Index

Part 1

  • Introducing Flask: a quick review of the Flask Docs, where you will find all the information you need for this tutorial;
  • Connecting to InterSystems IRIS: a detailed step-by-step of how to use SQLAlchemy to connect to an IRIS instance;

Part 2

  • A discussion about this kind of implementation: why we should use it and situations where it is applicable.
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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.

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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.

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I am just writing something to share what I encountered last night, which is the IRIS 2024.3 does not comes with Python by default any more!!!

Which means that I need to install it by myself!!😅 The pros is, I can select my python version😁🤭💃 The trouble is.... at the first place.... I don't know what I should do😥. By going through the community (I am much more prefer than the official document, sorry InterSystems document team😓 ), I found the following piece

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   _________ ___ ____  
  |__  /  _ \_ _|  _ \ 
    / /| |_) | || |_) |
   / /_|  __/| ||  __/ 
  /____|_|  |___|_|    

Starting in version 2021.1, InterSystems IRIS began shipping with a python runtime in the engine's kernel. However, there was no way to install packages from within the instance. The main draw of python is its enormous package ecosystem. With that in mind, I introduce my side project zpip, a pip wrapper that is callable from the iris terminal.

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image

Hi Community,
In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):

  • Step1: Install required libraries

  • Step2: Create patterns and responses file

  • Step3: Train the Model

  • Step4: Create ChatBot Application based on the trained model

So Let us start.

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Article
· Apr 5, 2022 4m read
Serializing Python objects in globals

Motivation

This project was thought of when I was thinking of how to let Python code deal naturally with the scalable storage and efficient retrieving mechanism given by IRIS globals, through Embedded Python.

My initial idea was to create a kind of Python dictionary implementation using globals, but soon I realized that I should deal with object abstraction first.

So, I started creating some Python classes that could wrap Python objects, storing and retrieving their data in globals, i.e., serializing and deserializing Python objects in IRIS globals.

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This is my introduction to a series of posts explaining how to create an end-to-end Machine Learning system.

Starting with one problem

Our IRIS Development Community has several posts without tags or wrong tagged. As the posts keep growing the organization
of each tag and the experience of any community member browsing the subjects tends to decrease.

First solutions in mind

We can think some usual solutions for this scenario, like:

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For the upcoming Python contest, I would like to make a small demo, on how to create a simple REST application using Python, which will use IRIS as a database. Using this tools

  • FastAPI framework, high performance, easy to learn, fast to code, ready for production
  • SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL
  • Alembic is a lightweight database migration tool for usage with the SQLAlchemy Database Toolkit for Python.
  • Uvicorn is an ASGI web server implementation for Python.

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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.

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You can learn a lot from a first impression; we want to hear about yours.

As a continuation of our User Insights Interview program (see this post for more details), we’re expanding our scope to include Python developers, particularly those of you who are new to working with InterSystems technology. We’re looking to conduct one-on-one interviews to hear your honest thoughts about getting started: What made sense, what didn’t, and where we could improve.

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InterSystems IRIS currently limits classes to 999 properties.

But what to do if you need to store more data per object?

This article would answer this question (with the additional cameo of Community Python Gateway and how you can transfer wide datasets into Python).

The answer is very simple actually - InterSystems IRIS currently limits classes to 999 properties, but not to 999 primitives. The property in InterSystems IRIS can be an object with 999 properties and so on - the limit can be easily disregarded.

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Why should you connect Flask to InterSystems IRIS?

The first thing that comes to mind when we think about combining Flask with IRIS is a portal to interact with your clients and partners. A good example would be a website for patients to access their clinical exams. Of course, this case would require a whole new layer of security, which we did not cover in our last article. However, we can effortlessly add it with Werkzeug, for instance.

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