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#Python

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Python is an interpreted high-level programming language for general-purpose programming. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace

Official site.

InterSystems Python Binding Documentation.

Here you'll find a simple program that uses Python in an IRIS environment and another simple program that uses ObjectScript in a Python environment. Also, I'd like to share a few of the troubles I went trough while learning to implement this.

Python in IRIS environment

Let's say, for example, you're in an IRIS environment and you want to solve a problem that you find easy, or more efficient with Python.

You can simply change the environment: create your method as any other, and in the end of it's name and specifications, you add [ Language = python ]:

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Article
· Jul 25, 2022 8m read
Introduction to Django part 2

In the first part, I've shown how to start a new project on Django, as well as define new models and add already existing models.

This time, I'll introduce an admin panel, available out of the box and how it can be useful.

Important note: do not expect that if you try to repeat actions from this post it will work for you, it does not. During the article, I had to do some fixes in the django-iris project, and even in DB-API driver made by InterSystems to fix some issues there as well, and I think this driver is still in development, and we will get more stable driver in future. Let's decide that this article only explains how it could be if we would have all done.

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Apache Spark has rapidly become one of the most exciting technologies for big data analytics and machine learning. Spark is a general data processing engine created for use in clustered computing environments. Its heart is the Resilient Distributed Dataset (RDD) which represents a distributed, fault tolerant, collection of data that can be operated on in parallel across the nodes of a cluster. Spark is implemented using a combination of Java and Scala and so comes as a library that can run on any JVM.

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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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Article
· Mar 24, 2024 8m read
Python BPL in preview

BPL from 10,000 feet

BPL stands for Business Process Language.
This is an XML format for describing complex information orchestration interactions between systems.
InterSystems Integration engine has for two decades, provided a visual designer to build, configure, and maintain, BPL using a graphical interface.
Think of it like drawing a process flow diagram that can be compiled and deployed.

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Article
· Jun 12, 2023 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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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>

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Article
· Dec 6, 2022 3m read
OCR DEMO

OCR DEMO

This is a demo of the OCR functionality of the pero-ocr library.

It used in the iris application server in python.

Demo

This is an example of input data :

input

This is the result of the OCR :

In this example you have the following information:

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ObjectScript Kernel Logo
Jupyter Notebook is an interactive environment consisting of cells that allow executing code in a great number of different markup and programming languages.

To do this Jupyter has to connect to an appropriate kernel. There was no ObjectScript Kernel, that is why I decided to create one.

You can try it out here.

Here's a sneak peek of the results:

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Introduction

As the health interoperability landscape expands to include data exchange across on-premise as well as hosted solutions, we are seeing an increased need to integrate with services such as cloud storage. One of the most prolifically used and well supported tools is the NoSQL database DynamoDB (Dynamo), provided by Amazon Web Services (AWS).

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Many factors affect a person's quality of life, and one of the most important is sleep. The quality of our sleep determines our ability to function during the day and affects our mental and physical health. Good quality sleep is critical to our overall health and well-being. Therefore, by analyzing indicators preceding sleep, we can determine the quality of our sleep. This is precisely the functionality of the Sheep's Galaxy application.

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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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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.

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This is the first article of a series diving into visualization tools and analysis of time series data. Obviously we are most interested in looking at performance related data we can gather from the Caché family of products. However, as we'll see down the road, we are absolutely not limited to that. For now we are exploring python and the libraries/tools available within that ecosystem.

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Introduction

In InterSystems IRIS 2024.3 and subsequent IRIS versions, the AutoML component is now delivered as a separate Python package that is installed after installation. Unfortunately, some recent versions of Python packages that AutoML relies on have introduced incompatibilities, and can cause failures when training models (TRAIN MODEL statement). If you see an error mentioning "TypeError" and the keyword argument "fit_params" or "sklearn_tags", read on for a quick fix.

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Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 3 – REST and Interoperability

Now that we have finished the configuration of the SQL Gateway and we have been able to access the data from the external database via python, and we have set up our vectorized base, we can perform some queries. For this in this part of the article we will use an application developed with CSP, HTML and Javascript that will access an integration in Iris, which then performs the search for data similarity, sends it to LLM and finally returns the generated SQL. The CSP page calls an API in Iris that receives the data to be used in the query, calling the integration. For more information about REST in the Iris see the documentation available at https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls...

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Using embedded Python while building your InterSystems-based solution can add very powerful and deep capabilities to your toolbox.

I'd like to share one sample use-case I encountered - enabling a CDC (Change Data Capture) for a mongoDB Collection - capturing those changes, digesting them through an Interoperability flow, and eventually updating an EMR via a REST API.

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The objective of the article is to provide the reader with the following informations:

  • Configure and use the FHIR server
  • Create an OAuth2 Authorization Server
  • Bind the FHIR server to the OAuth2 Authorization Server for support of SMART on FHIR
  • Use the interoperability capabilities of IRIS for Health to filter FHIR resources
  • Create a custom operation on the FHIR server

Schema of the article:

Schema

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Introduction

Not so long ago, I came across the idea of using Python Class Definition Syntax to create IRIS classes on the InterSystems Ideas Portal. It caught my attention since integrating as many syntaxes as possible gives visibility to InterSystems’s products for programmers with experience in many languages.

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Hello Community,

SQL language remains the most practical way to retrieve information stored in a database.

The JSON format is very often used in data exchange.

It is therefore common to seek to obtain data in JSON format from SQL queries.

Below you will find simple examples that can help you meet this need using ObjectScript and Python code.

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It seems like yesterday when we did a small project in Java to test the performance of IRIS, PostgreSQL and MySQL (you can review the article we wrote back in June at the end of this article). If you remember, IRIS was superior to PostgreSQL and clearly superior to MySQL in insertions, with no big difference in queries.

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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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