Best Practices recommendations on how to develop, test, deploy and manage solutions on InterSystems Data Platforms better.
In the previous article we saw how we could recover a resource stored in the database of our particular HIS, so today we will see how we can add new records in our HIS whose origin is an FHIR resource that we receive in our system.
We resume our series of articles on the FHIR Adapter tool available to HealthShare HealthConnect and InterSystems IRIS users.
In the previous articles we have presented the small application on which we set up our workshop and showed the architecture deployed in our IRIS instance after installing the FHIR Adapter. In today's article we will see an example of how we can perform one of the most common CRUD (Create - Read - Update - Delete) operations, the reading operation, and we will do it by recovering a Resource.
We return with our example of using the FHIR Adapter, in this article we are going to review how we can configure it in our IRIS instances and what the result of the installation is.
The steps taken to configure the project are the same as indicated in the official documentation, you can review them directly here. Well, let's get to work!
Surely you have all heard about FHIR as the panacea and solution to all interoperability and compatibility problems between systems. Right here we can see one of his classic defenders holding a FHIR resource in his hand and enjoying it immensely:
But for the rest of us mortals we are going to make a small introduction.
Hi, developers!
Currently, I'm working on a project that requires highly dynamic event management. In the context of the Java programming language, my first instinct should be to opt for the "Observer Pattern", which is an approach to managing interactions between objects by establishing a notification mechanism. It allows multiple observers to react to changes in the state of a subject autonomously, promoting code flexibility and modularity. If you are not familiar with this design pattern, check out Wikipedia to find more information about it.
While it's natural and commonly used in certain programming languages as Java and C++, in ObjectScript, it's quite a different story.
For Microsoft Windows, please consult the InterSystems product documentation.
The IRIS installer will detect if a web server is installed on the same machine, which gives you the option to automatically have the web server configured.
All Apache installations will require sudo (recommended) or root permission to install the web server. This requirement supports recommended best practices.
In this article, I walk through the %JSON.Adaptor class. This class is extremely useful in exporting data into serialized JSON and importing the JSON objects and saves into class object.
I'll start with the %JSON. Adaptor parameters. The parameters are crucial part of the JSON import and export operations.
Here you'll find a simple program that uses Python in an IRIS environment and another simple program that uses ObjectScript in a Python environment. Also, I'd like to share a few of the troubles I went trough while learning to implement this.
Let's say, for example, you're in an IRIS environment and you want to solve a problem that you find easy, or more efficient with Python.
You can simply change the environment: create your method as any other, and in the end of it's name and specifications, you add [ Language = python ]:
This article will cover turning over control of provisioning the InterSystems Kubernetes Operator, and starting your journey managing your own "Cloud" of InterSystems Solutions through Git Ops practices. This deployment pattern is also the fulfillment path for the PID^TOO||| FHIR Breathing Identity Resolution Engine.
Hi developers!
Today I would like to address a subject that has given me a hard time. I am sure this must have been the case for quite a number of you already (so-called “the bottleneck”). Since this is a broad topic, this article will only focus on identifying incoming HTTP requests that could be causing slowness issues. I will also provide you with a small tool I have developed to help identify them.
Our software is becoming more and more complex, processing a large number of requests from different sources, be it front-end or third-party back-end applications. To ensure optimal performance, it is essential to have a logging system capable of taking a few key measurements, such as the response time, the number of global references and the number of lines of code executed for each HTTP response. As part of my work, I get involved in the development of EMR software as well as incident analysis. Since user load comes mostly from HTTP requests (REST API or CSP application), the need to have this type of measurement when generalized slowness issues occur has become obvious.
IRIS External Table is an InterSystems Community Open Source Project, that allows you to use files, stored in the local file system and cloud object storage such as AWS S3 as SQL Tables.
It can be found on Github https://github.com/intersystems-community/IRIS-ExternalTable Open Exchange https://openexchange.intersystems.com/package/IRIS-External-Table and is included in InterSystems Package Manager ZPM.
To instal External Table from GitHub use:
I am often asked by customers, vendors or internal teams to explain CPU capacity planning for large production databases running on VMware vSphere.
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!
You can set the maximum size of the IRISTemp database at IRIS startup by setting a configuration parameter called MaxIRISTempSizeAtStart.
After setting, the system will truncate IRISTemp to the set value (MB) at the next IRIS startup. If the current size is less than the specified MaxIRISTempSizeAtStart, no truncation will occur. Also, if 0 is specified, truncation will not be performed, so the size will start without changing. (Default) Settings are made from the menu below.
I wanted to provide a heads up of an improvement in how we generate and call method code in IRIS 2023.1.
A class in IRIS is composed of two main runtime components:
I tried OpenAI GPT's coding model a couple of weeks ago, to see whether it can do e.g. some message transformations between healthcare protocols. It surely "can", to a seemingly fair degree.
It has been nearly 3 weeks, and it's a long, long time for ChatGPT, so I am wondering how quickly it grows up by now, and whether it could do some of integration engineer jobs for us, e.g. can it create an InterSystems COS DTL tool to turn the HL7 into FHIR message?
