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Proc::ZMQed zef:antononcube last updated on 2022-12-11

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Raku Proc::ZMQed

This package, "Proc::ZMQed", provides external evaluators (Julia, Mathematica, Python, R, etc.) via ZeroMQ (ZMQ).

Functionality-wise, a closely related Raku package is "Text::CodeProcessing", [AAp1]. For example, Raku can be used in Mathematica sessions (i.e. notebooks) with [AAp1] and [AAp2]; see [AA1] for more details. With this package, "Proc::ZMQed", we can use Mathematica in Raku sessions.

Installation

From GitHub:

zef install https://github.com/antononcube/Raku-Proc-ZMQed.git

From Zef ecosystem:

zef install Proc::ZMQed

Usage example: symbolic computation with Mathematica

Mathematica is also known as Wolfram Language (WL).

The following example shows:

Establishing connection to Wolfram Engine (which is free for developers.)
Sending a formula for symbolic algebraic expansion.
Getting the symbolic result and evaluating it as a Raku expression.

use Proc::ZMQed;

# Make object
my Proc::ZMQed::Mathematica $wlProc .= new(url => 'tcp://127.0.0.1', port => '5550');

# Start the process (i.e. Wolfram Engine)
$wlProc.start-proc;

my $cmd = 'Expand[(x+y)^4]';
my $wlRes = $wlProc.evaluate($cmd);
say "Sent : $cmd";
say "Got  :\n $wlRes";

# Send computation to Wolfram Engine
# and get the result in Fortran form.
say '-' x 120;
$cmd = 'FortranForm[Expand[($x+$y)^4]]';
$wlRes = $wlProc.evaluate($cmd);
say "Sent : $cmd";
say "Got  : $wlRes";

# Replace symbolic variables with concrete values 
my $x = 5;
my $y = 3;

use MONKEY-SEE-NO-EVAL;
say 'EVAL($wlRes) : ', EVAL($wlRes);

# Terminate process
$wlProc.terminate;

# Sent : Expand[(x+y)^4]
# Got  :
#   4      3        2  2        3    4
# x  + 4 x  y + 6 x  y  + 4 x y  + y
# ------------------------------------------------------------------------------------------------------------------------
# Sent : FortranForm[Expand[($x+$y)^4]]
# Got  : $x**4 + 4*$x**3*$y + 6*$x**2*$y**2 + 4*$x*$y**3 + $y**4
# EVAL($wlRes) : 4096

Remark: Mathematica can have variables that start with $, which is handy if we want to treat WE results as Raku expressions.

Here is a corresponding flowchart:

graph TD
  WE{{Wolfram Engine}}
  Raku{{Raku}}
  CO["Create connection object<br>(ZMQ sockets)"]
  SC[Send symbolic computation<br>to Wolfram Engine]
  AV[Assign values to symbols]
  ES[Evaluate WE output string]
  CO --> SC --> AV --> ES
  SC -.- Raku
  SC -.-> |ZMQ.send|WE
  WE -.-> |ZMQ.recv|SC
  CO -.- Raku
  AV -.- Raku
  ES -.- |EVAL|Raku

Setup

In this section we outline setup for different programming languages as "servers."

Generally, there are two main elements to figure out:

What is the concrete Command Line Interface (CLI) name to use?
- And related code option. E.g. julia -e or wolframscript -code.
Is ZMQ installed on the server system?

The CLI names can be specified with the option cli-name. The code options can be specified with code-option.

Julia

In order to setup ZMQ computations with Julia start Julia and execute the commands:

using Pkg
Pkg.add("ZMQ")
Pkg.add("JSON")

(Also, see the instructions at "Configure Julia for ExternalEvaluate".)

By default "Proc::ZMQed::Julia" uses the CLI name julia. Here is an alternative setup:

```{perl6, eval=FALSE} my Proc::ZMQed::Julia $juliaProc .= new(url => 'tcp://127.0.0.1', port => '5560', cli-name => '/Applications/Julia-1.8.app/Contents/Resources/julia/bin/julia');


### Mathematica

Install [Wolfram Engine (WE)](https://www.wolfram.com/engine/). (As it was mentioned above, WE is free for developers. WE has ZMQ functionalities "out of the box.")

Make sure `wolframscript` is installed. (This is the CLI name used with "Proc::ZMQed::Mathematica".)

### Python

Install the ZMQ library ["PyZMQ"](https://pypi.org/project/pyzmq/). For example, with:

python -m pip install --user pyzmq


By default "Proc::ZMQed::Python" uses the CLI name `python`.
Here we connect to a Python virtual environment (made and used with 
[miniforge](https://github.com/conda-forge/miniforge)):

```{perl6, eval=FALSE}
my Proc::ZMQed::Python $pythonProc .= new(url => 'tcp://127.0.0.1', 
                                          port => '5554', 
                                          cli-name => $*HOME ~ '/miniforge3/envs/SciPyCentric/bin/python');

Implementation details

The package architecture is Object-Oriented Programming (OOP) based and it is a combination of the OOP design patterns Builder, Template Method, and Strategy.

