Merge branch 'master' into master

Author: djm21

.conda/meta.yaml

@@ -21,6 +21,7 @@ requirements:
     - python >=3.6
     - pip
   run:
+    - dill
     - python >=3.6
     - pandas
     - requests

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

@@ -21,7 +21,7 @@ jobs:
       LANG: en_US.UTF-8
     strategy:
       matrix:
-        python-version: ['3.6', '3.7', '3.8', '3.9', '3.10']
+        python-version: ['3.8', '3.9', '3.10', '3.11']
         os-version: ['ubuntu-20.04', 'windows-latest', 'macos-latest']
 # Pinned Ubuntu version to 20.04 since no Python 3.6 builds available on ubuntu-latest (22.04) as of 2022-12-7.
 #        os-version: [ubuntu-latest, windows-latest, macos-latest]
@@ -45,7 +45,7 @@ jobs:
         run: |
           # Setup tox & code coverage
           pip install --upgrade pip
-          pip install tox tox-gh-actions pytest pytest-cov scikit-learn
+          pip install tox tox-gh-actions pytest pytest-cov 'scikit-learn<=1.5.0' 'numpy<2.0.0'
 
       - name: Run Tests
         run: |
@@ -113,7 +113,7 @@ jobs:
         run: sphinx-build -Ean -b html -j auto -D todo_include_todos=0 ./docs ./docs/_build/html
 
       - name: Archive artifacts
-        uses: actions/upload-artifact@v2
+        uses: actions/upload-artifact@v4
         with:
           name: html-docs
           path: ./docs/_build/html
@@ -159,13 +159,13 @@ jobs:
 
       - name: Archive distribution artifacts
         # Archive distribution files for use by auto (or manual) PyPI upload
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: pypi-dist
           path: ./dist
 
       - name: Archive changelog artifacts
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: release_notes
           path: release_notes.md
@@ -199,7 +199,7 @@ jobs:
 
       # Archive distribution files.  Will upload in a downstream job.
       - name: Archive distribution artifacts
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: conda-dist
           path: .build
@@ -214,19 +214,19 @@ jobs:
 
     steps:
       - name: Download documentation
-        uses: actions/download-artifact@v3
+        uses: actions/download-artifact@v4
         with:
           name: html-docs
           path: ./html-docs
 
       - name: Download release
-        uses: actions/download-artifact@v3
+        uses: actions/download-artifact@v4
         with:
           name: pypi-dist
           path: ./dist
 
       - name: Download release notes
-        uses: actions/download-artifact@v3
+        uses: actions/download-artifact@v4
         with:
           name: release_notes
 
@@ -292,7 +292,7 @@ jobs:
 
       # Download release files
       - name: Download release
-        uses: actions/download-artifact@v3
+        uses: actions/download-artifact@v4
         with:
           name: conda-dist
           path: ./dist

CHANGELOG.md

@@ -1,12 +1,49 @@
-Unreleased
-----------
+v1.10.7 (2024-10-02)
+--------------------
+**Bugfixes**
+ - Fixed a bug that caused an error when performing SSL verification without a CA bundle specified.
+
+v1.10.6 (2024-08-26)
+--------------------
 **Improvements**
  - Refactor `tasks.py` to utilize `sasctl.pzmm` functions.
  - Add `model_info` class to better capture model information.
- - Test `/examples` Jupyter notebooks within normal test suite.
+
+v1.10.5 (2024-08-01)
+--------------------
+**Buxfixes**
+- Updated `write_json_files.py` to allow for better support for prediction models
+- Fixed issues relating to model card support.
+
+v1.10.4 (2024-07-08)
+--------------------
+**Improvements**
+- Added example Jupyter notebook for OpenAI models.
+
+**Buxfixes**
+- Dropped support for Python 3.6 and Python 3.7, as those are no longer officially supported versions.
+- Added `dmcas_misc.json` template file for model card generation.
+- Updated generation of `ModelProperties.json` to allow for model card generation immediately upon upload.
+
+v1.10.3 (2024-04-12)
+--------------------
+**Bugfixes**
+- Updated all examples to use current versions of sasctl functions
+- Fixed bug in `generate_model_card` that threw an error when trying to generate the `dmcas_misc.json` file
+
+v1.10.2 (2024-04-10)
+--------------------
+**Improvements**
+- Introduced `generate_model_card` into `write_json_files.py` to allow for python models to work with planned model card tab in SAS Model Manager.
+
+**Bugfixes**
+- Allow for score code to impute NaN values in tables that have been loaded into SAS Model Manager.
+- Fix issue where target_value was not being properly set during score code generation
+- Updated `pzmm_generate_requrirements_json.ipynb` so the requirements file is generated properly.
+- Added missing statistics to `dmcas_fitstat.json` file.
 
