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.

Before proceeding to the other functions. let us briefly review the execute function within the iris package. This function is exceptionally beneficial for executing the arbitrary ObjectScript functions and class invocation.

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.

Earlier this year I announced availability of a VS Code extension for coding in ObjectScript, Embedded Python or SQL using the notebook paradigm popularized by Jupyter. Today I published a maintenance release to correct a "getting started" problem.

Here's a video of the installation steps from the extension's README:

(video superseded by an update in a later comment)

Why not try it for yourself?

Last Chapter: Creating a REST client to get Tracks from Spotify REST API - Part4 Save the Search Result

Git link: https://github.com/ecelg/InterSystems-IRIS-as-a-Spotify-REST-client

OK.... based on what I have done.... I am able to 

1. Query Track information by making use of the Spotify API

2. Store the necessary data into my own album, artists, and track table

so.... what next?🤔 How about I set up my own REST API service on my IRIS for the other people to query my table?🤔🤨

ok... 1st... start from document Introduction to Creating REST Services

Git link: https://github.com/ecelg/InterSystems-IRIS-as-a-Spotify-REST-client

Recently, I come up an idea in my mind that how can I put my playlist on IRIS.🧐

At the same time, I was told to pay for my Spotify subscription💸💸... ooo.. how about to get some data from the Spotify API... so I started to do study about it.

Like most of the development, let's start from Documentation of  the API https://developer.spotify.com/documentation/web-api

In order to get the data, i am required to request an access token from for the token endpoint URL.🧐

Last Chapter: Creating a REST client to get Tracks from Spotify REST API - Part2 Save and Refresh Token

Git link: https://github.com/ecelg/InterSystems-IRIS-as-a-Spotify-REST-client
 

Ok, now I am pretty sure i have a valid token for making query.😀

Shall we try to query something from the API.

Again, its time to go through the API document https://developer.spotify.com/documentation/web-api/tutorials/getting-started

Search for Request artist data

the suggested code is like the following

I'm trying to use embedded python code that receives an Iris %Stream.GlobalBinary and uses image manipulation library PIL.

Because PIL can't work with IRIS %Stream, I need to convert the image to python bytes.

This process seems to have very bad performance compared to writing to a file and then loading it from a file in python.

Is there a better way to send a stream into python? The conversion code I'm using is below.

Thanks.

defiris_stream_to_bytes(stream):
	stream.Rewind()
	s = ""whilenot stream.AtEnd:
		r = stream.Read(1024)
		s += r
	b = bytearray()
	b.extend(map(ord, s))
	return b

As we keep updating our software, we often realize that we require more and more modern solutions. So far, only one major piece of our software relies on reading barcodes in documents and images. Since Cache did not have a means of reading barcodes in the past, we have always achieved our goals by using a Visual Basic 6 application. However, it is no longer an ideal solution because it is currently complicated to maintain it. IRIS also lacks this capability, but it has recently got an option that makes up for it: embedded Python!

Hi Community,

Play the new video on InterSystems Developers YouTube:

⏯ Using LLMs with InterSystems IRIS Interoperability Productions @ Global Summit 2024

Hello Community,

This article aims to walk you through the process of setting up and utilizing the Flexible Python Runtime Feature for embedded Python. Prior to version 2024.2, Intersystems IRIS installer included a preinstalled version of Python, You can find the Python libraries and application files located in the \lib\python directory within your IRIS installation folder (for example, C:\InterSystems\IRIS20242\lib\python).

This is for IRIS For Health 2024.2.0

We are migrating away from the .NET Gateway and trying to use the python integration instead.

I followed the instructions to install IRIS

Then I installed python following the IRIS documentation indicating that python should be installed globally.

I set up the PythonRuntimeLibrary and PythonRuntimeLibraryVersion options under System->Configuration->Advanced memory settings and when I run the shell function, I get python:

Hi Community,
In this article, I will introduce my application iris-DataViz
iris-DataViz is an Exploratory Data Analysis and Visualization Streamlit Application that leverages the functionality of IRIS embedded python and SQLAlchemy to interact with IRIS, as well as the PyGWalker python library for data analysis and data Visualization. PyGWalker (Python Graphic Walker) is an interactive data visualization library built for Python, aiming to bring the ease and functionality of Tableau-style drag-and-drop visualization into Python environments.

Application Features 

The test data generator is mainly used to generate test data, which can be used to generate test data for tables and fields to meet the needs of different fields according to different types, currently supports Text, Number, Enum, UUID, regular expression, Multiple date and time formats, and Time Seven different types
 

How to use:

1. Select a namespace, you can see all the tables under the namespace,

2. Select the table we want to generate test data from, click on the field, and select the type on the right

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.

