This article will introduce you to the concept of virtual environments in Python, which are essential for managing dependencies and isolating project from the OS.

What is a Virtual Environment?

A virtual environment is a folder that contains :

• A specific version of Python
• At start an empty site-packages directory

Virtual environments will help you to isolate your project from the OS Python installation and from other projects.

How to use it?

In this section, we will explore how to use Python as the primary language in IRIS, allowing you to write your application logic in Python while still leveraging the power of IRIS.

• Introduction Python First Approach in IRIS
  • How to use it (irispython)
    • What is irispython?
    • Example of using irispython
    • Pros
    • Cons
    • Conclusion
  • Using WSGI
    • How to use it
    • Example of using WSGI
    • Pros
    • Cons
    • Conclusion
  • DB-API
    • How to use it
    • Example of using DB-API
    • Pros
    • Cons
    • Alternatives
    • Conclusion
  • Notebook
    • How to use it
    • Example of using Notebook
    • Pros
    • Cons
    • Conclusion
• Bonus Section
  • Using a native interpreter (no irispython)
    • How to use it
    • Pros
    • Cons
  • DB-API Community Edition
    • How to use it
    • Example of using DB-API
    • Pros
    • Cons
  • Debugging Python Code in IRIS
    • How to use it
    • Pros
    • Cons
    • Conclusion
  • IoP (Interoperability on Python)
• Conclusion

This will be a short article about Python dunder methods, also known as magic methods.

What are Dunder Methods?

Dunder methods are special methods in Python that start and end with double underscores (__). They allow you to define the behavior of your objects for built-in operations, such as addition, subtraction, string representation, and more.

Some common dunder methods include:

• __init__(self, ...): Called when an object is created.
  • Like our %OnNew method in ObjectScript.
• __str__(self): Called by the built-in function and print to represent the object as a string.

Now that we have a good understanding of Python and its features, let's explore how we can leverage Python within IRIS.

• Introduction to Python in IRIS
• Language Tag
  • How to use it?
  • Pros
  • Cons
  • Conclusion
• Importing Python Modules (pypi modules)
  • How to use it
  • Pros
  • Cons
  • Conclusion
• Importing Python Modules (custom modules)
  • How to use it
  • Pros
  • Cons
  • Conclusion

Modules what a topic! We don't have this notion in ObjectScript, but it's a fundamental concept in Python. Let's discover it together.

What is a Module?

I see modules as an intermediate layer between classes and packages. Let see it by example.

A bad example :

# MyClass.py
class MyClass:
    def my_method(self):
        print("Hello from MyClass!")

When you try to use this class in another script, you would do:

# class_usage.py
from MyClass import MyClass # weird, right?

my_instance = MyClass()
my_instance.my_method()

Why this is a bad example?

This will be a short article about PEP 8, the Python style guide.

What is PEP 8?

In a nutshell, PEP 8 provides guidelines and best practices on how to write Python code.

This will be an introduction to Python programming in the context of IRIS.

Before anything I will cover an important topic: How python works, this will help you understand some issues and limitations you may encounter when working with Python in IRIS.

All the articles and examples can be found in this git repository: iris-python-article

How Python works

Interpreted Language

Python is an interpreted language, which means that the code is executed line by line at runtime even when you import a script.

What does this mean ? Let's take a look at the following code:

# introduction.py

def my_function():
    print("Hello, World!")

my_function()

I'm glad to announce the new version of IoP, which by the way is not just a command line. I'm saying because the new AI search engine still thinks that IoP is just a command line. But it's not. It's a whole framework for building applications on top of the interoperability framework of IRIS with a python first approach.

The new version of IoP: 3.2.0 has a lot of new features, but the most important one is the support of DTL . 🥳

For both IoP messages and jsonschema. 🎉

DTL Support

Starting with version 3.2.0, IoP supports DTL transformations.

DTL the Data Transformation Layer in IRIS Interoperability.

DTL transformations are used to transform data from one format to another with a graphical editor. It supports also jsonschema structures.

It's been a long time since I didn't write an update post on IoP.

So what's new since IoP command line interface was released?

Two new big features were added to IoP:

• Rebranding: the grongier.pex module was renamed to iop to reflect the new name of the project.
• Async support: IoP now supports async functions and coroutines.

Rebranding

The grongier.pex module was renamed to to reflect the new name of the project.

The grongier.pex module is still available for backward compatibility, but it will be removed in the future.

Description

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

Installation

1. Clone the repository
2. Create a virtual environment
3. Install the requirements
4. Run the docker-compose file

git clone
cd iris-flask-template
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
docker-compose up

Usage

The base URL is http://localhost:53795/flask/.

