Releases: sassoftware/python-sasctl
Releases · sassoftware/python-sasctl
v1.9.1
Improvements
- Updated handling of H2O models in
sasctl.pzmm.- Models are now saved with the appropriate
h2ofunctions within thesasctl.pzmm.PickleModel.pickle_trained_modelfunction. - Example notebooks have been updated to reflect this change.
- Models are now saved with the appropriate
Bugfixes
- Added check for
sasctl.pzmm.JSONFiles.calculate_model_statsisticsfunction to replace float NaN values invalid for JSON files. - Fixed issue where the
sasctl.pzmm.JSONFiles.write_model_propertiesfunction 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.pzmmrefactored to follow PEP8 standards, include type hinting, and major expansion of code coverage.sasctl.pzmmfunctions 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.pzmmusage and model assets.- Examples from older versions moved to
examples/ARCHIVE/vX.X.
- Examples from older versions moved to
- 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 theinput=parameter was renamed to
prompts=to avoid conflicting with the built-ininput().
v1.8.1
Changes
- Adjusted workflow for code coverage reporting. Prepped to add components in next release.
- Added
generate_requirements_json.ipynbexample.
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 ofmodel_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.saslogonfor creating and removing OAuth clients.
Changes
- Deprecated
core.platform_version()in favor ofSession.version_info(). - A
RuntimeErroris 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
Sessionto 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
Nonewould throw an error on most services instead
of returningNone. - 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
v1.7.0
Improvements
- Added Git integration for better tracking of model history and versioning.
- Added MLFlow integration for simple models, allowing users to import simple MLFlow models, such as sci-kit
learn, to SAS Model Manager
v1.6.4
Bugfixes
- Fixed an issue where
folders.create_folder()would attempt to use root folder as parent if desired parent
folder wasn't found. Now correctly handles parent folders and raises an error if folder not found.