As an example of an application on Java working with Hibernate dialect for IRIS, wanted to use RealWorld application, and found realization for Quarkus. RealWorld application is an example of an application close to some real one, with already prepared tests for the backend. Most of the examples of realizations can be found here

The RealWorld example application is often referred to as the "Wikipedia for building full-stack applications." It serves as a standardized prototype that developers can use to create applications using various programming languages and frameworks. The application provides a real-world use case by mimicking a blogging platform, complete with features like user authentication, profile management, article posting, and comments. With a comprehensive set of specifications, including ready-made backend API documentation and frontend designs, it allows developers to see how the same functional requirements are implemented across different technology stacks. The RealWorld example is widely used as a learning tool and a benchmark for comparing various technologies.

Quarkus

Quarkus is an open-source, Kubernetes-native Java framework tailored for the GraalVM and HotSpot. Created with the aim to enhance the modern cloud-native environment, it significantly reduces the footprint and startup time of Java applications. Quarkus is known for its "container-first" philosophy, allowing developers to build lightweight, high-performing applications with a focus on microservices architecture. This flexibility has made it a popular choice for organizations looking to transition into serverless or cloud-based platforms, combining both imperative and reactive programming models. Whether it's a traditional web application or a complex system of microservices, Quarkus provides a robust platform for building scalable and maintainable software.

For the upcoming Python contest, I would like to make a small demo, on how to create a simple REST application using Python, which will use IRIS as a database. Using this tools

• FastAPI framework, high performance, easy to learn, fast to code, ready for production
• SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL
• Alembic is a lightweight database migration tool for usage with the SQLAlchemy Database Toolkit for Python.
• Uvicorn is an ASGI web server implementation for Python.

I have a persistent class (GetOrgUpdatesResponse) that has a property which is a list of another persistent class (Organization).

What would be the best way to cascade deletes so that on deletion of a parent row each object in the list property is then also deleted? 

I have included a sample of my classes here for clarity

Class Integration.ISIS.BO.SyncOrg.Custom.GetOrgUpdatesResponse Extends (%Persistent, Ens.

I am trying to create the JSON message below for a REST API:

Class REST.Test.Sample.ItemDetails Extends (%Persistent, %JSON.Adaptor)
{

Property ItemId As %String;

Property Item As list Of AllItems;

}

Class AllItems:

Class REST.Test.Sample.AllItems Extends (%JSON.Adaptor, Ens.

When installing IRIS, all the system AUDIT events are not enabled.

What is the fastest way to activate all events?

  System > Security Management > System Audit Events 

It's a feature of ObjectScript (perhaps widely known, perhaps not) that if you open the same object ID multiple times, you end up with the same OREF. For example:

USER>set obj1 = ##class(Sample.Person).%OpenId(1)
 
USER>set obj2 = ##class(Sample.Person).%OpenId(1)

USER>w obj1,!,obj2
1@Sample.Person
1@Sample.Person

Generally speaking, this is an important feature - you won't end up accidentally modifying the same record via multiple paths and losing some of the changes.

Nowadays so much noise around LLM, AI, and so on. Vector databases are kind of a part of it, and already many different realizations for the support in the world outside of IRIS. 

Why Vector?

• Similarity Search: Vectors allow for efficient similarity search, such as finding the most similar items or documents in a dataset. Traditional relational databases are designed for exact match searches, which are not suitable for tasks like image or text similarity search.
• Flexibility: Vector representations are versatile and can be derived from various data types, such as text (via embeddings like Word2Vec, BERT), images (via deep learning models), and more.
• Cross-Modal Searches: Vectors enable searching across different data modalities. For instance, given a vector representation of an image, one can search for similar images or related texts in a multimodal database.

And many other reasons.

So, for this pyhon contest, I decided to try to implement this support. And unfortunately I did not manage to finish it in time, below I'll explain why.

Hi Community,

to learn quickly and in total autonomy on IRIS, I offer you some links which can help you in this beautiful bicycle ride rich in discoveries: 

1. InterSystems Developer Hub​​​​​​
   • Full Stack Tutorial Build the IT infrastructure for a company that roasts and sells coffee.

Hi Community,

This is my first post in the developer community - would appreciate any feedback!

For testing or demo purposes, you may want to send emails from your Interoperability Production. In this post then I will walk you through connecting an InterSystems IRIS Production to Gmail so you can use it to send emails alerts.
 

1. Set up a new Gmail

1. Create a new Gmail account and document the username and password for future references.
2. Go into the Settings icon on the top right corner of the gmail interface then click on "See all settings".

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.

What is a Resource?

