Citrine

This release includes client support for estimating `Bounds` for columns of data in hosted CSV files, migration utilities for up-converting `EnumeratedDesignSpace`s into `DataSourceDesignSpaces`, and improvements to documentation and argument validation.

**What's new:**

- The `dataset.files.process` method now includes information about what `Bound` might be appropriate for the data in each column (https://github.com/CitrineInformatics/citrine-python/pull/489)
- Two migration methods that up-convert `EnumeratedDesignSpace`s to `DataSourceDesignSpace`, either locally or on a platform (https://github.com/CitrineInformatics/citrine-python/pull/487)

**Improvements:**

- The AI Engine documentation makes better use of utility methods from our SDK. (https://github.com/CitrineInformatics/citrine-python/pull/483)
- The `IngredientQuantityByProcessAndName` class validates that the present of a `unit` is consistent with the type of quantity (https://github.com/CitrineInformatics/citrine-python/pull/490)

This release adds a formulation design space and associated ingredient and label constraints.

**What's new:**

- `FormulationDesignSpace` defines a formulation domain from a set of ingredient names, ingredient labels and formulation constraints.
- There are 3 new formulation constraints:
1. `IngredientFractionConstraint` limits the total ingredient fraction in a formulation. It can be used in a `FormulationDesignSpace` to restrict formulations or with a `Score` to penalize candidates that do not satisfy the constraint.
2. `LabelFractionConstraint` limits the total fraction of ingredients with a given label in a formulation.
3. `IngredientCountConstraint` limits the total number of ingredients in a single formulation. If a label is specified, only ingredients with the label will count towards the total.

This is a maintenance release that fixes a bug in the json support module that hindered feature development.

Improvements:
* Default values of any type can be set when defining json properties (https://github.com/CitrineInformatics/citrine-python/pull/485)

This release includes initial Alpha-level support for deep asynchronous validations on data object updates.

**What’s New**

* Alpha-level support for deep asynchronous validations on data object updates. This allows us to support editing of templates, specifically the narrowing of the template bounds and the allowed names and labels on a template. The relevant data will be checked to ensure the update is valid relative to existing data. This also includes a dry run option to check if the update would succeed.

This is the beta release of the Predictor Evaluation Workflow system! Checkout the [user guide](https://citrineinformatics.github.io/citrine-python/workflows/predictor_evaluation_workflows.html) for details.

**Improvements**
* Improved documentation of the CrossValidationEvaluator (https://github.com/CitrineInformatics/citrine-python/pull/478, https://github.com/CitrineInformatics/citrine-python/pull/480)
* New specific "TimedOut" status for DesignWorkflowExecutions (https://github.com/CitrineInformatics/citrine-python/pull/482)

This is a maintenance release that improves consistency of behavior in the client and SDK, particularly around the new Predictor Evaluation system. It also updates the included version of `gemd.`

**Improvements**
* Trying to delete a PredictorEvaluationWorkflow or PredictorEvaluationExecution will result in a `NotImplementedError` instead of a `NotFound` exception (https://github.com/CitrineInformatics/citrine-python/pull/476)
* `wait_while_executing` will return an updated execution (https://github.com/CitrineInformatics/citrine-python/pull/475)
* Updated version of gemd-python (https://github.com/CitrineInformatics/citrine-python/pull/474)
* Experimental logs will work for PredictorEvaluationWorkflows and Executions (https://github.com/CitrineInformatics/citrine-python/pull/475)