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.

Demonstration example for the current Grand Prix contest for use of a more complex Parameter template to test the AI.

Interview Questions

There is documentation. A recruitment consultant wants to quickly challenge candidates with some relevant technical questions to a role.

Can they automate making a list of questions and answers from the available documentation?

Interview Answers and Learning

One of the most effective ways to cement new facts into accessible long term memory is with phased recall.

Iris-python-template

Template project with various Python code to be used with InterSystems IRIS Community Edition with container.

Featuring :

• Notebooks
  • Embedded Python Kernel
  • ObjectScript Kernel
  • Vanilla Python Kernel
• Embedded Python
  • Code example
  • Flask demo
• IRIS Python Native APIs
  • Code example

2. Table of Contents

• 1. iris-python-template
• 2. Table of Contents
• 3. Installation
  • 3.1. Docker
• 4. How to start coding
  • 4.1. Prerequisites
    • 4.1.1. Start coding in ObjectScript
    • 4.1.2. Start coding with Embedded Python
    • 4.1.3. Start coding with Notebooks
• 5. What's inside the repository
  • 5.1.

Hi all. Today we are going to upload a ML model into IRIS Manager and test it.

Note: I have done the following on Ubuntu 18.04, Apache Zeppelin 0.8.0, Python 3.6.5.

Introduction

These days many available different tools for Data Mining enable you to develop predictive models and analyze the data you have with unprecedented ease. InterSystems IRIS Data Platform provide a stable foundation for your big data and fast data applications, providing interoperability with modern DataMining tools. 

In this series of articles we explore Data mining capabilities available with InterSystems IRIS.

Schematron is a rule-based validation language for making assertions about the presence or absence of certain patterns in XML documents. A schematron refers to a collection of one or more rules containing tests. Schematrons are written in a form of XML, making them relatively easy for everyone, even non-programmers, to inspect, understand, and write

FHIR has revolutionized the healthcare industry by providing a standardized data model for building healthcare applications and promoting data exchange between different healthcare systems. As the FHIR standard is based on modern API-driven approaches, making it more accessible to mobile and web developers. However, interacting with FHIR APIs can still be challenging especially when it comes to querying data using natural language.

Introducing the FHIR - AI and OpenAPI Chain application, a solution that allows users to interact with FHIR APIs using natural language queries.

Hi all,
I am trying to execute a query like the below code.
set statement = ##class(%ResultSet).%New("some_class:query_method").   // here query method is empty and with rowspec some columname

statement.Execute(param1)

I want to fetch data type of column value returned from above. eg - Name - VARCHAR, amount - INTEGER etc.
How can I get it. Or if not possible directly. Is there any other way to validate or get datatype of values returned. Line we have type() in python3

Yet another example of applying LangChain to give some inspiration for new community Grand Prix contest.

I was initially looking to build a chain to achieve dynamic search of html of documentation site, but in the end it was simpler to borg the static PDFs instead.

Create new virtual environment

mkdir chainpdf

cd chainpdf

python -m venv .

This series of articles would cover Python Gateway for InterSystems Data Platforms. Execute Python code and more from InterSystems IRIS. This project brings you the power of Python right into your InterSystems IRIS environment:

• Execute arbitrary Python code
• Seamlessly transfer data from InterSystems IRIS into Python
• Build intelligent Interoperability business processes with Python Interoperability Adapter
• Save, examine, modify and restore Python context from InterSystems IRIS

Other articles

The plan for the series so far (subject to change).

My major interest is  Working with Globals in Embedded Python.
So I checked the available official documentation.

#1 Introduction to Globals
an attempt of a generic description of what a global is. Pointing to

#2 A Closer Look at ObjectScript
But where is Embedded Python ?
Way down you see

#3 Embedded Python

3.1 Embedded Python Overview
3.1.1 Work with Globals
Great if you have never seen a Global before
Otherwise a shocking primitive example
3.2 Using Embedded Python
Last hope: >>> but there is just NOTHING visible.
This is more than just disappointing! Even IRIS Native API for Python is more detailed.