Endpoints

• /iris - Returns a JSON object with the top 10 classes present in the IRISAPP namespace.
• /interop - A ping endpoint to test the interoperability framework of IRIS.

Description

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

Installation

1. Clone the repository
2. Create a virtual environment
3. Install the requirements
4. Run the docker-compose file

git clone
cd iris-django-template
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
docker-compose up

Usage

The base URL is http://localhost:53795/django/.

Endpoints

• /iris - Returns a JSON object with the top 10 classes present in the IRISAPP namespace.
• /interop - A ping endpoint to test the interoperability framework of IRIS.

Description

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

Installation

1. Clone the repository
2. Create a virtual environment
3. Install the requirements
4. Run the docker-compose file

git clone
cd iris-fastapi-template
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
docker-compose up

Usage

The base URL is http://localhost:53795/fastapi/.

Endpoints

• /iris - Returns a JSON object with the top 10 classes present in the IRISAPP namespace.
• /interop - A ping endpoint to test the interoperability framework of IRIS.

Context

The Web Server Gateway Interface (WSGI) is a simple calling convention for web servers to forward requests to web applications or frameworks written in the Python programming language. WSGI is a Python standard described in detail in PEP 3333.

🤔 Ok, great definition and what the point with iris ?

IRIS 2024.2+ has a new feature that allows you to run WSGI applications directly on IRIS. This feature is a great way to integrate IRIS with other Python frameworks and libraries.

The objective of the article is to provide the reader with the following informations:

• Configure and use the FHIR server
• Create an OAuth2 Authorization Server
• Bind the FHIR server to the OAuth2 Authorization Server for support of SMART on FHIR
• Use the interoperability capabilities of IRIS for Health to filter FHIR resources
• Create a custom operation on the FHIR server

Schema of the article:

I have been using embedded python for more than 2 years now on a daily basis. May be it's time to share some feedback about this journey.

Why write this feedback? Because, I guess, I'm like most of the people here, an ObjectScript developer, and I think that the community would benefit from this feedback and could better understand the pros & cons of chosing embedded python for developing stuff in IRIS. And also avoid some pitfalls.

• Feedback : Using embedded python daily for 2 years
• Introduction
• Starting with Python
  • Python is not ObjectScript
    • Pep8
    • Modules
    • Dunders
  • Conclusion
• Embedded Python
  • What is Embedded Python ?
  • How to use Embedded Python ?
  • How I use Embedded Python
    • Use Python libraries and code as they were ObjectScript classes
      • With the language tag
      • Without the language tag
      • Conclusion
    • Use a python first approach
      • Example : iris-fhir-python-strategy
      • Remarks
      • Where to find the code
        • How to implement a Strategy
        • Implementation of InteractionsStrategy
        • Implementation of Interactions
        • Interactions in Python
        • Implementation of the abstract python class
      • Too long, do a summary

1. IRIS RAG Demo

This demo showcases the powerful synergy between IRIS Vector Search and RAG (Retrieval Augmented Generation), providing a cutting-edge approach to interacting with documents through a conversational interface. Utilizing InterSystems IRIS's newly introduced Vector Search capabilities, this application sets a new standard for retrieving and generating information based on a knowledge base. The backend, crafted in Python and leveraging the prowess of IRIS and IoP, the LLM model is orca-mini and served by the ollama server. The frontend is an chatbot written with Streamlit.

InstallFoundation method is missing (IRIS 2023.2+)

Recently IRIS 2023.2 was released. This version removed this method InstallFoundation from this class HS.HC.Util.Installer. This was a private method and it was not documented. But it was widely used by the community to install FHIR server.

So if you encounter this error:

<METHOD DOES NOT EXIST> *InstallFoundation,HS.HC.Util.Installer

While build a demo our your own FHIR server, you can fix it by replacing this line:

to

  Do ##class(HS.Util.Installer.Foundation).Install(namespace)

This is a sample to deploy iris-oauth-fhir on k3d with IKO.

• iris-oauth-fhir is a sample to deploy a FHIR server with OAuth2 authentication with InterSystems IRIS for Health as a resource server and Google OpenId as an authorization server.
• k3d is a lightweight wrapper to run k3s (Rancher Lab's minimal Kubernetes distribution) in docker.
• IKO is a tool to deploy InterSystems IRIS for Health on Kubernetes.

This is a sample application that demonstrates how to use the InterSystems IRIS for Health FHIR Repository to build a FHIR Repository with OAuth2 authorization, the FHIR endpoint will be the resource server and Google OpenId will be the authorization server.