 v1.10.1 (2023-08-24)
-----------
+--------------------
 **Improvements**
 - Introduced ability to specify the target index of a binary model when creating score code.
   - index can be specified in `pzmm.import_model.ImportModel.import_model()`
@@ -17,7 +54,7 @@ v1.10.1 (2023-08-24)
 - Added template files for `assess_model_bias.py` to allow for proper execution
 
 v1.10 (2023-08-31)
-----------
+------------------
 **Improvements**
  - `write_score_code.py` refactored to include ability to run batch scoring.
  - Added handling for TensorFlow Keras models.
@@ -30,7 +67,7 @@ v1.10 (2023-08-31)
    - Updated `pzmm_custom_kpi_model_parameters` notebook to have correct parameter casing.
 
 v1.9.4 (2023-06-15)
-----------
+-------------------
 **Improvements**
  - Created pytest fixture to begin running Jupyter notebooks within the GitHub automated test actions.
  - Updated examples:
@@ -44,7 +81,7 @@ v1.9.4 (2023-06-15)
  - Fixed call to `pzmm.JSONFiles.calculate_model_statistics()` in `pzmm_binary_classification_model_import.ipynb`.
 
 v1.9.3 (2023-06-08)
-----------
+-------------------
 **Improvements**
  - Refactored gitIntegration.py to `git_integration.py` and added unit tests for better test coverage.
 
@@ -57,7 +94,7 @@ v1.9.3 (2023-06-08)
  - 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.
 
 v1.9.2 (2023-05-17)
-----------
+-------------------
 **Improvements**
  - Add recursive folder creation and an example.
  - Add example for migrating models from SAS Viya 3.5 to SAS Viya 4.
@@ -69,7 +106,7 @@ v1.9.2 (2023-05-17)
  - Fix minor errors in h2o score code generation
 
 v1.9.1 (2023-05-04)
-----------
+-------------------
 **Improvements**
  - Updated handling of H2O models in `sasctl.pzmm`.
    - Models are now saved with the appropriate `h2o` functions within the `sasctl.pzmm.PickleModel.pickle_trained_model` function.
@@ -81,7 +118,7 @@ v1.9.1 (2023-05-04)
  - Added NpEncoder class to check for numpy values in JSON files. Numpy-types cannot be used in SAS Viya.
 
 v1.9.0 (2023-04-04)
-----------
+-------------------
 **Improvements**
  - `sasctl.pzmm` refactored to follow PEP8 standards, include type hinting, and major expansion of code coverage.
    - `sasctl.pzmm` functions that can generate files can now run in-memory instead of writing to disk.
@@ -109,7 +146,7 @@ v1.8.2 (2023-01-30)
    - Better handling for invalid project versions included.
 
 v1.8.1 (2023-01-19)
-----------
+-------------------
 **Changes**
  - Adjusted workflow for code coverage reporting. Prepped to add components in next release.
  - Added `generate_requirements_json.ipynb` example.

doc/api/services/report_images.rst

@@ -3,4 +3,5 @@ sasctl.services.report_images
 
 .. automodule:: sasctl._services.report_images
     :members:
-    :undoc-members:
+    :undoc-members:
+    :show-inheritance:

doc/api/services/reports.rst

@@ -4,3 +4,4 @@ sasctl.services.reports
 .. automodule:: sasctl._services.reports
     :members:
     :undoc-members:
+    :show-inheritance:

doc/conf.py

@@ -44,23 +44,32 @@
     "sphinx.ext.autodoc",
     "sphinx.ext.autosummary",
     "sphinx.ext.viewcode",
-    "numpydoc",  # "sphinx.ext.napoleon",
+    "sphinx.ext.napoleon",
     "sphinx.ext.intersphinx",
     "sphinx.ext.todo",
 ]
 
