Azure Databricks SDK Python¶
Warning
This project has been archived and is no longer actively maintained or supported. We highly recommend migrating to the official Databricks SDK for Python available at https://github.com/databricks/databricks-sdk-py.
Release v0.0.2. (Installation)
)
azure-databricks-sdk-python is a Python SDK for the Azure Databricks REST API 2.0.
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Easily, perform all the operations as if on the Databricks UI:
from azure_databricks_sdk_python import Client
from azure_databricks_sdk_python.types.clusters import AutoScale, ClusterAttributes
client = Client(databricks_instance="<instance>", personal_access_token="<token>")
spark_conf = {'spark.speculation': True}
autoscale = AutoScale(min_workers=0, max_workers=1)
attributes = ClusterAttributes(cluster_name="my-cluster",
spark_version="7.2.x-scala2.12",
node_type_id="Standard_D3_v2",
spark_conf=spark_conf,
autoscale=autoscale)
created = client.clusters.create(attributes)
print(created.cluster_id)
Beloved Features¶
azure-databricks-sdk-python is ready for your use-case:
- Clear standard to access to APIs.
- Contains custom types for the API results and requests.
- Support for Personal Access token authentification.
- Support for Azure AD authentification.
- Support for the use of Azure AD service principals.
- Allows free-style API calls with a force mode -(bypass types validation).
- Error handeling and proxy support.
Officially supports 3.6+, and runs great on PyPy.
The User Guide¶
This part of the documentation, which is mostly prose, begins with some background information about azure-databricks-sdk-python, then focuses on step-by-step instructions for getting the most out of it.
The API Documentation¶
If you are looking for information on a specific function, class, or method, this part of the documentation is for you.
Miscellaneous¶
There are no more guides. You are now guideless. Good luck.