Description

With InterSystems IRIS FHIR Server you can build a Strategy to customize the behavior of the server (see documentation for more details).

This repository contains a Python Strategy that can be used as a starting point to build your own Strategy in python.

This demo strategy provides the following features:

• Update the capability statement to remove the Account resource
• Simulate a consent management system to allow or not access to the Observation resource
  • If the User has sufficient rights, the Observation resource is returned
  • Otherwise, the Observation resource is not returned

When it comes to build an iris image, we can use the cpf merge files.

Here is an cpf merge example:

[Actions]
CreateDatabase:Name=IRISAPP_DATA,Directory=/usr/irissys/mgr/IRISAPP_DATA

CreateDatabase:Name=IRISAPP_CODE,Directory=/usr/irissys/mgr/IRISAPP_CODE

CreateNamespace:Name=IRISAPP,Globals=IRISAPP_DATA,Routines=IRISAPP_CODE,Interop=1

ModifyService:Name=%Service_CallIn,Enabled=1,AutheEnabled=48

CreateApplication:Name=/frn,NameSpace=IRISAPP,DispatchClass=Formation.REST.Dispatch,AutheEnabled=48

ModifyUser:Name=SuperUser,PasswordHash=a31d24aecc0bfe560a7e45bd913ad27c667dc25a75cbfd358c451bb595b6bd52bd25c82cafaa23ca1dd30b3b4947d12d3bb0ffb2a717df29912b743a281f97c1,0a4c463a2fa1e7542b61aa48800091ab688eb0a14bebf536638f411f5454c9343b9aa6402b4694f0a89b624407a5f43f0a38fc35216bb18aab7dc41ef9f056b1,10000,SHA512

I'm proud to announce the new release of iris-pex-embedded-python (v2.3.1) with a new command line interface.

This command line is called iop for Interoperability On Python.

First I would like to present in few words the project the main changes since the version 1.

A breif history of the project

Version 1.0 was a proof of concept to show how the interoperability framework of IRIS can be used with a python first approach while remaining compatible with any existing ObjectScript code.

What does it mean? It means that any python developer can use the IRIS interoperability framework without any knowledge of ObjectScript.

Example :

from grongier.pex import BusinessOperation

class MyBusinessOperation(BusinessOperation):

    def on_message(self, request):
        self.log.info("Received request")

Great, isn't it?

Named parameters can be achieved with SQLAlchemy :  

from sqlalchemy import create_engine, text,types,engine

_engine = create_engine('iris+emb:///')

with _engine.connect() as conn:
    rs = conn.execute(text("select :some_private_name"), {"some_private_name": 1})
    print(rs.all())

or with native api

from sqlalchemy import create_engine, text,types,engine

# set URL for SQLAlchemy
url = engine.url.URL.create('iris', username='SuperUser', password='SYS', host='localhost', port=33782, database='FHIRSERVER')

_engine = create_engine(url)

with _engine.connect() as conn:
    rs = conn.execute(text("select :some_private_name"), {"some_private_name": 1})
    print(rs.all())

iris-docker-multi-stage-script

A python script to keep your docker iris images in shape ;)

Witout changing your dockerfile or your code you can reduce the size of your image by 50% or more !

TL;DR

Name the builder image builder and the final image final and add this to end of your Dockerfile:

Modify your Dockerfile to use a multi-stage build:

ARG IMAGE=intersystemsdc/irishealth-community:latest
FROM $IMAGE as builder

Add this to end of your Dockerfile:

FROM $IMAGE as final

ADD --chown=${ISC_PACKAGE_MGRUSER}:${ISC_PACKAGE_IRISGROUP} https://github.com/grongierisc/iris-docker-multi-stage-script/releases/latest/download/copy-data.py /irisdev/app/copy-data.py

RUN --mount=type=bind,source=/,target=/builder/root,from=builder \
    cp -f /builder/root/usr/irissys/iris.cpf /usr/irissys/iris.cpf && \
    python3 /irisdev/app/copy-data.py -c /usr/irissys/iris.cpf -d /builder/root/ 

Boom! You're done!

Hi, I spend most of my time on VsCode and I love the dark theme.

But when I go to the InterSystems Community it's all white and I can't read anything.

Is it possible to have a dark theme for the community?

OCR DEMO

This is a demo of the OCR functionality of the pero-ocr library.

It used in the iris application server in python.

