Hello,

I've recently updated the python version of a linux server running Red Hat Enterprise Linux 8.10 (Ootpa). We have an instance 2023.1 running there, and whenever I run the $System.Pyhthon.Shell() I can see it's still pointing to the old version. From within linux, it runs the latest one (we've change all the links to the new 3.11, so no scripts are broken).

So I guess the problem comes from the fact irispython is still compiled using old python version. So, how can I do to force IRIS to use the current version on the server, or update the irispython file?

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1. IRIS RAG Demo

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.

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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>.

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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.

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I implemented a Python Flask application for the 2024 Python Contest with a page that provides common form fields for an outgoing email such as the To and CC fields. And it lets you input a message as well as uploading text based attachments.

Then using LlamaIndex in Python, the app analyzes the content you put in and returns to you in a result box if there is anything that should stop you from sending that email.

Take a look at the Github repo here.

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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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If you are using Python, you can use the built-in venv module to create a virtual environment. This module is the recommended way to create and manage virtual environments.

A virtual environment is a tool that helps to keep dependencies required by different projects separate by creating isolated python virtual environments for them. It solves the “Project X depends on version 1.x but, Project Y needs 4.x” dilemma, and keeps your global site-packages directory clean and manageable.

So if like me you work a lot with Python, you can use the venv module to create a virtual environment for your project. This will allow you to install packages without affecting the global Python installation.

You will find here two neat alias to create and activate a virtual environment.

Python aliases

alias venv="python3 -m venv .venv; source .venv/bin/activate"
alias irisvenv="python3 -m venv .venv; source .venv/bin/activate; pip install https://github.com/grongierisc/iris-embedded-python-wrapper/releases/download/v0.0.3/iris-0.0.3-py3-none-any.whl"

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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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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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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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In the world of APIs, REST is very extended. But what happens when you need more flexibility in your data-fetching strategies? For instance letting the client to choose what fields is going to receive. Enter GraphQL, a query language for your APIs that provides a flexible alternative to REST.

In this post, we will:

  • Compare REST and GraphQL.
  • Dive into the basics of GraphQL: Queries, Mutations, and HTTP.
  • Build a simple GraphQL server implementation using Graphene, SQLAlchemy, and Flask over data in InterSystems IRIS.
  • Explore how to deploy your GraphQL server as a WSGI application in IRIS.
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I was interested in accessing IRIS (Healthshare) using Python. I found instructions how to this here: https://github.com/intersystems/quickstarts-python/tree/master/Solutions...

The installation went well using pip and when python executes "import irisnative" it works fine. It just fails with a connection timeout when I try "irisnative.createConnection(...)." Below is my code:

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I have just created a new Global Master Topic, "IRIS Cheatsheets". IRIS has introduced a lot of new functionality, especially in scripting languages, FHIR R4 support, enhanced Interoperability Tools, and IRIS Analytics. Having spent 35 years working on Windows-based PC's and Laptops, I have surprisingly little knowledge of Linux, Docker and Git. Furthermore, I have written almost every application and Interface in ObjectScript with splatterings of SQL, .Net, and Java Gateways and the most basic knowledge of WinSCP, Putty, SSH. All that changed when I received my first Raspberry Pi.

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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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New to Python. Attempting to use pypyodbc to select data from a table in one Cache database, and inserting into a similarly configured table in another. Process works fine except for tables containing Date types. NULL values in date columns are handled without issue, but when data is present, insert fails with:

An error occurred: argument 7: TypeError: 'NoneType' object cannot be interpreted as an integer.

Source table:

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Is there a way to automatically transform Object Script arrays to Python lists? This code results in a list of arrays

Iter0 =  dbnative.iterator("HS.Data.OIDMapD")
for subscript, value in Iter0.items():
    print(f"subscript={subscript}, value={value}")

Here is the result:

subscript=1, value=2.16.840.1.113883.3.86ISCInterSystems Corporation

I suppose it would be too hard to parse this into a list, I was just wondering if there was a function provided to make it convenient and proper.

Thanks,

Marlin Mixon

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Hello,

When setting up a new web app in iris (iris is in a container) iris complains that a WSGI framework is not installed. I have installed python into the container as well as both flask and django via the python virtual environment (see second screenshot) and the python language server is running

Is this the wrong way to install flask? How do I get the container version to recoginize that flask is installed?

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