quite remarkable, and that they have a fix for the problem that is quite different from what I had in mind.

Today I want to write something about register allocation, however. Register allocation is probably not my favorite problem, on account of being both messy and thankless. It is a messy problem because - aside from being NP-hard to solve optimally - hardware instruction sets and software ABI's introduce all sorts of annoying constraints. And it is a thankless problem because the case in which a good register allocator is useful - for instance, when there's lots of intermediate values used over a long stretch of code - are fairly rare. Much more common are the cases in which either there are trivially sufficient registers, or ABI constraints force a spill to memory anyway (e.g. when calling a function, almost all registers can be overwritten).

So, on account of this being not my favorite problem, and also because I promised to implement optimizations in the register allocator, I've been researching if there is a way to do better. And what better place to look than one of the fastest dynamic language implementations arround, LuaJIT? So that's what I did, and this post is about what I learned from that.

Truth be told, LuaJIT is not at all a learners' codebase (and I don't think it's author would claim this). It uses a rather terse style of C and lots and lots of preprocessor macros. I had somewhat gotten used to the style from hacking dynasm though, so that wasn't so bad. What was more surprising is that some of the steps in code generation that are distinct and separate in the MoarVM JIT - instruction selection, register allocation and emitting bytecode - were all blended together in LuaJIT. Over multiple backend architectures, too. And what's more - all these steps were done in reverse order - from the end of the program (trace) to the beginning. Now that's interesting...

I have no intention of combining all phases of code generation like LuaJIT has. But processing the IR in reverse seems to have some interesting properties. To understand why that is, I'll first have to explain how linear scan allocation currently works in MoarVM, and is most commonly described:

  1. First, the live ranges of program values are computed. Like the name indicates, these represent the range of the program code in which a value is both defined and may be used. Note that for the purpose of register allocation, the notion of a value shifts somewhat. In the expression DAG IR, a value is the result of a single computation. But for the purposes of register allocation, a value includes all its copies, as well as values computed from different conditional branches. This is necessary because when we actually start allocating registers, we need to know when a value is no longer in use (so we can reuse the register) and how long a value will remain in use -
  2. Because a value may be computed from distinct conditional branches, it is necessary to compute the holes in the live ranges. Holes exists because if a value is defined in both sides of a conditional branch, the range will cover both the earlier (in code order) branch and the later branch - but from the start of the later branch to its definition that value doesn't actually exist. We need this information to prevent the register allocator from trying to spill-and-load a nonexistent value, for instance.
  3. Only then can we allocate and assign the actual registers to instructions. Because we might have to spill values to memory, and because values now can have multiple definitions, this is a somewhat subtle problem. Also, we'll have to resolve all architecture specific register requirements in this step.
In the MoarVM register allocator, there's a fourth step and a fifth step. The fourth step exists to ensure that instructions conform to x86 two-operand form (Rather than return the result of an instruction in a third register, x86 reuses one of the input registers as the output register. E.g. all operators are of the form a = op(a, b)  rather than a = op(b, c). This saves on instruction encoding space). The fifth step inserts instructions that are introduced by the third step; this is done so that each instruction has a fixed address in the stream while the stream is being processed.

Altogether this is quite a bit of complexity and work, even for what is arguably the simplest correct global register allocation algorithm. So when I started thinking of the reverse linear scan algorithm employed by LuaJIT, the advantages became clear:
There are downsides as well, of course. Not knowing exactly how long a value will be live while processing it may cause the algorithm to make worse choices in which values to spill. But I don't think that's really a great concern, since figuring out the best possible value is practically impossible anyway, and the most commonly cited heuristic - evict the value that is live furthest in the future, because this will release a register over a longer range of code, reducing the chance that we'll need to evict again - is still available. (After all, we do always know the last use, even if we don't necessarily know the first definition).

Altogether, I'm quite excited about this algorithm; I think it will be a real simplification over the current implementation. Whether that will work out remains to be seen of course. I'll let you know!

brrt to the future: Something about IR optimization

Published by Bart Wiegmans on 2019-03-17T06:23:00

Hi hackers! Today I want to write about optimizing IR in the MoarVM JIT, and also a little bit about IR design itself.

One of the (major) design goals for the expression JIT was to have the ability to optimize code over the boundaries of individual MoarVM instructions. To enable this, the expression JIT first expands each VM instruction into a graph of lower-level operators. Optimization then means pattern-matching those graphs and replacing them with more efficient expressions.

As a running example, consider the idx operator. This operator takes two inputs (base and element) and a constant parameter scale and computes base+element*scale. This represents one of the operands of an  'indexed load' instruction on x86, typically used to process arrays. Such instructions allow one instruction to be used for what would otherwise be two operations (computing an address and loading a value). However, if the element of the idx operator is a constant, we can replace it instead with the addr instruction, which just adds a constant to a pointer. This is an improvement over idx because we no longer need to load the value of element into a register. This saves both an instruction and valuable register space.

Unfortunately this optimization introduces a bug. (Or, depending on your point of view, brings an existing bug out into the open). The expression JIT code generation process selects instructions for subtrees (tile) of the graph in a bottom-up fashion. These instructions represent the value computed or work performed by that subgraph. (For instance, a tree like (load (addr ? 8) 8) becomes mov ?, qword [?+8]; the question marks are filled in during register allocation). Because an instruction is always represents a tree, and because the graph is an arbitrary directed acyclic graph, the code generator projects that graph as a tree by visiting each operator node only once. So each value is computed once, and that computed value is reused by all later references.

It is worth going into some detail into why the expression graph is not a tree. Aside from transformations that might be introduced by optimizations (e.g. common subexpression elimination), a template may introduce a value that has multiple references via the let: pseudo-operator. See for instance the following (simplified) template:

(let: (($foo (load (local))))
    (add $foo (sub $foo (const 1))))

Both ADD and SUB refer to the same LOAD node


In this case, both references to $foo point directly to the same load operator. Thus, the graph is not a tree. Another case in which this occurs is during linking of templates into the graph. The output of an instruction is used, if possible, directly as the input for another instruction. (This is the primary way that the expression JIT can get rid of unnecessary memory operations). But there can be multiple instructions that use a value, in which case an operator can have multiple references. Finally, instruction operands are inserted by the compiler and these can have multiple references as well.