Python has become the most used programming language in the world (source: https://www.tiobe.com/tiobe-index/) and SQL continues to lead the way as a database language. Wouldn't it be great for Python and SQL to work together to deliver new functionality that SQL alone cannot? After all, Python has more than 380,000 published libraries (source: https://pypi.org/) with very interesting capabilities to extend your SQL queries within Python. This article details how to create new SQL Stored Procedures in InterSystems IRIS Database using Embedded Python.

To install the Python binding on Windows one must follow the instructions in the following: 

https://blogs.msdn.microsoft.com/pythonengineering/2016/04/11/unable-to…

The reason is that ActiveState Python version 2.7.X is built with Visual Studio 2008 and Microsoft provides Visual Studio 2008, which one must install, so that Python C extensions can be built. 

Also, if one still sees the "error "error: Unable to find vcvarsall.bat" message at the Visual Studio 2008 command prompt, then one needs to do the following: 

pip install --upgrade​ setuptools

Keywords:  Anaconda, Jupyter Notebook, Tensorflow GPU, Deep Learning,  Python 3 and HealthShare    

1. Purpose and Objectives

This "Part I" is a quick record on how to set up a "simple" but popular deep learning demo environment step-by-step with a Python 3 binding to a HealthShare 2017.2.1 instance .  I used a Win10 laptop at hand, but the approach works the same on MacOS and Linux.

Last week it was noticed that Python overtook Java by becoming the most popular language in PYPL Index  Tensorflow is a powerful computation engine, very popular in research and academic worlds too.

Creating a Chatbot with IRIS and Python

In this article I'm going to show how to integrate the InterSystems IRIS Database with Python to serve a Machine Learning Model of Natural Language Processing (NLP).

Why Python?

With a large adoption and use in the world, Python have a great community and a lot of accelerators | libraries to deploy any kind of application. If you are curious (https://www.python.org/about/apps/).

Iris Globals

As I start to learn about ^globals they became familiar to use as a fast way to ingest data in a out-of-box data model.

Hi,

this is a public announcement for the first release of Intersystems Cache Object-Relational Mapper in Python 3. Project's main repository is located at Github (healiseu/IntersystemsCacheORM).

About the project

CacheORM module is an enhanced OOP porting of Intersystems Cache-Python binding. There are three classes implemented:

• CacheClient This is the super class of CachePython module. It wraps two functions from intersys.pythonbind module pythonbind3.connection() and pythonbind3.database().

• CacheQuery A subclass of CacheClient that wraps methods and adds extra functionality in intersys.pythonbind.databaseand intersys.pythonbind.query classes

• CacheClass A subclass of CacheClient, that wraps methods and adds extra functionality in intersys.pythonbind.databaseand intersys.pythonbind.object classes

The intersys.pythonbind package is a Python C extension that provides Python application with transparent connectivity to the objects stored in the Caché database.

Some time ago I introduced a new driver for Django for IRIS. Now, let's see how to use Django with IRIS in practice.

This is a first attempt to use Embedded Python in IRIS
The Python code is adapted from solutions for Advent of Code 2020 contest.
Test data are all input to my personal challenge.

Prerequisites

Make sure you have git and Docker desktop installed.

Installation

Clone/git pull this repo into any local directory

$ git clone https://github.

I have seen the Cache Python binding documentation and would like to know if it's also possible with IRIS so I can write data and also read/get it from the DB? The cachesys folder does not contain any python libraries.

Hi, Community!
In this article, I will introduce Python Streamlit Web Framework.
Below, you can find the topics we will cover:

• 1-Introduction to Streamlit Web Framework
• 2-Installation of Streamlit module
• 3-Running Streamlit Application
• 4-Streamlit Basic commands
• 5-Display multimedia 
• 6-Input widgets
• 7-Display progress and status
• 8-Sidebar and container
• 9-Data Visualization
• 10-Display a DataFrame

So, let's start with the first topic.

