This post is a introduction of my openexchange iris-python-apps application. Build by using Embedded Python and Python Flask Web Framework. Application also demonstrates some of the Python functionalities like Data Science, Data Plotting, Data Visualization and QR Code generation.
Features
Responsive bootstrap IRIS Dashboard
View dashboard details along with interoperability events log and messages.
If one of your packages on OEX receives a review you get notified by OEX only on YOUR package. It reflects my experience with the status I found at the time of my review. It is kind of a snapshot and might have changed meanwhile.
This post provides guidelines for configuration, system sizing and capacity planning when deploying Caché 2015 and later on a VMware ESXi 5.5 and later environment.
Hello everyone.
I present this project to the contest. The export module is essential in many of my projects and is often used in all my product servers.
If your embedded python code calls tkinter library (which is used by a lot of graphic producing libraries, including matplotlib), you might get this error:
In this series, I will not show you how to use IRIS for Health, but rather how to use SUSHI, a tool for creating FHIR profiles, as an associated technology.
With the right tools, the profile information (specifications, limitations, extensions, etc.) of a FHIR project can be well organized and published.
Before we begin, what is SUSHI? I will briefly explain it.
I have created a package to export a Global into JSON object file and to re-create it by reloading from this file embeddedPython refers to the new available technologies. It should be understood as a learning exercise of how to handle the language interfaces. Only Global nodes containing data are presented in the generated JSON file. Differently from the previous example, this one is using embedded Python only, no ObjectScript. Therefore PURE
I have created a package to export a Global into JSON object file and to re-create it by reloading from this file embeddedPython refers to the new available technologies. It should be understood as a learning exercise of how to handle the language interfaces. Only Global nodes containing data are presented in the generated JSON file.
The MONITOR process (also called the Caché Monitor) scans the messages in your cconsole.log file and sends you emails based on the severity of those messages. The MONITOR is configured using the ^MONMGR utility in terminal.
The MONITOR should not be confused with the similarly named System Monitor, which checks a variety of system health and performance metrics and can log messages regarding them to the cconsole.log, where they can then be scanned by the MONITOR.
This concept may be known to some, but I just found it very useful and I would like to share as it may help someone else.
If you are working with CSP or Zen you sometimes come across the need to use embedded JavaScript. Suppose you are working with some loops, which use < or > as shown in example below:
I will give you some additional information on my first embedded Python package. it is written as a mix of python and ObjectScript to take the best of both worlds.
Spring Boot is the most used Java framework to create REST API and microservices. It can be used to deploy web or executable web or desktop self-contained apps, where the application and another dependencies are packaged toghether. Springboot allows you do to a lot of functions, see:
Finding errors in your code or examining unexpected behavior is the main purpose of Debugging I will try to refresh the traditional tools away from the helpers you have in Studio, VScode, Serenji, .... to the basics which have been there before your preferred EDI used it in the background.
Maybe someday you will need to use Adaptive Analytics but there is little information about this, so I decided to write an article on how to start developing a dashboard on Tableau using the Atscale cube.
The InterSystems IRIS IntegratedML feature is used to get predictions and probabilities using the AutoML technique. The AutoML is a Machine Learning technology used to select the better Machine Learning algorithm/model to predict status, numbers and general results based in the past data (data used to train the AutoML model). You don't need a Data Scientist, because the AutoML it will test the most common Machine Learning algorithms and select the better algorithm to you, based in the data features analysed. See more here, in this article.
This article is a follow-up to the previous one on how to migrate from popular databases (like PostgreSQL and MySQL) to IRIS. We will use the same procedures utilized to migrate from PostgreSQL. However, you will see that it is even easier since the data types in MySQL are very similar to IRIS. That is why we will not need to create transformation rules in the columns.
Get the sample data to the migration process
In GitHub it is possible to download a docker-compose project to build and run 2 databases:
Apache Zeppelin it's a Multi-purpose notebook that allow you:
Data Ingestion
Data Discovery
Data Analytics
Data Visualization and Collaboration.
Apache Zeppelin interpreter concept allows any language/data-processing-backend to be plugged into Zeppelin. Currently Apache Zeppelin supports many interpreters such as Apache Spark, Apache Flink, Python, R, JDBC, Markdown and Shell.
From IRIS 2021.2 is possible write Class Methods using the Python Language. I used this new feature to detect persons and objects into images, using ImageAI (https://github.com/OlafenwaMoses/ImageAI).
I have created a package that offers a utility to load a Global into JSON object and reverse to create a Global from this type of JSON object. Academic refers to the structure created. Each logical node of the Global is presented separately with all its descendants. Even if they don't contain any stored data.
We recently encountered an Embedded SQL issue while upgrading to IRIS 2021.1, and thought the issue and workaround might be interesting to share.
Key takeaway: Host variables in an ORDER BY clause of an embedded SQL query that is inside of a method don't work as expected. IRIS versions starting with 2020.1 are affected. As a workaround, add the host variable to the Method's PublicList list and "new" them so the embedded query has access to them.
If you're deploying to more than one environment/region/cloud/customer, you will inevitably encounter the issue of configuration management.
While all (or just several) of your deployments can share the same source code, some parts, such as configuration (settings, passwords) differ from deployment to deployment and must be managed somehow.
In this article, I will try to offer several tips on that topic. This article talks mainly about container deployments.
Sometimes it is necessary to transfer or migrate data and data schema from Postgres to IRIS. There are currently a few options for doing this, but the two most popular options are using DBeaver (https://openexchange.intersystems.com/package/DBeaver) or SQLGateway.
By update
Open Exchange app
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