Data analytics is a crucial aspect of business decision-making in today's fast-paced world. Organizations rely heavily on data analysis to make informed decisions and stay ahead of the competition. In this article, we will explore how data analytics can be performed using Pandas and Intersystems Embedded Python. We will discuss the basics of Pandas, the benefits of using Intersystems Embedded Python, and how they can be used together to perform efficient data analytics.

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A python script to keep your docker iris images in shape ;)

Witout changing your dockerfile or your code you can reduce the size of your image by 50% or more !


Name the builder image builder and the final image final and add this to end of your Dockerfile:

Modify your Dockerfile to use a multi-stage build:

ARG IMAGE=intersystemsdc/irishealth-community:latest
FROM $IMAGE as builder

Add this to end of your Dockerfile:

FROM $IMAGE as final


RUN --mount=type=bind,source=/,target=/builder/root,from=builder \
    cp -f /builder/root/usr/irissys/iris.cpf /usr/irissys/iris.cpf && \
    python3 /irisdev/app/ -c /usr/irissys/iris.cpf -d /builder/root/ 

Boom! You're done!

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InterSystems FAQ rubric

In the sample below, an image file is encoded into a Base64 string in a class property, saved, decoded again with Base64, and restored to another file.

【Usage class】

Class User.test Extends %Persistent
Property pics As %GlobalBinaryStream;

【When importing】

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If you work with Productions, highlighting connections between Business Hosts is a very convenient feature, allowing developers to get a visual representation of a data flow.

This feature works by default with all system Business Hosts. If a user writes their own Business Services, Processes, or Operations, they must implement the OnGetConnections method for this functionality to work with their custom Business Hosts (or use Ens.DataType.ConfigName properties for connections).
That said, the SMP shows only the first layer of connections of the selected Business Host. Sometimes, we need to get connections of connections recursively to build a complete data flow graph. Or we might need this connection information to check which downstream systems might be affected by a change upstream.

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· Feb 1 17m read
OpenAPI Suite - Part 1

Hi Community,

I would like to present my last package OpenAPI-Suite, this is a set of tools to generate ObjectScript code from an OpenAPI specification version 3.0. In short, these packages allow to:

  • Generate server-side class. It’s pretty similar to the generated code by ^%REST but the added value is the version 3.0 support.
  • Generate HTTP client classes.
  • Generate client production (business services, business operation, business process, Ens.Request, Ens.Response) classes.
  • A web interface to generate and download the code or generate and compile directly on the server.
  • Convert specification from version 1.x, 2.x to version 3.0.

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Effective documentation is a cornerstone of software development, aiding in code comprehension, maintenance, and collaboration. By harnessing the power of Doxygen and the ObjectScript filter I've created, you can generate rich static documentation from your source code. This approach does not require a running IRIS instance and thus is a good choice in situations when access to IRIS is not possible. Static documentation may be provided to end-users as-is, together with the source code.

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The related package avoids adding %JSONAdaptor to each class but uses instead
SQL functions JSON_OBJECT() to create my JSON objects. With this approach, you can
add JSON to any class - even deployed ones - without any need for change or recompiling.

The trigger was the Export of M:N relationships as JSON objects or arrays.

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Nowadays so much noise around LLM, AI, and so on. Vector databases are kind of a part of it, and already many different realizations for the support in the world outside of IRIS.

Why Vector?

  • Similarity Search: Vectors allow for efficient similarity search, such as finding the most similar items or documents in a dataset. Traditional relational databases are designed for exact match searches, which are not suitable for tasks like image or text similarity search.
  • Flexibility: Vector representations are versatile and can be derived from various data types, such as text (via embeddings like Word2Vec, BERT), images (via deep learning models), and more.
  • Cross-Modal Searches: Vectors enable searching across different data modalities. For instance, given a vector representation of an image, one can search for similar images or related texts in a multimodal database.

And many other reasons.

So, for this pyhon contest, I decided to try to implement this support. And unfortunately I did not manage to finish it in time, below I'll explain why.

