In the preceding section, we explored the installation process and initiated the writing of the IRIS in native Python. We will now proceed to examine global traversal and engage with IRIS class objects.

get: this function is used to get values from the traversal node.

Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 1 - SQL Gateway

Hello

In this article we will look at the use of SQL Gateway in Iris. SQL Gateway allows Iris to have access to tables from other (external) database via ODBC or JDBC. We can access Tables or Views from various databases, such as Oracle, PostgreSQL, SQL Server, MySQL and others.

This is the third post of a series explaining how to create an end-to-end Machine Learning system.

Training a Machine Learning Model

When you work with machine learning is common to hear this work: training. Do you what training mean in a ML Pipeline?
Training could mean all the development process of a machine learning model OR the specific point in all development process
that uses training data and results in a machine learning model.

This is a translation of the following article. Thanks [@Evgeny Shvarov] for the help in translation.

This post is also available on Habrahabr^ru.

The post was inspired by this Habrahabr article: Interval-associative array^ru→en.

Since the original implementation relies on Python slices, the Caché public may find the following article useful: Everything you wanted to know about slices^ru→en.

Note: Please note that the exact functional equivalent of Python slices has never been implemented in Caché, since this functionality has never been required.

And, of course, some theory: Interval tree^ru→en.

All right, let’s cut to the chase and take a look at some examples.

Hello,

I became aware of Python in the early 2000s when I started automating tasks. Some of our processes utilized python scripts. I never figured it out very well, and we decided to do away with Python because nobody on our team was familiar with it.

Using Flask, REST API, and IAM with InterSystems IRIS

Part 3 – IAM

InterSystems API Manager (IAM) is a component that allows you to monitor, control, and manage traffic from HTTP-based APIs. It also acts as an API gateway between InterSystems IRIS applications and servers.

Hello everyone, I’m a French student in academical exchange for my fifth year of engineering school and here is my participation in the FHIR for Women's Health contest.

This project is supposed to be seen as the backend of a bigger application. It can be plugged into a Front End app and help you gather information from your patients. It will read your data in local and use a Data Transformation to make it into a FHIR object before sending it to the included local FHIR server.

This series of articles would cover Python Gateway for InterSystems Data Platforms. Execute Python code and more from InterSystems IRIS. This project brings you the power of Python right into your InterSystems IRIS environment:

• Execute arbitrary Python code
• Seamlessly transfer data from InterSystems IRIS into Python
• Build intelligent Interoperability business processes with Python Interoperability Adapter
• Save, examine, modify and restore Python context from InterSystems IRIS

Other articles

The plan for the series so far (subject to change).

• Part I: Overview, Landscape, and Introduction
• Part II: Installation and Troubleshooting
• Part III: Basic functionality
• Part IV: Interoperability Adapter
• Part V: Execute function
• Part VI: Jupyter Notebook <-- you're here
• Part VII: Dynamic Gateway
• Part VIII: Proxy Gateway
• Part IX: Use cases and ML Toolkit

Intro

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.

This extension allows you to browse and edit InterSystems IRIS BPL processes as jupyter notebooks.

Hello everyone, this is with great pleasure that I announce the V2 of my application 'Contest-FHIR'.

In this new version, I used new tools and techniques I discovered at the EUROPEAN HEALTHCARE HACKATHON in which I was invited by InterSystems as a guest and as a mentor to display the multiple projects I did in my intership back in April 2022.

Today I present to you the V2 of my application, it can now transform CSV to FHIR to SQL to JUPYTER notebook.

Introduction

To achieve optimized AI performance, robust explainability, adaptability, and efficiency in healthcare solutions, InterSystems IRIS serves as the core foundation for a project within the x-rAI multi-agentic framework. This article provides an in-depth look at how InterSystems IRIS empowers the development of a real-time health data analytics platform, enabling advanced analytics and actionable insights. The solution leverages the strengths of InterSystems IRIS, including dynamic SQL, native vector search capabilities, distributed caching (ECP), and FHIR interoperability. This innovative approach directly aligns with the contest themes of "Using Dynamic SQL & Embedded SQL," "GenAI, Vector Search," and "FHIR, EHR," showcasing a practical application of InterSystems IRIS in a critical healthcare context.

We are happy to share interesting information with you, as well as tell you why Python is good, where it is used.

Among the most used libraries are NumPy and Pandas. NumPy (Numerical Python) is used to sort large datasets. It simplifies mathematical operations and their vectorization on arrays. Pandas offers two data structures: Series (a list of elements) and Data Frames (a table with multiple columns). This library converts data into a Data Frame, allowing you to remove and add new columns, as well as perform various operations.

Continuing to observe the possibilities of Django, and usage with IRIS. The first we have looked how to define models and connect to tables already existing in IRIS, than we extended embedded Django Administration portal, with an ability to see what data we have in that models, with filters, editing and even pagination.

Time to go to real action, now we a going to create some REST API, on Django, based on the same data, we used before from the package posts-and-tags.

To do so, we will use Django REST Framework

Django REST framework is a powerful and flexible toolkit for building Web APIs.

Some reasons you might want to use REST framework:

• The Web browsable API is a huge usability win for your developers.
• Authentication policies including packages for OAuth1a and OAuth2.
• Serialization that supports both ORM and non-ORM data sources.
• Customizable all the way down - just use regular function-based views if you don't need the more powerful features.
• Extensive documentation, and great community support.
• Used and trusted by internationally recognised companies including Mozilla, Red Hat, Heroku, and Eventbrite.

Making a Chart using Intersystems IRIS + Python

How to use the IRIS Native API in Python to access globals and plot some charts.

Why Python?

With a large adoption and use in the world, Python have a great community and a lot of accelerators | libraries to deploy any kind of application.
If you are curious (https://www.python.org/about/apps/)

Headache-free stored objects: a simple example of working with InterSystems Caché objects in ObjectScript and Python

Neuschwanstein Castle

Tabular data storages based on what is formally known as the relational data model will be celebrating their 50th anniversary in June 2020. Here is an official document – that very famous article. Many thanks for it to Doctor Edgar Frank Codd. By the way, the relational data model is on the list of the most important global innovations of the past 100 years published by Forbes.

On the other hand, oddly enough, Codd viewed relational databases and SQL as a distorted implementation of his theory. For general guidance, he created 12 rules that any relational database management system must comply with (there are actually 13 rules). Honestly speaking, there is zero DBMS's on the market that observes at least Rule 0. Therefore, no one can call their DBMS 100% relational :) If you know any exceptions, please let me know.