Immediately I got some quick answers, in less than one minute or two.
This article is a simple quick starter (what I did was) with SqlDatabaseChain.
Hope this ignites some interest.
Many thanks to:
sqlalchemy-iris author @Dmitry Maslennikov
Your project made this possible today.
The article script uses openai API so caution not to share table information and records externally, that you didn't intend to.
A local model could be plugged in , instead if needed.
Saw the other day an article with the usage of the %ZEN package when working with JSON and decided to write an article describing a more modern approach. At some recent point, there was a big switch from using %ZEN.Auxiliary.* to dedicated JSON classes. This allowed to work with JSONs more organically.
Thus, at this point there are basically 3 main classes to work with JSON:
%Library.DynamicObject - provides a simple and efficient way to encapsulate and work with standard JSON documents. Also, there is a possibility instead of writing the usual code for creating an instance of a class likeset obj = ##class(%Library.DynamicObject).%New()it is possible to use the following syntax
set obj = {}%Library.DynamicArray - provides a simple yet efficient way to encapsulate and work with standard JSON arrays. With arrays you can use the same approach as with objects, meaning that yu can either create an instance of the classset array = ##class(%DynamicArray).%New()or you can do it by using brackets []
set array = []%JSON.Adaptor is a means for mapping ObjectScript objects (registered, serial or persistent) to JSON text or dynamic entities.Hi Community,
In this article, I listed 5 useful SQL functions with explanations and query examples 👇🏻
These 5 functions are
So Let us start with COALESCE function
Data analytics is a crucial aspect of business decision-making in today's fast-paced world. Organizations rely heavily on data analysis to make informed decisions and stay ahead of the competition. In this article, we will explore how data analytics can be performed using Pandas and Intersystems Embedded Python. We will discuss the basics of Pandas, the benefits of using Intersystems Embedded Python, and how they can be used together to perform efficient data analytics.
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In this article I will explain how to Authenticate, Authorize and Audit by code by using CSP Web Application along with Enabling /Disabling and Authenticate/Unauthenticate any Web Application.
Application Layout
Yet another example of applying LangChain to give some inspiration for new community Grand Prix contest.
I was initially looking to build a chain to achieve dynamic search of html of documentation site, but in the end it was simpler to borg the static PDFs instead.
mkdir chainpdf cd chainpdf python -m venv . scripts\activate pip install openai pip install langchain pip install wget pip install lancedb pip install tiktoken pip install pypdf set OPENAI_API_KEY=[ Your OpenAI Key ] python
To connect to AtScale, we will use the SQL Server Analysis Services database. Let's open it in the Power Query editor. To do that, select Transform Data on the Home.
In the window that appears, go to the Home, expand New Source and select Analysis Services.
In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:
In the first article, we covered Git basics, why a high-level understanding of Git concepts is important for modern software development, and how Git can be used to develop software.
In the second article, we covered GitLab Workflow - a complete software life cycle process and Continuous Delivery.
In the third article, we covered GitLab installation and configuration and connecting your environments to GitLab
In the fourth article, we wrote a CD configuration.
In the fifth article, we talked about containers and how (and why) they can be used.
In the sixth article let's discuss main components you'll need to run a continuous delivery pipeline with containers and how they all work together.
In this article, we'll build Continuous Delivery configuration discussed in the previous articles.
Before we start talking about databases and different data models that exist, first we'd better talk about what a database is and how to use it.
A database is an organized collection of data stored and accessed electronically. It is used to store and retrieve structured, semi-structured, or raw data which is often related to a theme or activity.
At the heart of every database lies at least one model used to describe its data. And depending on the model it is based on, a database may have slightly different characteristics and store different types of data.
To write, retrieve, modify, sort, transform or print the information from the database, a software called Database Management System (DBMS) is used.
The size, capacity, and performance of databases and their respective DBMS have increased by several orders of magnitude. It has been made possible by technological advances in various areas, such as processors, computer memory, computer storage, and computer networks. In general, the development of database technology can be divided into four generations based on the data models or structure: navigational, relational, object and post-relational.
In the first article I discussed testing and debugging Caché web applications with external tools. Second part would cover Caché tools.
They are:
We often run into connectivity problems with HealthShare (HS) deployments in Microsoft Azure that have multiple HealthShare components (instances or namespaces) installed on the same VM, especially when needing to communicate to other HS components while using the Azure Load Balancer (ILB) to provide mirror VIP functionality. Details on how and why a load balancer is used with database mirroring can be found this community article.
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How to include IRIS Data into your Google Big Query Data Warehouse and in your Data Studio data explorations. In this article we will be using Google Cloud Dataflow to connect to our InterSystems Cloud SQL Service and build a job to persist the results of an IRIS query in Big Query on an interval. If you were lucky enough to get access to Cloud SQL at Global Summit 2022 as mentioned in "InterSystems IRIS: What's New, What's Next", it makes the example a snap, but you can pull this off with any publicly or vpc accessible listener you have provisioned instead. |
This proof of concept aims to show how the iris interoperability framework can be used with embedded python.
