diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json index acd6dfa..0d877c7 100644 --- a/.devcontainer/devcontainer.json +++ b/.devcontainer/devcontainer.json @@ -12,10 +12,12 @@ "vscode": { "extensions": [ "ms-python.black-formatter", + "ms-python.python", "streetsidesoftware.code-spell-checker", "tamasfe.even-better-toml" ], "settings": { + "black-formatter.importStrategy": "fromEnvironment", "python.languageServer": "Pylance", "[python]": { "editor.defaultFormatter": "ms-python.black-formatter", diff --git a/.github/CODE_OF_CONDUCT.md b/.github/CODE_OF_CONDUCT.md new file mode 100644 index 0000000..b8e9dd3 --- /dev/null +++ b/.github/CODE_OF_CONDUCT.md @@ -0,0 +1,128 @@ +# Contributor Covenant Code of Conduct + +## Our Pledge + +We as members, contributors, and leaders pledge to make participation in our +community a harassment-free experience for everyone, regardless of age, body +size, visible or invisible disability, ethnicity, sex characteristics, gender +identity and expression, level of experience, education, socio-economic status, +nationality, personal appearance, race, religion, or sexual identity +and orientation. + +We pledge to act and interact in ways that contribute to an open, welcoming, +diverse, inclusive, and healthy community. + +## Our Standards + +Examples of behavior that contributes to a positive environment for our +community include: + +* Demonstrating empathy and kindness toward other people +* Being respectful of differing opinions, viewpoints, and experiences +* Giving and gracefully accepting constructive feedback +* Accepting responsibility and apologizing to those affected by our mistakes, + and learning from the experience +* Focusing on what is best not just for us as individuals, but for the + overall community + +Examples of unacceptable behavior include: + +* The use of sexualized language or imagery, and sexual attention or + advances of any kind +* Trolling, insulting or derogatory comments, and personal or political attacks +* Public or private harassment +* Publishing others' private information, such as a physical or email + address, without their explicit permission +* Other conduct which could reasonably be considered inappropriate in a + professional setting + +## Enforcement Responsibilities + +Community leaders are responsible for clarifying and enforcing our standards of +acceptable behavior and will take appropriate and fair corrective action in +response to any behavior that they deem inappropriate, threatening, offensive, +or harmful. + +Community leaders have the right and responsibility to remove, edit, or reject +comments, commits, code, wiki edits, issues, and other contributions that are +not aligned to this Code of Conduct, and will communicate reasons for moderation +decisions when appropriate. + +## Scope + +This Code of Conduct applies within all community spaces, and also applies when +an individual is officially representing the community in public spaces. +Examples of representing our community include using an official e-mail address, +posting via an official social media account, or acting as an appointed +representative at an online or offline event. + +## Enforcement + +Instances of abusive, harassing, or otherwise unacceptable behavior may be +reported to the community leaders responsible for enforcement at +a-taniguchi@mail.kitami-it.ac.jp. +All complaints will be reviewed and investigated promptly and fairly. + +All community leaders are obligated to respect the privacy and security of the +reporter of any incident. + +## Enforcement Guidelines + +Community leaders will follow these Community Impact Guidelines in determining +the consequences for any action they deem in violation of this Code of Conduct: + +### 1. Correction + +**Community Impact**: Use of inappropriate language or other behavior deemed +unprofessional or unwelcome in the community. + +**Consequence**: A private, written warning from community leaders, providing +clarity around the nature of the violation and an explanation of why the +behavior was inappropriate. A public apology may be requested. + +### 2. Warning + +**Community Impact**: A violation through a single incident or series +of actions. + +**Consequence**: