The Lab

The lab offers an opportunity to test the { kitems } framework.

The package defines itself as a framework because it comes with a flexible mindset & many features:

• it allows different architecture / implementation patterns
• it has flexible create / update / delete workflows
• it comes with a communication strategy
• a concept of filtering layers has been implemented

For the sake of the example, a very basic data model is defined in this example with date, name, value and checked attributes.
This was done through the admin console that can't be accessed by users for security reasons (see data model tab).

Visit the package website to get details.

Introduction video

• Items
• Data model

For demonstration purpose, autosave is turned OFF
(data will be lost if you refresh the page)

Date

Strategy

this-year keep-range

The item table is empty (all attributes are filtered or there is no item).

Behind the scene

How does it work?

The UI components are the visible part of the iceberg.
A R / Shiny (module) server is running in the background.

Once the data model is defined (see data model tab),
kitems takes care of all the core tasks:

• create / update / delete items
• manage data persistence (turned off here)
• generate dynamic forms based on the data model
• apply filter(s) on the data

But all it takes is... a single line!
data <- kitems::kitems(id = 'lab', path = '/some/path')

From there, you can use the data object to navigate & use the items.

Server-to-server back-end capabilities may be used to programmatically create (update / delete) items:

Generate x10 items Generate x100 items Clear all items

In the below example, the data object is used to build two basic plots:

The data model documents the definition of an item.
It holds attributes that are defined with:

• a type
• a default value or function (optional)
• whether they are displayed in the item table
• whether they are skipped in the item form
• options if used to order the items

The reason why the admin console is not implemented in this lab is because of the default function mechanism,
which evaluates code defined by the package user (the admin of the app!).
Allowing the app users to do so would lead to a severe security vulnerability (code injection).

Screenshots of the admin console:

Technical-Functional Data Services

Backed by 25 years of data experience.

Services are organized into three main axes — each of them involves a combination of technical-functional skills.

Contacts & Links

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Links to other platforms

About me

I am a Senior Data Project Manager with a technical-functional background.

Since 2001, it has always been about data projects and technical-functional roles:
From Data Management, Exchanges & Transformation to Data Analysis & BI.

I enjoy working with complex data pipelines & carefully designed dashboards.

I do photography as a hobby www.thediamondbay.fr and I traveled around the world for a year.

Stack

Here you can find the key (i.e. not exhaustive) tools I'm using in 2026.
Note that I mainly use R for my own developments & Python on the Data Analyst program & for AI.

Resume

In case you'd like to know more about my career path, here's my full resume.

Certifications & Degree