Demo

This is an example of input data :

This is the result of the OCR :

In this example you have the following information:

• The text is in the TextEquiv tag
• The confidence is in the conf attribute of the TextEquiv tag
• The coordinates of the text are in the Coords tag

<PcGts xmlns="http://schema.primaresearch.org/PAGE/gts/pagecontent/2019-07-15" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://schema.primaresearch.org/PAGE/gts/pagecontent/2019-07-15/pagecontent.xsd">
  <Metadata>
    <Creator>Pero OCR</Creator>
    <Created>2022-12-13T08:47:12.207893+00:00</Created>
    <LastChange>2022-12-13T08:47:12.207893+00:00</LastChange>
  </Metadata>
  <Page imageFilename="/irisdev/app/misc/in/United_States_Declaration_of_Independence.jpg" imageWidth="3923" imageHeight="4656">
    <TextRegion id="r004">
      <Coords points="977,121 932,121 932,283 1189,277 1178,114 977,121"/>
      <TextLine id="r004-l002" index="0" custom="heights_v2:[123.7,39.0]">
        <Coords points="932,121 932,283 1189,277 1178,114 1130,118 1100,117 1048,121 1019,121 977,121 932,121"/>
        <Baseline points="932,244 977,244 1019,244 1058,244 1100,241 1138,241 1186,238"/>
        <TextEquiv conf="1.000">
          <Unicode>IN</Unicode>
        </TextEquiv>
      </TextLine>
    </TextRegion>
    <TextRegion id="r008">
      <Coords points="1461,107 1241,107 1241,287 2116,290 2549,281 2986,287 3211,277 3203,98 2978,107 2552,101 2114,111 1461,107"/>
      <TextLine id="r008-l001" index="0" custom="heights_v2:[133.8,45.8]">
        <Coords points="1241,107 1241,287 1464,287 1681,284 1896,287 2116,290 2549,281 2986,287 3211,277 3203,98 2978,107 2552,101 2327,107 2114,111 1461,107 1241,107"/>
        <Baseline points="1241,241 1463,241 1682,238 1897,241 2116,244 2331,241 2550,235 2765,238 2984,241 3209,231"/>
        <TextEquiv conf="0.910">
          <Unicode>CONGRESS, JULY 4, 1776.</Unicode>
        </TextEquiv>
      </TextLine>
    </TextRegion>
    <TextRegion id="r001">
      <Coords points="591,452 208,455 209,611 1723,602 2100,608 2855,595 3617,598 3618,442 2855,439 2098,452 1725,446 591,452"/>
      <TextLine id="r001-l003" index="0" custom="heights_v2:[113.8,42.1]">
        <Coords points="208,455 209,611 592,608 968,605 1218,605 1723,602 2100,608 2855,595 3231,595 3617,598 3618,442 2855,439 2477,446 2098,452 1725,446 1346,449 1159,449 591,452 208,455"/>
        <Baseline points="209,569 592,566 968,563 1347,563 1723,559 2100,566 2479,559 2855,553 3231,553 3617,556"/>
        <TextEquiv conf="0.289">
          <Unicode>Dhe unaniwons Declaratton of te Heten maiss States of TNmerica</Unicode>
        </TextEquiv>
      </TextLine>
    </TextRegion>
    <TextRegion id="r000">
      <Coords points="161,3474 161,3539 423,3539 633,3536 958,3468 1354,3472 1764,3581 1944,3571 2246,3730 2653,3718 2718,3633 2855,3608 3238,3557 3514,3554 3739,3462 3762,3397 3761,3333 3735,3139 3743,2696 3730,2177 3735,1920 3723,1727 3736,1341 3717,1014 3724,943 3719,818 3697,693 1012,712 795,776 421,776 183,786 173,848 168,1032 173,2392 160,2713 161,3474"/>
      <TextLine id="r000-l004" index="0" custom="heights_v2:[40.2,18.4]">
        <Coords points="2796,699 2501,703 2205,706 1909,709 1611,709 1460,709 1012,712 1013,771 1315,768 1611,768 1910,768 2206,764 2502,761 2800,758 3096,758 3392,755 3698,752 3697,693 3392,696 3096,699 2802,699 2796,699"/>
        <Baseline points="1013,752 1315,749 1611,749 1910,749 2206,746 2501,743 2800,739 3096,739 3392,736 3697,733"/>
        <TextEquiv conf="0.281">
          <Unicode>hen n lí loune z human venl, i kemu nematy k mpeopě toíohohhehttcal bandí uhích have connechdí tem vith ancthet, andíl</Unicode>
        </TextEquiv>
      </TextLine>
      <TextLine id="r000-l005" index="1" custom="heights_v2:[40.4,19.2]">
        <Coords points="421,776 421,836 794,836 1157,839 1521,839 1884,836 2244,833 2608,829 2971,826 3335,823 3704,813 3703,754 3333,763 2970,767 2607,770 2244,773 1884,776 1520,779 1157,779 795,776 421,776"/>
        <Baseline points="421,817 794,817 1157,820 1521,820 1884,817 2244,813 2608,810 2971,807 3334,804 3704,794"/>
        <TextEquiv conf="0.211">
          <Unicode>o hi ſhwes f he eail, fie rehatal andequal flohon &amp; ufch lhe laav  . kalut and   Aloil ped entilt ttem, a dant rafech to the ofunin o manknd tequies fhat thep</Unicode>
        </TextEquiv>
      </TextLine>
     <!-- Truncated for readme-->
      <TextLine id="r019-l105" index="9" custom="heights_v2:[47.5,21.7]">
        <Coords points="3209,4269 3214,4336 3257,4333 3296,4333 3332,4333 3373,4337 3411,4337 3452,4336 3488,4333 3527,4333 3575,4333 3575,4264 3527,4264 3488,4264 3446,4267 3411,4267 3373,4267 3338,4264 3296,4264 3257,4264 3209,4267 3209,4269"/>
        <Baseline points="3212,4315 3257,4312 3296,4312 3334,4312 3373,4315 3411,4315 3450,4315 3488,4312 3527,4312 3575,4312"/>
        <TextEquiv conf="0.283">
          <Unicode>imuiaa</Unicode>
        </TextEquiv>
      </TextLine>
      <TextLine id="r019-l108" index="10" custom="heights_v2:[40.9,20.2]">
        <Coords points="3198,4406 3251,4409 3294,4409 3339,4412 3394,4415 3398,4354 3343,4351 3298,4348 3251,4348 3202,4345 3198,4406"/>
        <Baseline points="3199,4386 3251,4389 3296,4389 3341,4392 3395,4395"/>
        <TextEquiv conf="0.370">
          <Unicode>Qlver</Unicode>
        </TextEquiv>
      </TextLine>
      <TextLine id="r019-l114" index="11" custom="heights_v2:[39.2,19.1]">
        <Coords points="3181,4469 3225,4466 3263,4466 3305,4466 3327,4466 3352,4465 3386,4462 3424,4462 3472,4462 3472,4404 3424,4404 3386,4404 3341,4407 3305,4407 3263,4407 3225,4407 3177,4411 3181,4469"/>
        <Baseline points="3180,4450 3225,4447 3263,4447 3305,4447 3344,4447 3386,4443 3424,4443 3472,4443"/>
        <TextEquiv conf="0.312">
          <Unicode>Vbalřew/</Unicode>
        </TextEquiv>
      </TextLine>
    </TextRegion>
    <TextRegion id="r020">
      <Coords points="3685,4399 3607,4399 3607,4465 3685,4465 3685,4399"/>
      <TextLine id="r020-l112" index="0" custom="heights_v2:[44.3,21.4]">
        <Coords points="3607,4399 3607,4465 3685,4465 3685,4399 3607,4399"/>
        <Baseline points="3607,4443 3685,4443"/>
        <TextEquiv conf="0.486">
          <Unicode>17.</Unicode>
        </TextEquiv>
      </TextLine>
    </TextRegion>
  </Page>
</PcGts>

