Skip to main content

🎮 Learn Microsoft Fabric by Playing - Gamified tutorials and demos

Project description

🎮 Fabric Arcade

Learn Microsoft Fabric by Playing - A gamified catalog of projects to learn Real-Time Intelligence, Data Engineering, Power BI and Data Science through fun experiences.

PyPI version Python License: MIT


🚀 Quick Start (Fabric Notebook)

Just 3 lines of code to install a complete learning environment in your Fabric workspace!

# Cell 1 - Install the package
%pip install -q fabric-arcade
# Cell 2 - Import and explore
from fabric_arcade import arcade

# List all available games
arcade.list()
# Cell 3 - Install a game in your current workspace!
arcade.install("fabric-racing-game")

That's it! The game assets (Eventhouse, KQL Database, tables, notebooks) are automatically created in your workspace.


🎯 What You Learn

Instead of boring technical tutorials, you learn by building:

Game You Learn Workloads
🏎️ Fabric Racing Game Custom Endpoints, JSON mapping, streaming dashboards RTI
🚀 Mission Artemis 2 Real-time telemetry, multi-table streaming, video sync RTI, DE
Sports Tracker ML predictions on streaming data RTI, DS
🏰 Quest Data Pipeline Medallion architecture (Bronze/Silver/Gold) DE, DF
🎯 Target Practice Eventstream → Eventhouse basics RTI

📋 Requirements

Requirement Detail
Fabric Capacity F2 or higher (trial works!)
Workspace Any workspace where you have Contributor access

No local installation needed - everything runs inside Fabric notebooks!


🎮 API Reference

arcade.list()

Display all available games with their difficulty and duration.

arcade.info(game_id)

Show detailed information about a specific game.

arcade.info("fabric-racing-game")

arcade.install(game_id, workspace_id=None)

Install a game in a workspace. If workspace_id is not provided, uses the current notebook's workspace.

# Install in current workspace
arcade.install("fabric-racing-game")

# Install in a specific workspace
arcade.install("fabric-racing-game", workspace_id="your-workspace-guid")

🎲 Game Catalog

Game Type Difficulty Duration Status
🏎️ Fabric Racing Game Mission ⭐⭐ 30 min ✅ Available
🚀 Mission Artemis 2 Mission ⭐⭐⭐ 45 min ✅ Available
⚽ Sports Tracker Challenge ⭐⭐ 25 min 🔜 Coming Soon
🏰 Quest Data Pipeline Mission ⭐⭐⭐ 40 min 🔜 Coming Soon
🎯 Target Practice Challenge 15 min 🔜 Coming Soon

Workload Legend:

  • RTI = Real-Time Intelligence (Eventstream, Eventhouse, KQL)
  • DE = Data Engineering (Spark, Lakehouse, Notebooks)
  • DS = Data Science (ML Models, Predictions)
  • DF = Data Factory (Pipelines, Dataflows)
  • PBI = Power BI (Reports, Dashboards)

🛠️ Local Development (CLI)

For contributors or local testing:

# Clone and install
git clone https://github.com/maenglar78/fabric-arcade.git
cd fabric-arcade
pip install -e .

# Login to Azure
az login

# Use CLI
arcade list
arcade install fabric-racing-game -w "My Workspace"

🤝 Contributing

Want to create a new game? See CONTRIBUTING.md.

Project Structure

catalog/
└── my-new-game/
    ├── manifest.json       # Game metadata
    ├── notebooks/          # Fabric notebooks
    ├── schemas/            # KQL table schemas
    └── eventstream/        # Eventstream definitions

📜 License

MIT License - see LICENSE for details.


Made with ❤️ for the Fabric Community

"Data is more fun when you're playing with it!"

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fabric_arcade-0.1.9.tar.gz (145.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fabric_arcade-0.1.9-py3-none-any.whl (25.8 kB view details)

Uploaded Python 3

File details

Details for the file fabric_arcade-0.1.9.tar.gz.

File metadata

  • Download URL: fabric_arcade-0.1.9.tar.gz
  • Upload date:
  • Size: 145.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.13

File hashes

Hashes for fabric_arcade-0.1.9.tar.gz
Algorithm Hash digest
SHA256 8a1f37e7742ed3f2ba8042d0b7d18430c907dbe6fc0cd23a98c40116e74d6249
MD5 741f36386ed79958dd68ec63cd559a01
BLAKE2b-256 52c74f08477d43d72af917a3248945e3c00bb84f931f6d5c7df0e7b91c6bd77c

See more details on using hashes here.

File details

Details for the file fabric_arcade-0.1.9-py3-none-any.whl.

File metadata

  • Download URL: fabric_arcade-0.1.9-py3-none-any.whl
  • Upload date:
  • Size: 25.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.13

File hashes

Hashes for fabric_arcade-0.1.9-py3-none-any.whl
Algorithm Hash digest
SHA256 795b067523e64c1992e11b24e6ce99ce813c74e006d19f7025ac7b1ae155914f
MD5 75299159806e7dc75182c50e5f64fd77
BLAKE2b-256 5228a4e34da25b4dd382e498e3df2fb602f7ac41b8f14fd0485f22de288cb583

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page