Article
· Mar 15, 2019 2m read
Tar compress tool in ObjectScript

I'm sure most of you have already familiar with the possibility of using GZIP in InterSystems products. But, the problem is that GZIP working only with one file or stream, and it does not support folders. When you work in Unix systems, there is a possibility how to solve it, using tar compress tool which goes with every Linux system from out of the box. But what to do if you have work on Windows as well, which does not have it.

I am pleased to offer you my new project isc-tar, which will help you do not care about operating system, and deal with tar files anywhere.

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Hi Developers!

InterSystems Package Manager (ZPM) is a great thing, but it is even better if you don't need to install it but can use immediately.

There are several ways how to do this and here is one approach of having IRIS container with ZPM built with dockerfile.

I've prepared a repository which has a few lines in dockerfile which perform the download and install the latest version of ZPM.

Add these lines to your standard dockerfile for IRIS community edition and you will have ZPM installed and ready to use.

To download the latest ZPM client:

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As you know in Caché / IRIS you have the possibility to define a property as Multidimensional as documented here:
https://docs.intersystems.com/iris20201/csp/docbook/DocBook.UI.Page.cls?KEY=GOBJ_proplit#GOBJ_proplit_multidim
and the explanation of how to use it
https://docs.intersystems.com/iris20201/csp/docbook/Doc.View.cls?KEY=GOBJ_proplit#GOBJ_proplit_multidim_values

Though the access is quite comfortable (in traditional COS sense) there are 2 main restrictions that hurt:

#1) It is not saved to disk unless your application includes code to save it specifically.
#2) It cannot be stored in or exposed through SQL tables
there are some more
I'll show how to overcome these limits

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Article
· Feb 27, 2022 2m read
Dash-Python-IRIS

We are happy to share interesting information with you, as well as tell you why Python is good, where it is used.

Among the most used libraries are NumPy and Pandas. NumPy (Numerical Python) is used to sort large datasets. It simplifies mathematical operations and their vectorization on arrays. Pandas offers two data structures: Series (a list of elements) and Data Frames (a table with multiple columns). This library converts data into a Data Frame, allowing you to remove and add new columns, as well as perform various operations.

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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.

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Article
· Jan 23, 2023 2m read
Global-Streams-to-SQL

In general Global Streams are data objects embedded in Classes / Tables.
Using and viewing them with SQL is normally a part of the access to the containing tables.

SO WHAT?

During debugging or searching for strange or unexpected behavior there could be the need to
get closer to the stored stream. No big problem with direct access to Globals with SMP or Terminal.
But with SQL you are lost.
So my tool provides dynamic access to Global Streams wherever you may need this
Special thanks to @Oliver Wilms for the inspiration for this tool.

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Article
· Jun 29, 2023 3m read
IRIS Api Tester

Hello Community!!

I just upload my lastest application "IRIS Api Tester" to the Open Exchange.

It's a docker project with InterSystems IRIS + Newman that will allow you to test your Postman Collections in a quick and easy way..

It's ready to work out of the box, you just have to clone the repo: https://github.com/daniel-aguilar-garcia/irisapitester

Run the docker-compose file:

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image
Hello to all developers and IRIS users.
I am submitting to the competition a project for an alternative IRIS management portal that I have long wanted to create. The project was implemented on the Django framework and the intersystems_irispython-3.2.0-py3-none-any.whl library using native IRIS. The Django project is integrated with the telegram messenger and can be launched from a docker container or directly.

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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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In the last article we presented the architecture of our SMART On FHIR project, so it's time to get down to business and start configuring all the elements that we are going to need.

We will first start with Auth0.

AUTH0 configuration

We will start by creating an Auth0 account with a valid email, once registered we will have to create our first application, and we will do it from the menu on the left:

Application menu

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Article
· Nov 15, 2024 2m read
HL7 -> SDA -> FHIR -> Personal Growth

I have a large tree outside my window. Here in Phoenix, Arizona, USA it's still warm and sunny so our plants are still covered in lush foliage despite so many other places in the full throws of Autumn. My desk is oriented such that I can look out at the tree throughout the day.

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Article
· Feb 19, 2016 1m read
Simple WorkMgr example

Attached code contains a very basic $system.WorkMgr example.

It uses several jobs (workers) to update different chunks of rows of a table.

Steps:

  • Creates a table with 100 records.
  • Split table in chunks
  • Initialize WorkMgr and queue chunks to workers.
    • Every worker simply sets its process number in the Job field of the processed row.

In this case, I have tested the example in a 8-core laptop:

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Article
· May 16, 2016 11m read
Accelerate Ensemble

Introducing non-persistent messages. eXpert-to-eXpert

Background

InterSystems Ensemble as a tool does a lot for the Developer. One of the nice features is the Message trace utility. It shows a message flow diagram. The diagram shows the progress of the message processing real time. You can get many-many useful information from the production. In any case, someone needs to find a bug in a production implementation, without the Message trace utility it could turn into a real nightmare.

On the other hand, keeping message “traceability” is not for free. A heavy loaded production can very quickly run out of resources just because of the house keeping functions of Ensemble. House keeping functions such as maintaining message header, log entries, message queue generates a significant load on the Caché database used by Ensemble.

This article is about to show how to force Ensemble work more for the everyday life, instead of being prepared for “any-time-debugging”.

This is an eXpert-to-eXpert article. Therefore, I assume the deep understanding of Ensemble.

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