Making a blog using Python + IRIS Globals

Since I started to use internet (late 90's), I always had a CMS (content management system) present to make easier post
any information in a blog, social media or even an enterprise page. And later years putting all my code into github I
used to document it on a markdown file. Observing how easy could be persisting data into Intersystems IRIS with the
Native API I decided to make this application and force myself to forget a little of SQL and stay open to key-value database
model.

Description

This is a template for a Flask application that can be deployed in IRIS as an native Web Application.

Continuing to observe the possibilities of Django, and usage with IRIS. The first we have looked how to define models and connect to tables already existing in IRIS, than we extended embedded Django Administration portal, with an ability to see what data we have in that models, with filters, editing and even pagination.

Time to go to real action, now we a going to create some REST API, on Django, based on the same data, we used before from the package posts-and-tags.

To do so, we will use Django REST Framework

Django REST framework is a powerful and flexible toolkit for building Web APIs.

Some reasons you might want to use REST framework:

• The Web browsable API is a huge usability win for your developers.
• Authentication policies including packages for OAuth1a and OAuth2.
• Serialization that supports both ORM and non-ORM data sources.
• Customizable all the way down - just use regular function-based views if you don't need the more powerful features.
• Extensive documentation, and great community support.
• Used and trusted by internationally recognised companies including Mozilla, Red Hat, Heroku, and Eventbrite.

The Jupyter Notebook is an open source web application that can be used to create and share documents that contain live text, code, equations and visualizations. It is maintained by the people at Project Jupyter.

Hi Developers!

This is the second post on the resources for Developers. This part is about Open Exchange

Using Open Exchange to Learn InterSystems

InterSystems Open Exchange is a applications gallery of tools, connectors, and libraries which InterSystems Developers submit to share the experience, approaches and do business. All the applications are either built with InterSystems data platforms or are intended to use for development with InterSystems data platforms.

If you are a beginner developer you can take a look at applications in Technology Example category. All the applications in this category come with open source code repositories, so you are able to run the samples and examples in a docker container with IRIS on your laptop or in the cloud IRIS sandbox. Examples:

In the previous article. Practices of class members and their execution within embedded Python. We will now turn our attention to the process of switching namespaces, accessing global variables , traversing and routine executions within embedded Python.

A Quick Start to InterSystems Cloud SQL Data in Databricks

Hello Community,

In this article, I will outline and illustrate the process of implementing ObjectScript within embedded Python. This discussion will also reference other articles related to embedded Python, as well as address questions that have been beneficial to my learning journey.

As you may know, the integration of Python features within IRIS has been possible for quite some time. This article will focus on how to seamlessly incorporate ObjectScript with embedded Python.

Introduction

As the health interoperability landscape expands to include data exchange across on-premise as well as hosted solutions, we are seeing an increased need to integrate with services such as cloud storage. One of the most prolifically used and well supported tools is the NoSQL database DynamoDB (Dynamo), provided by Amazon Web Services (AWS).

This is the third post of a series explaining how to create an end-to-end Machine Learning system.

Training a Machine Learning Model

When you work with machine learning is common to hear this work: training. Do you what training mean in a ML Pipeline?
Training could mean all the development process of a machine learning model OR the specific point in all development process
that uses training data and results in a machine learning model.

InterSystems has been at the forefront of database technology since its inception, pioneering innovations that consistently outperform competitors like Oracle, IBM, and Microsoft.

In my previous articles, I described my Command Line Extension to NativeAPI.
Of course, this is also available for any other NativeAPI package.
So I created this example in Python as a demo.

Hello everyone, I’m a French student that just arrived in Prague for an academical exchange for my fifth year of engineering school and here is my participation in the interop contest.

I hadn’t much time to code since I was moving from France to Prague and I’m participating alone, so I decided to make a project that’s more like a template rather than an application.