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.

With the introduction of vector data types and the Vector Search functionality in IRIS, a whole world of possibilities opens up for the development of applications and an example of these applications is the one that I recently saw published in a public contest by the Ministry of Health from Valencia in which they requested a tool to assist in ICD-10 coding using AI models.

How could we implement an application similar to the one requested? Let's see what we would need:

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.

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.

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

Hello,

as it took me some time to figure out what's wrong, I would like to share this experience, so that you do not fall into the same trap.

I've just noticed that if you name your package "code" (all lowercase), in a class using some embedded python using [Language = python], you'll face the <THROW> *%Exception.PythonException <PYTHON EXCEPTION> 246 <class 'ModuleNotFoundError'>: No module named 'code.basics'; 'code' is not a package

Why am I writting this?

Last year I made an article for starters on using embedded python. Later, it started a little discussion on how to return values with python and I found some interesting observations that are worth writing a little article. Also, hopefully I can reach more people by writing this.

Possible situations

There are two things you'll need to care about when returning a value with python. The first is the type you're trying to return and the second is where you're returning it.

Hi Community,

In this article I will explain how to display management portal dashboard by using Python Flask web and Boostrap framework with the help of embedded python

Hello Community,

SQL language remains the most practical way to retrieve information stored in a database.

The JSON format is very often used in data exchange.

It is therefore common to seek to obtain data in JSON format from SQL queries.

Below you will find simple examples that can help you meet this need using ObjectScript and Python code.

ipython-iris-magic

%%iris magic for IPython, can run ObjectScript command in Notebooks

It can be run in any Notebook and does not require any special setup on IRIS or the Notebook.

Demo

Native Api

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.

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:

While starting the development with IRIS we have a distribution kit or in case of Docker we are pulling the docker image and then often we need to initialize it and setup the development environment. We might need to create databases, namespaces, turn on/off some services, create resources. We often need to import code and data into IRIS instance and run some custom code to init the solution.

And there plenty of templates on Open Exchange where we suggest how to init REST, Interoperability, Analytics, Fullstack and many other templates with ObjectScript. What if we want to use only Python to setup the development environment for Embedded Python project with IRIS?

So, the recent release of Embedded Python template is the pure python boilerplate that could be a starting point for developers that build python projects with no need to use and learn ObjectScript. This article expresses how this template could be used to initialize IRIS. Here we go!

Using embedded Python while building your InterSystems-based solution can add very powerful and deep capabilities to your toolbox.

I'd like to share one sample use-case I encountered - enabling a CDC (Change Data Capture) for a mongoDB Collection - capturing those changes, digesting them through an Interoperability flow, and eventually updating an EMR via a REST API.