If each operator is visited only once during code generation, then this may introduce a problem when combined with another feature - conditional expressions. For instance, if two branches of a conditional expression both refer to the same value (represented by name $foo) then the code generator will only emit code to compute its value when it encounters the first reference. When the code generator encounters $foo for the second time in the other branch, no code will be emitted. This means that in the second branch, $foo will effectively have no defined value (because the code in the first branch is never executed), and wrong values or memory corruption is then the predictable result.

This bug has always existed for as long as the expression JIT has been under development, and in the past the solution has been not to write templates which have this problem. This is made a little easier by a feature the let: operator, in that it inserts a do operator which orders the values that are declared to be computed before the code that references them. So that this is in fact non-buggy:

(let: (($foo (load (local))) # code to compute $foo is emitted here
  (if (...)  
    (add $foo (const 1)) # $foo is just a reference
    (sub $foo (const 2)) # and here as well

The DO node is inserted for the LET operator. It ensures that the value of the LOAD node is computed before the reference in either branch


Alternatively, if a value $foo is used in the condition of the if operator, you can also be sure that it is available in both sides of the condition.

All these methods rely on the programmer being able to predict when a value will be first referenced and hence evaluated. An optimizer breaks this by design. This means that if I want the JIT optimizer to be successful, my options are:

  1. Fix the optimizer so as to not remove references that are critical for the correctness of the program
  2. Modify the input tree so that such references are either copied or moved forward
  3. Fix the code generator to emit code for a value, if it determines that an earlier reference is not available from the current block.
In other words, I first need to decide where this bug really belongs - in the optimizer, the code generator, or even the IR structure itself. The weakness of the expression IR is that expressions don't really impose a particular order. (This is unlike the spesh IR, which is instruction-based, and in which every instruction has a 'previous' and 'next' pointer). Thus, there really isn't a 'first' reference to a value, before the code generator introduces the concept. This is property is in fact quite handy for optimization (for instance, we can evaluate operands in whatever order is best, rather than being fixed by the input order) - so I'd really like to preserve it. But it also means that the property we're interested in - a value is computed before it is used in, in all possible code flow paths - isn't really expressible by the IR. And there is no obvious local invariant that can be maintained to ensure that this bug does not happen, so any correctness check may have to check the entire graph, which is quite impractical.

I hope this post explains why this is such a tricky problem! I have some ideas for how to get out of this, but I'll reserve those for a later post, since this one has gotten quite long enough. Until next time!

brrt to the future: A short post about types and polymorphism

Published by Bart Wiegmans on 2019-01-14T13:34:00

Hi all. I usually write somewhat long-winded posts, but today I'm going to try and make an exception. Today I want to talk about the expression template language used to map the high-level MoarVM instructions to low-level constructs that the JIT compiler can easily work with:

This 'language' was designed back in 2015 subject to three constraints:
Recently I've been working on adding support for floating point operations, and  this means working on the type system of the expression language. Because floating point instructions operate on a distinct set of registers from integer instructions, a floating point operator is not interchangeable with an integer (or pointer) operator.

This type system is enforced in two ways. First, by the template compiler, which attempts to check if you've used all operands correctly. This operates during development, which is convenient. Second, by instruction selection, as there will simply not be any instructions available that have the wrong combinations of types. Unfortunately, that happens at runtime, and such errors so annoying to debug that it motivated the development of the first type checker.

However, this presents two problems. One of the advantages of the expression IR is that, by virtue of having a small number of operators, it is fairly easy to analyze. Having a distinct set of operators for each type would undo that. But more importantly, there are several MoarVM instructions that are generic, i.e. that operate on integer, floating point, and pointer values. (For example, the set, getlex and bindlex instructions are generic in this way). This makes it impossible to know whether its values will be integers, pointers, or floats.

This is no problem for the interpreter since it can treat values as bags-of-bits (i.e., it can simply copy the union MVMRegister type that holds all values of all supported types). But the expression JIT works differently - it assumes that it can place any value in a register, and that it can reorder and potentially skip storing them to memory. (This saves work when the value would soon be overwritten anyway). So we need to know what register class that is, and we need to have the correct operators to manipulate a value in the right register class.

To summarize, the problem is:
There are two ways around this, and I chose to use both. First, we know as a fact for each local or lexical value in a MoarVM frame (subroutine) what type it should have. So even a generic operator like set can be resolved to a specific type at runtime, at which point we can select the correct operators. Second, we can introduce generic operators of our own. This is possible so long as we can select the correct instruction for an operator based on the types of the operands.

For instance, the store operator takes two operands, an address and a value. Depending on the type of the value (reg or num), we can always select the correct instruction (mov or movsd). It is however not possible to select different instructions for the load operator based on the type required, because instruction selection works from the bottom up. So we need a special load_num operator, but a store_num operator is not necessary. And this is true for a lot more operators than I had initially thought. For instance, aside from the (naturally generic) do and if operators, all arithmetic operators and comparison operators are generic in this way.

I realize that, despite my best efforts, this has become a rather long-winded post anyway.....

Anyway. For the next week, I'll be taking a slight detour, and I aim to generalize the two-operand form conversion that is necessary on x86. I'll try to write a blog about it as well, and maybe it'll be short and to the point. See you later!

brrt to the future: New years post

Published by Bart Wiegmans on 2019-01-06T13:15:00

Hi everybody! I recently read jnthns Perl 6 new years resolutions post, and I realized that this was an excellent example to emulate. So here I will attempt to share what I've been doing in 2018 and what I'll be doing in 2019.

In 2018, aside from the usual refactoring, bugfixing and the like:
So 2019 starts with me trying to complete the goals specified in that grant request. I've already partially completed one goal (as explained in the interim report) - ensuring that register encoding works correctly for SSE registers in DynASM. Next up is actually ensuring support for SSE (and floating point) registers in the JIT, which is surprisingly tricky, because it means introducing a type system where there wasn't really one previously. I will have more to report on that in the near future.

After that, the first thing on my list is the support for irregular register requirements in the register allocator, which should open up the possibility of supporting various instructions.

I guess that's all for now. Speak you later!

6guts: My Perl 6 wishes for 2019

Published by jnthnwrthngtn on 2019-01-02T01:35:51

This evening, I enjoyed the New Year’s fireworks display over the beautiful Prague skyline. Well, the bit of it that was between me and the fireworks, anyway. Rather than having its fireworks display at midnight, Prague puts it at 6pm on New Year’s Day. That makes it easy for families to go to, which is rather thoughtful. It’s also, for those of us with plans to dig back into work the following day, a nice end to the festive break.