With the release of InterSystems IRIS Cloud SQL, we're getting more frequent questions about how to establish secure connections over JDBC and other driver technologies. While we have nice summary and detailed documentation on the driver technologies themselves, our documentation does not go as far to describe individual client tools, such as our personal favourite DBeaver. In this article, we'll describe the steps to create a secure connection from DBeaver to your Cloud SQL deployment.

In a customer project I was asked how you can keep track of database changes: Who changed what at which date and time. Goal was to track insert, update and delete for both SQL and object access.

This is the table that I created to keep the Change Log:

/// Changelog, keep track of changes to any table
Class ChangeLog.DB.ChangeLog Extends (%Persistent, %JSON.

I have been using embedded python for more than 2 years now on a daily basis. May be it's time to share some feedback about this journey.

Why write this feedback? Because, I guess, I'm like most of the people here, an ObjectScript developer, and I think that the community would benefit from this feedback and could better understand the pros & cons of chosing embedded python for developing stuff in IRIS. And also avoid some pitfalls.

• Feedback : Using embedded python daily for 2 years
• Introduction
• Starting with Python
  • Python is not ObjectScript
    • Pep8
    • Modules
    • Dunders
  • Conclusion
• Embedded Python
  • What is Embedded Python ?
  • How to use Embedded Python ?
  • How I use Embedded Python
    • Use Python libraries and code as they were ObjectScript classes
      • With the language tag
      • Without the language tag
      • Conclusion
    • Use a python first approach
      • Example : iris-fhir-python-strategy
      • Remarks
      • Where to find the code
        • How to implement a Strategy
        • Implementation of InteractionsStrategy
        • Implementation of Interactions
        • Interactions in Python
        • Implementation of the abstract python class
      • Too long, do a summary

1. IRIS RAG Demo

This demo showcases the powerful synergy between IRIS Vector Search and RAG (Retrieval Augmented Generation), providing a cutting-edge approach to interacting with documents through a conversational interface. Utilizing InterSystems IRIS's newly introduced Vector Search capabilities, this application sets a new standard for retrieving and generating information based on a knowledge base. The backend, crafted in Python and leveraging the prowess of IRIS and IoP, the LLM model is orca-mini and served by the ollama server. The frontend is an chatbot written with Streamlit.

InterSystems FAQ rubric

If the system does not stop for 24 hours, old journal files will be deleted at 0:30 according to the "Journal file deletion settings".

A possible cause of journal files remaining that are older than the "Journal file deletion settings" is that there are transactions that remain open.

In that case, you will be able to delete the journal file by searching for processes executing transactions and finalizing the transactions.

The sample below checks for the existence of open transactions, and if they exist, outputs the target file name and journal record information.

IRIS 2023.3.0 ASQ

Abstract Set Query, ASQ, is a super set of JSON Path Language, JPL, which was first introduced by the 2016 ISO SQL Standard. JPL is only defined within the context of SQL. In 2023.3, we introduced classes that implement ASQ. It works on any implementation of %Library.AbstractSet. The complete syntax for ASQ will be documented later. This is just a quick introduction to a few of its features. This implementation comes with a nice utility as well. You will know it when you see it!

First, let's get some data from the NHL database. This step requires a valid SSL/TLS configuration.

Pandas is not just a popular software library. It is a cornerstone in the Python data analysis landscape. Renowned for its simplicity and power, it offers a variety of data structures and functions that are instrumental in transforming the complexity of data preparation and analysis into a more manageable form. It is particularly relevant in such specialized environments as ObjectScript for Key Performance Indicators (KPIs) and reporting, especially within the framework of the InterSystems IRIS platform, a leading data management and analysis solution.

I would like to share with you a little trick to customize how messages are displayed in the Message Viewer. In particular, how you can display messages as JSON (instead of the default XML representation).

Messages are objects that are used to communicate interoperability productions components. In my example I have defined a message that later I serialize as JSON to send to an external API. This message is defined as a regular message and also as a %JSON.Adaptor so I can export / import directly to or from JSON.

Class interop.msg.DeviceOrderReq Extends (Ens.Request, %JSON.

If you are a customer of the new InterSystems IRIS® Cloud SQL and InterSystems IRIS® Cloud IntegratedML® cloud offerings and want access to the metrics of your deployments and send them to your own Observability platform, here is a quick and dirty way to get it done by sending the metrics to Google Cloud Platform Monitoring (formerly StackDriver).

We have JSON type data in a Dynamic Object.  Is there a simple way to export / dump that data to a delimited string or file?

e.g.

Results={"ClassA":{"ClassName":"ClassA","ACount":367191880,"BCount":367191880,"CurrentDiff":0,"PreviousDiff":0,"ReportDate":"2024-03-02 00:00:00"}
"ClassB":{"ClassName":"ClassB","ACount":5352149227,"BCount":5352149227,"CurrentDiff":0,"PreviousDiff":0,"ReportDate":"2024-03-02 00:00:00"}}