A warning with consequences for continued behavior. No +interaction with the people involved, including unsolicited interaction with +those enforcing the Code of Conduct, for a specified period of time. This +includes avoiding interactions in community spaces as well as external channels +like social media. Violating these terms may lead to a temporary or +permanent ban. + +### 3. Temporary Ban + +**Community Impact**: A serious violation of community standards, including +sustained inappropriate behavior. + +**Consequence**: A temporary ban from any sort of interaction or public +communication with the community for a specified period of time. No public or +private interaction with the people involved, including unsolicited interaction +with those enforcing the Code of Conduct, is allowed during this period. +Violating these terms may lead to a permanent ban. + +### 4. Permanent Ban + +**Community Impact**: Demonstrating a pattern of violation of community +standards, including sustained inappropriate behavior, harassment of an +individual, or aggression toward or disparagement of classes of individuals. + +**Consequence**: A permanent ban from any sort of public interaction within +the community. + +## Attribution + +This Code of Conduct is adapted from the [Contributor Covenant][homepage], +version 2.0, available at +https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. + +Community Impact Guidelines were inspired by [Mozilla's code of conduct +enforcement ladder](https://github.com/mozilla/diversity). + +[homepage]: https://www.contributor-covenant.org + +For answers to common questions about this code of conduct, see the FAQ at +https://www.contributor-covenant.org/faq. Translations are available at +https://www.contributor-covenant.org/translations. diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml index f930c55..cc91fb9 100644 --- a/.github/workflows/docs.yaml +++ b/.github/workflows/docs.yaml @@ -12,15 +12,14 @@ jobs: container: ghcr.io/astral-sh/uv:python3.12-bookworm env: UV_PROJECT_ENVIRONMENT: /usr/local + permissions: + contents: write steps: - uses: actions/checkout@v4 - - run: echo "::set-output name=tag::${GITHUB_REF##*/}" - id: tag - run: uv sync --frozen - run: docs/build - uses: peaceiris/actions-gh-pages@v4 with: - destination_dir: ${{ steps.tag.outputs.tag }} - force_orphan: true github_token: ${{ secrets.GITHUB_TOKEN }} publish_dir: ./docs/_build + keep_files: true diff --git a/.github/workflows/pypi.yaml b/.github/workflows/pypi.yaml index a4cbd4d..6916855 100644 --- a/.github/workflows/pypi.yaml +++ b/.github/workflows/pypi.yaml @@ -12,7 +12,8 @@ jobs: container: ghcr.io/astral-sh/uv:python3.12-bookworm env: UV_PROJECT_ENVIRONMENT: /usr/local - UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN }} + permissions: + id-token: write steps: - uses: actions/checkout@v4 - run: uv build && uv publish diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml index 4b2020d..53bbc3d 100644 --- a/.github/workflows/tests.yaml +++ b/.github/workflows/tests.yaml @@ -20,14 +20,15 @@ jobs: fail-fast: false matrix: env: - - python3.9-bookworm - python3.10-bookworm - python3.11-bookworm - python3.12-bookworm - python3.13-bookworm + - python3.14-bookworm steps: - uses: actions/checkout@v4 - run: uv sync --frozen - run: black --check ${PYTHON_DIRS} - run: pyright ${PYTHON_DIRS} + - run: pytest -v tests - run: docs/build diff --git a/CITATION.cff b/CITATION.cff index 9cf4b90..eb870bb 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -17,7 +17,7 @@ identifiers: - type: doi value: 10.5281/zenodo.10652375 repository-code: 'https://github.com/astropenguin/xarray-dataclasses' -url: 'https://astropenguin.github.io/xarray-dataclasses/v2.0.0' +url: 'https://astropenguin.github.io/xarray-dataclasses' abstract: xarray data creation by data classes keywords: - python @@ -26,5 +26,5 @@ keywords: - typing - xarray license: MIT -version: 2.0.0 -date-released: '2025-01-01' +version: 1.10.0 +date-released: '2026-02-20' diff --git a/LICENSE b/LICENSE index 43abeed..b9ad274 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ MIT License -Copyright (c) 2020-2025 Akio Taniguchi +Copyright (c) 2020-2026 Akio