Enhanced Password Management: Edit Passwords Seamlessly

In the ever-evolving landscape of digital security, robust password management tools have become indispensable. Our password management application, designed to simplify and secure your online life, now comes with an enhanced feature – the ability to edit passwords with ease.

Why is this feature a game-changer?

1. Flexibility: Life is dynamic, and so are our online accounts. With the new edit password feature, you have the flexibility to modify your saved passwords whenever you need to.

native-api-py-demo

This is a demo of IRIS Native API for Python, which uses Python to call the Object Script method and flow the message in production. Python obtains the message after flow and the message in global, and uses ZPM Package deployment.

Firstly, we need to install the Native API package

Enter on the command line

Hi Developers!

Hey Developers,

Watch this video to learn how to use Embedded Python using applications from the Open Exchange app gallery:

⏯ Embedded Python Use Cases @ Global Summit 2023

Hi Developers,

We are pleased to invite you all to the new InterSystems online programming contest focused on Python! 

🏆 InterSystems Python Programming Contest 🏆

Duration: September 4 - 24, 2023

Prize pool: $14,000

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

Hi Community
In this article, I will introduce my application IRIS-FlaskBlog.
IRIS-FlaskBlog Application is a real-world application that leverages the functionality of Flask web framework, SQLALchemy ORM, and InterSystems IRIS. The application contains user registration and authentication with the help of Flask-Login python library, a responsive user interface to create and edit posts.

In my previous articles, I described my Command Line Extension to NativeAPI.
Of course, this is also available for any other NativeAPI package.
So I created this example in Python as a demo.

Introduction

In some of the last few articles I've talked about types between IRIS and Python, and it is clear that it's not that easy to access objects from one side at another. 

Fortunately, work has already been done to create SQLAlchemy-iris (follow the link to see it on Open Exchange), which makes everything much easier for Python to access IRIS' objects, and I'm going to show the starters for that.

Thank you @Dmitry Maslennikov !

I'm using the PEX framework to create non-polling Business Services in Python. Below is the code I've used to instantiate my Python Business Service from the application I have written:

conn = iris.connect(...)
IRIS = iris.createIRIS(conn)
#...#
pexserv = iris.pex.Director.CreateBusinessService(conn, "Demo.PEX.FlaskPEXService")
response = pexserv.ProcessInput(record_id)
IRIS.close() # Release IRIS obj
conn.close()

Introducing Django

Django is a web framework designed to develop servers and APIs, and deal with databases in a fast, scalable, and secure way. To assure that, Django provides tools not only to create the skeleton of the code but also to update it without worries. It allows developers to see changes almost live, correct mistakes with the debug tool, and treat security with ease.

To understand how Django works, let’s take a look at the image:

Hello,

I need AES ECB with PKSC7 padding for an interface.
Unfortunately, the %SYSTEM.Encryption.AESEncode cannot do this.

Therefore I wanted to include the following python lib.
PyCrptydome -> https://pycryptodome.readthedocs.io/en/latest/index.html

We need to install the package offline on the system. So I downloaded it and put it in the MGR/Python/ directory.

However, when I try to install it, I get the following error message:

E:\HealthConnect\20201\bin>irispip install E:\HealthConnect\20201\Mgr\python\pycryptodome-3.18.0.tar.

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.

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.

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

1. interoperability-embedded-python

This proof of concept aims to show how the iris interoperability framework can be used with embedded python.

1.1. Table of Contents

• 1. interoperability-embedded-python
  • 1.1. Table of Contents
  • 1.2. Example
  • 1.3. Register a component
• 2. Demo
• 3. Prerequisites
• 4. Installation
  • 4.1. With Docker
  • 4.2. Without Docker
  • 4.3. With ZPM
  • 4.4. With PyPI
    • 4.4.1. Known issues
• 5. How to Run the Sample
  • 5.1. Docker containers
  • 5.2. Management Portal and VSCode
  • 5.3. Open the production
• 6. What's inside the repository
  • 6.1. Dockerfile
  • 6.2. .vscode/settings.json
  • 6.3. .

