The InterSystems IRIS is a great data platform and it is met the current features required by the market. In this article, you see the top 10:

Note: this list was updated because many features are added to IRIS in last 3 years (thanks @Kristina.

Hi Community,
In this article, I will introduce Python Flask Web Framework. Together we will create a minimal web application to connect to IRIS and get data from it.
Below you can find the steps we will need to follow:

• Step 1 : Introduction to Python Flask Web Framework
• Step 2 : Installation of Flask module
• Step 3 : Creation of web application using Flask
• Step 4 : Use of HTML Templates 
• Step 5 : Installation of IRIS Python Native module
• Step 6 : Establishment of a connection with IRIS 
• Step 7 : Transferring data from IRIS to Flask and displaying it

So Let's start with step 1

Step1-Introduction to Python Flask Web Framework 

Flask is a small and lightweight Python web framework that provides useful tools and features that make creating web applications in Python easier. It gives developers flexibility and is a more accessible framework for new developers since it allows to build a web application quickly using only a single Python file. Flask is also extensible and doesn’t requires a particular directory structure or complicated boilerplate code before getting started.

For more details please view Flask Documentations

Hello,

I'm trying to set Caché-Python Binding on Mac, but there is a problem.

I performed installation and configuration of Caché-Python binding module based on the manual (URL)
including setting of PATH and LD_LIBRARY_PATH in "bash_profile", 
and they seems to be done successfully (there was no error in the process).

However, when I execute test python file (test.py), it failed with error massage as below.
-----------------------Error Massage----------------------
Traceback (most recent call last):
  File "test.py", line 2, in <module>
    import intersys.pythonbind3
  File "/$USER$/.

Hi developers!

Recently we announced the preview of Embedded Python technology in InterSystems IRIS.

Check the Sneak Peak video by @Robert.Kuszewski.

Embedded python gives the option to load and run python code in the InterSystems IRIS server. You can either use library modules from Python pip, like numpy, pandas, etc, or you can write your own python modules in the form of standalone py files.

So once you are happy with the development phase of the IRIS Embedded Python solution there is another very important question of how the solution could be deployed.

One of the options you can consider is using the ZPM Package manager which is described in this article.

If you are looking for a slick way to integrate your IRIS solution in the Amazon Web Services ecosystem, server less application, or boto3 powered python script, using the IRIS Python Native API could be the way to go. You don't have to build out to far with a production implementation until you'll need to reach out and get something or set something in IRIS to make your application do its awesome sauce, so hopefully you will find value in this article and build something that matters or doesn't matter at all to anybody else but you as that is equally important.

Welcome to day 3 of Virtual Summit 2021!  We have incredible content available to you this year and I'd just like to bring your attention to the 4(!) sessions that we have on Embedded Python.

• Introduction to Embedded Python - What is Embedded Python and Why is it awesome
• Embedded Python for ObjectScript developers - A technical deep dive into using Python and ObjectScript together inside IRIS
• Embedded Python with Interoperability - Covers how to use Embedded Python to create your own custom interoperability components.

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:

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.

Well, shortly after @Dmitry Maslennikov told me "Why don't you test it from a Python project?" Well, here is the Python version of the tests we previously performed using the JDBC connections.

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:

Jupyter Kernels 101

There are several ways to create a Jupyter Kernel. I decided to make a Python wrapper kernel.

We have to create a subclass of ipykernel.kernelbase.

I'd like to share an example on how the new Embedded Python feature in IRIS helped me in my daily routines.

While I’m participating in the iris-kaggle-socrata-generator project with Henrique Dias, I got to unzip datasets from Kaggle in order to import them.

Such a task was easily achieved by using the zipfile lib in Python (this code was copied from this stackoverflow):

Method UnZip(pZipFileName As %String, pExtractToDir As %String) As %DynamicArray [ Language = python ]
{
    import zipfile
    import iris
    with zipfile.ZipFile(pZipFileName, 'r') as zip_ref:
        zip_ref.

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:

#!/usr/irissys/bin/irispython
import iris
# call arbitrary class methods
result = iris.cls('%SYS.Namespace').Exists('USER')
if result == 1:
    print(f"Namespace USER is present")

But, what if my method in IRIS has special parameters such as Output and ByRef parameters?

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:

This is not an issue in ObjectScript, due to its typeless nature. But it's essential for external programming languages that care a bit more about types of variables.

And in any case, it's still reproducible in ObjectScript. I have table

CREATE TABLE some_table (
        id INTEGER NOT NULL, 
        x INTEGER, 
        y INTEGER, 
        z VARCHAR(50), 
        PRIMARY KEY (id)
)

And data

INSERT INTO some_table (id, x, y, z) VALUES (1, 1, 2, 'z1');
INSERT INTO some_table (id, x, y, z) VALUES (2, 2, 3, 'z2');
INSERT INTO some_table (id, x, y, z) VALUES (3, 3, 4, 'z3');
INSERT INTO some_table (id, x, y, z) VALUES (4, 4, 5, 'z4');

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>

Hi,

I am experimenting with Cache-Python binding.  In the following piece of Python code

import intersys.pythonbind3

conn = intersys.pythonbind3.connection( )
conn.connect_now('localhost[1972]:SAMPLES', '_SYSTEM', '123', None)
samplesDB = intersys.pythonbind3.database(conn)
p10 = samplesDB.openid("Sample.Person",'10',-1,-1)
p10.run_obj_method("PrintPerson",[])

I am opening the 10th record of Sample.Person class and then I am calling an object method (PrintPerson). 