ipython-iris-magic

%%iris magic for IPython, can run ObjectScript command in Notebooks

It can be run in any Notebook and does not require any special setup on IRIS or the Notebook.

Demo

Native Api

If you are using Python, you can use the built-in venv module to create a virtual environment. This module is the recommended way to create and manage virtual environments.

A virtual environment is a tool that helps to keep dependencies required by different projects separate by creating isolated python virtual environments for them. It solves the “Project X depends on version 1.x but, Project Y needs 4.x” dilemma, and keeps your global site-packages directory clean and manageable.

So if like me you work a lot with Python, you can use the venv module to create a virtual environment for your project. This will allow you to install packages without affecting the global Python installation.

You will find here two neat alias to create and activate a virtual environment.

Python aliases

alias venv="python3 -m venv .venv; source .venv/bin/activate"
alias irisvenv="python3 -m venv .venv; source .venv/bin/activate; pip install https://github.com/grongierisc/iris-embedded-python-wrapper/releases/download/v0.0.3/iris-0.0.3-py3-none-any.whl"

1. iris-dollar-list

Interpretor of $list for python named DollarList.

This interpretor was made because :

• I wanted to use $list in python.
• Embedded Python do not support $list.
• The native API version do not support embedded $list in $list.

This is a work in progress. For now, it only support embedded $list in $list, int and string.

WIP float,decimal,double

This module is available on Pypi :

pip3 install iris-dollar-list

It is compatible with embedded python and native api.