Some time ago I got a WRC case transferred where a customer asks for the availability of a raw DEFLATE compression/decompression function built-in Caché.

When we talk about DEFLATE we need to talk about Zlib as well, since Zlib is the de-facto standard free compression/decompression library developed in the mid-90s.

Zlib works on particular DEFLATE compression/decompression algorithm and the idea of encapsulation within a wrapper (gzip, zlib, etc.).
https://en.wikipedia.org/wiki/Zlib

In this article, I would like to talk about the spec-first approach to REST API development.

While traditional code-first REST API development goes like this:

• Writing code
• REST-enabling it
• Documenting it (as a REST API)

Spec-first follows the same steps but reverse. We start with a spec, also doubling as documentation, generate a boilerplate REST app from that and finally write some business logic.

This is advantageous because:

• You always have relevant and useful documentation for external or frontend developers who want to use your REST API
• Specification created in OAS (Swagger) can be imported into a variety of tools allowing editing, client generation, API Management, Unit Testing and automation or simplification of many other tasks
• Improved API architecture. In code-first approach, API is developed method by method so a developer can easily lose track of the overall API architecture, however with the spec-first developer is forced to interact with an API from the position if API consumer which usually helps with designing cleaner API architecture
• Faster development - as all boilerplate code is automatically generated you won't have to write it, all that's left is developing business logic.
• Faster feedback loops - consumers can get a view of the API immediately and they can easier offer suggestions simply by modifying the spec

Let's develop our API in a spec-first approach!

Those of you who are following the FullStack competition here in the Developer Community will know that I submitted an entry named qewd-conduit. I wanted to summarise why I think it's something worth you taking a bit of time to check out.

qewd-conduit uses the Node.js-based QEWD framework alongside IRIS to implement the back-end REST APIs for something known as the RealWorld Conduit application:

https://github.com/gothinkster/realworld

Add a credential to login the FHIR REST interface - in this case only consider a basic authentication

Hi developers!

Observing the avalanche of AI-driven and vibe-coding developer tools that have been appearing lately almost every month with more and more exciting dev features, I was puzzled whether it is possible to leverage it with InterSystems IRIS. At least to build a frontend. And the answer - yes! At least with the approach I followed.

Here is my recipe to prompt the UI vs InterSystems IRIS Backend:

1. Have the REST API on the IRIS side, which reflects some Open API (swagger) spec.
2. Generate the UI with any vibe-coding tool (e.g., Lovable) and point the UI to the REST API endpoint.
3. Profit!

Here is the result of my own exercise - a 100% prompted UI vs IRIS REST API that allows to list, create, update delete entries of a persistent class (Open Exchange, frontend source, video):

What is the recipe in detail?

Intro

For many in today's interoperability landscape, REST reigns supreme. With the overabundance of tools and approaches to REST API development, what tools do you choose and what do you need to plan for before writing any code?
This article focuses on design patterns and considerations that allow you to build highly robust, adaptive, and consistent REST APIs. Viable approaches to challenges of CORS support and authentication management will be discussed, along with various tips and tricks and best tools for all stages of REST API development. Learn about the open-source REST APIs available for InterSystems IRIS Data Platform and how they tackle the challenge of ever-increasing API complexity.
The article is a write-up for a recent webinar on the same topic.

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.

Hi guys.

Recently, I get interest in FHIR in order to run for the IRIS for Health FHIR
contest. As a beginner on this topic, I've heard somewhat about it, but I didn't know how complex and powerful was FHIR. As pointed out by @Henrique.GonçalvesDias here, you can model several aspects of the patient history and other related entities.

Background:

This guideline provides an overview of how to design and implement a REST API interface for querying patient demographic data from an Electronic Patient Record (EPR) system using HealthConnect. The process involves sending a query request with the patient's identification number, retrieving the response from the EPR system, extracting the required patient demographic data from the HL7 message, and sending it as a JSON response to the supplier. The high-level process diagram is shown below (Screenshot 1).

The XData (https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=GOBJ_XDATA) is a powerful feature to set documentation and metadata information for classes and methods.

FHIR has revolutionized the healthcare industry by providing a standardized data model for building healthcare applications and promoting data exchange between different healthcare systems. As the FHIR standard is based on modern API-driven approaches, making it more accessible to mobile and web developers. However, interacting with FHIR APIs can still be challenging especially when it comes to querying data using natural language.

What if you could serialize/deserialize objects in whatever format: JSON, XML, CSV,...; attending different criteria: export/import some properties and not others, transform values in this or that way before exporting/importing,...; and all of this without having to change the class definition? Wouldn't that be great??

Well, perhaps it's a goal too ambitious to reach 100% but, exploring this idea, I've developed a bunch of classes that I thought it was good to share. If you want to test, change, modify or improve the code, or just take a look at it, you can do it here. There you'll find a more detailed explanation (see Readme.md)

or "Didn't you say you would cover Persistent Objects in Part 5, Chris?"

Yes, that was the plan. This is a pretty important topic, so it get's its own Article

Up until now, we've display widget JSON that has been created by a basic loop. Clearly this isn't of much value. Now we have our stack connected together, and we can see that the data is flowing to the Welcome page, it's time to complete the stack and start feeding our service from "real" data.

This little guide would help you start running Ensemble REST services in no time.