OpenSearch-py-ml
- Welcome!
- Getting Started
- Compatibility with OpenSearch
- Project Resources
- Code of Conduct
- License
- Copyright
Welcome!
opensearch-py-ml is a Python client that provides a suite of data analytics and machine learning tools for OpenSearch.
It is a community-driven, open source fork a fork of eland, which provides data analysis and machine learning licensed under the Apache v2.0 License.
opensearch-py-ml lets users call OpenSearch indices and manipulate them as if they were pandas DataFrames, supporting complex filtering and aggregation operations. It also provides rudimentary support for uploading models to OpenSearch clusters using the ml-commons plugin.
For more information, see opensearch.org and the API Doc.
Installing Opensearch-py-ml
Opensearch-py-ml can be installed from PyPI via pip:
$ python -m pip install opensearch-py-ml
Code of Conduct
This project has adopted the Amazon Open Source Code of Conduct. For more information see the Code of Conduct FAQ, or contact opensource-codeofconduct@amazon.com with any additional questions or comments.
License
This project is licensed under the Apache v2.0 License.
Copyright
Copyright OpenSearch Contributors. See NOTICE for details.
Metadata
Release files for opensearch-py-ml 1.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| opensearch_py_ml-1.3.0.tar.gz | 172.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| opensearch_py_ml-1.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 402.7 kB
Release files / opensearch_py_ml-1.3.0.tar.gz
| Download URL | opensearch_py_ml-1.3.0.tar.gz |
|---|---|
| Size | 172.0 kB |
| Tags | Source |
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Transparency logRelease files / opensearch_py_ml-1.3.0-py3-none-any.whl
| Download URL | opensearch_py_ml-1.3.0-py3-none-any.whl |
|---|---|
| Size | 230.7 kB |
| Tags | Python 3 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
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