If you want to dynamically serve images as a property of JSON then there is no perfect encoding solution. One method used frequently is to Base64 encode the image. Whilst there are some negatives to doing this, such as data inflation, there are some positives to working with Base64 images inside the browser.

Let's say you have an image placeholder on a web page...

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We finished our last lesson with our Widgets Direct page iterating over a list of widgets, displaying an ID and a Name value. While we have been able to achieve this with only a small amount of coding, the page itself is not the most visually appealing place to be. The AngularJS framework is providing a powerful Model-View-Controller framework for our structure and logic, but it does not implement anything that will provide a nice UI experience.

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As we keep updating our software, we often realize that we require more and more modern solutions. So far, only one major piece of our software relies on reading barcodes in documents and images. Since Cache did not have a means of reading barcodes in the past, we have always achieved our goals by using a Visual Basic 6 application. However, it is no longer an ideal solution because it is currently complicated to maintain it. IRIS also lacks this capability, but it has recently got an option that makes up for it: embedded Python!

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Hello community,

I'd like to briefly announce three new packages, available on the Open Exchange / through ZPM, that can really help accelerate modern full-stack application development on IRIS. I announced all of these in a Global Summit session last week, but you may have missed it - and I hear there's a full-stack application development contest coming up!

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You may have heard about our mg-dbx-napi interface for IRIS which provides insanely fast access from Node.js. If you've been following recent developments in the server-side JavaScript world, you'll be excited to know that mg-dbx-napi also works with Bun.js, the latter proving to be significantly faster than Node.js for many/most purposes.

Of course, if you're a Node.js user, you'll probably wonder how mg-dbx-napi compares with the Native API for Node.js that is included with IRIS.

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Developing a Full-Stack JavaScript web app with Caché requires you to bring together the right building blocks. In the previous part, we created a basic front-end React application. In the second part of this article series I will show how to choose the right back-end technology for your application. You will see Caché allows you to use many different approaches to link your front-end to your Caché server, depending on your application's needs. In this part we will set up a back-end with Node.js/QEWD and CSP/REST. In the next part we will enhance our basic web app and connect it to Caché using these technologies.

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Article
· Sep 23, 2016 6m read
Creating a RESTful Service using Ensemble

This is a detailed guide to develop RESTful services using InterSystems Ensemble. The goal of this guide is to make you understanding the basic concept and building blocks of a RESTful service. The service is going to provide a very basic functionality (a “Hello world!”).

You will learn how to create required components as Ensemble classes, configure the run-time as an Ensemble Production and create a service configuration as a web application.

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Article
· Jan 24, 2022 1m read
GlobalToJSON-Compact

I have created a package that offers a utility to load a Global into JSON object and reverse
to create a Global from this type of JSON object. Compact refers to the structure created.
Globals nodes are included with data for a fast data load.
But also the related code is quite compact.

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Announcement
· May 5, 2020
ObjectScript Json Patch

objectscript-json-patch

alt text

An implementation of JSON-Patch in ObjectScript.

Why you should use JSON-Patch

JSON-Patch (RFC6902) is a standard format that allows you to update a JSON document by sending the changes rather than the whole document.
JSON Patch plays well with the HTTP PATCH verb (method) and REST style programming.

Install

With zpm :

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Hi Community!

You're very welcome to watch a new video on InterSystems Developers YouTube, recorded by @Stefan Wittmann, InterSystems Product Manager:

InterSystems API Manager Introduction

https://www.youtube.com/embed/vO6kz1G4eVg
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

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Generally speaking, InterSystems products supported dynamic objects and JSON for a long while, but version 2016.2 came with a completely new implementation of these features, and the corresponding code was moved from the ObjectScript level to the kernel/C level, which made for a substantial performance boost in these areas. This article is about innovations in the new version and the migration process (including the ways of preserving backward compatibility).

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This series of articles aims to address the following topics:

  • Creation of a web application based on REST pages;
  • Overview of some tools for tracing (debugging) HTTP requests;
  • Switching from hyperevents to... hyperevents;
  • Integration with jQuery File Upload;
  • Conversion of JSON from the {id:1,parentId:1} format to the {id:1,children:[{}]} format for tree visualization;
  • Integration with jQuery EasyUI (using datagrid and tree as examples);
  • Other topics.

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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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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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Article
· Feb 18, 2021 2m read
Basic JSON Compare

Hi Dev Community

I thought i would share a little method I knocked together to traverse and compare 2 JSON objects for basic equivilance. I'm currently working on some data migration, and wanted a basic sanity check to validate that the JSON output is basically equivliant between the old and new, excluding a few things like timestamps.

It's a basic little recurvsive method, that will bubble up any differences over a nested structure. It's very low tech, as that's all I need it to do, but I thought it might be useful for others?

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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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Article
· Jan 22 4m read
JSON Support in IRIS SQL

While working on getting JSON support for some Python libraries, I discovered some capabilities IRIS provided.

  • JSON_OBJECT - A conversion function that returns data as a JSON object.
  • JSON_ARRAY - A conversion function that returns data as a JSON array.
  • IS JSON - Determines if a data value is in JSON format.
  • JSON_TABLE function returns a table that can be used in a SQL query by mapping JSON.
  • JSONPath support - is a query language for querying values in JSON.

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The architect of the JSON schema (MS) asked if IRIS could perform schema validation. I asked on Discord objectscript channel how we could validate a Dynamic Object against a JSON schema. Dmitry Maslennikov replied that probably the easiest way would be to use python, but it would require converting ObjectScript JSON to Python dict.

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