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Merge branch 'refs/heads/master' into scoring_services
# Conflicts: # examples/pzmm_binary_classification_model_import.ipynb # src/sasctl/__init__.py # src/sasctl/tasks.py # tests/conftest.py # tox.ini
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.conda/meta.yaml

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.github/workflows/build-test-deploy.yml

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run: sphinx-build -Ean -b html -j auto -D todo_include_todos=0 ./docs ./docs/_build/html
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- name: Archive artifacts
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uses: actions/upload-artifact@v2
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uses: actions/upload-artifact@v4
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with:
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name: html-docs
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path: ./docs/_build/html
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- name: Archive distribution artifacts
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# Archive distribution files for use by auto (or manual) PyPI upload
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uses: actions/upload-artifact@v3
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uses: actions/upload-artifact@v4
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with:
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name: pypi-dist
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path: ./dist
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- name: Archive changelog artifacts
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uses: actions/upload-artifact@v3
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uses: actions/upload-artifact@v4
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with:
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name: release_notes
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path: release_notes.md
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# Build a package for distribution through Anaconda.org (conda install sasctl)
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build_conda:
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name: "Build Conda Package"
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runs-on: ubuntu-latest
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needs: test
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if: startsWith(github.ref, 'refs/tags/') # run only on tagged commits
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steps:
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# Setup Miniconda
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- uses: conda-incubator/setup-miniconda@v2
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with:
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auto-update-conda: true
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- name: Install conda-build
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shell: bash -l {0}
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run: |
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conda install conda-build
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- name: Checkout repository
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uses: actions/checkout@v3
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# Build package and store results in .build folder
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- name: Build package
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shell: bash -l {0}
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run: |
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conda build --output-folder .build .conda
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# Archive distribution files. Will upload in a downstream job.
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- name: Archive distribution artifacts
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uses: actions/upload-artifact@v3
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with:
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name: conda-dist
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path: .build
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# build_conda:
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# name: "Build Conda Package"
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# runs-on: ubuntu-latest
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# needs: test
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# if: startsWith(github.ref, 'refs/tags/') # run only on tagged commits
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#
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# steps:
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# # Setup Miniconda
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# - uses: conda-incubator/setup-miniconda@v2
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# with:
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# auto-update-conda: true
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#
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# - name: Install conda-build
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# shell: bash -l {0}
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# run: |
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# conda install conda-build
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#
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# - name: Checkout repository
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# uses: actions/checkout@v3
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#
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# # Build package and store results in .build folder
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# - name: Build package
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# shell: bash -l {0}
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# run: |
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# conda build --output-folder .build .conda
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#
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# # Archive distribution files. Will upload in a downstream job.
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# - name: Archive distribution artifacts
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# uses: actions/upload-artifact@v4
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# with:
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# name: conda-dist
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# path: .build
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# Publishes the new package to PyPI, uploads the latest documentation to GitHub Pages
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# and creates a new release with change notes on GitHub.
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publish:
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name: "Publish"
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runs-on: ubuntu-latest
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needs: [gh-pages, build_pypi, build_conda]
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needs: [gh-pages, build_pypi]
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- name: Download documentation
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uses: actions/download-artifact@v3
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uses: actions/download-artifact@v4
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with:
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name: html-docs
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path: ./html-docs
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- name: Download release
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uses: actions/download-artifact@v3
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uses: actions/download-artifact@v4
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with:
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name: pypi-dist
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path: ./dist
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- name: Download release notes
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uses: actions/download-artifact@v3
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uses: actions/download-artifact@v4
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with:
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name: release_notes
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# NOTE: could be merged with `publish` job above. Left as a separate, final job since it
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# involves multiple steps to setup the environment and if this job fails, the package
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# has already been made available through pip, and the release info published.
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upload_conda:
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name: "Upload Conda Package"
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runs-on: ubuntu-latest
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needs: [publish]
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steps:
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# Setup Miniconda
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- uses: conda-incubator/setup-miniconda@v2
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with:
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auto-update-conda: true
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# Setup Anaconda client (required for upload)
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- name: Install anaconda client
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shell: bash -l {0}
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run: |
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conda install anaconda-client
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# Download release files
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- name: Download release
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uses: actions/download-artifact@v3
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with:
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name: conda-dist
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path: ./dist
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# Upload release to Anaconda.org
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- name: Upload release
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shell: bash -l {0}
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run: |
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anaconda -t ${{ secrets.ANACONDA_TOKEN }} upload -u sas-institute ./dist/noarch/sasctl-*.tar.bz2
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# upload_conda:
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# name: "Upload Conda Package"
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# runs-on: ubuntu-latest
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# needs: [publish]
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#
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# steps:
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# # Setup Miniconda
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# - uses: conda-incubator/setup-miniconda@v2
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# with:
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# auto-update-conda: true
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#
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# # Setup Anaconda client (required for upload)
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# - name: Install anaconda client
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# shell: bash -l {0}
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# run: |
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# conda install anaconda-client
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#
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# # Download release files
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# - name: Download release
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# uses: actions/download-artifact@v4
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# with:
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# name: conda-dist
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# path: ./dist
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#
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# # Upload release to Anaconda.org
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# - name: Upload release
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# shell: bash -l {0}
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# run: |
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# anaconda -t ${{ secrets.ANACONDA_TOKEN }} upload -u sas-institute ./dist/noarch/sasctl-*.tar.bz2

