I'm looking for an efficient way in DBeaver to filter system tables (ex: belonging to a schema starting with "%").

By using a user with the %All role, DBeaver shows us a long list of system schemas, which forces us to go down the list before accessing the user tables.

This is more for my memory that anything else but I thought I'd share it because it often comes up in comments, but is not in the InterSystems documentation.

There is a wonderful utility called ^REDEBUG that increases the level of logging going into mgr\cconsole.log.

You activate it by

a) start terminal/login

b) zn "%SYS"

c) do ^REDEBUG

The VS Code extension development team is looking for beta testers to provide feedback on a proposed overhaul of the client-side editing workflow. The full list of changes can be found in the GitHub pull request description. Here are the highlights:

During a major version upgrade it is advisable to recompile the classes and routines of all your namespaces (see Major Version Post-Installation Tasks).

FHIR has revolutionized the healthcare industry by providing a standardized data model for building healthcare applications and promoting data exchange between different healthcare systems. As the FHIR standard is based on modern API-driven approaches, making it more accessible to mobile and web developers. However, interacting with FHIR APIs can still be challenging especially when it comes to querying data using natural language.

Introduction

We are in the age of the multiplatform economy and APIs are the "glue" in this digital scenario. Since they are so important, they are seen by developers as a service or product to be consumed. Therefore, usage experience is a crucial factor for its success.

Looking at the DTL, we can pretty much understand what the provided mapping from FHIR to SDA3.

But, is there any Intersystems document, where the mapping To/From FHIR is documented, at least FHIR to SDA3 ?

Schematron is a rule-based validation language for making assertions about the presence or absence of certain patterns in XML documents. A schematron refers to a collection of one or more rules containing tests. Schematrons are written in a form of XML, making them relatively easy for everyone, even non-programmers, to inspect, understand, and write

I was searching for the most simple way to connect from visual studio code to my local instance via terminal without having to change any window.

I know this can also be achieved via telnet but seems a bit overhead if you're in your local machine.

For me the simplest sollution is to open a terminal window in VS Code, navigate to the /bin folder of your instance installation and run .\csession.exe INSTANCENAME

For simplicity you can just include your /bin folder in your path so you don't even need to navigate there

Hi Community,

I recently needed to interrogate some folders/sub-folders to retrieve filenames using cache object script(COS) and I implemented it in the following way.

Python has become the most used programming language in the world (source: https://www.tiobe.com/tiobe-index/) and SQL continues to lead the way as a database language. Wouldn't it be great for Python and SQL to work together to deliver new functionality that SQL alone cannot? After all, Python has more than 380,000 published libraries (source: https://pypi.org/) with very interesting capabilities to extend your SQL queries within Python.

Loading your IRIS Data to your Google Cloud Big Query Data Warehouse and keeping it current can be a hassle with bulky Commercial Third Party Off The Shelf ETL platforms, but made dead simple using the iris2bq utility.

Let's say IRIS is contributing to workload for a Hospital system, routing DICOM images, ingesting HL7 messages, posting FHIR resources, or pushing CCDA's to next provider in a transition of care. Natively, IRIS persists these objects in various stages of the pipeline via the nature of the business processes and anything you included along the way. Lets send that up to Google Big Query to augment and compliment the rest of our Data Warehouse data and ETL (Extract Transform Load) or ELT (Extract Load Transform) to our hearts desire.

A reference architecture diagram may be worth a thousand words, but 3 bullet points may work out a little bit better:

• It exports the data from IRIS into DataFrames
• It saves them into GCS as .avro to keep the schema along the data: this will avoid to specify/create the BigQuery table schema beforehands.
• It starts BigQuery jobs to import those .avro into the respective BigQuery tables you specify.

I don't know execute witch one?

Hi,

I am getting below error while starting production

ERROR <Ens>ErrException: <CLASS DOES NOT EXIST>zgetProductionItems+29^Ens.Director.1 *HS.FHIRServer.Interop.Service -- logged as '-' number - @''

Thanks