Citrine v3.11.0 is released!

We're excited to announce the latest enhancements to Citrine Python that continue our commitment to providing our users with a robust and efficient experience. In this release, we've focused on improving our table configuration processes and optimizing our ingestion workflows.

As our platform evolves, we are incorporating faster and easier ways for users to define their training sets, and we now connect our power users to those methods. Users can now leverage direct access to our advanced default table definition processes that leverage GemdQuery objects for even smoother table builds.

We've also taken steps to ensure that your data ingestion is not just effective, easy to use, with a direct link from data ingestion to training-set builds inside of a project. For those who value up-to-date and clear documentation, we've made corrections and enhancements to ensure that your integration with our SDK is as smooth as possible. Additionally, this release includes several internal improvements aimed at streamlining development, allowing us to consistently deliver the reliability and performance you expect from Citrine.

What's New

• Provide direct access to our latest default table definition methods via from_query for constructing a Table Config. #967

Improvements

• Modify compound ingest operation to wait for table build completion #970
• Internal improvements to streamline development #963, #964, #965, #968

Fixes

• Corrections to our documentation #966
• Add project argument to ingestion routes to enable table builds in the same call as ingestion #969

Full Changelog: v3.5.3...v3.11.0

Citrine v3.5.3 is released!

In this release of Citrine Python, we have a few bug fixes to improve our user experience. We've also deprecated the training_data field on our sub-predictors, as those have been required to match the root graph predictor for quite some time. And we've been keeping our dependencies in line, to make sure you all can install and maintain your environment smoothly.

Fixes

• Update to dependencies, eliminating warnings. #961
• Fix reading file links in Windows environments. #950
• Correction to GEM Table creation warning strings. #962

Deprecated

• The training_data field on sub-predictors has been deprecated, as having a data source distinct from the root graph predictor would fail to register. #960

Full Changelog: v3.4.8...v3.5.3

Citrine v3.4.8 is released!

In this release of Citrine Python, we are excited to now support more ratio-type units, such as % and ppm, in our GEMD ingestion. And, per usual, continuous updates to address instabilities and keep you running smoothly!

What's New

• We've updated our gemd-python dependency to now support % and other ratio expressions as units. %, ppm, and other ratios are available here and on our platform. #959

Fixes

• Updated enumerated design spaces to restrict the allowed data value types. #958

Full Changelog: v3.4.6...v3.4.8

Citrine v3.4.6 is released!

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 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 guide in the FAQ section of our documentation or reach our to your Citrine support team. #947, #949, #951, #952, #953, #956

Improvements

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

Fixes

• Fix to our PyPi Deployment #957
• Internal maintenance and fixes #945, #946, #948, #953

Full Changelog: v3.2.11...v3.4.6

Citrine v3.4.4 is released!

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 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 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: v3.2.11...v3.4.4

Citrine v3.2.11 is now released!

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: v3.2.4...v3.2.11

Citrine v3.2.4 is now released!

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: v3.1.0...v3.2.4

Citrine v3.1.0 is now released!

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: v3.0.0...v3.1.0

Citrine v3.0.0 is now released!

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) 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.

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: v2.42.2...v3.0.0

Citrine v2.42.2 is released!

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: v2.42.1...v2.42.2