fabrix 0.1.0

A python toolkit to evaluate, validate, and debug Azure Data Factory & Microsoft Fabric pipeline expressions with rich tracing.

🧵 fabrix

fabrix is a Python toolkit to evaluate, validate, and debug Microsoft Fabric / Azure Data Factory pipeline expressions. It helps you test expressions locally, manage variables & parameters, and visualize execution with rich tracing.

⚠️ This project is still in progress. Expect changes and new features soon.

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🔗 Links

• 📖 Documentation (WIP)
• 💻 Source Code

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✨ Features

• Parse & evaluate Fabric/ADF expressions locally
• Manage variables, pipeline parameters, and scope values
• Validate syntax: unmatched brackets, wrong quotes, unknown functions
• Debug with beautiful Rich tree traces
• Extend with your own custom functions via a registry

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📦 Requirements

• Python 3.11+
• pydantic v2
• rich

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⚙️ Installation

pip install fabrix

🚀 Usage

from fabrix import Context, evaluate

# Create a context with parameters & variables
ctx = Context(
    pipeline_parameters={"myNumber": 42},
    variables={"greeting": "hello"}
)

# Simple expression
result = evaluate("@concat('Answer is: ', string(pipeline().parameters.myNumber))", ctx)
print(result)  # Answer is: 42

# With variable assignment
from fabrix import Expression

expr = Expression(expression="@toUpper(variables('greeting'))", result="shout")
evaluate(expr, context=ctx)

print(ctx.variables["shout"])  # HELLO

🗺️ Roadmap

• Add more Fabric/ADF built-in functions
• Improve error messages with fuzzy suggestions
• Advanced type checking for function arguments
• VS Code extension with syntax highlighting & validation
• Better documentation and tutorials
• Publish first stable release on PyPI