Azure Databricks API Wrapper
A Python, object-oriented wrapper for the Azure Databricks REST API 2.0
Installation
This package is pip installable.
pip install azure-databricks-api
Implemented APIs
As of June 25th, 2020 there are 12 different services available in the Azure Databricks API. Currently, the following services are supported by the Azure Databricks API Wrapper.
- Clusters
- Cluster Policies (Preview)
- DBFS
- Groups (Must be Databricks admin)
- Instance Pools
- Jobs
- Libraries
- MLflow
- SCIM (Preview)
- Secrets
- Token
- Workspace
Client Instantiation
To create the client object, you pass the Azure region your workspace is located in and the generated Personal Access Token
from azure_databricks_api import AzureDatabricksRESTClient
azure_region = '[INSERT YOUR AZURE REGION HERE]'
token = '[INSERT YOUR PERSONAL ACCESS TOKEN]'
client = AzureDatabricksRESTClient(region=azure_region, token=token)
Clusters Client Usage
The services above are implemented as children objects of the client. For example, to pin a cluster, you can either pass the cluster_name or cluster_id to the pin() method:
client.clusters.pin(cluster_name='test_cluster_name')
The other services are implemented similarly. (e.g. client.tokens or client.groups)
1 maintainer
Metadata
1 maintainer
Release files for azure-databricks-api 0.6.2
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Release files / azure-databricks-api-0.6.2.tar.gz
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Release files / azure_databricks_api-0.6.2-py3-none-any.whl
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