The below code is not working. its unable retrieve Record count and merge files

Class Util

{

ClassMethod zPyRecordCount(inputfile) As %Integer [ Language = python ]

{

import pandas as pd

import iris

import io

try:

df = pd.read_csv(inputfile, sep='|')

recordcount=len(df.index)

sys.stdout.write(len(df.index))

return recordcount

except Exception as e:

return 0

}

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Hi noble devs!

Just building a simple frontend->JSON->IRIS backend story, and figured that IRIS while importing via %JSON.Adaptor wants JSON fields to match property names, meaning even should match the case. Like:

{ name: "John", 

surname: "Doe"}

will have issues while saving the dynamic object to a class Sample.Person with:

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Introduction

InterSystems IRIS allows you to build REST APIs using ObjectScript classes and the %CSP.REST framework. This enables the development of modern services to expose data for web apps, mobile apps, or system integrations.

In this article, you'll learn how to create a basic REST API in InterSystems IRIS, including:

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IRIS supports CCDA and FHIR transformations out-of-the-box, yet the ability to access and view those features requires considerable setup time and product knowledge. The IRIS Interop DevTools application was designed to bridge that gap, allowing implementers to immediately jump in and view the built-in transformation capabilities of the product.

In addition to the IRIS XML, XPath, and CCDA Transformation environment, the Interop DevTools package now provides:

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Hi Community,

In this article, I will introduce my application iris-fhir-bridge

IRIS-FHIR-Bridge is a robust interoperability engine built on InterSystems IRIS for Health, designed to transform healthcare data across multiple formats into FHIR and vice versa. It leverages the InterSystems FHIR Object Model (HS.FHIRModel.R4.*) to enable smooth data standardization and exchange across modern and legacy healthcare systems.

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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?

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The Good Old Days

The %Library.DynamicObject class has been in IRIS since before it became IRIS. If you have been using it since the Cache days, you may want to brush up on some of its changes.

In Cache 2018, the %Get method only had one argument. It was the key to retrieving from the JSON, meaning that if your JSON object called myObj, it would look like the following:

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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).

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REST API with Swagger in InterSystems IRIS

Hello

The HTTP protocol allows you to obtain resources, such as HTML documents. It is the basis of any data exchange on the Web and a client-server protocol, meaning that requests are initiated by the recipient, usually a Web browser.

REST APIs take advantage of this protocol to exchange messages between client and server. This makes REST APIs fast, lightweight, and flexible. REST APIs use the HTTP verbs GET, POST, PUT, DELETE, and others to indicate the actions they want to perform.

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What is JWT?

JWT (JSON Web Token) is an open standard (RFC 7519) that offers a lightweight, compact, and self-contained method for securely transmitting information between two parties. It is commonly used in web applications for authentication, authorization, and information exchange.

A JWT is typically composed of three parts:

1. JOSE (JSON Object Signing and Encryption) Header
2. Payload
3. Signature

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Using Flask, REST API, and IAM with InterSystems IRIS

Part 2 – Flask App

Flask is a web development microframework written in Python. It is known for being simple, flexible, and enabling rapid application development.

Installing Flask is very simple. Once you have python installed correctly on your operating system, we need to install the flask library with the pip command. For REST API consumption, it is advisable to use the requests library. The following link provides a guide to installing flask: https://flask.palletsprojects.com/en/stable/installation/

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Using Flask, REST API, and IAM with InterSystems IRIS

Part 1 - REST API

Hello

In this article we will see the implementation of a REST API to perform the maintenance of a CRUD, using Flask and IAM.

In this first part of the article we will see the construction and publication of the REST API in Iris.

First, let's create our persistent class to store the data. To do this, we go to Iris and create our class:

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Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 2 – Python and Vector Search

Since we have access to the data from our external table, we can use everything that Iris has to offer with this data. Let's, for example, read the data from our external table and generate a polynomial regression with it.

For more information on using python with Iris, see the documentation available at https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=AFL_epython

Let's now consume the data from the external database to calculate a polynomial regression. To do this, we will use a python code to run a SQL that will read our MySQL table and turn it into a pandas dataframe:

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