v1.9.3

Improvements

• Refactored gitIntegration.py to git_integration.py and added unit tests for better test coverage.

Bugfixes

• Fixed issue with ROC and Lift charts not properly being written to disk.
• Fixed JSON conversion for Lift charts that caused TRAIN and TEST charts to be incorrect.
• Fixed issue with H2O score code and number of curly brackets.
• Updated score code logic for H2O to account for incompatibility with Path objects.
• Fixed issue where inputVar.json could supply invalid values to SAS Model Manager upon model import.
• 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

Improvements

• Add recursive folder creation and an example.
• Add example for migrating models from SAS Viya 3.5 to SAS Viya 4.

Bugfixes

• Fixed improper json encoding for pzmm_h2o_model_import.ipynb example.
• Set urllib3 < 2.0.0 to allow requests to update their dependencies.
• Set pandas >= 0.24.0 to include df.to_list alias for df.tolist.
• Fix minor errors in h2o score code generation

v1.9.1

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.
  • Example notebooks have been updated to reflect this change.

Bugfixes

• Added check for sasctl.pzmm.JSONFiles.calculate_model_statsistics function to replace float NaN values invalid for JSON files.
• Fixed issue where the sasctl.pzmm.JSONFiles.write_model_properties function was replacing the user-defined model_function argument.
• Added NpEncoder class to check for numpy values in JSON files. Numpy-types cannot be used in SAS Viya.

v1.9.0

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.
• Added custom KPI handling via pzmm.model_parameters, allowing users to interact with the KPI table generated by model performance via API.
  • Added a method for scikit-learn models to generate hyperparameters as custom KPIs.
• Reworked the pzmm.write_score_code() logic to appropriately write score code for binary classification, multi-class classification, and regression models.
• Updated all examples based on sasctl.pzmm usage and model assets.
  • Examples from older versions moved to examples/ARCHIVE/vX.X.
• DataStep or ASTORE models can include additional files when running tasks.register_model().

Bugfixes

• Fixed an issue where invalid HTTP responses could cause an error when using Session.version_info().

v1.8.2

Improvements

• folders.get_folder() can now handle folder paths and delegates (e.g. @public).

Bugfixes

• Fixed an issue with model_management.execute_model_workflow_definition() where input values for
  workflow prompts were not correctly submitted. Note that the input= parameter was renamed to
  prompts= to avoid conflicting with the built-in input().

v1.8.1

Changes

• Adjusted workflow for code coverage reporting. Prepped to add components in next release.
• Added generate_requirements_json.ipynb example.

Bugfixes

• Fixed improper math.fabs use in sasctl.pzmm.writeJSONFiles.calculateFitStat().
• Fixed incorrect ast node walk for module collection in sasctl.pzmm.writeJSONFiles.create_requirements_json().

v1.8.0

Improvements

• Added Session.version_info() to check which version of Viya the session is connected to.
• Updated the properties= parameter of model_repository.create_model() to accept a dictionary containing
  custom property names and values, and to correctly indicate their type (numeric, string, date, datetime) when
  passing the values to Viya.
• Added services.saslogon for creating and removing OAuth clients.

Changes

• Deprecated core.platform_version() in favor of Session.version_info().
• A RuntimeError is now raised if an obsolete service is called on a Viya 4 session (sentiment_analysis,
  text_categorization, and text_parsing)
• Replaced the JSON cassettes used for testing with compressed binary cassettes to save space.
• Updated the testing framework to allow regression testing of multiple Viya versions.
• Refactored the authentication functionality in Session to be more clear and less error prone. Relevant
  functions were also made private to reduce clutter in the class's public interface.

Bugfixes

• Fixed an issue with register_model() that caused invalid SAS score code to be generated when registering an
  ASTORE model in Viya 3.5.
• Fixed a bug where calling a "get_item()" function and passing None would throw an error on most services instead
  of returning None.
• Fixed a bug that caused the authentication flow to be interrupted if Kerberos was missing.

v1.7.3

Improvements

• Refactor astore model upload to fix 422 response from SAS Viya 4
  • ASTORE model import now uses SAS Viya to generate ASTORE model assets
• Expanded usage for cas_management service (credit to @SilvestriStefano)

Bugfixes

• ASTORE model import no longer returns a 422 error
• Fix improper filter usage for model_repository service
• Fix error with loss of stream in add_model_content call for duplicate content
• Update integration test cassettes for SAS Viya 4

v1.7.2

Improvements

• Added a new example notebook for git integration
• Added a model migration tool for migrating Python models from Viya 3.5 to Viya 4
• Improved handling of CAS authentication with tokens

Bugfixes

• Fixed git integration failure caused by detached head
• Fixed minor bugs in score code generation feature
• Fixed 500 error when importing models to Viya 4 with prewritten score code
• Fixed incorrect handling of optional packages in pzmm

v1.7.1

Bugfixes

• Removed linux breaking import from new git integration feature
• Various minor bug fixes in the git integration feature