CHANGELOG.md

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Unreleased
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----------
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v1.10.7 (2024-10-02)
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--------------------
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**Changes**
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- Due to licensing restrictions, the `sasctl` package will no longer be available through Anaconda.
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**Bugfixes**
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- Fixed a bug that caused an error when performing SSL verification without a CA bundle specified.
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v1.10.6 (2024-08-26)
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--------------------
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**Improvements**
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- Refactor `tasks.py` to utilize `sasctl.pzmm` functions.
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- Add `model_info` class to better capture model information.
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- Test `/examples` Jupyter notebooks within normal test suite.
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v1.10.5 (2024-08-01)
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--------------------
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**Buxfixes**
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- Updated `write_json_files.py` to allow for better support for prediction models
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- Fixed issues relating to model card support.
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v1.10.4 (2024-07-08)
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--------------------
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**Improvements**
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- Added example Jupyter notebook for OpenAI models.
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**Buxfixes**
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- Dropped support for Python 3.6 and Python 3.7, as those are no longer officially supported versions.
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- Added `dmcas_misc.json` template file for model card generation.
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- Updated generation of `ModelProperties.json` to allow for model card generation immediately upon upload.
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--------------------
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- Fixed bug in `generate_model_card` that threw an error when trying to generate the `dmcas_misc.json` file
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--------------------
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--------------------
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- Introduced ability to specify the target index of a binary model when creating score code.
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----------
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------------------
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- Added handling for TensorFlow Keras models.
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-------------------
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- Created pytest fixture to begin running Jupyter notebooks within the GitHub automated test actions.
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- Updated examples:
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- Fixed call to `pzmm.JSONFiles.calculate_model_statistics()` in `pzmm_binary_classification_model_import.ipynb`.
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----------
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-------------------
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- Fixed issue with `services.model_publish.list_models`, which was using an older API format that is not valid in SAS Viya 3.5 or SAS Viya 4.
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-------------------
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-------------------
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- Updated handling of H2O models in `sasctl.pzmm`.
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- Models are now saved with the appropriate `h2o` functions within the `sasctl.pzmm.PickleModel.pickle_trained_model` function.
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-------------------
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- `sasctl.pzmm` refactored to follow PEP8 standards, include type hinting, and major expansion of code coverage.
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-------------------
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- Added `generate_requirements_json.ipynb` example.

doc/api/services/report_images.rst

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.. automodule:: sasctl._services.report_images
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:undoc-members:
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:show-inheritance:

doc/api/services/reports.rst

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.. automodule:: sasctl._services.reports
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:show-inheritance:

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