Article
· Dec 20, 2021 1m read
Holiday Reading: What Lies Beneath!

For those of you who might be new to IRIS, and even those who have used Cache or IRIS for some time but want to explore beyond its usually-assumed boundaries and practices, you might want to dive into this detailed exploration of the database engine that is at its heart, and discover just what you can really do with it, going way beyond what InterSystems have done with it for you.

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1.Background

1.1 I met a few project that their interface servers were crashed. Cutoms wanted resume server as fast as we can. their servers are running at lan,and they can't use git,there are some namesapce in the server running different service,and usualy there is only one server.

1.2 In the message,it has property in type of characterstream,as you know,the message search page doesn't support filtering with property of characterstream,so it's so hard to find the messge you want.

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GmOwl is a solution that offers an organized and engaging learning platform. It was developed to cater to the increasing need, for learning tools providing a versatile quiz environment that meets users requirements.

The main objective of GmOwl is to deliver an user experience for individuals participating in quizzes while giving administrators comprehensive control, over content and user engagement.

GmOwl uses Java EE with MVC template, and the InterSystems IRIS database is used to store data. The InterSystems JDBC Driver is used to connect to the database.

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Article
· Mar 24 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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I'm pleased to announce a major release of the InterSystems Server Manager extension. It has gained a UI!

Read more at Open Exchange.

Right now version 2.0 is like an aircraft at the start of the runway (remember those days before COVID-19?), waiting for the control tower to give final clearance. Will you be an early adopter, downloading the VSIX from GitHub, installing it into your VS Code, and posting back here to confirm that we haven't left anything critical behind at the gate? Then I'll push the throttles forward, publish to Marketplace, and we'll all be on our way.

Server Manager 2.0 is my entry for the current contest. If you like it maybe you'll vote for me it.

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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
· Jul 21, 2020 1m read
Snapshot to JSON

This is a sample to use %JSON.Adaptor class available in IRIS to produce a snapshot of your object.

The sample consists of 2 classes that are variations of what was known in Caché/SAMPLES as Sample.Person.
Be aware that the possibilities are limited by %JSON.Adapter and how you make use of it.

Once in place, you create some test data by Populate().
You select an object and take a snapshot.
You apply changes to your object and take another snapshot.
And see the difference.

BINGO!

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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
· Jan 8 9m read
IRIS Document Database (DocDB)

InterSystems IRIS Document Database (DocDB) offers a flexible and dynamic approach to managing database data. DocDB embraces the power of JSON (JavaScript Object Notation), providing a schema-less environment for storing and retrieving data.

It is a powerful tool, enables developers to bypass a ton of boiler plate code in interaction with existing applications, serialization, pagination and integration. the seamless flow of DocDB with Interoperability Rest services and operations, gives a big leap in API production and management.

for full DocDB documentation Here. in the context of this article i will showcase a use case in which DocDB will make a perfect fit.

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Intro

In a fast-paced digital era, effective communication is crucial. This article introduces a Java-based chat project, combining the strength of IRIS database and ChatGPT intelligence. Built on Java, it goes beyond real-time messaging, leveraging IRIS and ChatGPT for an enhanced chat experience. Also, the name of the project references the cultural classic - Star Wars.

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Hi Developers!

In March we are starting our first InterSystems IRIS Programming Contest! It's a competition in creating open-source solutions using InterSystems IRIS Data Platform.

The topic for the first contest is InterSystems IRIS, Docker and ObjectScript!

The contest will last three weeks: March 9-31, 2020.

Prizes:

There will be money prizes for Experts Nomination - winners will be determined by a specially selected jury:

🥇 1st place - $2,000

🥈 2nd place - $1,000

🥉 3rd place - $500

Also, there will be Community Nomination - an application that will receive the most votes in total:

🏆 1st place - $1,000

And we provide winners with high-level badges on Global Masters.

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Article
· May 11, 2021 8m read
IRIS in Astronomy

In this article we are going to show the results of the comparision between IRIS and Postgress when handling Astronomy data.

Introduction

Since the earliest days of human civilization we have been fascinated by the sky at night. There are so many stars! Everybody has dreamed about them and fantasized about life in other planets.

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Article
· Jan 2, 2022 3m read
DB Migration using SQLgateway

Thanks to @Yuri Marx we have seen a very nice example for DB migration from Postgres to IRIS.
My personal problem is the use of DBeaver as a migration tool.
Especially as one of the strengths of IRIS ( and also Caché) before is the availability of the
SQLgateways that allow access to any external Db as long as for them an access usinig
JDBC or ODBC is available. So I extended the package to demonstrate this.

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In this article you will have access to the curated base of articles from the InterSystems Developer Community of the most relevant topics to learning InterSystems IRIS. Find top published articles ranked by Machine Learning, Embedded Python, JSON, API and REST Applications, Manage and Configure InterSystems Environments, Docker and Cloud, VSCode, SQL, Analytics/BI, Globals, Security, DevOps, Interoperability, Native API. Learn and Enjoy!

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Pouring The Coffee: Creating and scheduling a task

Don't you wish a fresh, hot cup of coffee could be waiting for you right when you get into the office? Let's automate that!

Cache and IRIS come with a built-in Task Manager, which should have a familiar feel to those used to using the Windows task scheduler or using cron on Linux. Your user account will need access to the %Admin_Task resource to use it, and you can access it in the management portal under System Operation -> Task Manager. When first installed, there are roughly 20 types of task that you can schedule.

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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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Article
· Mar 31, 2023 3m read
Using JSON in IRIS

Saw the other day an article with the usage of the %ZEN package when working with JSON and decided to write an article describing a more modern approach. At some recent point, there was a big switch from using %ZEN.Auxiliary.* to dedicated JSON classes. This allowed to work with JSONs more organically.

Thus, at this point there are basically 3 main classes to work with JSON:

  • %Library.DynamicObject - provides a simple and efficient way to encapsulate and work with standard JSON documents. Also, there is a possibility instead of writing the usual code for creating an instance of a class like
set obj = ##class(%Library.DynamicObject).%New()

it is possible to use the following syntax

set obj = {}
  • %Library.DynamicArray - provides a simple yet efficient way to encapsulate and work with standard JSON arrays. With arrays you can use the same approach as with objects, meaning that yu can either create an instance of the class
set array = ##class(%DynamicArray).%New()

or you can do it by using brackets []

set array = []
  • %JSON.Adaptor is a means for mapping ObjectScript objects (registered, serial or persistent) to JSON text or dynamic entities.
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In recent versions of IRIS, a powerful new data loading command has been introduced to SQL: LOAD DATA. This feature has been highly optimized to import data into IRIS extremely fast, allowing hundreds of gigabytes of data to be inserted in seconds instead of hours or days.

This is a very exciting improvement. However, a big problem in the data loading experience still exists. Namely, the time and hassle it takes to:

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Suppose you have an application that allows users to write posts and comment on them. (Wait... that sounds familiar...)

For a given user, you want to be able to list all of the published posts with which that user has interacted - that is, either authored or commented on. How do you make this as fast as possible?

Here's what our %Persistent class definitions might look like as a starting point (storage definitions are important, but omitted for brevity):

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Foreword

InterSystems IRIS versions 2022.2 and newer feature the ability to authenticate to a REST API using JSON web tokens (JWTs). This feature enhances security by limiting where and how often passwords transfer over the network in addition to setting an expiration time on access.

The goal of this article is to serve as a tutorial on how to implement a mock REST API using InterSystems IRIS and lock access to it behind JWTs.

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