The package has a general role "Proc::ZMQed::Abstraction" that plays Abstract class in Template method. The concrete programming language of the classes provide concrete operations for:

ZMQ-server side code
Processing of setup code lines

Here is the corresponding UML diagram:

```perl6, output-lang=mermaid, output-prompt=NONE use UML::Translators; to-uml-spec(, format=>'mermaid');

```mermaid
classDiagram
class Proc_ZMQed_Julia {
  +$!cli-name
  +$!code-option
  +$!context
  +$!port
  +$!proc
  +$!receiver
  +$!url
  +BUILD()
  +BUILDALL()
  +cli-name()
  +code-option()
  +context()
  +evaluate()
  +make-code()
  +port()
  +proc()
  +process-setup-lines()
  +receiver()
  +start-proc()
  +terminate()
  +url()
}
Proc_ZMQed_Julia --|> Proc_ZMQed_Abstraction


class Proc_ZMQed_Mathematica {
  +$!cli-name
  +$!code-option
  +$!context
  +$!port
  +$!proc
  +$!receiver
  +$!url
  +BUILD()
  +BUILDALL()
  +cli-name()
  +code-option()
  +context()
  +evaluate()
  +make-code()
  +port()
  +proc()
  +process-setup-lines()
  +receiver()
  +start-proc()
  +terminate()
  +url()
}
Proc_ZMQed_Mathematica --|> Proc_ZMQed_Abstraction


class Proc_ZMQed_Python {
  +$!cli-name
  +$!code-option
  +$!context
  +$!port
  +$!proc
  +$!receiver
  +$!url
  +BUILD()
  +BUILDALL()
  +cli-name()
  +code-option()
  +context()
  +evaluate()
  +make-code()
  +port()
  +proc()
  +process-setup-lines()
  +receiver()
  +start-proc()
  +terminate()
  +url()
}
Proc_ZMQed_Python --|> Proc_ZMQed_Abstraction


class Proc_ZMQed_R {
  +$!cli-name
  +$!code-option
  +$!context
  +$!port
  +$!proc
  +$!receiver
  +$!url
  +BUILD()
  +BUILDALL()
  +cli-name()
  +code-option()
  +context()
  +evaluate()
  +make-code()
  +port()
  +proc()
  +process-setup-lines()
  +receiver()
  +start-proc()
  +terminate()
  +url()
}
Proc_ZMQed_R --|> Proc_ZMQed_Abstraction


class Proc_ZMQed_Raku {
  +$!cli-name
  +$!code-option
  +$!context
  +$!port
  +$!proc
  +$!receiver
  +$!url
  +BUILD()
  +BUILDALL()
  +cli-name()
  +code-option()
  +context()
  +evaluate()
  +make-code()
  +port()
  +proc()
  +process-setup-lines()
  +receiver()
  +start-proc()
  +terminate()
  +url()
}
Proc_ZMQed_Raku --|> Proc_ZMQed_Abstraction

(Originally, "Proc::ZMQed::Abstraction" was named "Proc::ZMQish", but the former seems a better fit for the role.)

The ZMQ connections are simple REP/REQ. It is envisioned that more complicated ZMQ patterns can be implemented in subclasses. I have to say though, that my attempts to implement "Lazy Pirate" were very unsuccessful because of the half-implemented (or missing) polling functionalities in [ASp1]. (See the comments here.)

TODO

[ ] TODO Robust, comprehensive ZMQ-related failures handling.
[ ] TODO More robust ZMQ patterns.
- Like the "Lazy Pirate" mentioned above.
[ ] TODO Implement "Proc::ZMQed::Java".
[ ] TODO Better message processing in "Proc::ZMQed::R".
[ ] TODO Verify that "Proc::ZMQed::JavaScript" is working.
- Currently, I have problems install ZMQ in JavaScript.

References

Articles

[AA1] Anton Antonov, "Connecting Mathematica and Raku", (2021), RakuForPrediction at WordPress.

Packages

[AAp1] Anton Antonov Text::CodeProcessing Raku package, (2021-2022), GitHub/antononcube.

[AAp2] Anton Antonov, RakuMode Mathematica package, (2020-2021), ConversationalAgents at GitHub/antononcube.

[ASp1] Arne Skjærholt, Net::ZMQ, (2017), GitHub/arnsholt.