Hi all,

Does anybody have the same issue?

$ZF(-100) to run python script not work when directly execute in studio or in storedproc called by TrakCare, but can work when do in iris session.

The python script imports a "barcode" package. It seems that when directly execute in studio or in storedproc called by TrakCare, the package can not be imported.

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 am sending an httpRequest from ObjectScript to a python server. I am not receiving a response in OS

OS config On the client side

// Create an HTTP request object
Set httpRequest = ##class(%Net.HttpRequest).%New()

// Set the server URL
Set httpRequest.Server = "http://127.0.0.1:8080"

// Set content type to JSON
Set httpRequest.ContentType = "application/json"

The invention and popularization of Large Language Models (such as OpenAI's GPT-4) has launched a wave of innovative solutions that can leverage large volumes of unstructured data that was impractical or even impossible to process manually until recently.

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

Django, a high-level web framework written in Python, has become a staple for developers seeking a robust, efficient, and easy-to-learn solution for building web applications. Its popularity stems from its versatility, offering developers an efficient toolkit for building web applications. Integrating Django with InterSystems IRIS introduces a dynamic synergy, providing developers with a comprehensive web development and database management solution. That's why on the Ideas Portal, @Evgeny Shvarov suggested that having Examples to work with IRIS from Django would be beneficial. In this article, we'll explore two projects created to answer the posted idea — Django-iris by @Dmitry Maslennikov and Iris-size-django by @Heloisa Paiva.

With the advent of Embedded Python, a myriad of use cases are now possible from within IRIS directly using Python libraries for more complex operations. One such operation is the use of natural language processing tools such as textual similarity comparison.

Using the below python script I am getting :

$ ./hello_world.py
Traceback (most recent call last):
File "/home/wwillett/dev/vscode-objectscript/Samples-python-helloworld/./hello_world.py", line 34, in <module>
run()
File "/home/wwillett/dev/vscode-objectscript/Samples-python-helloworld/./hello_world.py", line 21, in run
connection = irisnative.createConnection(ip, port, namespace, username, password)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: * [ERROR_SEQUENCE_ERROR]

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.

Good morning,

I have a question about the python version, I read in the documentation that the compatible version is 3.9.5 for the proper functioning of python on Iris.

Do we have to stay on this version or can we use newer versions?

Thanks in advance

Regards

How can IRIS productions be deployed more quickly and with greater peace of mind?

The aim of interoperability productions is to enable you to connect systems in order to transform and route messages between them. To connect systems, you develop, configure, deploy and manage productions that integrate several software systems.

New to coding in InterSystems IRIS® data platform? Try this brand-new learning program to get the basics, and see how to develop an application with InterSystems ObjectScript alongside your language of choice: Java, .NET, Python, or Node.js.

I have an existing Python script that opens a child session using the pexpect library. But currently all it does is send hard-coded commands to the Cache process and expect a hard-coded response back in order to continue in the script.

I would like to run a Cache routine from the script, pass in a parameter, and wait for a response that will be different every time (a date, in this case). So the call would be something like D $$Tag^Routine(parameter) and wait for the routine to complete and return the response.

import os

# Get environment variables
db_host = os.getenv('DB_HOST')
db_port = os.getenv('DB_PORT')
db_namespace = os.getenv('DB_NAMESPACE')
db_username = os.getenv('DB_USERNAME')
db_password = os.getenv('DB_PASSWORD')

# Create a database connection
conn = irisnative.createConnection(db_host, db_port, db_namespace, db_username, db_password)

# Create an IRIS instance from this connection
iris_native = irisnative.createIris(conn)

status = iris_native.classMethodValue('%SYSTEM.OBJ', 'Load', 'Production.cls', 'ck')