Using FabricRestClient To Make Fabric REST API Calls

Accessing Fabric REST endpoints in Fabric notebooks was already easy but it became easier and straightforward with semantic-link version 0.4.0. You can use the FabricRestClient class from sempy to set up a REST client and call the APIs. Authentication is automatically managed for you.

#sempy version 0.4.0 or higher
!pip install semantic-link --q 

import pandas as pd
import sempy.fabric as fabric

#Instantiate the client
client = fabric.FabricRestClient()

Refer to the official documentation for API details. To call an API, you only need to pass the below portion of the URL.

#example usage
url = "v1/workspaces/<workspaceId>/items"
result = client.get(url)

This approach is not substantially different from using requests to make API calls, but there are a few advantages:

• You don't have to generate and pass the authentication token. sempy uses the environment details to authenticate the user automatically.

• This approach is similar to using requests.Session() to maintain a persistent connection, keeping the session open longer. This is particularly beneficial if you plan to call multiple REST endpoints within the same session.

• sempy has a few nice utilities and functions for exception handling and getting workspace/lakehouse ids.

Example

In this simple example, I will get a list of Fabric items from a workspace. I will show how some of the utilities can help make this even easier and robust.

#instantiate the client
client = fabric.FabricRestClient()

#get a list of items from a workspace
workspaceId = "<workspaceid>"
client.get(f"/v1/workspaces/{workspaceId}/items")

In this example, I manually provided the workspace ID. However, we can obtain the notebook's workspace ID automatically without needing to define it.

#instantiate the client
import pandas as pd
client = fabric.FabricRestClient()

#get the default workspace id of the notebook
workspaceId = fabric.get_workspace_id()

#get a list of items from a workspace
response = client.get(f"/v1/workspaces/{workspaceId}/items")
df_items = pd.json_normalize(response.json()['value'])
df_items

For production use cases you will need to include exception handling. sempy provides a few nice utilities, see an example below:

import sempy.fabric as fabric
from sempy.fabric.exceptions import FabricHTTPException, WorkspaceNotFoundException
import pandas as pd

client = fabric.FabricRestClient()

def get_workspace_items(workspace=None):
    """
    Sandeep Pawar | fabric.guru
    Get a list of workspace items using FabricRestClient
    """
    df_items = None
    if workspace is None:
        workspaceId = fabric.get_workspace_id()
    else:
        try:
            workspaceId = fabric.resolve_workspace_id(workspace)
            response = client.get(f"/v1/workspaces/{workspaceId}/items")

            # Check the status code of the response for this endpoint
            # Use 200 if operation is completed, 201 if item is created
            if response.status_code != 200:
                raise FabricHTTPException(response)

            df_items = pd.json_normalize(response.json()['value'])
        except WorkspaceNotFoundException as e:
            print("Caught a WorkspaceNotFoundException:", e)
        except FabricHTTPException as e:
            print("Caught a FabricHTTPException. Check the API endpoint, authentication.")

    return df_items

get_workspace_items("<dataflow name or id>")

In the above example:

• workspace is optional. If no workspace name/id is passed, fabric.get_workspace_id() will use the workspace id of the default workspace. Similarly, you can use fabric.get_lakehouse_id() to get the id of the default lakehouse attached to the notebook.

• All APIs require using workspace id. With fabric.resolve_workspace_id(workspace) you can get the id of a workspace if the user enters workspace name

• WorkspaceNotFoundException, FabricHTTPException help catch workspace and REST endpoint exceptions.

Update: 1/21/2024

Making a POST Request

A redear asked how to make a POST request using the FABRICRestClient. Below is te example where I create a lakehouse using a POST request.

import sempy.fabric as fabric
from sempy.fabric.exceptions import FabricHTTPException, WorkspaceNotFoundException

client = fabric.FabricRestClient()

def create_lakehouse(payload:dict, workspace=None):
    """
    Sandeep Pawar | fabric.guru
    Create a lakehouse using POST request
    """

    if workspace is None:
        workspaceId = fabric.get_workspace_id()
    else:
        workspaceId = fabric.resolve_workspace_id(workspace)

    try:
        response = client.post(f"/v1/workspaces/{workspaceId}/items",json= payload)

        if response.status_code != 201:
            raise FabricHTTPException(response)

    except WorkspaceNotFoundException as e:
        print("Caught a WorkspaceNotFoundException:", e)
    except FabricHTTPException as e:
        print("Caught a FabricHTTPException. Check the API endpoint, authentication.")

    return
#payload/body for the POST request as a dict
#example; create a lakehouse named "mylh" in the default workspace
payload = {
        "displayName": "mylh",
        "type": "Lakehouse"
          }
#workspace name or id is optional. If None, default workspace is used.
create_lakehouse(payload=payload, workspace=None)

Thanks to Markus Cozowicz for answering my questions and for his input.