Taniguchi Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/README.md b/README.md index aad60aa..7e9c7a6 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ [![Python](https://img.shields.io/pypi/pyversions/xarray-dataclasses?label=Python&color=cornflowerblue&style=flat-square)](https://pypi.org/project/xarray-dataclasses/) [![Downloads](https://img.shields.io/pypi/dm/xarray-dataclasses?label=Downloads&color=cornflowerblue&style=flat-square)](https://pepy.tech/project/xarray-dataclasses) [![DOI](https://img.shields.io/badge/DOI-10.5281/zenodo.4624819-cornflowerblue?style=flat-square)](https://doi.org/10.5281/zenodo.4624819) -[![Tests](https://img.shields.io/github/actions/workflow/status/astropenguin/xarray-dataclasses/tests.yml?label=Tests&style=flat-square)](https://github.com/astropenguin/xarray-dataclasses/actions) +[![Tests](https://img.shields.io/github/actions/workflow/status/astropenguin/xarray-dataclasses/tests.yaml?label=Tests&style=flat-square)](https://github.com/astropenguin/xarray-dataclasses/actions) xarray data creation by data classes diff --git a/docs/_static/switcher.json b/docs/_static/switcher.json new file mode 100644 index 0000000..5828c6d --- /dev/null +++ b/docs/_static/switcher.json @@ -0,0 +1,7 @@ +[ + { + "name": "1.10.0 (latest)", + "version": "1.10.0", + "url": "https://astropenguin.github.io/xarray-dataclasses/" + } +] diff --git a/docs/build b/docs/build index 91be5c7..6e68b1b 100755 --- a/docs/build +++ b/docs/build @@ -1,4 +1,8 @@ #!/bin/bash -eu +export LANG=C.UTF-8 +export LC_ALL=C.UTF-8 + sphinx-apidoc -efMT -d 2 -o docs/_apidoc xarray_dataclasses -sphinx-build -a docs docs/_build +sphinx-build -a -b html docs docs/_build +sphinx-build -a -b html docs docs/_build/1.10.0 diff --git a/docs/conf.py b/docs/conf.py index 140fdfd..4189e17 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -1,18 +1,4 @@ -# project information -author = "Akio Taniguchi" -copyright = "2020-2025 Akio Taniguchi" - - -# general configuration -add_module_names = False -autodoc_member_order = "bysource" -autodoc_typehints = "both" -autodoc_typehints_format = "short" -exclude_patterns = [ - "_build", - "Thumbs.db", - ".DS_Store", -] +copyright = "2020-2026 Akio Taniguchi" extensions = [ "myst_parser", "sphinx.ext.autodoc", @@ -20,13 +6,18 @@ "sphinx.ext.napoleon", "sphinx.ext.viewcode", ] -myst_heading_anchors = 3 -templates_path = ["_templates"] - - -# options for HTML output +html_static_path = ["_static"] html_theme = "pydata_sphinx_theme" html_theme_options = { "github_url": "https://github.com/astropenguin/xarray-dataclasses", "logo": {"text": "xarray-dataclasses"}, + "navbar_end": [ + "version-switcher", + "theme-switcher", + "navbar-icon-links", + ], + "switcher": { + "json_url": "https://astropenguin.github.io/xarray-dataclasses/_static/switcher.json", + "version_match": "1.10.0", + }, } diff --git a/pyproject.toml b/pyproject.toml index f590724..66d16e7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,11 +1,21 @@ [project] name = "xarray-dataclasses" -version = "2.0.0" +version = "1.10.0" description = "xarray data creation by data classes" readme = "README.md" -keywords = ["dataclasses", "specifications", "typing", "xarray"] -requires-python = ">=3.9,<3.14" -dependencies = ["dataspecs>=2.0,<3.0", "xarray>=2022.3,<2026.0"] +keywords = [ + "dataclasses", + "specifications", + "python", + "typing", + "xarray", +] +requires-python = ">=3.10,<3.15" +dependencies = [ + "numpy>=2,<3", + "typing-extensions>=4,<5", + "xarray>=2024,<2027", +] classifiers = [ "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 3", @@ -14,28 +24,30 @@ classifiers = [ "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", + "Programming Language :: Python :: 3.14", ] [[project.authors]] name = "Akio Taniguchi" -email = "taniguchi.akio@gmail.com" +email = "a-taniguchi@mail.kitami-it.ac.jp" [project.license] file = "LICENSE" [project.urls] -homepage = "https://astropenguin.github.io/xarray-dataclasses/v2.0.0" +homepage = "https://astropenguin.github.io/xarray-dataclasses" repository = "https://github.com/astropenguin/xarray-dataclasses" [dependency-groups] dev = [ - "black>=24.8", - "ipython>=8.18", - "myst-parser>=3.0", - "pydata-sphinx-theme>=0.16", - "pyright>=1.1", - "pytest>=8.3", - "sphinx>=7.4", + "black>=25,<27", + "ipython>=8,<10", + "myst-parser>=3,<5", + "pandas-stubs>=2,<3", + "pydata-sphinx-theme>=0.16,<1.0", + "pyright>=1,<2", + "pytest>=9,<10", + "sphinx>=8,<9", ] [build-system] diff --git a/tests/__init__.py b/tests/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/tests/test_data.py b/tests/test_data.py new file mode 100644 index 0000000..570907a --- /dev/null +++ b/tests/test_data.py @@ -0,0 +1,70 @@ +# standard library +from dataclasses import dataclass +from typing import Collection, Literal as L, Tuple, Union + +# dependencies +import numpy as np +from typing_extensions import Annotated as Ann +from xarray_dataclasses.typing import Attr, Coord, Coordof, Data + +# type hints +X = L["x"] +Y = L["y"] +T = L["time"] +_ = Tuple[()] + + +# test data +@dataclass +class Longitude: + """Specification of longitude.""" + + data: Data[Tuple[X, Y], float] + units: Attr[str] = "deg" + + +@dataclass +class Latitude: + """Specification of latitude.""" + + data: Data[Tuple[X, Y], float] + units: Attr[str] = "deg" + + +@dataclass +class Weather: + """Weather information.""" + + temp: Ann[Data[Tuple[X, Y, T], float], "Temperature ({.temp_unit})"] + """Measured temperature.""" + + prec: Ann[Data[Tuple[X, Y, T], float], "Precipitation ({.prec_unit})"] + """Measured precipitation.""" + + lon: Union[Ann[Coordof[Longitude], "Longitude"], Collection[float]] + """Longitude of the measured location.""" + + lat: Union[Ann[Coordof[Latitude], "Latitude"], Collection[float]] + """Latitude of the measured location.""" + + time: Coord[T, L["M8[ns]"]] + """Measured time.""" + + reference_time: Union[Coord[_, L["M8[ns]"]], np.datetime64] + """Reference time.""" + + temp_unit: str = "deg C" + """Unit of the temperature.""" + + prec_unit: str = "mm" + """Unit of the precipitation.""" + + +weather = Weather( + 15 + 8 * np.random.randn(2, 2, 3), + 10 * np.random.rand(2, 2, 3), + np.array([[-99.83, -99.32], [-99.79, -99.23]]), + np.array([[42.25, 42.21], [42.63, 42.59]]), + np.array(["2014-09-06", "2014-09-07", "2014-09-08"], "M8[ns]"), # type: ignore + np.datetime64("2014-09-05"), +) diff --git a/tests/test_dataarray.py b/tests/test_dataarray.py new file mode 100644 index 0000000..2d86a8a --- /dev/null +++ b/tests/test_dataarray.py @@ -0,0 +1,80 @@ +# standard library +from dataclasses import dataclass +from typing import Literal, Tuple + +# dependencies +import numpy as np +import xarray as xr + +# submodules +from xarray_dataclasses.dataarray import AsDataArray +from xarray_dataclasses.dataoptions import DataOptions +from xarray_dataclasses.typing import Attr, Coord, Data, Name + +# constants +DIMS = "x", "y" +SHAPE = 10, 10 + + +# type hints +X = Literal["x"] +Y = Literal["y"] + + +# dataclasses +class Custom(xr.DataArray): + """Custom DataArray.""" + + __slots__ = () + + +@dataclass +class Image(AsDataArray): + """2D image as DataArray.""" + + __dataoptions__ = DataOptions(Custom) + + data: Data[Tuple[X, Y], float] + x: Coord[X, int] = 0 + y: Coord[Y, int] = 0 + units: Attr[str] = "cd / m^2" + name: Name[str] = "luminance" + + +# test datasets +created = Image.ones(SHAPE) +expected = Custom( + np.ones(SHAPE, float), + dims=DIMS, + coords={ + "x": xr.DataArray(np.zeros(SHAPE[0]), dims="x"), + "y": xr.DataArray(np.zeros(SHAPE[1]), dims="y"), + }, + attrs={"units": "cd / m^2"}, + name="luminance", +) + + +# test functions +def test_type() -> None: + assert type(created) is type(expected) + + +def test_data() -> None: + assert (created == expected).all() # type: ignore + + +def test_dtype() -> None: + assert created.dtype == expected.dtype # type: ignore + + +def test_dims() -> None: + assert created.dims == expected.dims + + +def test_attrs() -> None: + assert created.attrs == expected.attrs + + +def test_name() -> None: + assert created.name == expected.name diff --git a/tests/test_datamodel.py b/tests/test_datamodel.py new file mode 100644 index 0000000..b5827f1 --- /dev/null +++ b/tests/test_datamodel.py @@ -0,0 +1,146 @@ +# standard library +from dataclasses import dataclass +from typing import Literal, Tuple + +# submodules +from xarray_dataclasses.datamodel import DataModel +from xarray_dataclasses.typing import