Prague fireworks over Narodni Divadlo

So, tomorrow I’ll be digging back into work, which of late has involved a lot of Perl 6. Having spent so many years working on Perl 6 compiler and runtime design and implementation, it’s been fun to spend a good amount of 2018 using Perl 6 for commercial projects. I’m hopeful that will continue into 2019. Of course, I’ll be continuing to work on plenty of Perl 6 things that are for the good of all Perl 6 users too. In this post, I’d like to share some of the things I’m hoping to work on or achieve during 2019.

Partial Escape Analysis and related optimizations in MoarVM

The MoarVM specializer learned plenty of new tricks this year, delivering some nice speedups for many Perl 6 programs. Many of my performance improvement hopes for 2019 center around escape analysis and optimizations stemming from it.

The idea is to analyze object allocations, and find pieces of the program where we can fully understand all of the references that exist to the object. The points at which we can cease to do that is where an object escapes. In the best cases, an object never escapes; in other cases, there are a number of reads and writes performed to its attributes up until its escape.

Armed with this, we can perform scalar replacement, which involves placing the attributes of the object into local registers up until the escape point, if any. As well as reducing memory operations, this means we can often prove significantly more program properties, allowing further optimization (such as getting rid of dynamic type checks). In some cases, we might never need to allocate the object at all; this should be a big win for Perl 6, which by its design creates lots of short-lived objects.

There will be various code-generation and static optimizer improvements to be done in Rakudo in support of this work also, which should result in its own set of speedups.

Expect to hear plenty about this in my posts here in the year ahead.

Decreasing startup time and base memory use

The current Rakudo startup time is quite high. I’d really like to see it fall to around half of what it currently is during 2019. I’ve got some concrete ideas on how that can be achieved, including changing the way we store and deserialize NFAs used by the parser, and perhaps also dealing with the way we currently handle method caches to have less startup impact.

Both of these should also decrease the base memory use, which is also a good bit higher than I wish.

Improving compilation times

Some folks – myself included – are developing increasingly large applications in Perl 6. For the current major project I’m working on, runtime performance is not an issue by now, but I certainly feel myself waiting a bit on compiles. Part of it is parse performance, and I’d like to look at that; in doing so, I’d also be able to speed up handling of all Perl 6 grammars.

I suspect there are some good wins to be had elsewhere in the compilation pipeline too, and the startup time improvements described above should also help, especially when we pre-compile deep dependency trees. I’d also like to look into if we can do some speculative parallel compilation.

Research into concurrency safety

In Perl 6.d, we got non-blocking await and react support, which greatly improved the scalability of Perl 6 concurrent and parallel programs. Now many thousands of outstanding tasks can be juggled across just a handful of threads (the exact number chosen according to demand and CPU count).

For Perl 6.e, which is still a good way off, I’d like to having something to offer in terms of making Perl 6 concurrent and parallel programming safer. While we have a number of higher-level constructs that eliminate various ways to make mistakes, it’s still possible to get into trouble and have races when using them.

So, I plan to spend some time this year quietly exploring and prototyping in this space. Obviously, I want something that fits in with the Perl 6 language design, and that catches real and interesting bugs – probably by making things that are liable to occasionally explode in weird ways instead reliably do so in helpful ways, such that they show up reliably in tests.

Get Cro to its 1.0 release

In the 16 months since I revealed it, Cro has become a popular choice for implementing HTTP APIs and web applications in Perl 6. It has also attracted code contributions from a couple of dozen contributors. This year, I aim to see Cro through to its 1.0 release. That will include (to save you following the roadmap link):

Comma Community, and lots of improvements and features

I founded Comma IDE in order to bring Perl 6 a powerful Integrated Development Environment. We’ve come a long way since the Minimum Viable Product we shipped back in June to the first subscribers to the Comma Supporter Program. In recent months, I’ve used Comma almost daily on my various Perl 6 projects, and by this point honestly wouldn’t want to be without it. Like Cro, I built Comma because it’s a product I wanted to use, which I think is a good place to be in when building any product.

In a few months time, we expect to start offering Comma Community and Comma Complete. The former will be free of charge, and the latter a commercial offering under a subscribe-for-updates model (just like how the supporter program has worked so far). My own Comma wishlist is lengthy enough to keep us busy for a lot more than the next year, and that’s before considering things Comma users are asking for. Expect plenty of exciting new features, as well as ongoing tweaks to make each release feel that little bit nicer to use.

Speaking, conferences, workshops, etc.

This year will see me giving my first keynote at a European Perl Conference. I’m looking forward to being in Riga again; it’s a lovely city to wander around, and I remember having some pretty nice food there too. The keynote will focus on the concurrent and parallel aspects of Perl 6; thankfully, I’ve still a good six months to figure out exactly what angle I wish to take on that, having spoken on the topic many times before!

I also plan to submit a talk or two for the German Perl Workshop, and will probably find the Swiss Perl Workshop hard to resist attending once more. And, more locally, I’d like to try and track down other Perl folks here in Prague, and see if I can help some kind of Praha.pm to happen again.

I need to keep my travel down to sensible levels, but might be able to fit in the odd other bit of speaking during the year, if it’s not too far away.

Teaching

While I want to spend most of my time building stuff rather than talking about it, I’m up for the occasional bit of teaching. I’m considering pitching a 1-day Perl 6 concurrency workshop to the Riga organizers. Then we’ll see if there’s enough folks interested in taking it. It’ll cost something, but probably much less than any other way of getting a day of teaching from me. :-)

So, down to work!

Well, a good night’s sleep first. :-) But tomorrow, another year of fun begins. I’m looking forward to it, and to working alongside many wonderful folks in the Perl community.

rakudo.org: Rakudo Star Release 2018.10

Published on 2018-11-11T00:00:00

Perlgeek.de: Perl 6 Coding Contest 2019: Seeking Task Makers

Published by Moritz Lenz on 2018-11-10T23:00:01

I want to revive Carl Mäsak's Coding Contest as a crowd-sourced contest.

The contest will be in four phases:

For the first phase, development of tasks, I am looking for volunteers who come up with coding tasks collaboratively. Sadly, these volunteers, including myself, will be excluded from participating in the second phase.

I am looking for tasks that ...

This is non-trivial, so I'd like to have others to discuss things with, and to come up with some more tasks.

If you want to help with task creation, please send an email to [email protected], stating your intentions to help, and your freenode IRC handle (optional).

There are other ways to help too:

In these cases you can use the same email address to contact me, or use IRC (moritz on freenode) or twitter.

