Citrine

In this version of Citrine Python, we are excited to introduce a pivotal change to the structure of assets on our platform. We know our users want to get every piece of value out of their data and one way to limit the value of your data that is to keep it locked up in silos. As part of the introduction of Data Manager in the Citrine Platform, we have taken Datasets out of Projects and made them assets of a Team, allowing users direct access to all of the data in their Team to leverage in AI Projects.

This introduces non-breaking changes, but our users are encouraged to migrate to new Team-based or Dataset-based endpoints for data management as soon as possible to (A) take advantage of the Data Manager feature on the Citrine Platform and (B) prepare for the eventual removal of Project-based endpoints. For more details on how this will affect your code, see the [Migrating to Use Data Manager](https://citrineinformatics.github.io/citrine-python/FAQ/data_manager_migration.html) guide in the FAQ section of our documentation or reach our to your Citrine support team.

But that's not all we're bringing in this release. We've also updated our Molecular Generation package to leverage SMARTS notation in defining constraints and introduced simpler filtering methods in our listing methods of AI Assets. And as always, we are keeping our code up to date to maintain data security and keep our users running smoothly!

What's New
* New endpoints and deprecation warnings are introduced to support the use of the Data Manager feature. The key change is that newly registered Datasets are now assets of Teams rather than Projects. We have included new collection methods at the Team and Dataset level to account for this, while also adding deprecation warnings for Project-level collections that will be no longer supported in v4.0. For more details on how this will affect your code, see the [Migrating to Use Data Manager](https://citrineinformatics.github.io/citrine-python/FAQ/data_manager_migration.html) guide in the FAQ section of our documentation or reach our to your Citrine support team. #947, 949, 951, 952, 953

Improvements
* Updates to our Generative Molecular Design package to use SMARTS format for constraining the substructure in a generative design execution 939
* A simpler filtering strategy for listing Predictors and Design Spaces 947

Fixes
* Internal maintenance and fixes 945, 946, 948, 953

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v3.2.11...v3.4.4

In this version of Citrine Python, we are pleased to provide some better communications to keep our users running smoothly. We've updated our ingestion methods to support warnings, and also have updated our documentation in multiple places. We've also included some internal improvements as well as part of broader efficiency improvements.

What's New
* We now support warnings for our python methods for data ingestion 940.

Improvements
* Improvement to our documentation deployments. 934
* Internal improvements for backend efficiency. 935, 937, 938
* Documentation on throttling limits to our API calls for our users. 941
* Correction to documentation around `descriptors.from_data_source()`. 942

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v3.2.4...v3.2.11

This release is primarily motivated by a fix for our design space sampling interactions. Users who interact with them should update to avoid access issues.

What's New
* We've got changes incorporated to support upcoming improvements to visualizations on the Citrine Platform. More details will follow when the whole caboodle gets released. 928

Improvements
* We've also migrated our CI/CD pipeline to Github Actions (929) and cleaned up our testing to hew closer to what's literally defined in our API documentation (925),

Fixes
* Resolved a bug in our ability to pull down results for from the `SampleDesignSpaceInput` method. 930

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v3.1.0...v3.2.4

This release of Citrine Python, we're excited to open up a new method of selecting materials for use in model training and visualization to our SDK users.

In our web application, the Citrine Platform has changed how the materials for training tables are selected by leveraging GemdQueries. With this release, we have deployed GemdQueries in Citrine Python as well. Now you may choose materials based on properties, material names, or other detailed properties of the material history, and we will return rows corresponding to the dependent subgraphs for all matching materials. This also supports nesting AND and OR queries, allowing for fine-grained control.

As usual, we've also included some minor fixes and improvements to keep our python SDK lean, clean, and to keep you running smoothly!

What's New
* Implementing `GemdQuery` objects for building tables. 926

Improvements
* Cleaning up disconnected code. 923

Fixes
* Description and summary field requirements are now optional for Datasets. 924

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v3.0.0...v3.1.0

We are proud to announce the 3rd major release of Citrine Python! The Citrine platform has made a lot of improvements over the past year, and our python SDK evolved along with it. This version of Citrine Python removes older methods that have been deprecated and keeps all our dependencies up to date to keep you running smoothly through 2024 and beyond.

It is recommended to migrate to version 3.0 as soon as possible. If all your code still runs without deprecation warnings with our previous release ([version 2.42.2](https://github.com/CitrineInformatics/citrine-python/releases/tag/v2.42.2)) then you have nothing to fear! Otherwise, things that were previously deprecation warnings may become errors.

Migrating to v3.0.0 immediately is not completely necessary, though continuing to use a 2.X version of Citrine Python may introduce instabilities in the near future. For any additional information on how to migrate your code, review the following deprecations below or consult our [V3 Migration Guide](https://citrineinformatics.github.io/citrine-python/FAQ/v3_migration.html).

Improvements
* Dependency updates 904 921 922
* Documentation improvements 910 917 920 919
* More efficient logging 913
* Internal testing improvements 916

Deprecated
The following deprecated features are no longer supported
* Python 3.7 is no longer supported 903
* Citrine.builders are no longer supported 909
* Require a team ID for `find_or_create_project` 912


**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v2.42.2...v3.0.0

This release of Citrine Python includes only a minor bug fix to correct our deployment to PyPI.

Fix
* Fix to our automatic deployment to PyPI. 911

Coming Soon

* We are very excited to announce that Citrine python v3.0 is expected to release in early February 2024. Note this means that currently deprecated methods will result in errors after this move, so be sure to check your code for any deprecation warnings. Contact Citrine support for any assistance in migration.

**Full Changelog**: https://github.com/CitrineInformatics/citrine-python/compare/v2.42.1...v2.42.2