# 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 This project has been archived and is no longer actively maintained or supported.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.
[](https://github.com/aminekaabachi/azure-databricks-sdk-python/actions?query=workflow%3A%22Unit+Tests%22)
[](https://coveralls.io/github/aminekaabachi/azure-databricks-sdk-python?branch=master)
[](https://pypi.org/project/azure-databricks-sdk-python/)
[](https://pypi.org/project/azure-databricks-sdk-python/)
[](https://azure-databricks-sdk-python.readthedocs.io/en/latest/)
[](https://github.com/aminekaabachi/azure-databricks-sdk-python/blob/master/LICENSE)
**azure-databricks-sdk-python** is a Python SDK for the [`Azure Databricks REST API 2.0`](https://docs.microsoft.com/en-gb/azure/databricks/dev-tools/api/latest/).
---
Easily, perform all the operations as if on the Databricks UI:
```python
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.
## Implementation Progress
Please refer to the progress below:
| Feature | Progress |
| :--------------- | :------: |
| Authentification | 100% ✔ |
| Custom types | 25% |
| API Wrappers | 25% |
| Error handling | 80% |
| Proxy support | 0% |
| Documentation | 20% |
As for specific API wrappers:
| API | Progress |
| :-------------------- | :------: |
| Clusters API | 100% ✔ |
| Secrets API | 100% ✔ |
| Token API | 100% ✔ |
| Jobs API | 0% |
| DBFS API | 0% |
| Groups API | 0% |
| Libraries API | 0% |
| Workspace API | 0% |
| Clusters Policies API | 0% |
| Instance Pools API | 0% |
| MLflow API | 0% |
| Permissions API | 0% |
| SCIM API | 0% |
| Token Management API | 0% |
## Documentation
Check the documentation on [readthedocs.org](https://azure-databricks-sdk-python.readthedocs.io/en/latest/).
---
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"description": "# Azure Databricks SDK Python\n\n> **Warning**\n> 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.\n\n[](https://github.com/aminekaabachi/azure-databricks-sdk-python/actions?query=workflow%3A%22Unit+Tests%22)\n[](https://coveralls.io/github/aminekaabachi/azure-databricks-sdk-python?branch=master)\n[](https://pypi.org/project/azure-databricks-sdk-python/)\n[](https://pypi.org/project/azure-databricks-sdk-python/)\n[](https://azure-databricks-sdk-python.readthedocs.io/en/latest/)\n[](https://github.com/aminekaabachi/azure-databricks-sdk-python/blob/master/LICENSE)\n\n**azure-databricks-sdk-python** is a Python SDK for the [`Azure Databricks REST API 2.0`](https://docs.microsoft.com/en-gb/azure/databricks/dev-tools/api/latest/).\n\n---\n\nEasily, perform all the operations as if on the Databricks UI:\n\n```python\nfrom azure_databricks_sdk_python import Client\nfrom azure_databricks_sdk_python.types.clusters import AutoScale, ClusterAttributes\n\nclient = Client(databricks_instance=\"<instance>\", personal_access_token=\"<token>\")\nspark_conf = {'spark.speculation': True}\nautoscale = AutoScale(min_workers=0, max_workers=1)\nattributes = ClusterAttributes(cluster_name=\"my-cluster\",\n spark_version=\"7.2.x-scala2.12\",\n node_type_id=\"Standard_D3_v2\",\n spark_conf=spark_conf,\n autoscale=autoscale)\ncreated = client.clusters.create(attributes)\nprint(created.cluster_id)\n```\n\n## Beloved Features\n\n**azure-databricks-sdk-python** is ready for your use-case:\n\n- Clear standard to access to APIs.\n- Contains custom types for the API results and requests.\n- Support for Personal Access token authentification.\n- Support for Azure AD authentification.\n- Support for the use of Azure AD service principals.\n- Allows free-style API calls with a force mode -(bypass types validation).\n- Error handeling and proxy support.\n\nOfficially supports 3.6+, and runs great on PyPy.\n\n## Implementation Progress\n\nPlease refer to the progress below:\n\n| Feature | Progress |\n| :--------------- | :------: |\n| Authentification | 100% \u2714 |\n| Custom types | 25% |\n| API Wrappers | 25% |\n| Error handling | 80% |\n| Proxy support | 0% |\n| Documentation | 20% |\n\nAs for specific API wrappers:\n\n| API | Progress |\n| :-------------------- | :------: |\n| Clusters API | 100% \u2714 |\n| Secrets API | 100% \u2714 |\n| Token API | 100% \u2714 |\n| Jobs API | 0% |\n| DBFS API | 0% |\n| Groups API | 0% |\n| Libraries API | 0% |\n| Workspace API | 0% |\n| Clusters Policies API | 0% |\n| Instance Pools API | 0% |\n| MLflow API | 0% |\n| Permissions API | 0% |\n| SCIM API | 0% |\n| Token Management API | 0% |\n\n## Documentation\n\nCheck the documentation on [readthedocs.org](https://azure-databricks-sdk-python.readthedocs.io/en/latest/).\n\n---\n\n",
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