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-0.1.4.tar.gz (96.9 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-0.1.4-py3-none-any.whl (25.4 kB view details)

Uploaded Python 3

File details

Details for the file fabric_arcade-0.1.4.tar.gz.

File metadata

  • Download URL: fabric_arcade-0.1.4.tar.gz
  • Upload date:
  • Size: 96.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.13

File hashes

Hashes for fabric_arcade-0.1.4.tar.gz
Algorithm Hash digest
SHA256 ae5cdc17049f06dc37f9cc3fe262c30cf759e5c6ce571c4f05433a4bcbca8c9f
MD5 26dcc4cb88b5c65a9255f540f3fe1121
BLAKE2b-256 9b4ac86072e2dc483781f8ec406a48ba59aad78c21b64d850a7529886d721310

See more details on using hashes here.

File details

Details for the file fabric_arcade-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: fabric_arcade-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 25.4 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-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 b64226b70da09369e26f877b20fa4e5adf0afcdbc03b68e3616559c4713e2f73
MD5 c32815ba067cbfd8fe57020e6ee5745a
BLAKE2b-256 633c0dd97a5a24784f25d5567c7f0a1f529a2526de9fe463af653941e91dde2f

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