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lakehouse Package

Functions

create_lakehouse

Create a lakehouse in the specified workspace.

create_lakehouse(display_name: str, description: str | None = None, workspace: str | UUID | None = None, folder: str | PathLike | UUID | None = None, enable_schema: bool = False, lro_config: LroConfig | None = None, credential: TokenCredential | None = None, **kwargs) -> str

Parameters

Name Description
display_name
Required
str

The display name of the lakehouse.
description
str

The optional description of the lakehouse.

Default value: None
workspace
str or UUID

The Fabric workspace name or UUID object containing the workspace ID. Defaults to None which resolves to the workspace of the attached lakehouse or if no lakehouse attached, resolves to the workspace of the notebook.

Default value: None
folder
str, PathLike or UUID

The Fabric folder path, folder ID, or UUID object containing the folder ID to create the lakehouse. Defaults to None which creates the lakehouse under the workspace root. Experimental: This parameter is experimental and may change in future versions.

Default value: None
enable_schema
bool

If True, the notebook will be created with schema enabled.

Default value: False
lro_config
<xref:sempy.fabric.lakehouse.LroConfig>

Options to control LRO polling behavior. See LroConfig for available keys and defaults.

Default value: None
credential
<xref:sempy.fabric.lakehouse.TokenCredential>

The credential for token acquisition. Must be an instance of azure.core.credentials.TokenCredential. If None, the default credential will be used.

Default value: None
**kwargs
Required

Deprecated keyword arguments. Use lro_config instead.

Returns

Type Description
str

The id of lakehouse.

delete_lakehouse

Delete a lakehouse in the specified workspace.

delete_lakehouse(lakehouse: str | UUID | None = None, workspace: str | UUID | None = None, credential: TokenCredential | None = None) -> None

Parameters

Name Description
lakehouse
str or UUID

The Fabric lakehouse name or UUID object containing the lakehouse ID. Defaults to None which resolves to the lakehouse of the attached lakehouse or if no lakehouse attached, raises an error.

Default value: None
workspace
str or UUID

The Fabric workspace name or UUID object containing the workspace ID. If None, defaults to the workspace of the attached lakehouse or if no lakehouse attached, resolves to the workspace of the notebook.

Default value: None
credential
<xref:sempy.fabric.lakehouse.TokenCredential>

The credential for token acquisition. Must be an instance of azure.core.credentials.TokenCredential. If None, the default credential will be used.

Default value: None

get_lakehouse_id

Return lakehouse id of the lakehouse that is connected to the workspace.

get_lakehouse_id() -> str

Returns

Type Description
str

Lakehouse id guid.

list_lakehouse_tables

List all tables in a lakehouse and their properties.

This is a wrapper function for Tables - List Tables.

-[ Notes ]-

When extended=True, this function attempts to retrieve capacity SKU information to calculate guardrail columns. If the capacity cannot be accessed (e.g., the user lacks permissions), a warning will be issued and guardrail columns will be set to None.

list_lakehouse_tables(lakehouse: str | UUID | None = None, workspace: str | UUID | None = None, extended: bool = False, count_rows: bool = False, extend_method: Literal['spark', 'python'] | None = None, credential: TokenCredential | None = None) -> DataFrame

Parameters

Name Description
lakehouse
str or UUID

The Fabric lakehouse name or UUID object containing the lakehouse ID. Defaults to None which resolves to the lakehouse of the attached lakehouse or if no lakehouse attached, raises an error.

Default value: None
workspace
str or UUID

The Fabric workspace name or UUID object containing the workspace ID. If None, defaults to the workspace of the attached lakehouse or if no lakehouse attached, resolves to the workspace of the notebook.

Default value: None
extended
bool

Obtains additional columns relevant to the size of each table.

Default value: False
count_rows
bool

Obtains a row count for each lakehouse table.

Default value: False
extend_method

The method to use for extending table statistics when extended=True.

  • "spark": Uses delta-spark for operations.
  • "python": Uses deltalake-rs for operations.
  • None: Defaults to "spark" when running in a Spark environment; otherwise defaults to "python".
Default value: None
credential
<xref:sempy.fabric.lakehouse.TokenCredential>

The credential for token acquisition. Must be an instance of azure.core.credentials.TokenCredential. If None, the default credential will be used.

Default value: None

Returns

Type Description
DataFrame

DataFrame with one row per table containing the table properties.

Exceptions

Type Description
ValueError

If count_rows=True is specified without extended=True

optimize_lakehouse_tables

Run the OPTIMIZE function over the specified lakehouse tables.