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· Sep 24 2m read
Reviews on Open Exchange - #32

If one of your packages on OEX receives a review you get notified by OEX only of YOUR own package.
The rating reflects the experience of the reviewer with the status found at the time of review.
It is kind of a snapshot and might have changed meanwhile.
Reviews by other members of the community are marked by * in the last column.

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Earlier this year I announced availability of a VS Code extension for coding in ObjectScript, Embedded Python or SQL using the notebook paradigm popularized by Jupyter. Today I published a maintenance release to correct a "getting started" problem.

Here's a video of the installation steps from the extension's README:

Why not try it for yourself?

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InterSystems FAQ rubric

The meaning of each timeout value is as follows.

1. [Server response timeout]

If IRIS/Caché processing (routine or query execution) does not finish within this set time, the browser will return an error.

For example, if this value is 60 seconds and it takes 90 seconds to execute a routine/method/query, an error will occur.

2. [Queued request timeout]

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Hi Community,
In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):

  • Step1: Install required libraries

  • Step2: Create patterns and responses file

  • Step3: Train the Model

  • Step4: Create ChatBot Application based on the trained model

So Let us start.

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Why to use it

This app offers an easy interface to analyze memory:

  • Filter by database (namespace), global name, used size, or allocated size;
  • View a sum of the used and allocated sizes for the filters applied;
  • Export the table to JSON, CSV, or XML.

How to use it

Follow the instructions on the README file from the GitHub repository, and configure the settings to connect to your instance.

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In the ever-evolving landscape of data science and machine learning, having the right tools at your disposal can make all the difference. In this article, we want to shine a spotlight on two essential Python libraries that have become indispensable for data scientists and machine learning practitioners alike: Matplotlib and scikit-learn.

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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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Hey Community,

Do you want to get help, discuss an interesting feature, make an announcement or share your knowledge? In this post, we will tell you how to do it all.

To make it easier to navigate this "how to" just follow the contents:

General guidelines

To begin, you need to click on the "New post" button in the top menu of the Developer Community site:

After that, you will see the editor that will give you the choice of creating a Question, an Announcement, an Article, or a Discussion. Different types of posts have their own sets of mandatory and optional fields.

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Hi Community

In this article, I will introduce my application IRIS-GenLab.

IRIS-GenLab is a generative AI Application that leverages the functionality of Flask web framework, SQLALchemy ORM, and InterSystems IRIS to demonstrate Machine Learning, LLM, NLP, Generative AI API, Google AI LLM, Flan-T5-XXL model, Flask Login and OpenAI ChatGPT use cases.

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Hello developers,

In this article, I'll show you how to run code at compile time with ObjectScript macros.

Here's a use case that recently led me to use this feature:

As part of a medical application developed for more than 20 years, we have a large number of parameters. Although we have procedures for documenting these settings, it can be helpful to have a quick view of which settings are actually used by the application code.

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Enhanced Password Management: Edit Passwords Seamlessly

In the ever-evolving landscape of digital security, robust password management tools have become indispensable. Our password management application, designed to simplify and secure your online life, now comes with an enhanced feature – the ability to edit passwords with ease.

Why is this feature a game-changer?

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· Sep 17 1m read


This is a demo of IRIS Native API for Python, which uses Python to call the Object Script method and flow the message in production. Python obtains the message after flow and the message in global, and uses ZPM Package deployment.

Firstly, we need to install the Native API package

Enter on the command line

pip install intersystems_irispython-3.2.0-py3-none-any.whl
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InterSystems FAQ rubric

It can be retrieved using the schema INFORMATION_SCHEMA.

INFORMATION_SCHEMA is a system schema and is not displayed by default in the SQL menu of the Management Portal.

The method to display it is as follows.

  1. Open Management Portal → System Explorer → SQL menu.
  2. Check "System" on the left of the schema drop-down.
  3. Select INFORMATION_SCHEMA from the schema dropdown.

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