6guts: Speeding up object creation

Published by jnthnwrthngtn on 2018-10-06T22:59:11

Recently, a Perl 6 object creation benchmark result did the rounds on social media. This Perl 6 code:

class Point {
    has $.x;
    has $.y;
}
my $total = 0;
for ^1_000_000 {
    my $p = Point.new(x => 2, y => 3);
    $total = $total + $p.x + $p.y;
}
say $total;

Now (on HEAD builds of Rakudo and MoarVM) runs faster than this roughly equivalent Perl 5 code:

use v5.10;

package Point;

sub new {
    my ($class, %args) = @_;
    bless \%args, $class;
}

sub x {
    my $self = shift;
    $self->{x}
}

sub y {
    my $self = shift;
    $self->{y}
}

package main;

my $total = 0;
for (1..1_000_000) {
    my $p = Point->new(x => 2, y => 3);
    $total = $total + $p->x + $p->y;
}
say $total;

(Aside: yes, I know there’s no shortage of libraries in Perl 5 that make OO nicer than this, though those I tried also made it slower.)

This is a fairly encouraging result: object creation, method calls, and attribute access are the operational bread and butter of OO programming, so it’s a pleasing sign that Perl 6 on Rakudo/MoarVM is getting increasingly speedy at them. In fact, it’s probably a bit better at them than this benchmark’s raw numbers show, since:

While dealing with Int values got faster recently, it’s still really making two Int objects every time around that loop and having to GC them later. An upcoming new set of analyses and optimizations will let us get rid of that cost too. And yes, startup will get faster with time also. In summary, while Rakudo/MoarVM is now winning that benchmark against Perl 5, there’s still lots more to be had. Which is a good job, since the equivalent Python and Ruby versions of that benchmark still run faster than the Perl 6 one.

In this post, I’ll look at the changes that allowed this benchmark to end up faster. None of the new work was particularly ground-breaking; in fact, it was mostly a case of doing small things to make better use of optimizations we already had.

What happens during construction?

Theoretically, the default new method in turn calls bless, passing the named arguments along. The bless method then creates an object instance, followed by calling BUILDALL. The BUILDALL method goes through the set of steps needed for constructing the object. In the case of a simple object like ours, that involves checking if an x and y named argument were passed, and if so assigning those values into the Scalar containers of the object attributes.

For those keeping count, that’s at least 3 method calls (newbless, and BUILDALL).

However, there’s a cheat. If bless wasn’t overridden (which would be an odd thing to do anyway), then the default new could just call BUILDALL directly anyway. Therefore, new looks like this:

multi method new(*%attrinit) {
    nqp::if(
      nqp::eqaddr(
        (my $bless := nqp::findmethod(self,'bless')),
        nqp::findmethod(Mu,'bless')
      ),
      nqp::create(self).BUILDALL(Empty, %attrinit),
      $bless(|%attrinit)
    )
}

The BUILDALL method was originally a little “interpreter” that went through a per-object build plan stating what needs to be done. However, for quite some time now we’ve instead compiled a per-class BUILDPLAN method.

Slurpy sadness

To figure out how to speed this up, I took a look at how the specializer was handling the code. The answer: not so well. There were certainly some positive moments in there. Of note:

However, the new method was getting only a “certain” specialization, which is usually only done for very heavily polymorphic code. That wasn’t the case here; this program clearly constructs overwhelmingly one type of object. So what was going on?

In order to produce an “observed type” specialization – the more powerful kind – it needs to have data on the types of all of the passed arguments. And for the named arguments, that was missing. But why?

Logging of passed argument types is done on the callee side, since:

The argument logging was done as the interpreter executed each parameter processing instruction. However, when there’s a slurpy, then it would just swallow up all the remaining arguments without logging type information. Thus the information about the argument types was missing and we ended up with a less powerful form of specialization.

Teaching the slurpy handling code about argument logging felt a bit involved, but then I realized there was a far simpler solution: log all of the things in the argument buffer at the point an unspecialized frame is being invoked. We’re already logging the entry to the call frame at that point anyway. This meant that all of the parameter handling instructions got a bit simpler too, since they no longer had logging to do.

Conditional elimination

Having new being specialized in a more significant way was an immediate win. Of note, this part:

      nqp::eqaddr(
        (my $bless := nqp::findmethod(self,'bless')),
        nqp::findmethod(Mu,'bless')
      ),

Was quite interesting. Since we were now specializing on the type of self, then the findmethod could be resolved into a constant. The resolution of a method on the constant Mu was also a constant. Therefore, the result of the eqaddr (same memory address) comparison of two constants should also have been turned into a constant…except that wasn’t happening! This time, it was simple: we just hadn’t implemented folding of that yet. So, that was an easy win, and once done meant the optimizer could see that the if would always go a certain way and thus optimize the whole thing into the chosen branch. Thus the new method was specialized into something like:

multi method new(*%attrinit) {
    nqp::create(self).BUILDALL(Empty, %attrinit),
}

Further, the create could be optimized into a “fast create” op, and the relatively small BUILDALL method could be inlined into new. Not bad.

Generating simpler code

At this point, things were much better, but still not quite there. I took a look at the BUILDALL method compilation, and realized that it could emit faster code.

The %attrinit is a Perl 6 Hash object, which is for the most part a wrapper around the lower-level VM hash object, which is the actual hash storage. We were, curiously, already pulling this lower-level hash out of the Hash object and using the nqp::existskey primitive to check if there was a value, but were not doing that for actually accessing the value. Instead, an .AT-KEY('x') method call was being done. While that was being handled fairly well – inlined and so forth – it also does its own bit of existence checking. I realized we could just use the nqp::atkey primitive here instead.

Later on, I also realized that we could do away with nqp::existskey and just use nqp::atkey. Since a VM-level null is something that never exists in Perl 6, we can safely use it as a sentinel to mean that there is no value. That got us down to a single hash lookup.

By this point, we were just about winning the benchmark, but only by a few percent. Were there any more easy pickings?

An off-by-one

My next surprise was that the new method didn’t get inlined. It was within the size limit. There was nothing preventing it. What was going on?

Looking closer, it was even worse than that. Normally, when something is too big to be inlined, but we can work out what specialization will be called on the target, we do “specialization linking”, indicating which specialization of the code to call. That wasn’t happening. But why?

Some debugging later, I sheepishly fixed an off-by-one in the code that looks through a multi-dispatch cache to see if a particular candidate matches the set of argument types we have during optimization of a call instruction. This probably increased the performance of quite a few calls involving passing named arguments to multi-methods – and meant new was also inlined, putting us a good bit ahead on this benchmark.