Attr, Coord, Coordof, Data, Dataof + +# type hints +X = Literal["x"] +Y = Literal["y"] + + +# test datasets +@dataclass +class XAxis: + data: Data[X, int] + units: Attr[str] = "pixel" + + +@dataclass +class YAxis: + data: Data[Y, int] + units: Attr[str] = "pixel" + + +@dataclass +class Image: + data: Data[Tuple[X, Y], float] + mask: Coord[Tuple[X, Y], bool] = False + x: Coordof[XAxis] = 0 + y: Coordof[YAxis] = 0 + + +@dataclass +class ColorImage: + red: Dataof[Image] + green: Dataof[Image] + blue: Dataof[Image] + + +xaxis_model = DataModel.from_dataclass(XAxis) +yaxis_model = DataModel.from_dataclass(YAxis) +image_model = DataModel.from_dataclass(Image) +color_model = DataModel.from_dataclass(ColorImage) + + +# test functions +def test_xaxis_attr() -> None: + units = xaxis_model.attrs[0] + assert units.name == "units" + assert units.tag == "attr" + assert units.type is str + assert units.value == "pixel" + assert units.cast == False + + +def test_xaxis_data() -> None: + data = xaxis_model.data_vars[0] + assert data.name == "data" + assert data.tag == "data" + assert data.dims == ("x",) + assert data.dtype == "int" + assert data.base is None + assert data.cast == True + + +def test_yaxis_attr() -> None: + units = yaxis_model.attrs[0] + assert units.name == "units" + assert units.tag == "attr" + assert units.type is str + assert units.value == "pixel" + assert units.cast == False + + +def test_yaxis_data() -> None: + data = yaxis_model.data_vars[0] + assert data.name == "data" + assert data.tag == "data" + assert data.dims == ("y",) + assert data.dtype == "int" + assert data.base is None + assert data.cast == True + + +def test_image_coord() -> None: + mask = image_model.coords[0] + assert mask.name == "mask" + assert mask.tag == "coord" + assert mask.dims == ("x", "y") + assert mask.dtype == "bool" + assert mask.base is None + assert mask.cast == True + + x = image_model.coords[1] + assert x.name == "x" + assert x.tag == "coord" + assert x.dims == ("x",) + assert x.dtype == "int" + assert x.base is XAxis + assert x.cast == True + + y = image_model.coords[2] + assert y.name == "y" + assert y.tag == "coord" + assert y.dims == ("y",) + assert y.dtype == "int" + assert y.base is YAxis + assert y.cast == True + + +def test_image_data() -> None: + data = image_model.data_vars[0] + assert data.name == "data" + assert data.tag == "data" + assert data.dims == ("x", "y") + assert data.dtype == "float" + assert data.base is None + assert data.cast == True + + +def test_color_data() -> None: + red = color_model.data_vars[0] + assert red.name == "red" + assert red.tag == "data" + assert red.dims == ("x", "y") + assert red.dtype == "float" + assert red.base is Image + assert red.cast == True + + green = color_model.data_vars[1] + assert green.name == "green" + assert green.tag == "data" + assert green.dims == ("x", "y") + assert green.dtype == "float" + assert green.base is Image + assert green.cast == True + + blue = color_model.data_vars[2] + assert blue.name == "blue" + assert blue.tag == "data" + assert blue.dims == ("x", "y") + assert blue.dtype == "float" + assert blue.base is Image + assert blue.cast == True diff --git a/tests/test_dataset.py b/tests/test_dataset.py new file mode 100644 index 0000000..bad490f --- /dev/null +++ b/tests/test_dataset.py @@ -0,0 +1,85 @@ +# standard library +from dataclasses import dataclass +from typing import Literal, Tuple + +# dependencies +import numpy as np +import xarray as xr + +# submodules +from xarray_dataclasses.dataarray import AsDataArray +from xarray_dataclasses.dataset import AsDataset +from xarray_dataclasses.dataoptions import DataOptions +from xarray_dataclasses.typing import Attr, Coord, Data + +# constants +DIMS = "x", "y" +SHAPE = 10, 10 + + +# type hints +X = Literal["x"] +Y = Literal["y"] + + +# dataclasses +class Custom(xr.Dataset): + __slots__ = () + + +@dataclass +class Image(AsDataArray): + """2D image as DataArray.""" + + data: Data[Tuple[X, Y], float] + + +@dataclass +class ColorImage(AsDataset): + """2D color image as Dataset.""" + + __dataoptions__ = DataOptions(Custom) + + red: Data[Tuple[X, Y], float] + green: Data[Tuple[X, Y], float] + blue: Data[Tuple[X, Y], float] + x: Coord[X, int] = 0 + y: Coord[Y, int] = 