Citrine

In this release of Citrine Python, we've added a few small but key additions. You can now edit a Predictor without having to wait for a retrain. Also, we've added documentation on how to use the `sample_design_space` feature to return a list of starting candidates for your SL project, even if you don't have any data. And of course, we have some minor changes to keep up with our evolving back-end.

What's New
* You can change a Predictor configuration without triggering a retrain by passing `train=False` when updating your Predictor. https://github.com/CitrineInformatics/citrine-python/pull/867

Improvements
* Add documentation on sampling a Design Space. https://github.com/CitrineInformatics/citrine-python/pull/870
* Updated design spaces to use new endpoints. https://github.com/CitrineInformatics/citrine-python/pull/868, https://github.com/CitrineInformatics/citrine-python/pull/871

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v2.24.1...v2.26.1

With this release we are excited to provide two new features for our users. You can now quickly change the name of a predictor without re-training and you can get a list of experiments even if you haven't yet built a model! As always, we've kept up our maintenance to keep you running smoothly.

What's New
* You can now change the name and/or description of a predictor without triggering a full validation and retraining process. Simply call `project.predictors.rename(uid, version, name, descriptor)`. 865
* Want to kick start your experiments but don't have enough data for a model? Now all you need to is a Design Space! Triggering a Sample Design Space Execution will give you a diverse list of candidates to take to the lab - no model needed. 860

Improvements
* Minor improvements for our developers. 861, 862, 864, 866

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v2.22.0...v2.24.1

We are excited to announce some highly impactful new features with this release of Citrine Python. You can now get the fully featurized training data associated with any valid predictor. We've also included more control over the generative molecular design process, as well as improved the data ingestion process.

What's New
* Finally, you can quickly access the fully featurized training data from a given predictor with the `get_featurized_training_data` method. Simply call `project.get_featurized_training_data` with the ID and version of your predictor and you will get a list of design materials representing your training data with features present. 858
* You can now designate the minimum number of substructures to construct when running generative molecular design by passing a dictionary to the new `min_substructure_counts` argument. 856
* Thanks to 859, a slew of new arguments to the ingest method make getting structured data on platform substantially easier:
* `upload` will copy files onto platform if they're not there already
* `delete_dataset_contents` and `delete_templates` will clear out old records prior to creating new ones
* `build_table` will follow object generation with creating a table for that data, ready for modeling

Improvements
* FileLink objects and the associated FileCollection methods (read, write, etc.) now work smoothly with local files just like remote ones: just use the [File URI scheme](https://en.wikipedia.org/wiki/File_URI_scheme) or convenient `from_path` method. #859

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v2.19.2...v2.22.0

Maintenance only release. Nothing exciting here.

Fixes
* Fixed an out-dated url in the ingest method 854
* Updated the python version used in the generation of the citrine-python documentation 855

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v2.19.0...v2.19.2

A handy new option and a little more maintenance.

What's New
* We've added an option when deleting the contents of a dataset to skip templates. This means that, for a pesky corpus that needs to be rebuilt rather than just updated, your templates can persist, and thus all your tables and AI artifacts will still work. 853

Deprecated
* We've deprecated the code associated with some design space reuse approaches the platform no longer supports 852


**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v2.17.1...v2.19.0

One new feature for generative design, and a whole bunch of maintenance work.

What's New
* Structure exclusion! As you mutate your base molecules to explore new chemistries, you can now specify what types of groups you don't want to consider. 848

Improvements
* We've reworked the relationships between our various libraries, which should result in faster code in your Jupyter notebooks and ETL scripts.
* And a better safety net: we've added Python 3.11 to our regular testing protocol. 851

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v2.15.0...v2.17.1