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.

Let me introduce my new project, which is irissqlcli, REPL (Read-Eval-Print Loop) for InterSystems IRIS SQL

• Syntax Highlighting
• Suggestions (tables, functions)
• 20+ output formats
• stdin support
• Output to files

Install it with pip

pip install irissqlcli

Or run with docker

docker run -it caretdev/irissqlcli irissqlcli iris://_SYSTEM:SYS@host.docker.internal:1972/USER

Connect to IRIS

$ irissqlcli iris://_SYSTEM@localhost:1972/USER -W
Password for _SYSTEM:
Server:  InterSystems IRIS Version 2022.3.0.606 xDBC Protocol Version 65
Version: 0.1.0
[SQL]_SYSTEM@localhost:USER> select $ZVERSION
+---------------------------------------------------------------------------------------------------------+
| Expression_1                                                                                            |
+---------------------------------------------------------------------------------------------------------+
| IRIS for UNIX (Ubuntu Server LTS for ARM64 Containers) 2022.3 (Build 606U) Mon Jan 30 2023 09:05:12 EST |
+---------------------------------------------------------------------------------------------------------+
1 row in set
Time: 0.063s
[SQL]_SYSTEM@localhost:USER> help
+----------+-------------------+------------------------------------------------------------+
| Command  | Shortcut          | Description                                                |
+----------+-------------------+------------------------------------------------------------+
| .exit    | \q                | Exit.                                                      |
| .mode    | \T                | Change the table format used to output results.            |
| .once    | \o [-o] filename  | Append next result to an output file (overwrite using -o). |
| .schemas | \ds               | List schemas.                                              |
| .tables  | \dt [schema]      | List tables.                                               |
| \e       | \e                | Edit command with editor (uses $EDITOR).                   |
| help     | \?                | Show this help.                                            |
| nopager  | \n                | Disable pager, print to stdout.                            |
| notee    | notee             | Stop writing results to an output file.                    |
| pager    | \P [command]      | Set PAGER. Print the query results via PAGER.              |
| prompt   | \R                | Change prompt format.                                      |
| quit     | \q                | Quit.                                                      |
| tee      | tee [-o] filename | Append all results to an output file (overwrite using -o). |
+----------+-------------------+------------------------------------------------------------+
Time: 0.012s
[SQL]_SYSTEM@localhost:USER>

The Jupyter Notebook is an open source web application that can be used to create and share documents that contain live text, code, equations and visualizations. It is maintained by the people at Project Jupyter.

Let's say you have Python including variable-length arguments methods. How can you call it from ObjectScript?

We have a rule to disable a user account if they have not logged in for a certain number of days. IRIS Audit database logs many events such as login failures for example. It can be configured to log successful logins as well. We have IRIS clusters with many IRIS instances. I like to run queries against audit data from ALL IRIS instances and identify user accounts which have not logged into ANY IRIS instance.

Hi Community,
In this article, I will introduce my application iris-mlm-explainer

Named parameters can be achieved with SQLAlchemy :

from sqlalchemy import create_engine, text,types,engine

_engine = create_engine('iris+emb:///')

with _engine.connect() as conn:
    rs = conn.execute(text("select :some_private_name"), {"some_private_name": 1})
    print(rs.all())

or with native api

from sqlalchemy import create_engine, text,types,engine

# set URL for SQLAlchemy
url = engine.url.URL.create('iris', username='SuperUser', password='SYS', host='localhost', port=33782, database='FHIRSERVER')

_engine = create_engine(url)

with _engine.connect() as conn:
    rs = conn.execute(text("select :some_private_name"), {"some_private_name": 1})
    print(rs.all())

Why I've decided to write this

In my last article I've talked about returning values with Python. But returning them is simple, what can make it harder is what I'm going to talk about today: where the value is treated.

Python object in IRIS

Following the example of the last aricle, we have the method:

I'm curious about how embedded Python is handled by %CSP classes, particularly in the case of defining REST endpoints on IRIS.

Here is a simple dispatch class for the endpoint /api/pythonapp on my local IRIS instance (2022.3):

In article

https://community.intersystems.com/print/518106

Traceback (most recent call last):
File "c:\Users\rochesterd\PythonScripts\fhir_stuff\fhir-client-python-main\fhir-client-python-main\src\client.py", line 57, in <module>
patient0 = Patient.parse_obj(patients_resources.search(
AttributeError: 'NoneType' object has no attribute 'serialize'

Background

In InterSystems IRIS versions >=2021.2 we can use the accompanying irispython binary to directly write python code on top of our IRIS instances. This lets us use python packages, call methods, make SQL queries, and do nearly anything in Objectscript but pythonic.

For example, below I check if a namespace is present:

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

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

We're having a problem with the way Python modules are being cached in Iris. If we modify some code and then reimport a module it is still processing the old code.

E.g. Create a python file:

helloWorld.py

def helloWorld() :
return "Hello world"

The run the following in the Iris terminal: