In this article you will have access to the curated base of articles from the InterSystems Developer Community of the most relevant topics to learning InterSystems IRIS. Find top published articles ranked by Machine Learning, Embedded Python, JSON, API and REST Applications, Manage and Configure InterSystems Environments, Docker and Cloud, VSCode, SQL, Analytics/BI, Globals, Security, DevOps, Interoperability, Native API. Learn and Enjoy!

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.

M:N Relationship is a recurring object of my interest for a long time.
So the subject turns up with me repeatedly.
For this article, I found a nice example with TWO  separate M:N relationships. Some M:N².

It is not pure fiction but taken from a closer view of OEX Contests that we run on a regular base.

Globals are the core of the InterSystems IRIS for data persistence. It is flexible, allowing store JSON documents, relational data, object oriented data, OLAP cubes and custom data models, like Mindmaps. To see how to store, delete and get mindmap data using globals, follow these steps:

1. Clone/git pull the repo into any local directory

Hi Community,

This article describes the small ZPM module global-archiver.
The goal is to move a part of a global from a database to another database.

Why this package?

A typical use case is read-only data sequentially added to your database that you can never delete.
For example:

This example demonstrates the difference you may experience when you write to
Gllobals directly from Embedded Python compared to native ObjectScript.

To make this demo useful I start 2 background jobs that simply write sequentially
to a dedicated global. A common control method signals for a synchronous start.
Similar a common stop & view interrupts data feeding.

That's the principle process:

Hi developers!

As you probably noticed in IRIS 2021 the names of globals are random.

And if you create IRIS classes with DDL and want to be sure what global was created you probably would want to provide a name.

And indeed you can do it. 

Use WITH %CLASSPARAMETER DEFAULTGLOBAL='^GLobalName' in CREATE Table to make it work. Documentation. See the example below:

I have created a package to export a Global into JSON object file and to re-create it by reloading from this file   
embeddedPython refers to the new available technologies. It should be understood as a learning exercise of 
how to handle the language interfaces. Only Global nodes containing data are presented in the generated JSON file.
Differently from the previous example, this one is using embedded Python only, no ObjectScript. Therefore PURE

This package was triggered by the extra bonus points in the contest for writing the example
in embedded Python only.  Therefore PURE

I have created a package that offers a utility to load a Global into JSON object and reverse     
to create a Global from this type of JSON object. Academic refers to the structure created.
Each logical node of the Global is presented separately with all its descendants.
Even if they don't contain any stored data.

For those of you who might be new to IRIS, and even those who have used Cache or IRIS for some time but want to explore beyond its usually-assumed boundaries and practices, you might want to dive into this detailed exploration of the database engine that is at its heart, and discover just what you can really do with it, going way beyond what InterSystems have done with it for you. 

I'd like to share with you some storage features that also exist in Caché but are almost 
unknown and mostly not used. They are of course available in IRIS and gain importance
with large and distributed storage architectures.

Standard error logs in IRIS / Caché / Ensemble are written global ^ERRORS.
As this piece dates back some decades back to previous millennium its structure
is far from the typical SQL storage structures.

Making a blog using Python + IRIS Globals

Since I started to use internet (late 90's), I always had a CMS (content management system) present to make easier post
any information in a blog, social media or even an enterprise page. And later years putting all my code into github I
used to document it on a markdown file. Observing how easy could be persisting data into Intersystems IRIS with the
Native API I decided to make this application and force myself to forget a little of SQL and stay open to key-value database
model.