I am demonstrating a use case of how we can create an IRIS Interoperability Production for special use in an external language.InterSystems IRIS, within Interoperability has a framework called Production Extension (PEX), using which we can create productions and program them as per their purpose using external languages like Java, Python etc, and also develop custom inbound and outbound adapters to communicate with other applications.

In this GitHub based on this InterSystems community rest api template Guillaume and I have created this example of all the import CRUD operations usable using ONLY Python on IRIS and using Flask.

Using the IRIS ORM or by simply doing SQL requests as both methods are seen in the GitHub.

1. intersystems-iris-docker-rest-template

This is a template of a REST API application built in python in InterSystems IRIS. It also has OPEN API spec, can be developed with Docker and VSCode.

• 1. intersystems-iris-docker-rest-template
• 2. Prerequisites
• 3. Installation
  • 3.1. Installation for development
  • 3.2.

Easy, easy, I'm not promoting a war against the machines in the best sci-fi way to avoid world domination of Ultron or Skynet. Not yet, not yet 🤔

I invite you to challenge the machines through the creation of a very simple game using ObjectScript with embedded Python.

I have to say that I got super excited with the feature of Embedded Python on InterSystems IRIS, it's incredible the bunch of possibilities that opens to create fantastic apps.

Let's build a tic tac toe, the rules are quite simple and I believe that everyone knows how to play.

That's what saved me of the tedium in my childhood

grpc-iris-interop

The aim of this proof of concept is to show how the gRPC protocl can be implemented with the IRIS ineroperabilty module.

architecture

On this schema, we can see that the gRPC Service is hosted by IRIS.

This service must invoke the IRIS interoperability module. For that it transforms the protobuf messages to IRIS messages.

The gRPC client is host by a Flask server for demo purpose, the gRPC client can also be invoke by the python script.

definition of each file

users.proto

syntax = "proto3";
package users;

service Users {
  rpc CreateUser (users.CreateUserRequest) returns

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

In my Python script I import intersys2.pythonbind3 to create the connection and define a database object as db

I execute the method 

     res = self.db.run_class_method("%Library.GlobalEdit", "GetGlobalSize",[<db>, allocated,used])

This executes correctly as I loop through a list of databases.

Upon success I see that the return arg of "res" contains the string "status(0,)" which I interpret as successful. This is verified by the returned values of allocated and used being accurate. But I want to use the class/methods to get the status values from the returned structure

In reading the documents, I

Hi all. Today we are going to install Jupyter Notebook and connect it to Apache Spark and InterSystems IRIS.

Note: I have done the following on Ubuntu 18.04,  Python 3.6.5.

Introduction

If you are looking for well-known, widely-spread and mainly popular among Python users notebook instead of Apache Zeppelin, you should choose Jupyter notebook. Jupyter notebook is a very powerful and great data science tool.it has a big community and a lot of additional software and integrations.

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.

I wanted to participate since my field (Data Science and AI) is not often linked with sustainability and the contest was a way for me to express myself in this important subject that is sustainability and Environnement.

As you know,

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!

1. Integrated ML Demonstration

This repository is a demonstration of IntegratedML and Embedded Python.

• 1. Integrated ML Demonstration
• 2. Building the demo
  • 2.1. Architecture
  • 2.2. Building the nginx container
• 3. Running the demo
• 4. Python back-end
  • 4.1. Embedded Python
    • 4.1.1. Setting up the container
    • 4.1.2. Using Embedded Python
    • 4.1.3. Side By Side Comparaison
  • 4.2. Launching the server
• 5. IntegratedML
  • 5.1. Exploring both datasets
  • 5.2. Managing models
    • 5.2.1. Creating a model
    • 5.2.2. Training a model
    • 5.2.3. Validating a model
    • 5.2.4. Making predictions
• 6. Using COS
• 7. More explainability with DataRobot
• 8. Conclusion

Hi everyone!

I am recruiting on a fully remote Intersystems Developer.  This role will be a long term contract to begin with high likelihood of extensions or conversion permanent.  Please check out the job description down below and feel free to send me an email with your resume: Spencer.Frey@insightglobal.com 

The Healthcare Integration Developer is responsible for designing, developing, and deploying the complex near real-time and real-time data interoperability solutions using Healthcare industry-standard data formats/specifications (HL7, FHIR, EDI, etc.).

In the previous articles, we learned the basics of using IMAP protocol to handle messages from mailboxes in an e-mail server. That was cool and interesting, but you could take advantage of implementations created by other ones, available in libraries ready to use.

One of the improvements to the IRIS data platform is the ability to write Python code alongside ObjectScript in the same IRIS process. This new feature is called Embedded Python. Embedded Python lets us bring to our ObjectScript code the power of the huge Python ecosystem’s libraries.

In this article, we’ll use one of those libraries,

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

1. IRIS-WEB-SCRAPING

• 1. IRIS-WEB-SCRAPING
• 2. What is Web Scraping:
  • 2.1. The popular libraries/tools used for web scraping are:
  • 2.2. The BS4 tool
• 3. Using full Python to web scrap on IRIS
  • 3.1. The Production
    • 3.1.1. Starting the Production
    • 3.1.2. Access the Production
    • 3.1.3. Closing the Production
  • 3.2.

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.

1. Fhir-orga-dt

• 1. Fhir-orga-dt
• 2. Prerequisites
• 3. Installation
  • 3.1. Installation for development
  • 3.2. Management Portal and VSCode
  • 3.3. Having the folder open inside the container
• 4. FHIR server
• 5. Walkthrough
  • 5.1. Messages and objects
  • 5.2. Business Service
  • 5.3.

In this GitHub we fine tune a bert model from HuggingFace on review data like Yelp reviews.
The objective of this GitHub is to simulate a simple use case of Machine Learning in IRIS :
We have an IRIS Operation that, on command, can fetch data from the IRIS DataBase to train an existing model in local, then if the new model is better, the user can override the old one with the new one.
That way, every x days, if the DataBase has been extended by the users for example, you can train the model on the new data or on all the data and choose to keep or let go this new model.
We are aware that training

Hey Developers,

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

⏯ Machine Learning 201 - Neural Networks and Image Recognition

Hey Developers,

Enjoy watching the new video on InterSystems Developers YouTube channel:

⏯ What is Embedded Python

Hi Developers!

We have great new articles for your to read and enjoy, thanks to our wonderful participants of the 3rd InterSystems Tech Article Contest: Python Edition!

🌟 12 AMAZING ARTICLES 🌟

And now it's time to announce the winners!

Let's meet the winners and their articles:

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.

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.

In this article, I am trying to identify the multiple areas to develop the features we can able to do using python and machine learning.

Each hospital is every moment trying to improve its quality of service and efficiency using technology and services. 

The healthcare sector is one of the very big and vast areas of service options available and python is one of the best technology for doing machine learning.

In every hospital, humans will come with some feelings, if this feeling will understand using technology is make a chance to provide better service.

Here we can combine both of these and in

Hi developers! In this article I’m going to explore the use of Iris Python Native API in a specific problem: large strings to store.

Why Python Native API?

Python Native API for Intersystems IRIS offers an useful way to persist data that you can’t have control over the schema or if the schema changes frequently. Combining the Native API with the IRIS Globals, you can easily use Iris Database as an Document Store. You can also see more details of globals use in documentation https://learning.intersystems.com/course/view.php?id=1110&ssoPass=1, or in my article https://community.intersystems.com/po

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.

IRIS-fix-protocol

Implementation of the fix protocol using an IRIS python container for the initiator and a regular python container for the acceptor.

The Financial Information eXchange (FIX®) Protocol has revolutionized the

Hello,

I became aware of Python in the early 2000s when I started automating tasks. Some of our processes utilized python scripts. I never figured it out very well, and we decided to do away with Python because nobody on our team was familiar with it.

Along the way, I heard a lot about Python. My interest was renewed when InterSystems offered bonus points for using Python in contests.

The things I like the most about Python so far is how easy it is to find the mean of the ages of all Titanic passengers. For my test-data app I wanted to find the largest value in the ‘Qty’ column in a CSV file.

The

Jupyter Notebook is an interactive environment consisting of cells that allow executing code in a great number of different markup and programming languages.

To do this Jupyter has to connect to an appropriate kernel. There was no ObjectScript Kernel, that is why I decided to create one.

You can try it out here.

Here's a sneak peek of the results:

Jupyter Kernels 101

There are several ways to create a Jupyter Kernel. I decided to make a Python wrapper kernel.

We have to create a subclass of ipykernel.kernelbase.Kernel and implement the do_execute method which receives a code to be executed in a

Hi Community,

We are excited to announce that InterSystems Developers Meetups are finally back in person!

The first Python-related meetup will take place on July 21 at 6:00 at Democracy Brewing, Boston, MA. There will be 2-3 short presentations related to Python, Q&A, networking sessions as well as free beer with snacks and brewery tours.

AGENDA:

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.

InterSystems Native SDK for Python is a lightweight interface to InterSystems IRIS APIs that were once available only through ObjectScript.

I'm especially interested in the ability to call ObjectScript methods, class methods, to be precise. It works, and it works great, but by default, calls only support scalar arguments: strings, booleans, integers, and floats.

But if you want to:

• Pass or return structures, such as dicts or lists
• Pass or return streams

You'll need to write some glue code or take this project (installs with pip install edpy). edpy package gives you one simple signature:

call(iris, class_name, method_name, args)

which allows you to call any ObjectScript method and get results back.

I think it's a known fact that Populate Utility has very limited functionality. It supports only one language and one country. The list of possible values does not have so many options. 

There is a kind of tool that now can help with it, named Faker. It has implementations in different languages, including Python. Since IRIS has now had the Embedded Python feature, Python faker can be implemented in IRIS.