Citrine

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1.33.0

Not secure
In this release of Citrine Python, we are all about improvements. We've made improvements to our default behavior around units in GEM Table column definitions to avoid the case of miss-matched units within a column. We also have improved backwards compatibility of project endpoints to reduce the amount of code changes required in the upcoming migration to Teams. Finally, as always, we continue to update our documentation and make minor improvements to better support our users.

Improvements
* Smarter behavior of the `target_units` parameter in GEM Table Column definition is now on platform. If you don't specify which units you want to work in, the table builder check if there's also an `OriginalUnitsColumnDefinition` to figure out if you wanted the numbers as reported; if not, you'll get the `default_units` from your Attribute Template. So if you don't specify units, the platform's got you covered. 758
* Increased backwards compatibility of project endpoints for our upcoming migration to Teams for access control. 759, 761
* Updated our documentation to be more descriptive about the relationship between branches, design workflows, and archival. 760
* Other minor improvements. 762

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v1.31.1...v1.33.0

1.31.1

Not secure
This release includes exiting new functionality for building predictors. For fans of the `SimpleMLPredictor`, we've included the `simple_ml_builder` that mimics the simple interface, but creates a `GraphPredictor` that is compatible with our web UI. We also now allow more flexibility in referencing files through our SDK. As always, we are improving our documentation, performance, and fixing bugs to keep our users running smoothly.

What's New
* We've introduced the `simple_ml_builder`: the ease of use of the `SimpleMLPredictor` but directly compatible with the current version of our Model Builder web UI. One can use this builder method to pass input, output, and latent variable descriptors and get a GraphPredictor with the necessary AutoML and featurizer nodes needed to predict your outputs. 737, 752, 755
* Users can now retrieve files by the `file_link` object, its UUID, _or_ its filename. 745

Improvements
* Improving our documentation for querying and waiting for asynchronous tasks. 749
* Updated dependency to latest release of `gemd-python` (see [`gemd-python` release notes](https://github.com/CitrineInformatics/gemd-python/releases/tag/v1.9.0) for details). #757
* Performance improvements to accelerate our internal development. 751, 756

Fixes
* Bugfixes to keep folks running smoothly. 750

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v1.28.3...v1.31.1

1.28.3

Not secure
This release contains new functionality to handle integers as descriptors in the AI Engine and improved functionality for registering batches of GEMD objects. As always, we are also making bug fixes and improving our documentation.

What's New
* Added a new `IntegerDescriptor` to use with discrete variables inside Predictors and Design Spaces. Stay tuned for functionality that allows one to pull these Descriptors directly from a GEM Table. 742, 743

Improvements
* Improvements to the `register_all` method, including new functionality to allow users to register nested GEMD objects. The `include_nested` handles all your GEMD hydration for fast and efficient data ingest. 744

Fixes
* Minor bug fixes to keep you running smoothly. 746, 747
* Documentation corrections. 748

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v1.26.0...v1.28.3

1.26.0

Not secure
This release gives users additional flexibility when creating auto-configured AI models and where files can be retrieved from using Citrine Python. We also are continually improving our documentation, tests, and contribution processes while fixing bugs to keep the API experience as smooth as possible.

What's New
* One may now override the `auto_config` Predictor behavior to produce a maximum-complexity predictor from a training data source (i.e., the "old" behavior) with the `prefer_valid=False` argument. Perfect for those times where you'd like to start from many nodes and pare down, or are just old fashioned and like big graphs. https://github.com/CitrineInformatics/citrine-python/pull/734
* Files can now be retrieved from off-platform sources! The workbooks, images and other files that support data might be located in a variety of locations around your organization, and this makes it simpler to pull them into your working environment. Just use `files.download`. https://github.com/CitrineInformatics/citrine-python/pull/741

Improvements
* Better documentation around our multi-objective capabilities. https://github.com/CitrineInformatics/citrine-python/pull/729, https://github.com/CitrineInformatics/citrine-python/pull/733
* Additional guidelines for contributors. https://github.com/CitrineInformatics/citrine-python/pull/677
* Increased test coverage for more stable functions. https://github.com/CitrineInformatics/citrine-python/pull/725

Fixes
* Minor bug fixes to keep you running smoothly. https://github.com/CitrineInformatics/citrine-python/pull/726, https://github.com/CitrineInformatics/citrine-python/pull/732, https://github.com/CitrineInformatics/citrine-python/pull/731, https://github.com/CitrineInformatics/citrine-python/pull/739, https://github.com/CitrineInformatics/citrine-python/pull/738, https://github.com/CitrineInformatics/citrine-python/pull/728, https://github.com/CitrineInformatics/citrine-python/pull/740, #735
* Dependency updates. https://github.com/CitrineInformatics/citrine-python/pull/727

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v1.23.0...v1.26.0

1.23.0

Not secure
This release introduces a couple new exciting features related to AI models, and continued improvements to documentation and access control.

What's New
* The `MeanPropertyPredictor` now supports featurization of both real and categorical properties in a formulation. The categorical-valued mean property is a quantity-weighted distribution over property values in the mixture. The same interface applies to both real and categorical values, so give it a go in your workflow! 723
* A new capability to convert deprecated `SimpleMLPredictor` nodes to `GraphPredictor`s with equivalent components. The methods `convert_to_graph` and `convert_and_update`, available on a `PredictorCollection`, enable this feature. 720

Improvements
* Expanded search behavior in support of our new Teams Access Control model. 718
* Expanded documentation on default predictors and the new `MeanPropertyPredictor`. 722 723

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v1.21.2...v1.23.0

1.21.2

Not secure
This release is mostly about supporting our new Access Control model, with some improvements in documentation, usability, and testing along the way.

What's New
* In support of our upcoming improvements to our Access Control model, we've added support for Teams. Note that Teams functionality will not be available to every deployment 699 701
* Branches are now available as an organizational concept for design workflows. See the documentation for more information on use cases: [Branches](https://citrineinformatics.github.io/citrine-python/workflows/design_workflows.html#branches) 702 707 708

Improvements
* Positional arguments for the [Citrine](https://citrineinformatics.github.io/citrine-python/reference/citrine.citrine.html?highlight=citrine#citrine.citrine.Citrine) constructor have been deprecated. Hopefully this will help avoid some stubbed toes, as people had an unfortunate habit of passing the `host` as the second argument. 706
* We've added python 3.9 and 3.10 to our travis tests and bumped required versions for pandas and sphinx packages. 713

Fixes
* Multiple corrections were made to the documentation. 704 709 711

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v1.16.0...v1.21.2

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