Method PrintPerson()

  {

    Write !, "Name: ", .

Headache-free stored objects: a simple example of working with InterSystems Caché objects in ObjectScript and Python

Neuschwanstein Castle

Tabular data storages based on what is formally known as the relational data model will be celebrating their 50th anniversary in June 2020. Here is an official document – that very famous article.  Many thanks for it to Doctor Edgar Frank Codd. By the way, the relational data model is on the list of the most important global innovations of the past 100 years published by Forbes.

On the other hand, oddly enough, Codd viewed relational databases and SQL as a distorted implementation of his theory.  For general guidance, he created 12 rules that any relational database management system must comply with (there are actually 13 rules). Honestly speaking, there is zero DBMS's on the market that observes at least Rule 0. Therefore, no one can call their DBMS 100% relational :) If you know any exceptions, please let me know.

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.
• The OpenExchange Application: if you are not interested in the development of this example, you can go directly to this section and learn how to use it as a template for your flask-iris application.

Hi Community,

We are pleased to invite you to the next InterSystems online programming contest, which is focused on Python!

🏆 InterSystems Python Contest 🏆

Duration: July 15 - August 4, 2024

Prize pool: $14,000

Connected Data London Conference

TRIADB is an emerging unique and valuable technology in NoSQL database modelling and BI analytics. The following video is from a presentation and demonstration of TRIADB prototype implemented on top of Intersystems Cache database and driven with a CLI in Python (Jupyter-Pandas). In fact this is the second time in the past year that a prototype based on this technology is implemented and demonstrated. The first one was built on top of OrientDB multi-model database and driven by a Mathematica notebook.

In this GitHub based on this InterSystems community rest api template Guillaume and I have created this example of all the import CRUD operations usable using ONLY Python on IRIS and using Flask.

Using the IRIS ORM or by simply doing SQL requests as both methods are seen in the GitHub.

1. intersystems-iris-docker-rest-template

This is a template of a REST API application built in python in InterSystems IRIS. It also has OPEN API spec, can be developed with Docker and VSCode.

• 1. intersystems-iris-docker-rest-template
• 2. Prerequisites
• 3. Installation
  • 3.1. Installation for development
  • 3.2.

Hello everyone,

Im just wondering if there is any possibility to "Listen" to a cache DB? We have our cache DB somewhere else provided by a different company, we are provided the interface to connect to that cache DB so we can extract the cache DB every night.

Im just curious if theres a way to "listen" to the cache DB, so if theres any changes on the table in the cache DB, I could make a trigger to extract the table again.

I know i could just set my ETL every hour or so... but that would extract all the tables in cache DB.

Thanks a lot for any help and information.

Kind regards,

mark

Hi Community, 

Let's meet virtually at our Third Community Roundtable! This will be a 60-min discussion on a given topic: Developing with Python. 

Register through >> this Global Masters challenge << 

UPDATE: the roundtable recording is available here.

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.

Hi Community,

This post is a introduction of my openexchange iris-globals-graphDB application.
In this article I will demonstrate how to save and retrieve Graph Data into InterSystems Globals with the help of Python Flask Web Framework and PYVIS Interactive network visualizations Library

Recommendation

• Read related documentations Using Globals
• Introduction to the Native SDK
• PYVIS Interactive network visualizations Liabrary

Step1 : Establish Connection with IRIS Globals by using python native SDK

 #create and establish connection
  if not self.iris_connection:
         self.

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.

I need connect to cache2016 database by python to get some data, but   I don' t know how to connect by python, did anyone know how to create connection？

If you can provide any python code, that will be better! 

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

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?

I have a table, with autoincremented id

CREATE TABLE users (
    id SERIAL NOT NULL,
    name VARCHAR(30) NOT NULL,
    PRIMARY KEY (id)
)

I can add a new item there with an explicit id 

INSERT INTO users (id, name) VALUES (2, 'fred')

And while my id is autoincremented, I can omit it

INSERT INTO users (name) VALUES ('ed')

So, this time, I don't know the id, and I want to somehow get it.

I could do it with LAST_IDENTITY() function, but it just uses %RowID, and have no relation to the primary id

Hello All, Can anyone tell me whats the best python IDE and code editors? I am a little bit confused between Eclipse + Pydev,  Pycharm, Sublime Text,  Visual Studio Code, Vim,  GNU/Emacs,  Atom/Atom-IDE, Cloud9. 

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.
    For the abovementioned situation and many other cases, you might want to fetch tables from IRIS to manage data outside InterSystems’ products.