Pyqalloy

Latest version: v0.3.9

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0.3.9

Minor Changes:
- Mitigate `pymatgen`'s incompatibility with `numpy>=2` by setting the maximum version.
- Minor updates to the testing routines and versions of Actions.
- `README` updates.

**Full Changelog**: https://github.com/PhasesResearchLab/PyQAlloy/compare/v0.3.7...v0.3.9

0.3.7

Major Changes:
- Added MontyDB to the dependencies and semi-officially started supporting it for all implemented methods so far. However, it is important to point out that not all future methods ported from the ULTERA project will work.
- Added tutorial `CustomDatasetFromBSON.ipynb` showing how to utilize a custom BSON snapshot of a database in-memory; for instance, based on a snapshot we provide in `devTools`.
- Added tests for the custom collection override methods.

Minor Changes:
- `README` improved all around and in the `Install` section in particular.

**Full Changelog**: https://github.com/PhasesResearchLab/PyQAlloy/compare/v0.3.6...v0.3.7

0.3.6

Major Changes:
- Added a subset of ULTERA Database (300 entries) in bf8bf50fbda0ecdb842bad7ff048d258a0391596 for PyQAlloy users to play with. You can insert them quickly into your initialized MongoDB `collection` with a simple:
python
with open('../ULTERA_sample.bson', 'rb+') as f:
collection.insert_many(bson.decode_all(f.read()))

and it should also work well with in-memory databases like MontyDB, as shown in [`dev/jDummyDatabaseInMemory.ipynb`](https://github.com/PhasesResearchLab/PyQAlloy/blob/main/dev/jDummyDatabaseInMemory.ipynb)

- Added ability to manually specify an already initialized MongoDB-like collection in `collectionManualOverride` for any Analyzer. As of now, all methods should work, but in the future, some functionalities may be limited because, for instance, MongoDB aggregation may be irreplaceable.

- Reimplemented `Analyzer`'s `get_allDOIs` function to use (slower) `find` instead of `aggregate` if `collectionManualOverride` is declared, as most users override with Mongo-like tools with limited capabilities.

- Dropped testing on Windows (temporarily) as there seems to be an issue that causes tests to time out when outputting excel spreadsheets, and it appears to be related to GitHub runners rather than code.

- Added Apple M1 Macs to the testing matrix, and everything seems to run smoothly.

Minor Changes:
- Typo fixes and style improvements in the documentation.
- Codebase style improvements.

**Full Changelog**: https://github.com/PhasesResearchLab/PyQAlloy/compare/v0.3.5...v0.3.6

0.3.5

Major Changes:
- PyPI release
- Official support for Python 3.11
- Automated testing in GitHub CLI on every code change; run across all 9 Windows/Mac/Linux and Python 3.9/3.10/3.11 combinations
- Automated test coverage analysis; reported to Codecov service

Minor Changes:
- Documentation imporvements
- Minor bug fixes

**Full Changelog**: https://github.com/PhasesResearchLab/PyQAlloy/compare/v0.3.4...v0.3.5

0.3.4

Minor Updates:
- Added configuration for ReadTheDocs and published it.
- Added autogenerating changelog to the ReadTheDocs.

**Full Changelog**: https://github.com/PhasesResearchLab/PyQAlloy/compare/v0.3.3...v0.3.4

0.3.3

Changes Breaking Backward-Compatibility:
- Changed the **submodules naming scheme** to be cleaner and more intuitive, e.g. _curation.analysis_ and _core.pyqalloy_. In the future, the _core_ will primarily serve user-facing features and GUI, while others will be specialized. The _curation_ will also include things like property and structure name unifiers from the ULTERA project (but user-definable). The future _database_ will include functions handling and setting up a MongoDB (or a substitute) database.

Minor Changes:
- Optimized requirements.

**Full Changelog**: https://github.com/PhasesResearchLab/PyQAlloy/compare/v0.3.1...v0.3.3

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