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:

10 4
3 922
Article
· Apr 19, 2023 2m read
Apache Superset now with IRIS

Apache Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.

And now it is possible to use with InterSystems IRIS as well.

An online demo is available and it uses IRIS Cloud SQL as a data source.

6 4
0 901

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.

4 0
3 893

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.

https://www.youtube.com/embed/BiEAbpCOC1A?rel=0
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

3 0
0 891

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",[])

0 14
0 886

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

2 2
1 884

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.

8 6
3 870
Article
· Jun 12, 2023 11m read
Examples to work with IRIS from Django

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:

12 9
3 868

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.

0 9
0 849

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>

10 20
3 845

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

8 8
4 845

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');

1 11
0 839

Hello everyone,

Recently, I've been working on a Business Process that processes a large JSON FHIR message containing up to 50k requests in an array within the JSON.

Currently, the code imports the JSON as a dynamic object from the original message stream, obtains an iterator from it, and processes each request one at a time in a loop.

0 2
0 807

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.
6 2
0 803

I have done Python - Cache binding setup following the guide from http://docs.intersystems.com/latest/csp/docbook/DocBook.UI.Page.cls?KEY=.... I have also run test.py from sample3 folder and it able to run and complete successfully.

However, when I try to run the same test.py code via $zf, it gives error with exit code 1.

I've tried running help("intersys.pythonbind3") via $zf and also running from Cache terminal as follows:

0 6
0 780

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.

5 13
1 772
   _________ ___ ____  
  |__  /  _ \_ _|  _ \ 
    / /| |_) | || |_) |
   / /_|  __/| ||  __/ 
  /____|_|  |___|_|    

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.

6 6
1 766

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

0 11
0 766

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.

6 5
1 761

The invention and popularization of Large Language Models (such as OpenAI's GPT-4) has launched a wave of innovative solutions that can leverage large volumes of unstructured data that was impractical or even impossible to process manually until recently.

27 4
5 759



This formation, accessible on my GitHub, will cover, in half a hour, how to read and write in csv and txt files, insert and get inside the IRIS database and a distant database using Postgres or how to use a FLASK API, all of that using the Interoperability framework using ONLY Python following the PEP8 convention.

12 1
1 752