What next?

The next round of performance improvements – both to this code and plenty more besides – will come from escape analysis, scalar replacement, and related optimizations. I’ve already started on that work, though expect it will keep me busy for quite a while. I will, however, be able to deliver it in stages, and am optimistic I’ll have the first stage of it ready to talk about – and maybe even merge – in a week or so.

brrt to the future: A future for fork(2)

Published by Bart Wiegmans on 2018-10-03T22:18:00

Hi hackers. Today I want to write about a new functionality that I've been developing for MoarVM that has very little to do with the JIT compiler. But it is still about VM internals so I guess it will fit.

Many months ago, jnthn wrote a blog post on the relation between perl 5 and perl 6. And as a longtime and enthusiastic perl 5 user - most of the JIT's compile time support software is written in perl 5 for a reason - I wholeheartedly agree with the 'sister language' narrative. There is plenty of room for all sorts of perls yet, I hope. Yet one thing kept itching me:
Moreover, it’s very much the case that Perl 5 and Perl 6 make different trade-offs. To pick one concrete example, Perl 6 makes it easy to run code across multiple threads, and even uses multiple threads internally (for example, performing optimization and JIT compilation on a background thread). Which is great…except the only winning move in a game involving both threads and fork() is not to play. Sometimes one just can’t have their cake and eat it, and if you’re wanting a language that more directly gives you your POSIX, that’s probably always going to be a strength of Perl 5 over Perl 6.
(Emphasis mine). You see, I had never realized that MoarVM couldn't implement fork(), but it's true. In POSIX systems, a fork()'d child process inherits the full memory space, as-is, from its parent process. But it inherits only the forking thread. This means that any operations performed by any other thread, including operations that might need to be protected by a mutex (e.g. malloc()), will be interrupted and unfinished (in the child process). This can be a problem. Or, in the words of the linux manual page on the subject:

       *  The child process is created with a single thread—the one that
called fork(). The entire virtual address space of the parent is
replicated in the child, including the states of mutexes,
condition variables, and other pthreads objects; the use of
pthread_atfork(3) may be helpful for dealing with problems that
this can cause.

* After a fork() in a multithreaded program, the child can safely
call only async-signal-safe functions (see signal-safety(7)) until
such time as it calls execve(2).

Note that the set of signal-safe functions is not that large, and excludes all memory management functions. As noted by jnthn, MoarVM is inherently multithreaded from startup, and will happily spawn as many threads as needed by the program. It also uses malloc() and friends rather a lot. So it would seem that perl 6 cannot implement POSIX fork() (in which both parent and child program continue from the same position in the program) as well as perl 5 can.

I was disappointed. As a longtime (and enthusiastic) perl 5 user, fork() is one of my favorite concurrency tools. Its best feature is that parent and child processes are isolated by the operating system, so each can modify its own internal state without concern for concurrency,. This can make it practical to introduce concurrency after development, rather than designing it in from the start. Either process can crash while the other continues. It is also possible (and common) to run a child process with reduced privileges relative to the parent process, which isn't possible with threads. And it is possible to prepare arbitrarily complex state for the child process, unlike spawn() and similar calls.

Fortunately all hope isn't necessarily lost. The restrictions listed above only apply if there are multiple threads active at the moment that fork() is executed. That means that if we can stop all threads (except for the one planning to fork) before actually calling fork(), then the child process can continue safely. That is well within the realm of possibility, at least as far as system threads are concerned.

The process itself isn't very exciting to talk about, actually - it involves sending stop signals to system threads, waiting for these threads to join, verifying that the forking thread is the really only active thread, and restarting threads after fork(). Because of locking, it is a bit subtle (tbere may be another user thread that is also trying to fork), but not actually very hard. When I finally merged the code, it turned out that an ancient (and forgotten) thread list modification function was corrupting the list by not being aware of generational garbage collection... oops. But that was simple enough to fix (thanks to timotimo++ for the hint).

And now the following oneliner should work on platforms that support fork():(using development versions of MoarVM and Rakudo):

perl6 -e 'use nqp; my $i = nqp::fork(); say $i;'

The main limitation of this work is that it won't work if there are any user threads active. (If there are any, nqp::fork() will throw an exception). The reason why is simple: while it is possible to adapt the system threads so that I can stop them on demand, user threads may be doing arbitrary work, hold arbitrary locks and may be blocked (possibly indefinitely) on a system call. So jnthn's comment at the start of this post still applies - threads and fork() don't work together.

In fact, many programs may be better off with threads. But I think that languages in the perl family should let the user make that decision, rather than the VM. So I hope that this will find some use somewhere. If not, it was certainly fun to figure out. Happy hacking!


PS: For the curious, I think there may in fact be a way to make fork() work under a multithreaded program, and it relies on the fact that MoarVM has a multithreaded garbage collector. Basically, stopping all threads before calling fork() is not so different from stopping the world during the final phase of garbage collection. And so - in theory - it would be possible to hijack the synchronization mechanism of the garbage collector to pause all threads. During interpretation, and in JIT compiled code, each thread periodically checks if garbage collection has started. If it has, it will synchronize with the thread that started GC in order to share the work. Threads that are currently blocked (on a system call, or on acquiring a lock) mark themselves as such, and when they are resumed always check the GC status. So it is in fact possible to force MoarVM into a single active thread even with multiple user threads active. However, that still leaves cleanup to deal with, after returning from fork() in the child process. Also, this will not work if a thread is blocked on NativeCall. Altogether I think abusing the GC in order to enable a fork() may be a bit over the edge of insanity :-)

6guts: Eliminating unrequired guards

Published by jnthnwrthngtn on 2018-09-29T19:59:28

MoarVM’s optimizer can perform speculative optimization. It does this by gathering statistics as the program is interpreted, and then analyzing them to find out what types and callees typically show up at given points in the program. If it spots there is at least a 99% chance of a particular type showing up at a particular program point, then it will optimize the code ahead of that point as if that type would always show up.

Of course, statistics aren’t proofs. What about the 1% case? To handle this, a guard instruction is inserted. This cheaply checks if the type is the expected one, and if it isn’t, falls back to the interpreter. This process is known as deoptimization.

Just how cheap are guards?

I just stated that a guard cheaply checks if the type is the expected one, but just how cheap is it really? There’s both direct and indirect costs.

The direct cost is that of the check. Here’s a (slightly simplified) version of the JIT compiler code that produces the machine code for a type guard.