0 + units: Attr[str] = "cd / m^2" + + +# test datasets +created = ColorImage.new( + Image.ones(SHAPE), + Image.ones(SHAPE), + Image.ones(SHAPE), +) +expected = Custom( + data_vars={ + "red": xr.DataArray(np.ones(SHAPE), dims=DIMS), + "green": xr.DataArray(np.ones(SHAPE), dims=DIMS), + "blue": xr.DataArray(np.ones(SHAPE), dims=DIMS), + }, + coords={ + "x": xr.DataArray(np.zeros(SHAPE[0]), dims="x"), + "y": xr.DataArray(np.zeros(SHAPE[1]), dims="y"), + }, + attrs={"units": "cd / m^2"}, +) + + +# test functions +def test_type() -> None: + assert type(created) is type(expected) + + +def test_data_vars() -> None: + assert (created == expected).all() # type: ignore + + +def test_dims() -> None: + assert created.dims == expected.dims + + +def test_attrs() -> None: + assert created.attrs == expected.attrs diff --git a/tests/test_typing.py b/tests/test_typing.py new file mode 100644 index 0000000..6c5db92 --- /dev/null +++ b/tests/test_typing.py @@ -0,0 +1,108 @@ +# standard library +from typing import Any, Literal as L, Tuple, Union + +# dependencies +import numpy as np +from pytest import mark +from typing_extensions import Annotated as Ann + +# submodules +from xarray_dataclasses.typing import ( + Attr, + Coord, + Data, + Name, + Role, + get_dims, + get_dtype, + get_name, + get_role, +) + +# test datasets +testdata_dims = [ + (Coord[Tuple[()], Any], ()), + (Coord[L["x"], Any], ("x",)), + (Coord[Tuple[L["x"]], Any], ("x",)), + (Coord[Tuple[L["x"], L["y"]], Any], ("x", "y")), + (Data[Tuple[()], Any], ()), + (Data[L["x"], Any], ("x",)), + (Data[Tuple[L["x"]], Any], ("x",)), + (Data[Tuple[L["x"], L["y"]], Any], ("x", "y")), + (Ann[Coord[L["x"], Any], "coord"], ("x",)), + (Ann[Data[L["x"], Any], "data"], ("x",)), + (Union[Ann[Coord[L["x"], Any], "coord"], Ann[Any, "any"]], ("x",)), + (Union[Ann[Data[L["x"], Any], "data"], Ann[Any, "any"]], ("x",)), +] + +testdata_dtype = [ + (Coord[Any, Any], None), + (Coord[Any, None], None), + (Coord[Any, int], np.dtype("i8")), + (Coord[Any, L["i8"]], np.dtype("i8")), + (Data[Any, Any], None), + (Data[Any, None], None), + (Data[Any, int], np.dtype("i8")), + (Data[Any, L["i8"]], np.dtype("i8")), + (Ann[Coord[Any, float], "coord"], np.dtype("f8")), + (Ann[Data[Any, float], "data"], np.dtype("f8")), + (Union[Ann[Coord[Any, float], "coord"], Ann[Any, "any"]], np.dtype("f8")), + (Union[Ann[Data[Any, float], "data"], Ann[Any, "any"]], np.dtype("f8")), +] + +testdata_name = [ + (Attr[Any], None), + (Data[Any, Any], None), + (Coord[Any, Any], None), + (Name[Any], None), + (Any, None), + (Ann[Attr[Any], "attr"], "attr"), + (Ann[Data[Any, Any], "data"], "data"), + (Ann[Coord[Any, Any], "coord"], "coord"), + (Ann[Name[Any], "name"], "name"), + (Ann[Any, "other"], None), + (Union[Ann[Attr[Any], "attr"], Ann[Any, "any"]], "attr"), + (Union[Ann[Data[Any, Any], "data"], Ann[Any, "any"]], "data"), + (Union[Ann[Coord[Any, Any], "coord"], Ann[Any, "any"]], "coord"), + (Union[Ann[Name[Any], "name"], Ann[Any, "any"]], "name"), + (Union[Ann[Any, "other"], Ann[Any, "any"]], None), +] + +testdata_role = [ + (Attr[Any], Role.ATTR), + (Data[Any, Any], Role.DATA), + (Coord[Any, Any], Role.COORD), + (Name[Any], Role.NAME), + (Any, Role.OTHER), + (Ann[Attr[Any], "attr"], Role.ATTR), + (Ann[Data[Any, Any], "data"], Role.DATA), + (Ann[Coord[Any, Any], "coord"], Role.COORD), + (Ann[Name[Any], "name"], Role.NAME), + (Ann[Any, "other"], 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b/xarray_dataclasses/__init__.py index 8c0d5d5..ea6c4ad 100644 --- a/xarray_dataclasses/__init__.py +++ b/xarray_dataclasses/__init__.py @@ -1 +1,33 @@ -__version__ = "2.0.0" +__all__ = [ + "AsDataArray", + "AsDataset", + "DataModel", + "DataOptions", + "Attr", + "Coord", + "Coordof", + "Data", + "Dataof", + "Name", + "asdataarray", + "asdataset", + "dataarray", + "dataset", + "datamodel", + "dataoptions", + "typing", +] +__version__ = "1.10.0" + + +# submodules +from . import dataarray +from . import dataset +from . import datamodel +from . import dataoptions +from . import typing +from .dataarray import * +from .dataset import * +from .datamodel import * +from .dataoptions import * +from .typing import * diff --git a/xarray_dataclasses/dataarray.py b/xarray_dataclasses/dataarray.py