I'm trying to get started with IRIS for Health but every time I got to a step that asks me to install a .whl-package I cant continue. I'm getting an error that the file does not exist.

Here is the complete error message:

PS C:\Users\x\GIT\quickstarts-multimodel-python> pip install nativeAPI_wheel\irisnative-1.0.0-cp39-cp39m-win_amd64.whl    
WARNING: Requirement 'nativeAPI_wheel\\irisnative-1.0.0-cp39-cp39m-win_amd64.whl' looks like a filename, but the file does not exist
ERROR: irisnative-1.0.0-cp39-cp39m-win_amd64.whl is not a supported wheel on this platform.

Am I doing something wrong?

Hello everyone, I’m a French student in academical exchange for my fifth year of engineering school and here is my participation in the FHIR for Women's Health contest.

This project is supposed to be seen as the backend of a bigger application. It can be plugged into a Front End app and help you gather information from your patients. It will read your data in local and use a Data Transformation to make it into a FHIR object before sending it to the included local FHIR server.

I wanted to participate because Women's Health is a really important topic that must be discussed more.

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.

The performance meets the requirements, even with much larger requests than the one exposed above.

In this short article we talk about how to get Yape running in a docker container to avoid having to setup python on your machine.

It's been a while since the last article in this series, so let's recap quickly.

We talked about using matplotlib to create a basic graph. Afterwards we introduced dynamic graphs using bokeh. In the 3rd part we talked about generating heatmaps using monlbl data.

A common theme in the feedback I got over various channels was the difficulty setting up an environment to run any of these.

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.

Apache Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.

And now it is possible to use with InterSystems IRIS as well.

An online demo is available and it uses IRIS Cloud SQL as a data source.

Keyword: Pandas DataFrame, IRIS, Python, JDBC

Purpose

Pandas DataFrame is popular tool for EDA (Exploratory Data Analysis). In ML tasks, the first thing we usually perform is to understand the data a bit more. Last week I was trying this Covid19 dataset in Kaggle Basically the data is a spreadsheet of 1925 encounter rows with 231 columns, and the task is simply to predict whether a patient (linked to  1 or more encounter records) would be admitted to ICU. So it's a normal classification task, and we would as usual use padas.DataFrame to take a quick look first.

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.

In last week's discussion we created a simple graph based on the data input from one file. Now, as we all know, sometimes we have multiple different datafiles to parse and correlate. So this week we are going to load additional perfmon data and learn how to plot that into the same graph. Since we might want to use our generated graphs in reports or on a webpage, we'll also look into ways to export the generated graphs.

Loading windows perfmon data

The perfmon data extracted from standard pbuttons report is a bit of a peculiar data format. On first glance it is a pretty straightforward csv file.

Pyodbc supports calling stored procedure  , but if the IRIS Stored Procedure ROWSPEC has a column with datatype specified as %Date or %Time, Pyodbc fails to fetch it and throws this error.

"

pyodbc.Error: (' 2201', '[ 2201] [Cache ODBC][State :  22018 ][Native Code 22005]\r\nERROR #388: Unknown error, code 22005 (22005) (SQLGetData)')

"

on printing the cursor execute description, pyodbc reads the column as <int>.

and if the ROWSPEC datatype specification was removed, it fetches successfully.

i'm using the driver "InterSystems IRIS ODBC35"  2019.2.0.107

Keywords:   Jupyter Notebook, Tensorflow GPU, Keras, Deep Learning, MLP,  and HealthShare    

1. Purpose and Objectives

In  previous"Part I" we have set up a deep learning demo environment. In this "Part II" we will test what we could do with it.

Many people at my age had started with the classic MLP (Multi-Layer Perceptron) model. It is intuitive hence conceptually easier to start with.

So let's try a Keras "deep learning MLP" with standard demo data that everybody in AI/NN community has been using. It is a kind of so called "supervised learning".