/* Load object that we should guard */
| mov TMP1, WORK[obj];
/* Get type table we expect and compare it with the object's one */
MVMint16 spesh_idx = guard->ins->operands[2].lit_i16;
| get_spesh_slot TMP2, spesh_idx;
| cmp TMP2, OBJECT:TMP1->st;
| jne >1;
/* We're good, no need to deopt */
| jmp >2;
|1:
/* Call deoptimization handler */
| mov ARG1, TC;
| mov ARG2, guard->deopt_offset;
| mov ARG3, guard->deopt_target;
| callp &MVM_spesh_deopt_one_direct;
/* Jump out to the interpreter */
| jmp ->exit;
|2:

Where get_spesh_slot is a macro like this:

|.macro get_spesh_slot, reg, idx;
| mov reg, TC->cur_frame;
| mov reg, FRAME:reg->effective_spesh_slots;
| mov reg, OBJECTPTR:reg[idx];
|.endmacro

So, in the case that the guard matches, it’s 7 machine instructions (note: it’s actually a couple more because of something I omitted for simplicity). Thus there’s the cost of the time to execute them, plus the space they take in memory and, especially, the instruction cache. Further, one is a conditional jump. We’d expect it to be false most of the time, and so the CPU’s branch predictor should get a good hit rate – but branch predictor usage isn’t entirely free of charge either. Effectively, it’s not that bad, but it’s nice to save the cost if we can.

The indirect costs are much harder to quantify. In order to deoptimize, we need to have enough state to recreate the world as the interpreter expects it to be. I wrote on this topic not so long ago, for those who want to dive into the detail, but the essence of the problem is that we may have to retain some instructions and/or forgo some optimizations so that we are able to successfully deoptimize if needed. Thus, the presence of a guard constrains what optimizations we can perform in the code around it.

Representation problems

A guard instruction in MoarVM originally looked like:

sp_guard r(obj) sslot uint32

Where r(obj) is an object register to read containing the object to guard, the sslot is a spesh slot (an entry in a per-block constant table) containing the type we expect to see, and the uint32 indicates the target address after we deoptimize. Guards are inserted after instructions for which we had gathered statistics and determined there was a stable type. Things guarded include return values after a call, reads of object attributes, and reads of lexical variables.

This design has carried us a long way, however it has a major shortcoming. The program is represented in SSA form. Thus, an invoke followed by a guard might look something like:

invoke r6(5), r4(2)
sp_guard r6(5), sslot(42), litui32(64)

Where r6(5) has the return value written into it (and thus is a new SSA version of r6). We hold facts about a value (if it has a known type, if it has a known value, etc.) per SSA version. So the facts about r6(5) would be that it has a known type – the one that is asserted by the guard.

The invoke itself, however, might be optimized by performing inlining of the callee. In some cases, we might then know the type of result that the inlinee produces – either because there was a guard inside of the inlined code, or because we can actually prove the return type! However, since the facts about r6(5) were those produced by the guard, there was no way to talk about what we know of r6(5) before the guard and after the guard.

More awkwardly, while in the early days of the specializer we only ever put guards immediately after the instructions that read values, more recent additions might insert them at a distance (for example, in speculative call optimizations and around spesh plugins). In this case, we could not safely set facts on the guarded register, because those might lead to wrong optimizations being done prior to the guard.

Changing of the guards

Now a guard instruction looks like this:

sp_guard w(obj) r(obj) sslot uint32

Or, concretely:

invoke r6(5), r4(2)
sp_guard r6(6), r6(5), sslot(42), litui32(64)

That is to say, it introduces a new SSA version. This means that we get a way to talk about the value both before and after the guard instruction. Thus, if we perform an inlining and we know exactly what type it will return, then that type information will flow into the input – in our example, r6(5) – of the guard instruction. We can then notice that the property the guard wants to assert is already upheld, and replace the guard with a simple set (which may itself be eliminated by later optimizations).

This also solves the problem with guards inserted away from the original write of the value: we get a new SSA version beyond the guard point. This in turn leads to more opportunities to avoid repeated guards beyond that point.

Quite a lot of return value guards on common operations simply go away thanks to these changes. For example, in $a + $b, where $a and $b are Int, we will be able to inline the + operator, and we can statically see from its code that it will produce an Int. Thus, the guard on the return type in the caller of the operator can be eliminated. This saves the instructions associated with the guard, and potentially allows for further optimizations to take place since we know we’ll never deoptimize at that point.

In summary

MoarVM does lots of speculative optimization. This enables us to optimize in cases where we can’t prove a property of the program, but statistics tell us that it mostly behaves in a certain way. We make this safe by adding guards, and falling back to the general version of the code in cases where they fail.

However, guards have a cost. By changing our representation of them, so that we model the data coming into the guard and after the guard as two different SSA versions, we are able to eliminate many guard instructions. This not only reduces duplicate guards, but also allows for elimination of guards when the broader view afforded by inlining lets us prove properties that we weren’t previously able to.

In fact, upcoming work on escape analysis and scalar replacement will allow us to start seeing into currently opaque structures, such as Scalar containers. When we are able to do that, then we’ll be able to prove further program properties, leading to the elimination of yet more guards. Thus, this work is not only immediately useful, but also will help us better exploit upcoming optimizations.

6guts: Faster box/unbox and Int operations

Published by jnthnwrthngtn on 2018-09-28T22:43:55

My work on Perl 6 performance continues, thanks to a renewal of my grant from The Perl Foundation. I’m especially focusing on making common basic operations faster, the idea being that if those go faster than programs composed out of them also should. This appears to be working out well: I’ve not been directly trying to make the Text::CSV benchmark run faster, but that’s resulted from my work.

I’ll be writing a few posts in on various of the changes I’ve done. This one will take a look at some related optimizations around boxing, unboxing, and common mathematical operations on Int.

Boxing and unboxing

Boxing is taking a natively typed value and wrapping it into an object. Unboxing is the opposite: taking an object that wraps a native value and getting the native value out of it.

In Perl 6, these are extremely common. Num and Str are boxes around num and str respectively. Thus, unless dealing with natives explicitly, working with floating point numbers and strings will involve lots of box and unbox operations.

There’s nothing particularly special about Num and Str. They are normal objects with the P6opaque representation, meaning they can be mixed into. The only thing that makes them slightly special is that they have attributes marked as being a box target. This indicates the attribute out as being the one to write to or read from in a box or unbox operation.

