Relational-datasets

Software Changes:

- ✨ Bump `datasets` to `v0.0.6`, Add `california_housing` and `roofworld20` https://github.com/srlearn/relational-datasets/pull/28

Documentation Changes:

- ✨ Dataset loading recommendations. All pages under "Dataset descriptions" now have Python and Julia tabs recommending how to load the latest version of each dataset https://github.com/srlearn/relational-datasets/pull/30

CI Changes:

- 🔧 Bump codecov-action to `v3` https://github.com/srlearn/relational-datasets/pull/29
- 🔧 Set `pythonpublish.yml` to use `pypi-publish` https://github.com/srlearn/relational-datasets/pull/31

Software Changes:

- Append the name of the variable to the discrete variable value in `from_numpy`
https://github.com/srlearn/relational-datasets/pull/25

Documentation Changes:

- Add `mkdocstrings-python` dependency https://github.com/srlearn/relational-datasets/pull/27
- Drop `handler` in `docs/api/*` for generating docstrings https://github.com/srlearn/relational-datasets/pull/27
- Update cells by running notebooks https://github.com/srlearn/relational-datasets/pull/26

Software Changes:

- Add multiclass support to `convert.from_numpy`

Documentation:

- Add notebook with overview on converting multiclass vector datasets

Testing:

- Add tests for `convert.from_numpy`

Software Changes:

- Add `drug_interactions` and `toy_machines` datasets
- Add `v0.0.5` as the latest `srlearn/datasets` release

Software Changes:

- Add `convert` module with `from_numpy` implementation to convert binary
classification and regression datasets based on ordinal encodings.
- Fix type annotations in `relational_datasets.request`
- Fix type annotations in `relational_datasets.types`

Documentation:

- Add tutorial for converting vector/propositional datasets to relational
- Add `mkdocs` dependency: `pymdownx.tasklist`
- Add `binder` and `colab` launch badges to Jupyter notebook tutorials

Testing:

- Add `lgtm` build step + README badge
- Add `codecov` build step + README badge
- Add `numpy>=1.20.0` as an optional setup target, and test against it
(this is the earliest version of `numpy` where type annotations for `mypy`
seem to be consistently available)

Pre-Alpha

Software Changes:

- Bump default dataset version: `v0.0.3` → `v0.0.4`.
- Between `v0.0.3` and `v0.0.4` of `srlearn/datasets`, all zipfiles now have the version number appended
(e.g. `toy_cancer_v0.0.4.zip`). Add logic to request the correct filename from GitHub.
- Add `deserialize_zipfile` function, split out code for pulling zipfile content from the `load` method.
- Add private `_make_file_path` function to handle where zipfiles are stored on a user's filesystem.
- Move `RelationalDataset` type into `relational_datasets/types.py`
- Fix `hayesall/relational_datasets` → `srlearn/relational_datasets` in `setup.py`
- Clarify `typing.Optional` in function signatures where default file paths are allowed.
- Add `__version__` to the main `__init__`, so `print(relational_datasets.__version__)` is valid.

Documentation:

- Add `mkdocs` builds with each push to the `main` branch.
- Add `requirements_dev.txt` with requirements to build documentation.
- Add `docs/build._docs.py` to build a *Downloads* page and an overview of each dataset pulled from the `srlearn/datasets` repository.
- Add `docs/notebooks/` directory for literate tutorials
- Add `00_loading_and_fetching.ipynb`
- Pages for functions and types:
- `types.RelationalDataset`
- `request.deserialize_zipfile`
- `request.fetch`
- `request.latest_version`
- `request.load`