This compacts small files into larger ones to improve read performance.

optimize_lakehouse_tables(tables: str | List[str] | None = None, lakehouse: str | UUID | None = None, workspace: str | UUID | None = None, method: Literal['spark', 'python'] | None = None, credential: TokenCredential | None = None) -> None

Parameters

Name Description
tables
str or List[str]

The table(s) to optimize. If no tables are specified, all Delta tables in the lakehouse will be optimized.

Default value: None
lakehouse
str or UUID

The Fabric lakehouse name or ID. Defaults to None which resolves to the lakehouse attached to the notebook.

Default value: None
workspace
str or UUID

The Fabric workspace name or ID used by the lakehouse. Defaults to None which resolves to the workspace of the attached lakehouse or if no lakehouse attached, resolves to the workspace of the notebook.

Default value: None
method

The method to use for optimizing Delta tables:

  • "spark": Uses delta-spark for operations.
  • "python": Uses deltalake-rs for operations.
  • None: Defaults to "spark" when running in a Spark environment; otherwise defaults to "python".
Default value: None
credential
<xref:sempy.fabric.lakehouse.TokenCredential>

The credential for token acquisition. Must be an instance of azure.core.credentials.TokenCredential. If None, the default credential will be used.

Default value: None

resolve_lakehouse_id

Resolve the ID of a lakehouse in the specified workspace.

resolve_lakehouse_id(lakehouse: str | UUID | None = None, workspace: str | UUID | None = None, credential: TokenCredential | None = None) -> str

Parameters

Name Description
lakehouse
str or UUID

The Fabric lakehouse name or UUID object containing the lakehouse ID. Defaults to None which resolves to the lakehouse of the attached lakehouse or if no lakehouse attached, raises an error.

Default value: None
workspace
str or UUID

The Fabric workspace name or UUID object containing the workspace ID. If None, defaults to the workspace of the attached lakehouse or if no lakehouse attached, resolves to the workspace of the notebook.

Default value: None
credential
<xref:sempy.fabric.lakehouse.TokenCredential>

The credential for token acquisition. Must be an instance of azure.core.credentials.TokenCredential. If None, the default credential will be used.

Default value: None

Returns

Type Description
str

The resolved lakehouse ID.

resolve_lakehouse_name

Resolve the name of a lakehouse in the specified workspace.

resolve_lakehouse_name(lakehouse: str | UUID | None = None, workspace: str | UUID | None = None, credential: TokenCredential | None = None) -> str

Parameters

Name Description
lakehouse
str or UUID

The Fabric lakehouse name or UUID object containing the lakehouse ID. Defaults to None which resolves to the lakehouse of the attached lakehouse or if no lakehouse attached, raises an error.

Default value: None
workspace
str or UUID

The Fabric workspace name or UUID object containing the workspace ID. If None, defaults to the workspace of the attached lakehouse or if no lakehouse attached, resolves to the workspace of the notebook.

Default value: None
credential
<xref:sempy.fabric.lakehouse.TokenCredential>

The credential for token acquisition. Must be an instance of azure.core.credentials.TokenCredential. If None, the default credential will be used.

Default value: None

Returns

Type Description
str

The resolved lakehouse name.

vacuum_lakehouse_tables

Run the VACUUM function over the specified lakehouse tables.

vacuum_lakehouse_tables(tables: str | List[str] | None = None, lakehouse: str | UUID | None = None, workspace: str | UUID | None = None, retention_hours: float | None = None, method: Literal['spark', 'python'] | None = None, credential: TokenCredential | None = None)

Parameters

Name Description
tables
str or List[str]

The table(s) to vacuum. If no tables are specified, all tables in the lakehouse will be vacuumed.

Default value: None
lakehouse
str or UUID

The Fabric lakehouse name or ID. Defaults to None which resolves to the lakehouse attached to the notebook.

Default value: None
workspace
str or UUID

The Fabric workspace name or ID used by the lakehouse. Defaults to None which resolves to the workspace of the attached lakehouse or if no lakehouse attached, resolves to the workspace of the notebook.

Default value: None
retention_hours
float

The number of hours to retain historical versions of Delta table files. Files older than this retention period will be deleted during the vacuum operation. If not specified, the default retention period configured for the Delta table will be used. The default retention period is 168 hours (7 days) unless manually configured via table properties.

Default value: None
method

The method to use for vacuuming Delta tables:

  • "spark": Uses delta-spark for operations.
  • "python": Uses deltalake-rs for operations.
  • None: Defaults to "spark" when running in a Spark environment; otherwise defaults to "python".
Default value: None
credential
<xref:sempy.fabric.lakehouse.TokenCredential>

The credential for token acquisition. Must be an instance of azure.core.credentials.TokenCredential. If None, the default credential will be used.

Default value: None