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 -

Fixing the terminology

A robot is not expected to be either huge or humanoid, or even material (in disagreement with Wikipedia, although the latter softens the initial definition in one paragraph and admits virtual form of a robot). A robot is an automate, from an algorithmic viewpoint, an automate for autonomous (algorithmic) execution of concrete tasks. A light detector that triggers street lights at night is a robot. An email software separating e-mails into “external” and “internal” is also a robot. Artificial intelligence (in an applied and narrow sense, Wikipedia interpreting it differently again) is algorithms for extracting dependencies from data. It will not execute any tasks on its own, for that one would need to implement it as concrete analytic processes (input data, plus models, plus output data, plus process control). The analytic process acting as an “artificial intelligence carrier” can be launched by a human or by a robot. It can be stopped by either of the two as well. And managed by any of them too.

InterSystems FAQ rubric

It can be obtained with a List query of the %SYS.Namespace class.

1. Create a routine like this:

Intro

For many in today's interoperability landscape, REST reigns supreme. With the overabundance of tools and approaches to REST API development, what tools do you choose and what do you need to plan for before writing any code?
This article focuses on design patterns and considerations that allow you to build highly robust, adaptive, and consistent REST APIs. Viable approaches to challenges of CORS support and authentication management will be discussed, along with various tips and tricks and best tools for all stages of REST API development. Learn about the open-source REST APIs available for InterSystems IRIS Data Platform and how they tackle the challenge of ever-increasing API complexity.
The article is a write-up for a recent webinar on the same topic.

You may have seen my series of articles on GlobalToJSON closing with Embedded Python.
And to me, Embedded means inside a Class and not PEX or other external variants.
The first variants showed that ePy is not an ultimate requirement. ISOS/COS may do it as well.
Here I try to position ePy inside IRIS.

One good thing about COVID-19 is that it taught people that online work and study are possible. I remember a week before the lockdown started, everyone said that working online was impossible, not secure, etc. And what do you know, it all became possible and "secure" in the blink of an eye. As with everything, it depends on whether a person is capable of organizing his or her day and their work or study attitude. Thus, I became a great believer in online education. As an associate professor who teaches databases, I find it beneficial to my schedule and students. One thing that studying online brings is flexibility. Another one is accepting third-party courses to grant credits to my students 😉

Considering that I'm teaching the basics of IRIS, I thought a new course, Getting Started with InterSystems IRIS for Coders, could be a relevant addition to my course. Therefore, I decided to follow the new Learning Path and see how it corresponds to my Syllabus and how many ECTS credits I can give for finishing it.

Previously, we trained our model using machine learning. However, the sample data we utilized was generated directly from insert statements.

Today, we will learn how to load this data straight from a file.

What is a portlet?

The simple answer is: a custom widget. A portlet can exist by itself on a DeepSee dashboard, it can be used along side standard DeepSee widgets, or along side other portlets. The rendering of the custom widget is completely user defined. This means you can embed a web page, create a form to perform any sort of action needed based on the data on your dashboard, use third party charting libraries, or simply display data from outside of a DeepSee cube.

How to get started

Say I have a persistent class in IRIS with an optional property EmailOptIn:

Class Person Extends %Persistent
{
Property Name As %String;
Property EmailOptIn As %Boolean;
}

I later realize that I'm doing a lot of null-checking on this property where I shouldn't need to. The solution is to make this a required property:

InterSystems IRIS provides a complete application development environment for building sophisticated data- and analytics-intensive applications that connect data and application silos. It is designed to work with all of the common development technologies in an open, standards-based fashion and supports both server-side and client-side programming.

I found myself in the not-so-comfortable situation of working with a Linux system on which someone had accidentally disabled user access to the Linux shell. HealthConnect was running, servicing hundreds of interfaces. To resolve the access issue, though, we needed to bring the host down for the application of a fix.

Without the shell, the iris command is not available to control the instance, so we were faced with the potential of shutting down the server ungracefully. We wanted to avoid that if possible ...

I already talked about GraphQL and the ways of using it in this article. Now I am going to tell you about the tasks I was facing and the results that I managed to achieve in the process of implementing GraphQL for InterSystems platforms.

What this article is about

• Generation of an AST for a GraphQL request and its validation
• Generation of documentation
• Generation of a response in the JSON format

Named parameters can be achieved with SQLAlchemy :

from sqlalchemy import create_engine, text,types,engine

_engine = create_engine('iris+emb:///')

with _engine.connect() as conn:
    rs = conn.execute(text("select :some_private_name"), {"some_private_name": 1})
    print(rs.all())

or with native api

from sqlalchemy import create_engine, text,types,engine

# set URL for SQLAlchemy
url = engine.url.URL.create('iris', username='SuperUser', password='SYS', host='localhost', port=33782, database='FHIRSERVER')

_engine = create_engine(url)

with _engine.connect() as conn:
    rs = conn.execute(text("select :some_private_name"), {"some_private_name": 1})
    print(rs.all())