Notebooks¶

Fabric Notebooks are interactive documents that combine code, visualizations, and markdown text. The Notebook API provides access to notebook metadata and content.

Getting a Notebook¶

import fabias

ws = fabias.workspace("Analytics")

# By name
notebook = ws.notebook("ETL Processing")

# By GUID
notebook = ws.notebook("a1b2c3d4-...")

Listing Notebooks¶

ws = fabias.workspace("Analytics")

# List all notebooks
for notebook in ws.notebooks():
    print(f"{notebook.name}: {notebook.id}")

Creating Notebooks¶

ws = fabias.workspace("Analytics")

# Create a new notebook
notebook = ws.notebooks.add("Data Exploration")

# Create with description and folder
notebook = ws.notebooks.add(
    "Data Exploration",
    description="Ad-hoc data exploration and analysis",
    folder_id="folder-guid"
)

Notebook Properties¶

notebook = ws.notebook("ETL Processing")

print(f"ID: {notebook.id}")
print(f"Name: {notebook.name}")
print(f"Description: {notebook.description}")
print(f"Type: {notebook.type}")
print(f"Workspace ID: {notebook.workspace_id}")

Getting Notebook Content¶

Notebook content is retrieved via the getDefinition() method, which returns a long-running operation:

notebook = ws.notebook("ETL Processing")

# Fetch notebook definition (async operation)
definition = notebook.getDefinition()

# Access notebook files
for file in definition.files:
    print(f"Path: {file.path}")
    print(f"Type: {file.type}")
    print(f"Content (first 100 chars): {file.content[:100]}")

Notebook Definition Structure¶

The NotebookDefinition object contains:

Property	Type	Description
`files`	List[NotebookFile]	List of notebook files/parts

Each NotebookFile has:

Property	Type	Description
`path`	str	File path within notebook
`type`	str	Payload type (e.g., "InlineBase64")
`content`	str	Decoded notebook content (UTF-8)
`base64`	str	Base64-encoded content

Notebook Formats¶

The format parameter accepts NotebookFormat enum values:

from fabias import NotebookFormat

# GitSource format (default)
definition = notebook.getDefinition(format=NotebookFormat.GITSOURCE)

Cached vs Fresh Load¶

By default, notebook definitions are cached after first retrieval. To force a fresh load:

notebook = ws.notebook("ETL Processing")

# First call - fetches from API
definition1 = notebook.getDefinition()

# Second call - returns cached definition
definition2 = notebook.getDefinition()

# Force fresh load
definition3 = notebook.getDefinition(freshLoad=True)

Updating Notebooks¶

notebook = ws.notebook("ETL Processing")

# Update name and description
notebook.update(
    name="ETL Processing v2",
    description="Updated ETL pipeline notebook"
)

Deleting Notebooks¶

notebook = ws.notebook("Old Notebook")

# Delete the notebook
notebook.delete()

# Or delete by name/ID via accessor
ws.notebooks.delete("Old Notebook")

Example: Export Notebook Content¶

import fabias
import json

ws = fabias.workspace("Analytics")
notebook = ws.notebook("ETL Processing")

# Get notebook definition
definition = notebook.getDefinition()

# Extract and save content
for file in definition.files:
    if file.path.endswith(".ipynb"):
        # Parse as JSON if it's a Jupyter notebook
        content_dict = json.loads(file.content)

        # Save to local file
        with open(f"{notebook.name}.ipynb", "w") as f:
            json.dump(content_dict, f, indent=2)

        print(f"Exported notebook to {notebook.name}.ipynb")

Example: List Notebooks with Metadata¶

import fabias

ws = fabias.workspace("Analytics")

print(f"\nNotebooks in {ws.name}:")
print("-" * 60)

for notebook in ws.notebooks():
    print(f"Name: {notebook.name}")
    print(f"  ID: {notebook.id}")
    if notebook.description:
        print(f"  Description: {notebook.description}")
    print()

Example: Search Notebook Content¶

import fabias

def search_notebooks(workspace_name: str, search_term: str):
    """Search for a term in all notebook content."""
    ws = fabias.workspace(workspace_name)

    print(f"Searching for '{search_term}' in notebooks...")

    for notebook in ws.notebooks():
        print(f"\nChecking {notebook.name}...")

        # Get notebook content
        definition = notebook.getDefinition()

        for file in definition.files:
            if search_term.lower() in file.content.lower():
                print(f"  ? Found in {notebook.name}")
                break

# Usage
search_notebooks("Analytics", "spark.read")

Long-Running Operations¶

The getDefinition() method returns a long-running operation that you can wait for:

notebook = ws.notebook("ETL Processing")

# Start the operation
print("Fetching notebook definition...")
definition = notebook.getDefinition()

# The operation automatically waits and returns the result
print(f"Definition loaded with {len(definition.files)} files")

Refreshing Notebook Data¶

Notebook properties are lazy-loaded and cached. To force a refresh:

notebook = ws.notebook("ETL Processing")

# Make changes via web UI or another client...

# Refresh local data
notebook.refresh()
print(f"Updated name: {notebook.name}")