Contestant
Contestant
Contestant

I have challenged to create a bot application using Azure Bot that can retrieve and post data to IRIS for Health.

A patient's data has already been registered in the FHIR repository of IRIS for Health.

The patient's MRN is 1001. His name is Taro Yamad. (in Japanese :山田 太郎)

This bot can post new pulse oximeter readings as an observation resource linked to the patient.

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Case description

Let’s imagine that you are a Python developer or have a well-trained team specialized in Python, but the deadline you got to analyze some data in IRIS is tight. Of course, InterSystems offers many tools for all kinds of analyses and treatments. However, in the given scenario, it is better to get the job done using the good old Pandas and leave the IRIS for another time.

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Hi, Community!

This article is an overview of SQLAlchemy, so let's begin!

SQLAlchemy is the Python SQL toolkit that serves as a bridge between your Python code and the relational database system of your choice. Created by Michael Bayer, it is currently available as an open-source library under the MIT License. SQLAlchemy supports a wide range of database systems, including PostgreSQL, MySQL, SQLite, Oracle, and Microsoft SQL Server, making it versatile and adaptable to different project requirements.

The SQLAlchemy SQL Toolkit and Object Relational Mapper from a comprehensive set of tools for working with databases and Python. It has several distinct areas of functionality which you can use individually or in various combinations. The major components are illustrated below, with component dependencies organized into layers:

_images/sqla_arch_small.png

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Contestant

While starting the development with IRIS we have a distribution kit or in case of Docker we are pulling the docker image and then often we need to initialize it and setup the development environment. We might need to create databases, namespaces, turn on/off some services, create resources. We often need to import code and data into IRIS instance and run some custom code to init the solution.

Lajos Simicska declares war on Viktor Orban: "It's either him or me!" - The  Budapest Beacon

And there plenty of templates on Open Exchange where we suggest how to init REST, Interoperability, Analytics, Fullstack and many other templates with ObjectScript. What if we want to use only Python to setup the development environment for Embedded Python project with IRIS?

So, the recent release of Embedded Python template is the pure python boilerplate that could be a starting point for developers that build python projects with no need to use and learn ObjectScript. This article expresses how this template could be used to initialize IRIS. Here we go!

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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.

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Hello,

First of all thanks for your time, thoughts, teaching and help:

We wonder how could we get the metrics from http://[Ip]:[Port]/api/monitor/metrics and use them in Kibana to chart statistics.

We would like to ask you how do you use the api monitor metrics, and as a second question, how would you suggest to utilize them in a third party software as Kibana to chart them.

We have thought to do the following:

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Contestant

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.

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Contestant

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.

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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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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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Article
· Jun 12 3m read
LangChain fixed the SQL for me

This article is a simple quick starter (what I did was) with SqlDatabaseChain.

Hope this ignites some interest.

Many thanks to:

sqlalchemy-iris author @Dmitry Maslennikov

Your project made this possible today.

The article script uses openai API so caution not to share table information and records externally, that you didn't intend to.

A local model could be plugged in , instead if needed.

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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')

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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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Hi everyone,

I'm attempting to compile a basic Python code on a remote server, but it appears that the compiler doesn't recognize the language.

The remote server is running a virtual machine with Oracle Linux Server 7.9 (64-bit), and it has IRIS for UNIX (Red Hat Enterprise Linux for x86-64) 2021.1 (Build 215U) [HealthConnect:3.3.0] installed.

When I try to compile a script that includes a Python ClassMethod, such as this "testpy.cls":

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All,

I've asked my teammate to open a WRC on this issue, but wanted to open the discussion to see if maybe we aren't the first people to see this issue.

The code we are deploying is a COS object with some Python methods. The code works fine locally on the developer's machine. However, when the business process runs in the server environment, we see the following when COS code attempts to call a [Language = python] method:

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In the ever-evolving landscape of data science and machine learning, having the right tools at your disposal can make all the difference. In this article, we want to shine a spotlight on two essential Python libraries that have become indispensable for data scientists and machine learning practitioners alike: Matplotlib and scikit-learn.

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