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

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.

What is zpip?

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

Idea sourced from InterSystems Ideas Portal

Previous Posts:

Using AI to Simplify Clinical Documents Storage, Retrieval, and Search

Doctor-Patient Conversations: AI-Powered Transcription and Summarization

Introduction

The healthcare industry is continuously evolving, and the need for efficient document management and patient data management is more critical than ever. In this article, we will focus on the specific aspects of integrating Google Docs and Google Sheets with FHIR data in the context of healthcare data interoperability.

Introduction

A password manager is an important security tool that allows users to store and manage their passwords without the need to remember or write them down in insecure places. In this article, we will explore the development of a simple password manager using the Flask framework and the InterSystems IRIS database.

Key Features

Our password manager application will provide the following key features:

1. User registration with account creation.
2. User authentication during login.
3. Adding new passwords with a title, login, and password.

This project is implemented as a tool for viewing temperature data taken from a temperature sensor installed in Rasperry PI and located in a remote place where there is Internet, for example, in dacha.

The module for regular reading and sending information is implemented in python and is built in the same project. If the temperature in the country house becomes lower or higher than the threshold values, then a notification will be sent to the telegram channel.

Our objective

In the last article, we talked about a few starters for Django. We learned how to begin the project, ensure we have all the requisites, and make a CRUD. However, today we are going a little further. 
Sometimes we need to access more complex methods, so today, we will connect IRIS to a Python environment, build a few functions and display them on a webpage. It will be similar to the last discussion, but further enough for you to make something new, even though not enough to feel lost.

As an AI language model, ChatGPT is capable of performing a variety of tasks like language translation, writing songs, answering research questions, and even generating computer code. With its impressive abilities, ChatGPT has quickly become a popular tool for various applications, from chatbots to content creation.
But despite its advanced capabilities, ChatGPT is not able to access your personal data. So in this article, I will demonstrate below steps to build custom ChatGPT AI by using LangChain Framework:

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.

Hi folks!

How can I refer to a classmethod of the same class while coding another classmethod with Embedded python?

I know that I can call it with iris.cls(classname).MethodName(), but it's more cumbersome even comparing with ObjectScript, where I can call ..MethodName().

Compare ObjectScript:

do ..SetupGame()

and the same call in EmbeddedPython:

    iris.cls('eshvarov.sample.SeaBattle.GamePython').SetupGame()

Thoughts?

Hi folks!

I have a need to use symilar to $property function from Python. Here is the code:

obj=iris.cls('some.persistent.class')._New()

for property, value in data.items():

 $property(obj.property)=value ; I invented this

How could I do this? Any trick?

For now I plan to implement a helper function in iris that I will call, but I doubt also how can I transfer oref to IRIS.

Thoughts?

Hi folks!

Consider I need to call a python function which name contains "_" symbol (which is quite often in Python). How it could be called from ObjectScript?

E.g. here is the code:

Set sm = ##class(%SYS.Python).Import("sample")

write sm.helloworld() ; function without _
white sm.hello_world() ; function with _ - won't compile.

Thanks in advance!

I want to connect IRIS system as it has all the database tables. on top of that I am creating a REST API in python. How can I connect to IRIS DB. here is my example code for connection

def connect():

connection_string = "localhost:1972/USER"

username = "_SYSTEM"

password = "SYS"

conn = iris.connect(connection_string, username, password)

after this connection is created but how can I get tables data. Please let me know more about how we can integrate IRIS database into a python REST API.

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.

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.

Here, models as example :

• https://huggingface.co/gpt2

• https://huggingface.co/Jean-Baptiste/camembert-ner

• https://huggingface.co/bert-base-uncased

• https://huggingface.co/facebook/detr-resnet-50

• https://huggingface.co/facebook/detr-resnet-50-panoptic

• 1. iris-huggingface

• 2. Installation

  • 2.1. Starting the Production
  • 2.