#Contest

Strap on this jetpack to boost your developer experience in Visual Studio Code.

DX Jetpack for VS Code was my entry for the 2023 Developer Tools Contest, where it achieved 2nd place in the Experts vote and 5th place in the Community vote. It is an extension pack for VS Code, bundling three entirely new extensions created by me, plus a couple that we at George James Software published previously.

The new extensions are:

• gj :: codeSpex
• ObjectScript Class View
• ServerDiff

If you're reluctant to install DX Jetpack right away, why not try it using a dev container? In the dev container is an InterSystems IRIS Community environment augmented with InterSystems Package Manager (IPM) and the isc-codetidy package.

Hi Community,

In the first part, we describe all packages, used libraries and REST services.

Now, I would like to add some details about converter and validator services.

By default, OpenAPI-Suite sends an HTTP request to converter.swagger.io if the specification version is less than 3.0 and another HTTP request to validator.swagger.io to simplify the structure of the specification document.

Although the usage of online utilities is convenient, in some cases it could be better to have our own instance of the converter and validator. For example, if OpenAPI-Suite is provided on a server in an organisation for ObjectScript developers, it may be preferable to avoid requests to external services (privacy, avoid request rate limits).

Just run:

docker run -d -p 8085:8080 --name swagger-converter swaggerapi/swagger-converter:latest
docker run -d -p 8086:8080 --name swagger-validator-v2 swaggerapi/swagger-validator-v2:latest

This is (the end) of a series of programming challenges for beginners and experienced Caché programmers.

For an introduction : go to article https://community.intersystems.com/post/advent-code-2016-day1-no-time-ta...

This is the 25th and last challenge of the 2016 series of Advent of Code.

Hello developers!

We are holding the first technical article contest on Japan's InterSystems Developer Community!

The first contest is a technical document writing contest, and you can submit any content related to the InterSystems IRIS/InterSystems IRIS for Health. (The article must be in Japanese.)

✍ InterSystems Japan Technical Document Writing Contest: Articles related to IRIS ✍

🎁 Participation prize: There will be a participation prize for everyone who submits an article for the contest.

🏆 Special prize: Authors of three selected works will receive special prizes.

Entering the contest is easy! Please post an article related to IRIS on the developer community during the period from Wednesday, September 6, 2023 to Monday, November 6, 2023.

Hi Community,

This post is a introduction of my open exchange iris-climate-change application.

iris-climate-change web application Imports The Food and Agriculture Organization (FAO) Climate Change dataset by using LOAD DATA (SQL) functionality and analyze and visualize data with the help of Python Flask Web Framework, Pandas Python data analysis Library, Plotly Open Source Graphing Library for Python and Plotly JavaScript Open Source Graphing Library.

Artificial Intelligence (AI) is getting a lot of attention lately because it can change many areas of our lives. Better computer power and more data have helped AI do amazing things, like improving medical tests and making self-driving cars. AI can also help businesses make better decisions and work more efficiently, which is why it's becoming more popular and widely used. How can one integrate the OpenAI API calls into an existing IRIS Interoperability application?

Frontend development can be a daunting, even nightmarish, task for backend-focused developers. Early in my career, the lines between frontend and backend were blurred, and everyone was expected to handle both. CSS, in particular, was a constant struggle; it felt like an impossible mission.

Hi colleagues!

Often when we collaborate to someone's repo in GitHub we do the following cycle:

Fork-Clone-Change-Commit-Push-Pull-Request-Merge to the original repo.

This is all great and works fine!

And if we want to make a second collaboration right after the merge you need to perform "Fetch upstream" to your forked repo first to "ingest" your own Pull-request in the original repo.

Geeky git-professionals do it with ease but this was always a headache for me so I usually simply deleted the fork and created a new one.

And today I figured that Github added a new UI feature that I can easily fetch-upstream for my fork with the original one and make it up to date and capable for pull-requests.

Here is where the button is:

This is a relief! )

Wanted to share this relief and productivity tip with you!

Bring more collaborations to Github repos!

And speaking of PR - I just made a PR with docker to Google Cloud Run deployment for the FHIRaaS demo made by @Anton Umnikov for the current FHIR Contest! Looking for more of your contributions!

Hi Community!

We are pleased to invite all the developers to the upcoming InterSystems Contest Kick-off Webinar dedicated to the InterSystems Programming Contest: Developer Tools!

In this webinar, we'll talk about the topics to expect from participants and show you how to develop, build and deploy applications on InterSystems IRIS data platform.

Date & Time: Monday, March 29 — 11:00 AM EDT

Speakers:
🗣 @Evgeny Shvarov, InterSystems Developer Ecosystem Manager
🗣 @Raj Singh, InterSystems Product Manager - Developer Experience
🗣 @Bob Kuszewski, InterSystems Product Manager - Developer Experience

Brainstorming the project we would build to showcase in the current female health themed InterSystems FHIR Contest, our girl band decided that we need to do something practical for the ordinary user and to solve some burning issues of the modern life. This discussion led to the idea of creating a project that will help women not to forget their health in daily grind - FemTech Reminder.

A few months ago, I read this interesting article from MIT Technology Review, explaing how COVID-19 pandemic are issuing challenges to IT teams worldwide regarding their machine learning (ML) systems.

Such article inspire me to think about how to deal with performance issues after a ML model was deployed.

Hi Community,

It's voting time! Cast your votes for the best applications in our InterSystems IRIS Cloud SQL and IntegratedML Contest:

🔥 VOTE FOR THE BEST APPS 🔥

How to vote? Details below.

Hey Developers!

This week is a voting week for the InterSystems Full Stack Contest!

So, it's time to give your vote to the best solutions built with InterSystems IRIS.

🔥 You decide: VOTING IS HERE 🔥

How to vote? This is easy: you will have one vote, and your vote goes either in Experts Nomination or in Community Nomination.

Currently, the process of using machine learning is difficult and requires excessive consumption of data scientist services. AutoML technology was created to assist organizations in reducing this complexity and the dependence on specialized ML personnel.

AutoML allows the user to point to a data set, select the subject of interest (feature) and set the variables that affect the subject (labels). From there, the user informs the model name and then creates his predictive or data classification model based on machine learning.