Hi developer folks!

Thanks to all of you who start the development with InterSystems IRIS from the basic development template!

Recently, thanks to @Dmitry Maslennikov's contributions I've updated the Dockerfile to make the development simpler, images lighter and the building process faster. And it looks more beautiful too ;)

Here is what changed:

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InterSystems Native SDK for Python is a lightweight interface to InterSystems IRIS APIs that were once available only through ObjectScript.

I'm especially interested in the ability to call ObjectScript methods, class methods, to be precise. It works, and it works great, but by default, calls only support scalar arguments: strings, booleans, integers, and floats.

But if you want to:
- Pass or return structures, such as dicts or lists
- Pass or return streams

You'll need to write some glue code or take this project (installs with pip install edpy). edpy package gives you one simple signature:

call(iris, class_name, method_name, args)

which allows you to call any ObjectScript method and get results back.

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An interesting pattern around unique indices came up recently (in internal discussion re: isc.rest) and I'd like to highlight it for the community.

As a motivating use case: suppose you have a class representing a tree, where each node also has a name, and we want nodes to be unique by name and parent node. We want each root node to have a unique name too. A natural implementation would be:

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This formation, accessible on my GitHub, will cover, in half a hour, how to read and write in csv and txt files, insert and get inside the IRIS database and a distant database using Postgres or how to use a FLASK API, all of that using the Interoperability framework using ONLY Python following the PEP8 convention.

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Adding VSCode into your IRIS container

One of the easiest ways to setup repeatable development environments is to spin up containers for them. I find that when iterating quickly, it was very convenient to host a vscode instance within my development container. Thus, I have created a quick container script to add a browser-based vscode into an IRIS container. This should work for most 2021.1+ containers. My code repository can be found here

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Contestant

Motivation

This project was thought of when I was thinking of how to let Python code deal naturally with the scalable storage and efficient retrieving mechanism given by IRIS globals, through Embedded Python.

My initial idea was to create a kind of Python dictionary implementation using globals, but soon I realized that I should deal with object abstraction first.

So, I started creating some Python classes that could wrap Python objects, storing and retrieving their data in globals, i.e., serializing and deserializing Python objects in IRIS globals.

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While reviewing our documentation for our ^pButtons (in IRIS renamed as ^SystemPerformance) performance monitoring utility, a customer told me: "I understand all of this, but I wish it could be simpler… easier to define profiles, manage them etc.".

After this session I thought it would be a nice exercise to try and provide some easier human interface for this.

The first step in this was to wrap a class-based API to the existing pButtons routine.

I was also able to add some more "features" like showing what profiles are currently running, their time remaining to run, previously running processes and more.

The next step was to add on top of this API, a REST API class.

With this artifact (a pButtons REST API) in hand, one can go ahead and build a modern UI on top of that.

For example -

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Article
Robert Cemper · Jan 2 3m read
DB Migration using SQLgateway

Thanks to @Yuri Marx we have seen a very nice example for DB migration from Postgres to IRIS.
My personal problem is the use of DBeaver as a migration tool.
Especially as one of the strengths of IRIS ( and also Caché) before is the availability of the
SQLgateways that allow access to any external Db as long as for them an access usinig 
JDBC or ODBC is available. So I extended the package to demonstrate this.

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Kidney Disease can be discovered from some parameters well known to the medical community. In this way, in order to help the medical community and computerized systems, especially AI, the scientist Akshay Singh published a very useful dataset for training ML algorithms in the detection/prediction of kidney disease. This publication can be found on the largest and best known data repository for ML, Kaggle at https://www.kaggle.com/datasets/akshayksingh/kidney-disease-dataset.

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Article
Sergey Mikhailenko · May 31 1m read
Project info chest

I think each of us has on the computer directories with photo files of relatives and friends, music albums of favorite bands and singers, as well as e-book libraries. I also have them, and I came up with the idea to implement a convenient interface for these files. You can read more about the project in the article.
And I proposed this project for the contest, maybe it will be useful to you.

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Hi Community,

Recently, I migrated a series of Objectscript repositories from XML to UDL format.
After the migration, I was a bit disappointed by the presentation on the GitLab web interface.

Since Objectscript syntax is supported by GitHub, I thought It would be also supported by GitLab. Unfortunately, the library used by GitLab to highlight the code does not have an extension to support Objectscript.

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Diabetes can be discovered from some parameters well known to the medical community. In this way, in order to help the medical community and computerized systems, especially AI, the National Institute of Diabetes and Digestive and Kidney Diseases published a very useful dataset for training ML algorithms in the detection/prediction of diabetes. This publication can be found on the largest and best known data repository for ML, Kaggle at https://www.kaggle.com/datasets/mathchi/diabetes-data-set.

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