raku = Easy | Hard

Larry Wall, the inventor of perl and raku (formerly known as perl6) coined the phrase “making the easy things easy and the hard things possible”. One way this applies is that developers are publishers and|or consumers of code. For example,

  • one programmer may write a compiler toolchain in C (or NQP) and another feed it high level language software to be complied
  • someone can write a module, someone else can use it
  • authors publish classes with defined APIs and others compose them into larger applications
  • a client-server model, where structured and scalable back-end data is accessed by web browsers using markup and reactive scripts

In general, this pattern helps system experts do the low level, tricksy stuff (parsers, VMs, threads, optimisers) and domain experts can then employ a higher level abstraction. Each can focus on their specific domain(s) of interest.

This pattern often entails the use of a powerful, low level language in the server, and a quick and flexible language in the client. You know the scene: Javascript and HTML accessing Java Object Oriented business logic and a SQL database with ACID transactions. And this asymmetric architecture has often made good sense, allowing the server to be fine tuned and type checked while still facilitating rapid application development and delivery via a variety of web / application presentations. Rust in general and the recently announced Rust rewrite of Apache come into this category

But, when these specialisations turn into silos, then barriers may arise that can hamper adaptability, speed of delivery and front-to-back consistency. That’s one reason why bridges have arisen between server and client – Javascript and Node.js being one typical response from the market.

Enter raku; like it predecessor perl, raku is a language that can ‘telescope’. From pithy one liners on the command line to deep class model introspection and mutation. Depending on the needs of the situation and the knowledge of the developer. So, raku combines an approachable on-ramp for less experienced coders and it offers power developers the keys they need to open up and adapt underlying structures to fit specialised requirements. Raku can even inline low level code (C, C++) where the limits of the language are reached. A reboot of the original perl philosophy of “making the easy things easy and the hard things possible”.

Those that follow my blog will know I am the author of Physics::Unit and Physics::Measure modules. I’m now working on Physics::Navigation — inspired by a recent theory course. This is a domain specific class library that consumes Physics::Measure and provides abstractions such as Latitude, Longitude and Bearing. My aim is primarily to have a piece of code that exercises the underlying modules in order to road test the API and to have some fun. One great benefit is that I can use it explore the clarity and power of expression that raku can bring.

It started with an example of calculating the spherical law of cosines formula (aka Haversine distance) thanks to the very informative and helpful movable type website. Code examples are based on the Rosetta Code variations.

As set out mathematically the formula to be calculated is:

a = sin²(Δφ/2) + cos φ1 ⋅ cos φ2 ⋅ sin²(Δλ/2)
d = 2 ⋅ R ⋅ asin( √a )

The example code in Java is:

public class Haversine {
    public static final double R = 6372.8; // In kilometers
    public static double haversine(double lat1, double lon1, double lat2, double lon2) {
        double dLat = Math.toRadians(lat2 - lat1);
        double dLon = Math.toRadians(lon2 - lon1);
        lat1 = Math.toRadians(lat1);
        lat2 = Math.toRadians(lat2);
 
        double a = Math.pow(Math.sin(dLat / 2),2) + Math.pow(Math.sin(dLon / 2),2) * Math.cos(lat1) * Math.cos(lat2);
        double c = 2 * Math.asin(Math.sqrt(a));
        return R * c;
    }
    public static void main(String[] args) {
        System.out.println(haversine(36.12, -86.67, 33.94, -118.40));
    }
}

In contrast, the decomposition in Raku is, the “client” ie. a method …

method haversine-dist(Position $p) {
        my \Δ = $.Δ( $p );

        my $a = sin(Δ.φ / 2)² + 
                sin(Δ.λ / 2)² * cos($.φ) * cos($p.φ);

        my $value = 2 * R * asin(sqrt($a));

        Distance.new( :$value, :units<m> )   
}   

… which is aided by the “server” ie. a class with class attributes and helper accessor methods that help partition the problem cleanly and deliver a new level of clarity, code reuse and maintainability.

class Position is export {
	has Latitude  $.lat;
	has Longitude $.long;

	# accessors for radians - φ is latitude, λ is longitude 
	method φ { +$.lat  * π / 180 }
	method λ { +$.long * π / 180 }

	method getΔ( $p ) {
		Position.new( ($p.lat - $.lat), ($p.long - $.long) )
	}
        #...
}

So hopefully, this example illustrates how a thoughtful partitioning of “client-server” code can drive conceptual clarity and productivity. Raku helps by providing:

  • strong native unicode support, for maths symbols, superscripts and so on
  • a very concise ‘no boilerplate’ class / role model to aid composition
  • super lightweight object / method / functional syntax
  • a language design that works at the symbolic level (ie character by character)

This is what I love about raku, the language that tries to fade away and to leave the resulting code speak for itself and reflect the original problem domain. In some ways the raku formulation is superior even to the original mathemetical formula.

I am very excited to learn of recent initiatives as reported in the last edition of Rakudo Weekly News 2021.04 Grant Reporting about the work by Vadim Belman on A New Release Of Cro::RPC::JSON.

This has the potential to functionally partition a program across client and server systems while retaining a consistent set of class definitions, data models and patterns with minimal remote method call overhead. I can even imagine a cadre of data scientists using this technology to create, share and exploit raku code as domain-specific programmers.

And, back to the title of this blog post, “making the easy things easy and the hard things possible”. Here’s a way to say that in raku, a Junction

enum Names <Easy Hard>;           #Map.new((Easy => 0, Hard => 1))
my \raku = Easy | Hard;           #any(Easy, Hard)
raku.^name;                       #Junction

~p6steve

3 thoughts on “raku = Easy | Hard”

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