Hello community,

How to install the iris  package installer for Python (pip) in python and import iris package in python source code. 

import iris
class Solution():
    iris.connection()

thanks!

If anyone has experience debugging Embedded Python or has insight into why an ObjectScript method when called from a Python method would not work but would work when called directly via ObjectScript or in a Python shell, your help would be appreciated! 

We have an ObjectScript ClassMethod called GetTemplateString() which takes in a templateName of String type and uses the template name to get the template object, access the Code, and read the code into a templateString. The string version of the Code is returned.

As a part of the IRIS Python 2024 contest, my colleague Damir and I went with an idea to build a platform called ShelterShare for connecting victims and volunteers for shelter requests . To do so we chose django as a framework and proceeded to build the first version with 3 different docker containers, django, iris and nginx which would then utilize IRIS as a pure Database engine via the beautifly composed django_iris (cudos to Dimitry). As we were progressing fast, we decided to explore the option of running it within the same container as IRIS by utilizing WSGI added in 2024.1. We knew ahead

Hi Community,
In this article, I will introduce my application iris-RAG-Gen .

Iris-RAG-Gen is a generative AI Retrieval-Augmented Generation (RAG) application that leverages the functionality of IRIS Vector Search to personalize ChatGPT with the help of the Streamlit web framework, LangChain, and OpenAI. The application uses IRIS as a vector store.

Application Features

• Ingest Documents (PDF or TXT) into IRIS
• Chat with the selected Ingested document
• Delete Ingested Documents
• OpenAI ChatGPT

Hi Contestansts!

Here are the results of bonuses gathered by applications in InterSystems Python Programming Contest 2024!

In the previous article we presented the d[IA]gnosis application developed to support the coding of diagnoses in ICD-10. In this article we will see how InterSystems IRIS for Health provides us with the necessary tools for the generation of vectors from the ICD-10 code list using a pre-trained language model, its storage and the subsequent search for similarities on all these generated vectors.

Introduction

Hi Community,

We are pleased to invite you to the next InterSystems online programming contest, which is focused on Python!

🏆 InterSystems Python Contest 🏆

Duration: July 15 - August 4, 2024

Prize pool: $14,000

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. Such applications may include data retrieval (see Don Woodlock's ML301 course for a great intro to Retrieval Augmented Generation), sentiment analysis, and even fully-autonomous AI agents, just to name a few!

Hi Developers!

Here are the technology bonuses for the InterSystems Python Contest 2024 that will give you extra points in the voting:

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

This is an attempt to run a vector search demo completely in IRIS
There are no external tools and all you need is a Terminal / Console and the management portal.
Special thanks to Alvin Ryanputra as his package iris-vector-search that was the base
of inspiration and the source for test data.
My package is based on IRIS 2024.1 release and requires attention to your processor capabilities.

I try to get a vector from calling GetEmbedding, but i failed to convert it into a vector 

Here is a simplyfied sample class: 

Class User.myclass Extends %Persistent
{Property myVECTOR As %Vector(CAPTION = "Vector");

Property myProperty As %String(MAXLEN = 40) [ Required ];

}

here the GetEmbedding part from User.mymethods:

Hello everyone,

Recently, I've been working on a Business Process that processes a large JSON FHIR message containing up to 50k requests in an array within the JSON.

Currently, the code imports the JSON as a dynamic object from the original message stream, obtains an iterator from it, and processes each request one at a time in a loop.

Pandas is not just a popular software library. It is a cornerstone in the Python data analysis landscape. Renowned for its simplicity and power, it offers a variety of data structures and functions that are instrumental in transforming the complexity of data preparation and analysis into a more manageable form. It is particularly relevant in such specialized environments as ObjectScript for Key Performance Indicators (KPIs) and reporting, especially within the framework of the InterSystems IRIS platform, a leading data management and analysis solution. In the realm of data handling and

Hi Community
In this article, I will introduce my application irisChatGPT which is built on LangChain Framework.
First of all, let us have a brief overview of the framework.

The entire world is talking about ChatGPT and how Large Language Models(LLMs) have become so powerful and has been performing beyond expectations, giving human-like conversations. This is just the beginning of how this can be applied to every enterprise and every domain! 

We have a yummy dataset with recipes written by multiple Reddit users, however most of the information is free text as the title or description of a post. Let's find out how we can very easily load the dataset, extract some features and analyze it using features from OpenAI large language model within Embedded Python and the Langchain framework.

Loading the dataset

First things first, we need to load the dataset or can we just connect to it?