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Git link: https://github.com/ecelg/InterSystems-IRIS-as-a-Spotify-REST-client

Recently, I come up an idea in my mind that how can I put my playlist on IRIS.🧐

At the same time, I was told to pay for my Spotify subscription💸💸... ooo.. how about to get some data from the Spotify API... so I started to do study about it.

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A benefit of using Doxygenerate is that Doxygen does more than just HTML output. Tweak the Doxyfile that tells Doxygen what to do and you can easily create a PDF. Our example MARINA application yielded a 524-page PDF. Here's what page 94 looks like:

You can browse the whole file here.

Open Exchange app
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An extension “extends” or enhances a FHIR resource or a data element in a custom way. The extension can be added to the root of a resource, such as “Patient.ethnicity” in US Core profile, and they can be added to individual elements such as HumanName, Address or Identifier.

Did you know that you can also add an extension to a primitive data type?

Primitives usually store a single item and are the most basic element in FHIR. For example: "Keren", false, 1234, 12/08/2024 etc.

For example, the patient resources might look like this:

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It's been a while since the new UI for Productions and DTL was published as a preview and I would like to know your opinions about it.

WARNING: This is a personal opinion, totally personal and not related with InterSystems Corporation.

I'm going to start with the Interoperabilty screen:

Production screen:

The style is sober and without frills, following the line of cloud services design, I like it.

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Hi, Community!

In the previous article, we introduced the Streamlit web framework, a powerful tool that enables data scientists and machine learning engineers to build interactive web applications with minimal effort. First, we explored how to install Streamlit and run a basic Streamlit app. Then, we incorporated some of Streamlit's basic commands, e.g., adding titles, headers, markdown, and displaying such multimedia as images, audio, and videos.

Later, we covered Streamlit widgets, which allow users to interact with the app through buttons, sliders, checkboxes, and more. Additionally, we examined how to display progress bars and status messages and organize the app with sidebars and containers. We also highlighted data visualization, using charts and Matplotlib figures to present data interactively.

In this article, we will cover the following topics:

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Introduction

Database performance has become a critical success factor in a modern application environment. Therefore identifying and optimizing the most resource-intensive SQL queries is essential for guaranteeing a smooth user experience and maintaining application stability.

This article will explore a quick approach to analyzing SQL query execution statistics on an InterSystems IRIS instance to identify areas for optimization within a macro-application.

Rather than focusing on real-time monitoring, we will set up a system that collects and analyzes statistics pre-calculated by IRIS once an hour. This approach, while not enabling instantaneous monitoring, offers an excellent compromise between the wealth of data available and the simplicity of implementation.

We will use Grafana for data visualization and analysis, InfluxDB for time series storage, and Telegraf for metrics collection. These tools, recognized for their power and flexibility, will allow us to obtain a clear and exploitable view.

More specifically, we will detail the configuration of Telegraf to retrieve statistics. We will also set up the integration with InfluxDB for data storage and analysis, and create customized dashboards in Grafana. This will help us quickly identify queries requiring special attention.

To facilitate the orchestration and deployment of these various components, we will employ Docker.

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My usecase is sorting and removing duplicates and getting count from a file that has json messages as a individual rows.

I am currently planning to use pandas for this purpose as its really fast. Below are the steps i am following

1) call a python function (called function) from IRIS classmethod(calling function)

2) the call python function will read the json file in a dataframe

3) perform sorting, dup removal, count in the dataframe

4) convert the dataframe into iris stream

5) return back the stream to iris calling function class method

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Article
· May 12 7m read
An Overview of Database Degrade

Introduction

Hello! In this article, I will be discussing database degrade, a type of data integrity issue one can face when using IRIS. First, I will be going over a review of the structure of IRIS databases. I'll then discuss how database degrade can manifest and common causes of degrade issues. I'll then conclude with general tips we give our customers about how to prevent or prepare for database degrade issues.

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Hi all,

I am trying to establish an HTTPS connection to a server using a %Net.HttpRequest object. I'm able to ping and curl the server via command line. The issue I am running into is that I am able to establish a connection, but something seems to be going wrong with verification from the server side. For example, if I use the CheckSSLCN method on the server, it returns this error message

ERROR #6155: Unable to verify SSL/TLS connected to correct system as no SSL certificate present for this socket. */

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The August Article Bounty on the Global Masters article caught my attention, and one of the proposed topics sounded quite interesting in regard to its future use in my teaching. So, here's what I'd like to tell my students about tables in IRIS and how they correlate with the object model.

First of all, InterSystems IRIS boasts a unified data model. This means that when you work with data, you are not locked into a single paradigm. The same data can be accessed and manipulated as a traditional SQL table, as a native object, or even as a multidimensional array (a global). It means that when you create an SQL table, IRIS automatically creates a corresponding object class. When you define an object class, IRIS automatically makes it available as an SQL table. The data itself is stored only once in IRIS's efficient multidimensional storage engine. The SQL engine and the object engine are simply different "lenses" to view and work with the same data.

First, let's look at the correlation between the relational model and the object model:

Relational Object
Table Class
Column Property
Row Object
Primary key Object Identifier

It's not always a 1:1 correlation, as you may have several tables represent one class, for example. But it's a general rule of thumb.

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Hey Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ FHIR Object Model Classes in VS Code

https://www.youtube.com/embed/e7kHwsmRY7U
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Hey Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ Security Database and Wallet - Encryption, Mirroring and More @ Global Summit 2024

https://www.youtube.com/embed/wwwnTOCT03Y
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Having been inspired with Shared code execution speed question/discussion, I dare to ask another one which is annoying me and my colleagues for several weeks.

We have a routine called Lib that comprises 200 $$-functions of 1500 code lines total. It was noticed that after calling _any_ function of another rather big routine (1900 functions, 32000 lines) the next call of $$someFunction^Lib(x) is getting 10-20% slower than previous call of the same function. This effect doesn't depend on:

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