Databricks MLflow Model Registry Webhooks Client
Databricks Model Registry Webhooks enable you to automate and integrate your machine learning pipelines with a variety of CI/CD tools and workflows. Databricks Model Registry Webhooks integrate with the Databricks MLflow Model Registry to provide event-based triggers for Model Registry actions, such as the creation of a new model or the transition of a model version into production.
Use cases for Databricks Model Registry Webhooks include triggering CI builds when a new model version is created, notifying team members each time a model transition to production is requested, and much more.
This package provides a Python client for managing Databricks Model Registry Webhooks. For more information about the feature and Python client usage, explore the documentation at https://docs.databricks.com/applications/mlflow/model-registry-webhooks.html.
Metadata
Release files for databricks-registry-webhooks 0.1.2
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| databricks-registry-webhooks-0.1.2.tar.gz | 23.0 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| databricks_registry_webhooks-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 53.9 kB
Release files / databricks-registry-webhooks-0.1.2.tar.gz
| Download URL | databricks-registry-webhooks-0.1.2.tar.gz |
|---|---|
| Size | 23.0 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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No |
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twine/4.0.1 CPython/3.8.8
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Release files / databricks_registry_webhooks-0.1.2-py3-none-any.whl
| Download URL | databricks_registry_webhooks-0.1.2-py3-none-any.whl |
|---|---|
| Size | 30.9 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.8.8
|
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