Fabric Data fetching API

Make sure that the token you are obtaining has the correct scope for accessing the Fabric APIs. When you request the token from https://login.microsoftonline.com/common/oauth2/v2.0/token, it must include the proper scopes related to Fabric APIs.

You need to specify the correct resource or scope parameter when requesting the access token. For Fabric APIs, you might need to provide specific resource identifiers such as:

scope=https://fabric.microsoft.com/.default

In your code, ensure that you are calling the correct API endpoint with the workspace and lakehouse IDs. From your example:

GET https://api.fabric.microsoft.com/v1/workspaces/<workspace_id>/lakehouses/<lakehouse_id>

The connectionString that you received in the response is likely to be used for querying data, especially if it’s a SQL endpoint. You can use this connection string to query the data using a tool or SDK that supports SQL-like access to Azure resources.

For example, in Azure Data Factory (ADF) or Synapse, you can use the returned connectionString to create a linked service or a dataset.

If you are connecting to the SQL endpoint in a custom application, you can use libraries like SQLAlchemy:

from sqlalchemy import create_engine
# Use the connection string returned by the API
connection_string = "your_connection_string_from_api"
engine = create_engine(f'mssql+pyodbc:///?odbc_connect={connection_string}')
with engine.connect() as connection:
    result = connection.execute("SELECT * FROM your_table")
    for row in result:
        print(row)

If you are accessing OneLake data (using the oneLakeTablesPath or oneLakeFilesPath), ensure that:

• Your OAuth2 token is valid for OneLake access.
• You may need to use Azure Blob storage SDK or ADLS Gen2 SDK to interact with those paths since OneLake is built on top of ADLS (Azure Data Lake Storage).

from azure.storage.filedatalake import DataLakeServiceClient

servicefrom azure.storage.filedatalake import DataLakeServiceClient

service_client = DataLakeServiceClient(account_url="https://<workspace_id>.dfs.fabric.microsoft.com", credential="your_token")

# Access a specific file system or directory
file_system_client = service_client.get_file_system_client(file_system="<lakehouse_id>")

If you're using Azure Data Factory (ADF) to connect to these resources, you should create linked services for the data source:

• For the oneLakeTablesPath and oneLakeFilesPath, you can use ADF's ADLS Gen2 linked service.
• For the SQL connection string, you can use ADF's Azure SQL or Synapse linked service.

@Shubham Following up to see if the below answer was helpful. If this answers your query, do click Accept Answer and Yes for was this answer helpful. And, if you have any further query do let us know.

I am using these scopes :

"https://api.fabric.microsoft.com/Workspace.ReadWrite.All", "https://api.fabric.microsoft.com/Item.ReadWrite.All", "https://api.fabric.microsoft.com/SQLEndpoint.Execute.All", "https://api.fabric.microsoft.com/Lakehouse.ReadWrite.All"

connection_string = f"Driver={{ODBC Driver 18 for SQL Server}};Server={server};Authentication=ActiveDirectoryServicePrincipal;UID={client_id};PWD={client_secret};TrustServerCertificate=no"

but while connecting with above I either get login timeout or authentication failed.