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#InterSystems IRIS

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InterSystems IRIS is a Complete Data Platform
InterSystems IRIS gives you everything you need to capture, share, understand, and act upon your organization’s most valuable asset – your data.
As a complete platform, InterSystems IRIS eliminates the need to integrate multiple development technologies. Applications require less code, fewer system resources, and less maintenance.

Article
· Oct 24, 2022 4m read
Embedded Python Template

Hi developers!

Let me share with you a minimal embedded python template, that I can recommend as a starting point for any general project with InterSystems IRIS that will use embedded python.

Features:

  • Embedded Python ready;
  • Examples of 3 ways of Embedded python development;
  • VSCode development ready;
  • Docker enabled;
  • Online demo enabled;
  • ZPM First development ready.

Let's discuss the features below!

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In this post, I am going to detail how to set up a mirror using SSL, including generating the certificates and keys via the Public Key Infrastructure built in to InterSystems IRIS Data Platform. I did a similar post in the past for Caché, so feel free to check that out here if you are not running InterSystems IRIS. Much like the original, the goal of this is to take you from new installations to a working mirror with SSL, including a primary, backup, and DR async member, along with a mirrored database. I will not go into security recommendations or restricting access to the files. This is meant to just simply get a mirror up and running. Example screenshots are taken on a 2018.1.1 version of IRIS, so yours may look slightly different.

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FTP (File Transfer Protocol) is a network protocol for transmitting files over TCP/IP connections in a network (including the Internet) configured to transfer files via this protocol. In an FTP transaction, a file sender is called a local host. A file receiver involved in FTP is a remote host, and it is usually a server. Although many file transfers can be conducted using Hypertext Transfer Protocol (HTTP), FTP is still commonly used to transfer files behind the scenes for other applications, such as banking services.

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I just wrote up a quick sample to help a colleague load data into IRIS from R using RJDBC, and figured it's worth sharing here for future reference.

Ultimately it was pretty simple, aside from IRIS not liking "." in column names; the workaround is to just rename the columns. Someone better at R than me could probably provide some generic approach. smiley

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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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Hi Developers,

Python has a large and powerful ecosystem that contains thousands of libraries and packages available, especially in data science.

Therefore, I wanted to have a first try in using a recent feature of IRIS called Embedded Python, to simply import a python library called datetime, generate data with a timestamp component and persist it in InterSystems IRIS for Health Data Platform. The same will work on IRIS Data Platform as well.

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Welcome to the next chapter of my CI/CD series, where we discuss possible approaches toward software development with InterSystems technologies and GitLab.

Today, let's talk about interoperability.

Issue

When you have an active interoperability production, you have two separate process flows: a working production that processes messages and a CI/CD process flow that updates code, production configuration and system default settings.

Clearly, CI/CD process affects interoperability. But questions are:

  • What exactly happens during an update?
  • What do we need to do to minimize or eliminate production downtime during an update?
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Article
· Jul 12, 2019 2m read
Basic Database Metrics example

This is a self contained class that can be run from the Intersystems Task Scheduler which records peak usage details for databases and licenses built up throughout the day and retaining 30 days history.

To schedule the task to run every hour:

d ##class(Metrics.Task).Schedule()

You can also specify your own start time, stop time, and run interval:

d ##class(Metrics.Task).Schedule(startTime, stopTime, intervalMins)

Metrics are stored in ^Metrics in the namespace that the class resides in/is run from.

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On the Latest GlobalSummit 2022, InterSystems Introduced Cloud SQL. So, you may have lightweight InterSystems IRIS with access to SQL only. Well, what if you would still need some Interoperability features in the cloud as well? There are various solutions on the market nowadays, which offer a bunch of integration adapters out of the box and can be extended with support from the community. Some time ago, I've implemented an adapter for the Node-RED project, which can be deployed manually everywhere you want. Now I would like to introduce a new integration with my recent discovery, n8n.io

Banner image

n8n.io is a workflow automation platform, that supports over 200 different integrations out of the box and from a community, and now including InterSystems IRIS.

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Hello everyone, I’m a French student that just arrived in Prague for an academical exchange for my fifth year of engineering school and here is my participation in the interop contest.

I hadn’t much time to code since I was moving from France to Prague and I’m participating alone, so I decided to make a project that’s more like a template rather than an application.

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I am happy to share with you my first experience of using a docker container version of IRIS for Health to explore your interest in using or having a trial by taking the advantage of a docker container that is lightweight, and easy to deploy. This cookbook will go through the implementation steps using the GitHub repository called ENSDEMO written by Renan Lourenco.

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