Gemd

0.6.0 is released! This release focuses on significant changes to JSON support, which should provide a more intuitive experience to users and a more expressive and extensible experience to developers.

What’s New
* `taurus.json` has been added as a drop-in replacement for python's builtin `json` module. (https://github.com/CitrineInformatics/taurus/pull/86)
* `taurus.json.TaurusJson` has been added to encapsulate the configuration of a taurus-compatible json serializer/deserializer. (https://github.com/CitrineInformatics/taurus/pull/86)
* `TaurusJson` objects have a new `register_classes` method to support the extension of json support to other classes in packages that develop on top of `taurus`. (https://github.com/CitrineInformatics/taurus/pull/86)
* `taurus.util` includes a public `writeable_sort_order` method that accepts either data objects or type strings. (https://github.com/CitrineInformatics/taurus/pull/85)

Improvements
* Output materials are now included when serializing processes. (https://github.com/CitrineInformatics/taurus/pull/87)

Bugfixes
* Measurements are now correctly included when serializing materials. (https://github.com/CitrineInformatics/taurus/pull/84)

Changes
* `taurus.client.json_encoder` has been moved to `taurus.json`. The `taurus.client.json_encoder` is now deprecated and will be removed in `v0.7.0`. (https://github.com/CitrineInformatics/taurus/pull/86)

What’s New
* The cake examples has been extended to demonstrate more of the data model
* The Strehlow and Cook example now imports directly from the Citrination PIF and includes a substantially increased number of attributes

Improvements
* The `flatten` method has been altered so that entire material histories can be flattened. The order of the returned objects is such that they can be created and re-linked in that order.
* The `raw_dumps` and `raw_loads` methods were added to the `json_encoder` to provide access to the custom class encoder/decoder without the normalization/denormalization logic present in the full `dumps` and `loads` methods.

What’s New
* The cake examples has been extended to demonstrate more of the data model
* The Strehlow and Cook example now imports directly from the Citrination PIF and includes a substantially increased number of attributes

What’s New

* As our experience with the data model grows, we are working hard to both improve the tools for interacting with it and pushing its structure forward, making to more representative of the real world information Materials Scientists work with every day. This release represents both improvements in those interfaces as well as fixing some bugs.

Improvements

* The serialization and deserialization as well as the helper functions to interact with and modify GEMD graphs have been improved. This should empower users to get more done in fewer lines of code.
* The data example Cake has been augmented to have complete coverage of the data model. This should help users ground their understanding of Templates, Objects and Values in a practical, relatable resource.

Fixes

* IngredientRuns and IngredientSpecs have been modified so that the logical equivalence of their name and labels fields is easier to have consistent when objects are being created.
* And, of course, all of this is tested and documented

Coming Soon

* More examples. We understand how much easier it is to understand a data model with concrete examples, so we're working hard to develop more and to use those examples in end-to-end demonstrations of how to use our entire data management and machine learning stack.

The largest change with this release is a large increase in the list of supported units. We've also improved documentation, particularly for the installation process in our README.

What's new:

* Augmented unit sets
* Improved documentation of installation, testing and units coverage
* Updated keyword handling for serialization technology
* Augmented test coverage

Coming Soon:

* More types for supporting data provenance

Most of this release is test coverage, which includes some changes to the exception types to better reflect the error that is being raised. This release also includes improvements to the string representation of data objects.

What's new
* 100% test coverage.
* A more intelligent `__repr__` method, which will include the names of soft-linked objects.

Changes
* Some `ValueError` changed to `TypeError` when validating arguments. This better reflects the error mode.

Coming Soon
* More units for real values, e.g. 23