Welcome, dear members of the community!

In this article we are going to demonstrate the great potential that IRIS/HealthConnect makes available to all its users with the use of Embedded Python and we are going to do it by developing a small production that will allow us to recognize and identify the faces present in a JPG file from some images that we will use as a reference.

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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.

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sql-embedding cover

InterSystems IRIS 2024 recently introduced the vector types.
This addition empowers developers to work with vector search, enabling efficient similarity searches, clustering, and a range of other applications.
In this article, we will delve into the intricacies of vector types, explore their applications, and provide practical examples to guide your implementation.

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By default InterSystems IRIS expose your endpoints using http, but can be necessary run https from your dev env and/or get public internet access to your app. You can buy or get a certificate and config a gateway, spending many hours or use a great public service called ngrok. Follow the steps:

1 - Run your app, I will use FHIR template as sample, see:

1.1 download the app: git clone https://github.com/intersystems-community/iris-fhir-template.git

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Article
· Mar 5, 2021 3m read
Using ECP across IRIS and Caché

Migration from Caché to IRIS can be quite a challenge if your code is grown over many years
and probably not so clean structured as you may like it. So you face the need to check your
migrated code against some reference data. A few samples might not be a problem,
but some hundred GB of data for testing might be.

A possible step could be to have your fresh code in IRIS but leave your huge datastore on Caché and connect both environments over ECP. I have created a demo project that gives you the opportunity to try this based on 2 Docker images with IRIS and with Caché connected over ECP.

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Article
· Nov 28, 2022 1m read
Use IntegratedML to 'predit' diseases

Hi Developers,

IntegratedML is a feature helps us and our teams easily implement machine learning (ML) without dedicated ML experts and data scientists. If you do not need particularly complex ML function, integratedML is a good choice and convenient that only requires executing 3 SQL queries to build predictive models directly from InterSystems IRIS to ML engine.

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Article
· Jan 10, 2023 4m read
Columnar Storage in 2022.3

As you may well remember from Global Summit 2022 or the 2022.2 launch webinar, we're releasing an exciting new capability for including in your analytics solutions on InterSystems IRIS. Columnar Storage introduces an alternative way of storing your SQL table data that offers an order-of-magnitude speedup for analytical queries. First released as an experimental feature in 2022.2, the latest 2022.3 Developer Preview includes a bunch of updates we thought were worth a quick post here.

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Our objective

Today we continue expanding our last article by sharing information about some features we added to our portal. We will include a pinch of CSS to visualize the available data better and export it. Finally, we will study how to add some filtering and ordering options. By the end of this article, you should be able to display a complete simple query beautifully.

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Killer presentations are essential for opening doors, doing business and delighting customers. These types of presentations move away from the traditional and tiring topics and portions of texts, or even pictures of happy people to get closer to the interests of their audience.The best presentations materialize what customers are looking for into something they can see working. Instead of promises, examples in execution and the ability to be very close to what you want to do.

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Article
· May 29 8m read
Integrate with Google Forms

Google Forms is the most popular solution on the market for collecting data, answering questionnaires and quizzes. So, it is the ideal solution for collecting patient data and responses in a practical way, without the need to expand or develop systems. In this article, I will detail how to create an account on Google Cloud, register the application that will consume the Google Forms API, generate the service user necessary to consume the API and finally perform actions to create new forms and collect data filled in them in an automated way in embedded Python and IRIS.

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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
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I have Mac OSX and Docker Desktop 2.2 (Engine 19.03).

I have a REST service running on my localhost (Mac) and I was trying to consume it from IRIS running in a Docker container.

If you try something like that don't use localhost as HTTP Server setting (using a Business Operation for example).

You have to use host.docker.internal.

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Article
· Nov 18, 2020 7m read
Creating a PEX Business Operation

PEX is a new InterSystems IRIS feature to allows extends IRIS with existent features from Java or .NET.

It is possible create interoperability inbound and outbound adapters, business services (integrate from external to internal) and operations (integrate internal to external).

To create a PEX component it is necessary import .NET (InterSystems.EnsLib.PEX.*) or Java (com.intersystems.enslib.pex.*) packages and extends or implements the properly class.

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Hello everyone!

We are Longevica (https://www.longevica.com/) Healthtech, a Boston-based healthy aging digital health startup. Longevica was born as a research company back in 2009; we pioneered the screening of chemicals, which would drastically extend the life span. With 1000 screened pharmaceuticals and 20 000 mice experiments, we have identified specific compounds that, if taken daily, could extend life by years. This discovery leads to two questions: how to measure the effect of aging progress in real-time and how to make this a lifelong habit. This led us to the digital health market to create a new company Longevica HealthTech.

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Article
· Jul 4, 2023 2m read
IntegratedMLandDashboardSample

A simple data analysis example created in IntegratedML and Dashboard

Based on InterSystems' Integrated ML technology and Dashboard, automatically generate relevant predictions and BI pages based on uploaded CSV files. The front and back ends are completed in Vue and Iris, allowing users to generate their desired data prediction and analysis pages with simple operations and make decisions based on them.

# ZPM installation

zpm:USER>install IntegratedMLandDashboardSample

# Process Deployment

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I recently had the need to monitor from HealthConnect the records present in a NoSQL database in the Cloud, more specifically Cloud Firestore, deployed in Firebase. With a quick glance I could see how easy it would be to create an ad-hoc Adapter to make the connection taking advantage of the capabilities of Embedded Python, so I got to work.

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Hi folks!

Often, when we develop commercial solutions, there is a necessity to deploy solutions without source code, e.g., in order to preserve the IP.

One of the ways how this can be achieved is to use InterSystems Package Manager.

Here I asked Midjourney to paint an intellectual property of software:

How this can be achieved with IPM?

In fact, this is very simple; just add the Deploy="true" clause in the Resource element in your module.xml manifest. Documentation.

I decided to provide the simplest possible example to illustrate how it works and also to give you a development environment template to let start building and deploying your own modules without source code. He we go!

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Who hasn't been developing a beautiful example using a Docker IRIS image and had the image generation process fail in the Dockerfile because the license under which the image was created doesn't contain certain privileges?

In my case, what I was deploying in Docker is a small application that uses the Vector data type. With the Community version, this isn't a problem because it already includes Vector Search and vector storage. However, when I changed the IRIS image to a conventional IRIS (the latest-cd), I found that when I built the image, including the classes it had generated, it returned this error:

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Template engines are essential for producing customizable dynamic content, without the need for compilation and opening up great possibilities of extensibility for the template user. Especially if the template engine supports Python. A popular solution for template engine is Mko. It is is a template library written in Python. It provides a familiar, non-XML syntax which compiles into Python modules for maximum performance. Mako's syntax and API borrows from the best ideas of many others, including Django and Jinja2 templates, Cheetah, Myghty, and Genshi.

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As a developer, you have probably spent at least some time writing repetetive code. You may have even found yourself wishing you could generate the code programmatically. If this sounds familiar, this article is for you!

We'll start with an example. Note: the following examples use the %DynamicObject interface, which requires Caché 2016.2 or later. If you are unfamiliar with this class, check out the documentation here: Using JSON in Caché. It's really cool!

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