2.1.1

We are happy to announce DataCards v2.1.1 “ZEN FOUNDATION”, the first stable release of our DataCards platform. 🎉

Core Features

Team & Project Organization

• Create and join multiple teams
• Set up projects within teams
• Configure computing resources (CPU/RAM) per project
• Use custom project names (with uniqueness validation)

Canvas & Deck Architecture

• Deck: A dashboard where you can visualize data using interactive cards
• Logic View: interactive canvas for arranging and managing notebooks
• Automatic linking between cards on the deck and the notebooks that publish them

Notebook Environment

• Seamlessly create and manage notebooks on the Logic View canvas
• Python code and Markdown content support
• Familiar Jupyter-style kernel management (restart, stop, kill)
• Syntax highlighting and smart autocompletion

Communication between notebooks

• Publish/consume mechanism for data exchange between notebooks
• Supports any JSON-serializable data type
• Automatic execution when published variables change

Card System

• Multiple card types available (e.g. slider, text output, number output, gauge, traffic-light)
• Card Store for easy selection and placement on the deck
• Programmatic card creation via the DataCards SDK (see below)

Collaboration

• Collaborative real-time editing with multiple users
• Robust performance, handling up to 10 concurrent operations per second
• Seamless teamwork between tech specialists and domain experts (“double-T knowledge”)

DataCards SDK

• DataCards Python SDK pre-installed for publishing and consuming data
• Simple interface for card management
• Intuitive API for building complex data products

Known Limitations

• Automated workflows across multiple notebooks are experimental and optimized for small processes (Directed Acyclic Graphs)
• No support for overlapping processes or parallelization
• System performance is optimized for typical workloads; processing very large datasets is not supported
• Loop-based processes (cyclic graphs) are not yet supported