Thus, a box operations is something like:

While unbox is:

Specialization of box and unbox

box is actually two operations: an allocation and a store. We know how to fast-path allocations and JIT them relatively compactly, however that wasn’t being done for box. So, step one was to decompose this higher-level op into the allocation and the write into the allocated object. The first step could then be optimized in the usual way allocations are.

In the unspecialized path, we first find out where to write the native value to, and then write it. However, when we’re producing a specialized version, we almost always know the type we’re boxing into. Therefore, the object offset to write to can be calculated once, and a very simple instruction to do a write at an offset into the object produced. This JITs extremely well.

There are a couple of other tricks. Binds into a P6opaque generally have to check that the object wasn’t mixed in to, however since we just allocated it then we know that can’t be the case and can skip that check. Also, a string is a garbage-collectable object, and when assigning one GC-able object into another one, we need to perform a write barrier for the sake of generational GC. However, since the object was just allocated, we know very well that it is in the nursery, and so the write barrier will never trigger. Thus, we can omit it.

Unboxing is easier to specialize: just calculate the offset, and emit a simpler instruction to load the value from there.

I’ve also started some early work (quite a long way from merge) on escape analysis, which will allow us to eliminate many box object allocations entirely. It’s a great deal easier to implement this if allocations, reads, and writes to an object have a uniform representation. By lowering box and unbox operations into these lower level operations, this eases the path to implementing escape analysis for them.

What about Int?

Some readers might have wondered why I talked about Num and Str as examples of boxed types, but not Int. It is one too – but there’s a twist. Actually, there’s two twists.

The first is that Int isn’t actually a wrapper around an int, but rather an arbitrary precision integer. When we first implemented Int, we had it always use a big integer library. Of course, this is slow, so later on we made it so any number fitting into a 32-bit range would be stored directly, and only allocate a big integer structure if it’s outside of this range.

Thus, boxing to a big integer means range-checking the value to box. If it fits into the 32-bit range, then we can write it directly, and set the flag indicating that it’s a small Int. Machine code to perform these steps is now spat out directly by the JIT, and we only fall back to a function call in the case where we need a big integer. Once again, the allocation itself is emitted in a more specialized way too, and the offset to write to is determined once at specialization time.

Unboxing is similar. Provided we’re specializing on the type of the object to unbox, then we calculate the offset at specialization time. Then, the JIT produces code to check if the small Int flag is set, and if so just reads and sign extends the value into a 64-bit register. Otherwise, it falls back to the function call to handle the real big integer case.

For boxing, however, there was a second twist: we have a boxed integer cache, so for small integers we don’t have to repeatedly allocate objects boxing them. So boxing an integer is actually:

  1. Check if it’s in the range of the box cache
  2. If so, return it from the cache
  3. Otherwise, do the normal boxing operation

When I first did these changes, I omitted the use of the box cache. It turns out, however, to have quite an impact in some programs: one benchmark I was looking at suffered quite a bit from the missing box cache, since it now had to do a lot more garbage collection runs.

So, I reinstated use of the cache, but this time with the JIT doing the range checks in the produced machine code and reading directly out of the cache in the case of a hit. Thus, in the cache hit case, we now don’t even make a single function call for the box operation.

Faster Int operations

One might wonder why we picked 32-bit integers as the limit for the small case of a big integer, and not 64-bit integers. There’s two reasons. The most immediate is that we can then use the 32 bits that would be the lower 32 of a 64-bit pointer to the big integer structure as our “this is a small integer” flag. This works reliably as pointers are always aligned to at least a 4-byte boundary, so a real pointer to a big integer structure would never have the lowest bits set. (And yes, on big-endian platforms, we swap the order of the flag and the value to account for that!)

The second reason is that there’s no portable way in C to detect if a calculation overflowed. However, out of the basic math operations, if we have two inputs that fit into a 32-bit integer, and we do them at 64-bit width, we know that the result can never overflow the 64-bit integer. Thus we can then range check the result and decide whether to store it back into the result object as 32-bit, or to store it as a big integer.

Since Int is immutable, all operations result in a newly allocated object. This allocation – you’ll spot a pattern by now – is open to being specialized. Once again, finding the boxed value to operate on can also be specialized, by calculating its offset into the input objects and result object. So far, so familiar.

However, there’s a further opportunity for improvement if we are JIT-compiling the operations to machine code: the CPU has flags for if the last operation overflowed, and we can get at them. Thus, for two small Int inputs, we can simply:

  1. Grab the values
  2. Do the calculation at 32-bit width
  3. Check the flags, and store it into the result object if no overflow
  4. If it overflowed, fall back to doing it wider and storing it as a real big integer

I’ve done this for addition, subtraction, and multiplication. Those looking for a MoarVM specializer/JIT task might like to consider doing it for some of the other operations. :-)

In summary

Boxing, unboxing, and math on Int all came with various indirections for the sake of generality (coping with mixins, subclassing, and things like IntStr). However, when we are producing type-specialized code, we can get rid of most of the indirections, resulting in being able to perform them faster. Further, when we JIT-compile the optimized result into machine code, we can take some further opportunities, reducing function calls into C code as well as taking advantage of access to the overflow flags.

samcv: Adding and Improving File Encoding Support in MoarVM

Published on 2018-09-26T00:00:00

Encodings. They may seem to some as horribly boring and bland. Nobody really wants to have to worry about the details. Encodings are how we communicate, transmit data. Their purpose is to be understood by others. When they work, nobody should even know they are there. When they don’t — and everyone can probably remember a time when they have tried to open a poorly encoded or corrupted file and been disappointed — they cannot be ignored.

Here I talk about the work I have done in the past and work still in progress to improve the support of current encodings, add new encodings, and add new features and new options to allow Perl 6 and MoarVM to support more encodings and in a way which better achieves the goals encodings were designed to solve.

Table of Contents

Which Encodings Should We Add?

I started looking at the most common encodings on the Web. We supported the two most common, UTF-8 and ISO-8859-1 but we did not support windows-1251 (Cyrillic) or ShiftJIS. This seemed like the makings of a new project so I got to work.

I decided to start with windows-1251 since it was an 8 bit encoding while Shift-JIS was a variable length one or two byte encoding (the shift in the name comes from the second byte 'shift'). While the encoding itself was simpler than Shift-JIS, I was soon realizing some issues with both windows-1251 and our already supported windows-1252 encoding.