new file mode 100644 index 0000000..15a859e --- /dev/null +++ b/xarray_dataclasses/dataarray.py @@ -0,0 +1,353 @@ +"""Submodule for DataArray creation.""" + +__all__ = ["AsDataArray", "asdataarray"] + + +# standard library +from functools import partial +from inspect import signature +from types import MethodType +from typing import Any, Callable, Optional, Protocol, Type, TypeVar, Union, overload + +# dependencies +import numpy as np +import xarray as xr +from typing_extensions import ParamSpec + +# submodules +from .datamodel import DataModel +from .dataoptions import DataOptions +from .typing import AnyArray, AnyXarray, DataClass, Order, Shape, Sizes + +# type hints +PInit = ParamSpec("PInit") +TDataArray = TypeVar("TDataArray", bound=xr.DataArray) + + +class OptionedClass(DataClass[PInit], Protocol[PInit, TDataArray]): + """Type hint for dataclass objects with options.""" + + __dataoptions__: DataOptions[TDataArray] + + +# runtime functions +@overload +def asdataarray( + dataclass: OptionedClass[PInit, TDataArray], + reference: Optional[AnyXarray] = None, + dataoptions: None = None, +) -> TDataArray: ... + + +@overload +def asdataarray( + dataclass: DataClass[PInit], + reference: Optional[AnyXarray] = None, + dataoptions: None = None, +) -> xr.DataArray: ... + + +@overload +def asdataarray( + dataclass: Any, + reference: Optional[AnyXarray] = None, + dataoptions: DataOptions[TDataArray] = DataOptions(xr.DataArray), +) -> TDataArray: ... + + +def asdataarray( + dataclass: Any, + reference: Optional[AnyXarray] = None, + dataoptions: Any = None, +) -> Any: + """Create a DataArray object from a dataclass object. + + Args: + dataclass: Dataclass object that defines typed DataArray. + reference: DataArray or Dataset object as a reference of shape. + dataoptions: Options for DataArray creation. + + Returns: + DataArray object created from the dataclass object. + + """ + if dataoptions is None: + try: + dataoptions = dataclass.__dataoptions__ + except AttributeError: + dataoptions = DataOptions(xr.DataArray) + + model = DataModel.from_dataclass(dataclass) + dataarray = dataoptions.factory(model.data_vars[0](reference)) + + for entry in model.coords: + if entry.name in dataarray.dims: + dataarray.coords[entry.name] = entry(dataarray) + + for entry in model.coords: + if entry.name not in dataarray.dims: + dataarray.coords[entry.name] = entry(dataarray) + + for entry in model.attrs: + dataarray.attrs[entry.name] = entry() + + if model.names: + dataarray.name = model.names[0]() + + return dataarray + + +# runtime classes +class classproperty: + """Class property only for AsDataArray.new(). + + As a classmethod and a property can be chained together since Python 3.9, + this class will be removed when the support for Python 3.7 and 3.8 ends. + + """ + + def __init__(self, func: Any) -> None: + self.__func__ = func + + @overload + def __get__( + self, + obj: Any, + cls: Type[OptionedClass[PInit, TDataArray]], + ) -> Callable[PInit, TDataArray]: ... + + @overload + def __get__( + self, + obj: Any, + cls: Type[DataClass[PInit]], + ) -> Callable[PInit, xr.DataArray]: ... + + def __get__(self, obj: Any, cls: Any) -> Any: + return self.__func__(cls) + + +class AsDataArray: + """Mix-in class that provides shorthand methods.""" + + @classproperty + def new(cls: Any) -> Any: + """Create a DataArray object from dataclass parameters.""" + + sig = signature(cls.__init__) # type: ignore + sig = sig.replace(return_annotation=TDataArray) + + def new(cls: Any, *args: Any, **kwargs: Any) -> Any: + return asdataarray(cls(*args, **kwargs)) + + setattr(new, "__doc__", cls.__init__.