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>

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:

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"

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.

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:

As most of you probably already know, since approximately the end of 2022 InterSystems IRIS included the columnar storage functionality to its database, well, in today's article we are going to put it to the test in comparison to the usual row storage.

Hi Community,

to learn quickly and in total autonomy on IRIS, I offer you some links which can help you in this beautiful bicycle ride rich in discoveries:

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.

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.

This is a first attempt to use Embedded Python in IRIS
The Python code is adapted from solutions for Advent of Code 2020 contest.
Test data are all input to my personal challenge.

Prerequisites

Make sure you have git and Docker desktop installed.

Installation

Clone/git pull this repo into any local directory

An experiment on how to use the LangChain framework, IRIS Vector Search, and LLMs to generate IRIS-compatible SQL from user prompts.

This article was based in this notebook. You can run it with a ready to use environment with this application in OpenExchange.

Setup

First, we need to install the necessary libraries:

Hi Developers,

Get a preview of the upcoming Embedded Python feature of InterSystems IRIS:

⏯ Embedded Python in InterSystems IRIS: Sneak Peek

Hi developers! In this article I’m going to explore the use of Iris Python Native API in a specific problem: large strings to store.

grpc-iris-interop

The aim of this proof of concept is to show how the gRPC protocl can be implemented with the IRIS ineroperabilty module.

architecture

On this schema, we can see that the gRPC Service is hosted by IRIS.

This service must invoke the IRIS interoperability module. For that it transforms the protobuf messages to IRIS messages.