One of the first major issues I found in windows-1252, you could create files which could not be decoded by other programs. An example of this is codepoint 0x81 (129) which does not have a mapping in the windows-1252 specification. This would cause many programs to not detect the file as windows-1252, or to fail saying the file was corrupted and could not be decoded.

While our non-8bit encodings would throw an error if asked to encode text which did not exist in that codemapping, our 8 bit encodings would happily pass through invalid codepoints, as long as they fit in 8 bits.

As I said at the start, encodings are a way for us to communicate, to exchange data and to be understood. This to me indicated a major failing. While the solution could be to never attempt to write codepoints that don’t exist in the target encoding, that was not an elegant solution and would just be a workaround.

To remedy this I had to add new ops, such as decodeconf to replace decode op, and encodeconf to replace encode (plus many others). This would allow us to specify a configuration for our encodings and allow Perl 6 to tell MoarVM if it wanted to encode strictly according to the standard or to be more lenient.

I added a new :strict option to open, encode and a few others to allow you to specify if it should be encoding strict or not strict. In the needs of backwards compatibility it still defaults to leniently encoding and decoding. Strict is planned to become the default for Perl 6 specification 6.e.

Replacements

Some of our other encodings had support for 'replacements'. If you tried to encode something that would not fit in the target encoding, this allowed you to supply a string that could be one or more characters which would but substituted instead of causing MoarVM to throw an exception.

Once I had the strictness nailed down I was able to add support for replacements so one could have the ability to write data in a strict mode while still ensuring all compatible characters would get written properly, and you did not have to choose between unstrict and writing incompatible files and strict and having the encoding or file write failing when you really needed it not to.

Shift-JIS

Encodings are not without difficulty. As with the previous encodings I talked about, Shift-JIS would not be without decisions that had to be made. With Shift-JIS, the question became, "which Shift-JIS?".

You see, there are dozens of different extensions to Shift-JIS, in addition to original Shift-JIS encoding. As a variable length encoding, most of the one byte codepoints had been taken while there were many hundreds of open and unallocated codepoints in the two byte range. This saw the wide proliferation of manufacturer specific extensions which other manufacturers may adopt while adding their own extensions to the format.

Which of the dozens of different Shift-JIS encodings should we support? I eventually decided on windows-932 because that is the standard that is used by browsers when they encounter Shift-JIS text and encompasses a great many symbols. It is the most widely used Shift-JIS format. This would allow us to support the majority of Shift-JIS encoded documents out there, and the one which web browsers use on the web. Most but not all the characters in it are compatible with the other extensions, so it seemed like it was the sensible choice.

The only notable exception to this is that windows-932 is not totally compatible with the original Shift-JIS encoding. While the original windows-932 encoding (and some extensions to it) map the ASCII’s backslash to the yen symbol ¥, windows-932 keeps it to the backslash. This was to retain better compatibility with ASCII and other formats.

UTF-16

While MoarVM had a UTF-16 encoder and decoder, it was not fully featured.

  • You could encode a string into a utf16 buffer:

    • "hello".encode('utf16') #> utf16:0x<68 65 6c 6c 6f>

  • You could decode a utf16 buffer into a string:

    • utf16.new(0x68, 0x65, 0x6C, 0x6C, 0x6F).decode('utf16') #> hello

That was about it. You couldn’t open a filehandle as UTF-16 and write to it. You couldn’t even do $fh.write: "hello".encode('utf16') as the write function did not know how to deal with writing a 16 bit buffer (it expected an 8-bit buffer).

In addition there was no streaming UTF-16 decoder, so there was no way to read a UTF-16 file. So I set out to work, first allowing us to write 16-bit buffers to a file and then being able to .print a filehandle and write text to it.

At this point I knew that I would have to confront the BOM in the room, but decided to first implement the streaming decoder and ensure all of our file handle operations worked.

The BOM in the Room

You may be noticing a theme here. You do not just implement an encoding. It does not exist in a vacuum. While there may be standards, there may be multiple standards. And those standards may or may not be followed in practice or it may not be totally straightforward.

Endianess defines which order the bytes are in a number. Big endian machines will store a 16-bit number with the larger section first, similar to how we write numbers, while little endian machines will put the smallest section first. This only matters for encoding numbers that are more than one byte. UTF-16 can be either big endian or little endian. Meaning big and little endian files will contain the same bytes, but the order is different.

Since swapping the two bytes of a 16-bit integer causes a different integer instead of an invalid one, the creators of UTF-16 knew it was not possible to determine with certainty the endianess of a 16 bit number. And so the byte order mark was created, a codepoint that would be added at the start of a file to signify which endianess the file was. Since they didn’t want to break already existing software, they used a "Zero width no-break space" (ZWNBSP) and designated that a ZWNBSP with bytes reversed would be invalid in UTF-16, a "non-character".

If the BOM was not removed, it would not be visible since it is zero width. If your program opens a file and sees a byte order mark it knew it was in the correct endianess. If it’s the "non-character" then it knew it had to swap the bytes when it read the file.

The standard states that utf16 should always use a BOM and that when reading a file as utf16 the BOM should be used to detect the endianess. It states the BOM is not passed through as it is assumed to not be part of the actual data. If it doesn’t exist then the system is supposed to decode as the endianess that the context suggests. So you get a format where you may lose the first codepoint of your file if that codepoint happens to be a zero width non-break space.

For utf16be (big endian) and utf16le (little endian) the standard states the byte order mark should not exist, and that any zero width no-break space at the start of a file is just that, and should be passed through.

Standards and practice are not identical and in practice many programs will remove a leading zero width non-break space even if set explicitly to utf16be or utf16le. I was unsure which route I should take. I looked at how Perl 5 handled it and after thinking for a long time I decided that we would follow the spec. Even though other software will get rid of any detected byte order mark, I think it’s important that if a user specifies utf16be or utf16le, they will always get back the same codepoints that they write to a file.

Current Work

I am currently working on adding support so that when you write a file in 'utf16' it will add a byte order mark, as utf16 is supposed to always have one. Until this is added you can write a file with Perl 6 on one computer using the 'utf16' encoding which will not decode correctly using the same 'utf16' setting if the two computers are of different endianess.

Since there was no functionality for writing utf-16 to a file previously, there should be no backwards compatibility issues to worry about there and we can set it to add a byte order mark if the utf16 encoder is used.

Release 2018.09

In the last release utf16, utf16le and utf16be should work, aside from utf16 not adding a byte order mark on file write. Anyone who uses utf16 and finds any issues or comments are free to email me or make an issue on the MoarVM or Rakudo issue trackers.