Metadata-Version: 2.1
Name: azure-databricks-api
Version: 0.6.2
Summary: A wrapper for the Azure Databricks REST API
Home-page: http://github.com/ezwiefel/azure-databricks-api
Author: Erik Zwiefel
Author-email: erikzw@outlook.com
Maintainer: Erik Zwiefel
Maintainer-email: erikzw@outlook.com
License: MIT
Keywords: azure,databricks
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
Requires-Dist: requests (>=2.20.0)

# Azure Databricks API Wrapper
A Python, object-oriented wrapper for the [Azure Databricks REST API 2.0](https://docs.azuredatabricks.net/api/latest/index.html)

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### Installation
This package is pip installable.
```bash
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.
* [x] Clusters
* [ ] Cluster Policies _(Preview)_
* [x] DBFS
* [x] Groups _(Must be Databricks admin)_
* [ ] Instance Pools
* [ ] Jobs
* [X] Libraries
* [ ] MLflow
* [ ] SCIM _(Preview)_
* [ ] Secrets
* [x] Token
* [x] Workspace


### Client Instantiation
To create the client object, you pass the Azure region your workspace is located in and the [generated Personal Access Token](https://docs.databricks.com/api/latest/authentication.html#generate-a-token)
```python
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:
```python
client.clusters.pin(cluster_name='test_cluster_name')
```

The other services are implemented similarly. (e.g. `client.tokens` or `client.groups`)