 intersphinx_mapping = {
-    "python": ("https://docs.python.org/3", None),
+    "python": ("https://docs.python.org/3/", None),
+    "pandas": ("https://pandas.pydata.org/docs/", None),
+    "sklearn": ("https://scikit-learn.org/stable/", None),
+    "numpy": ("https://numpy.org/doc/stable/", None),
     "swat": ("https://sassoftware.github.io/python-swat/", None),
     "pytest": ("https://docs.pytest.org/en/latest/", None),
     "betamax": ("https://betamax.readthedocs.io/en/latest/", None),
-    "requests": ("https://2.python-requests.org/en/master/", None),
-    "tox": ("https://tox.readthedocs.io/en/latest/", None),
-    "flake8": ("http://flake8.pycqa.org/en/latest/", None),
+    "requests": ("https://requests.readthedocs.io/en/latest/", None),
+    "tox": ("https://tox.wiki/en/latest/", None),
+    "flake8": ("https://flake8.pycqa.org/en/latest/", None),
 }
 
 autosummary_generate = True
 
+# Napoleon settings
+napoleon_google_docstring = False
+napoleon_numpy_docstring = True
+napoleon_use_ivar = True
+napoleon_use_rtype = False
+
 todo_include_todos = True
 
 todo_emit_warnings = True
@@ -92,6 +101,17 @@
 # The name of the Pygments (syntax highlighting) style to use.
 pygments_style = "sphinx"
 
+# Suppress warnings 'py:class reference target not found: <type>'
+nitpicky = True
+nitpick_ignore = [
+    ('py:class','optional'),
+    ('py:class','json.encoder.JSONEncoder'), # I don't understand why it can't find it
+    ('py:class','Response'),
+    ('py:class','Request'),
+    ('py:class','_io.BytesIO'),
+    ('py:class','sasctl.utils.pymas.ds2.Ds2Variable'), # not sure what is wrong
+    ('py:class','sasctl._services.service.Service') # should the Service class be documented?
+]
 
 # -- Options for HTML output -------------------------------------------------
 

doc/index.rst

@@ -4,11 +4,6 @@ sasctl
 
 Version |version|
 
-.. toctree::
-    :maxdepth: 3
-    :hidden: true
-
-    index
 
 Introduction
 ------------
@@ -313,7 +308,7 @@ Logging
 +++++++
 
 All logging is handled through the built-in :mod:`logging` module with standard module-level loggers.  The one exception
-to this is :class:`.Session` request/response logging.  Sessions contain a :attr:`~sasctl.core.Session.message_log` which is exclusively used
+to this is :class:`.Session` request/response logging.  Sessions contain a `message_log` which is exclusively used
 to record requests and responses made through the session.  Message recording can be configured on a per-session basis
 by updating this logger, or the ``sasctl.core.session`` logger can be configured to control all message recording by all sessions.
 
@@ -497,7 +492,7 @@ Python versions.
 
 Useful Tox Commands
 +++++++++++++++++++
-:mod:`tox`  is used to automate common development tasks such as testing, linting, and building documentation.
+:mod:`tox` is used to automate common development tasks such as testing, linting, and building documentation.
 Running :program:`tox` from the project root directory will automatically build virtual environments for all Python interpreters
 found on the system and then install the required packages necessary to perform a given task.  The simplest way to run Tox is:
 

examples/README.md

@@ -37,6 +37,8 @@ Tasks and Services
 - [Modeling with Python & SAS AutoML](#modeling-with-python--sas-automl)
 - [Making direct REST API calls](#making-direct-rest-api-calls)
 
+- [Register an Azure OpenAI GPT model using REST API calls](#register-an-azure-openai-gpt-model-using-rest-api-calls)
+
 ---
 Register binary classification models
 -------------------------------------
@@ -94,11 +96,11 @@ Generates a requirements.json file which includes the minimal number of dependen
 
 Create and update custom model KPIs
 -----------------------------------
-Filename: [pzmm_custom_kpis.ipynb](pzmm_custom_kpis.ipynb)
+Filename: [pzmm_custom_kpis.ipynb](pzmm_custom_kpi_model_parameters.ipynb)
 
 Level: Intermediate
 
-Create and update custom model parameters and kpis on SAS Model Manager
+Create and update custom model parameters and kpis on SAS Model Manager.
 
 
 Register a SAS classification model
@@ -206,3 +208,11 @@ Level: Advanced
 Demonstrates using `sasctl` to make REST calls over HTTP(S) directly to the SAS microservices.
 
 Use if you need to customize behavior or use functionality not yet exposed through higher-level `sasctl` functions.
+
+Register an Azure OpenAI GPT Model Using REST API Calls
+--------------------------
+Filename: [register_Azure_OpenAI_model_using_REST_calls.ipynb](register_Azure_OpenAI_model_using_REST_calls.ipynb)
+
+Level: Intermediate
+
+Leverages a GPT-3.5-Turbo model from Azure OpenAI in SAS® Model Manager and SAS® Intelligent Decisioning.