# ABOUTME: Lakehouse-related data models for Microsoft Fabric.
# ABOUTME: Provides FabricLakehouse model for lakehouse representation.
"""Lakehouse-related data models for Microsoft Fabric."""
from typing import Optional
from pydantic import BaseModel, ConfigDict, Field
class FabricLakehouse(BaseModel):
"""Fabric lakehouse model.
Represents a Microsoft Fabric lakehouse - a data architecture platform
combining data lake storage with warehouse capabilities.
Attributes:
id: Unique identifier for the lakehouse (GUID)
display_name: Display name of the lakehouse (shown in Fabric UI)
description: Optional description of the lakehouse
workspace_id: ID of the workspace containing this lakehouse
enable_schemas: Whether schemas are enabled in the lakehouse
type: Type of item (always "Lakehouse")
created_date: Creation timestamp (ISO 8601 format)
modified_date: Last modification timestamp (ISO 8601 format)
Example:
```python
lakehouse = FabricLakehouse(
id="lh-123-abc",
display_name="Bronze Lakehouse",
description="Raw data landing zone",
workspace_id="ws-456-def",
enable_schemas=True,
type="Lakehouse"
)
```
"""
id: str = Field(description="Unique identifier for the lakehouse")
display_name: str = Field(description="Display name of the lakehouse")
description: Optional[str] = Field(default=None, description="Description of the lakehouse")
workspace_id: str = Field(description="ID of the workspace containing this lakehouse")
enable_schemas: bool = Field(default=True, description="Whether schemas are enabled")
type: str = Field(default="Lakehouse", description="Type of item (always Lakehouse)")
created_date: Optional[str] = Field(default=None, description="Creation timestamp")
modified_date: Optional[str] = Field(default=None, description="Last modification timestamp")
model_config = ConfigDict(from_attributes=True)
