Metadata-Version: 2.4
Name: workbench-bridges
Version: 0.2.11
Summary: DEPRECATED — merged into the `workbench` package. Migrate to workbench.endpoints.*
Author-email: SuperCowPowers LLC <support@supercowpowers.com>
License: MIT
Project-URL: Homepage, https://github.com/SuperCowPowers/workbench-bridges
Keywords: SageMaker,Machine Learning,AWS,Python,Utilities,Deprecated
Classifier: Development Status :: 7 - Inactive
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: boto3>=1.28.76
Requires-Dist: botocore>=1.31.76
Requires-Dist: awswrangler>=3.4.0
Requires-Dist: requests>=2.26.0
Dynamic: license-file

# Workbench Bridges — DEPRECATED

> ⚠️ **This package is deprecated and no longer maintained.**
>
> All functionality has been merged into the main [Workbench](https://github.com/SuperCowPowers/workbench)
> package. New code should depend on `workbench` directly. Existing
> deployments will continue to work — this PyPI release is frozen,
> not removed.

## Migration

| `workbench_bridges` import | `workbench` replacement |
| --- | --- |
| `from workbench_bridges.endpoints.fast_inference import fast_inference` | `from workbench.endpoints.fast_inference import fast_inference` |
| `from workbench_bridges.endpoints.async_inference import async_inference` | `from workbench.endpoints.async_inference import async_inference` |
| `from workbench_bridges.api import ParameterStore` | `from workbench.endpoints.parameter_store import ParameterStore` |
| `from workbench_bridges.api import DFStore` | `from workbench.endpoints.df_store import DFStore` |
| `from workbench_bridges.api import InferenceStore` | `from workbench.api import InferenceStore` |
| `from workbench_bridges.api import PublicData` | `from workbench.api import PublicData` |
| `from workbench_bridges.utils.execution_environment import running_as_service` | `from workbench.utils.execution_environment import running_as_service` |
| `from workbench_bridges.aws.sagemaker_session import get_boto3_session` | `from workbench.core.cloud_platform.aws.boto_session import get_boto3_session` |

Lambda / model-script code that previously installed `workbench-bridges` for
its lightweight AWS surface should now `pip install workbench` — the core
install is endpoint-safe (boto3 / pandas / sklearn / scipy / rdkit) with
heavy orchestration deps moved to optional extras (`workbench[aws]`,
`workbench[modeling]`, `workbench[ui]`).

The `workbench.endpoints.*` namespace is the contract for code running
inside SageMaker endpoint containers — see Workbench's
`scripts/endpoint_import_smoke.py` for the enforced surface.

## Historical context

This package originally existed to give end-user applications a small,
fast-installing way to invoke deployed Workbench endpoints and read/write
AWS Parameter Store, DataFrame Store, etc., without pulling in Workbench's
full orchestration dependencies. The Workbench package now provides that
same lightweight surface via `workbench.endpoints.*` and its restructured
optional-extras layout, so a separate bridges package is no longer needed.
