Hi Community,


In this article, I will introduce Python Flask Web Framework. Together we will create a minimal web application to connect to IRIS and get data from it.

Below you can find the steps we will need to follow:

• Step 1 : Introduction to Python Flask Web Framework
• Step 2 : Installation of Flask module
• Step 3 : Creation of web application using Flask
• Step 4 : Use of HTML Templates 
• Step 5 : Installation of IRIS Python Native module
• Step 6 : Establishment of a connection with IRIS 
• Step 7 : Transferring data from IRIS to Flask and displaying it

So Let's start with step 1

Step1-Introduction to Python Flask Web Framework 

Flask is a small and lightweight Python web framework that provides useful tools and features that make creating web applications in Python easier. It gives developers flexibility and is a more accessible framework for new developers since it allows to build a web application quickly using only a single Python file. Flask is also extensible and doesn’t requires a particular directory structure or complicated boilerplate code before getting started.

For more details please view Flask Documentations

We're having a problem with the way Python modules are being cached in Iris. If we modify some code and then reimport a module it is still processing the old code.

E.g. Create a python file:

helloWorld.py

def helloWorld() :
  return "Hello world"

The run the following in the Iris terminal:

I'm after some more in-depth information about how the embedded python is implemented with regards to how it works when a python method is called from a CSP page. Will it run in the same Windows process? Will there be any issues with multitasking (considering python doesn't seem very good at this)?

Also, is there a performance penalty to pay for running embedded python vs "using IRIS APIs from Python". 

Another question is what python interpreter the embedded python is using? Is it an Intersystems one or the regular c.python? Version?

Excited to go Python!

This GitHub is the simplest way to scrap using IRIS and Python, all of that already incorporated in an IRIS PRODUCTION.

From here you can build any IRIS production in full Python or in ObjectScript as this module is interoperable.

See for more information

In this GitHub we gather information from a csv, use a DataTransformation to make it into a FHIR object and then, save that information to a FHIR server all that using only Python.

The objective is to show how easy it is to manipulate data into the output we want, here a FHIR Bundle, in the IRIS full Python framework.

Hey Developers,

Don't miss this hands-on session hosted by @Donald Woodlock, Vice President of InterSystems Healthcare:

⏯ Machine Learning 201 - Neural Networks and Image Recognition

On this GitHub you can find all the information on how to use a HuggingFace machine learning / AI model on the IRIS Framework using python.

1. iris-huggingface

Usage of Machine Learning models in IRIS using Python; For text-to-text, text-to-image or image-to-image models.

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.

Hey Community!

Here are the bonuses for participants' articles that take part in InterSystems Tech Article Contest: Python Edition:

Following this GitHub we will see how the FIX protocol can be implemented easily using IRIS and Python.

If you don't have much time focus on the Send a Quote before the Order part near the end, as it will, in a matter of minute, tell you how to send a Quote Request followed by an Order Request and show you the result from the server, and that in no more than five clicks.

In the first part, I've shown how to start a new project on Django, as well as define new models and add already existing models.

This time, I'll introduce an admin panel, available out of the box and how it can be useful.

Important note: do not expect that if you try to repeat actions from this post it will work for you, it does not. During the article, I had to do some fixes in the django-iris project, and even in DB-API driver made by InterSystems to fix some issues there as well, and I think this driver is still in development, and we will get more stable driver in future. Let's decide that this article only explains how it could be if we would have all done.

Python has become the most used programming language in the world (source: https://www.tiobe.com/tiobe-index/) and SQL continues to lead the way as a database language. Wouldn't it be great for Python and SQL to work together to deliver new functionality that SQL alone cannot? After all, Python has more than 380,000 published libraries (source: https://pypi.org/) with very interesting capabilities to extend your SQL queries within Python.

Hi Community,

This post is a introduction of my open exchange iris-climate-change application.

iris-climate-change  web application Imports  The Food and Agriculture Organization (FAO) Climate Change dataset by using LOAD DATA (SQL) functionality and analyze and visualize data with the help of Python Flask Web Framework, Pandas Python data analysis Library, Plotly Open Source Graphing Library for Python and Plotly JavaScript Open Source Graphing Library.

My major interest is  Working with Globals in Embedded Python.
So I checked the available official documentation.

#1 Introduction to Globals
an attempt of a generic description of what a global is. Pointing to