__doc__) + setattr(new, "__signature__", sig) + return MethodType(new, cls) + + @overload + @classmethod + def shaped( + cls: Type[OptionedClass[PInit, TDataArray]], + func: Callable[[Shape], AnyArray], + shape: Union[Shape, Sizes], + **kwargs: Any, + ) -> TDataArray: ... + + @overload + @classmethod + def shaped( + cls: Type[DataClass[PInit]], + func: Callable[[Shape], AnyArray], + shape: Union[Shape, Sizes], + **kwargs: Any, + ) -> xr.DataArray: ... + + @classmethod + def shaped( + cls: Any, + func: Callable[[Shape], AnyArray], + shape: Union[Shape, Sizes], + **kwargs: Any, + ) -> Any: + """Create a DataArray object from a shaped function. + + Args: + func: Function to create an array with given shape. + shape: Shape or sizes of the new DataArray object. + kwargs: Args of the DataArray class except for data. + + Returns: + DataArray object created from the shaped function. + + """ + model = DataModel.from_dataclass(cls) + key, entry = model.data_vars_items[0] + + if isinstance(shape, dict): + shape = tuple(shape[dim] for dim in entry.dims) + + return asdataarray(cls(**{key: func(shape)}, **kwargs)) + + @overload + @classmethod + def empty( + cls: Type[OptionedClass[PInit, TDataArray]], + shape: Union[Shape, Sizes], + order: Order = "C", + **kwargs: Any, + ) -> TDataArray: ... + + @overload + @classmethod + def empty( + cls: Type[DataClass[PInit]], + shape: Union[Shape, Sizes], + order: Order = "C", + **kwargs: Any, + ) -> xr.DataArray: ... + + @classmethod + def empty( + cls: Any, + shape: Union[Shape, Sizes], + order: Order = "C", + **kwargs: Any, + ) -> Any: + """Create a DataArray object without initializing data. + + Args: + shape: Shape or sizes of the new DataArray object. + order: Whether to store data in row-major (C-style) + or column-major (Fortran-style) order in memory. + kwargs: Args of the DataArray class except for data. + + Returns: + DataArray object without initializing data. + + """ + func = partial(np.empty, order=order) + return cls.shaped(func, shape, **kwargs) + + @overload + @classmethod + def zeros( + cls: Type[OptionedClass[PInit, TDataArray]], + shape: Union[Shape, Sizes], + order: Order = "C", + **kwargs: Any, + ) -> TDataArray: ... + + @overload + @classmethod + def zeros( + cls: Type[DataClass[PInit]], + shape: Union[Shape, Sizes], + order: Order = "C", + **kwargs: Any, + ) -> xr.DataArray: ... + + @classmethod + def zeros( + cls: Any, + shape: Union[Shape, Sizes], + order: Order = "C", + **kwargs: Any, + ) -> Any: + """Create a DataArray object filled with zeros. + + Args: + shape: Shape or sizes of the new DataArray object. + order: Whether to store data in row-major (C-style) + or column-major (Fortran-style) order in memory. + kwargs: Args of the DataArray class except for data. + + Returns: + DataArray object filled with zeros. + + """ + func = partial(np.zeros, order=order) + return cls.shaped(func, shape, **kwargs) + + @overload + @classmethod + def ones( + cls: Type[OptionedClass[PInit, TDataArray]], + shape: Union[Shape, Sizes], + order: Order = "C", + **kwargs: Any, + ) -> TDataArray: ... + + @overload + @classmethod + def ones( + cls: Type[DataClass[PInit]], + shape: Union[Shape, Sizes], + order: Order = "C", + **kwargs: Any, + ) -> xr.DataArray: ... + + @classmethod + def ones( + cls: Any, + shape: Union[Shape, Sizes], + order: Order = "C", + **kwargs: Any, + ) -> Any: + """Create a DataArray object filled with ones. + + Args: + shape: Shape or sizes of the new DataArray object. + order: Whether to store data in row-major (C-style) + or column-major (Fortran-style) order in memory. + kwargs: Args of the DataArray class except for data. + + Returns: + DataArray object filled with ones. + + """ + func = partial(np.ones, order=order) + return cls.shaped(func, shape, **kwargs) + + @overload + @classmethod + def full( + cls: Type[OptionedClass[PInit, TDataArray]], + shape: Union[Shape, Sizes], + fill_value: Any, + order: Order = "C", + **kwargs: Any, + ) -> TDataArray: ... + + @overload + @classmethod + def full( + cls: Type[DataClass[PInit]], + shape: Union[Shape, Sizes], + fill_value: Any, + order: Order = "C", + **kwargs: Any, + ) -> xr.DataArray: ... + + @classmethod + def full( + cls: Any, + shape: Union[Shape, Sizes], + fill_value: Any, + order: Order = "C", + **kwargs: Any, + ) -> Any: + """Create a DataArray object filled with given value. + + Args: + shape: Shape or sizes of the new DataArray object. + fill_value: Value for the new DataArray object. + order: Whether to store data in row-major (C-style) + or column-major (Fortran-style) order in memory. + kwargs: Args of the DataArray class except for data. + + Returns: + DataArray object filled with given value. + + """ + func = partial(np.full, fill_value=fill_value, order=order) + return cls.shaped(func, shape, **kwargs) diff --git a/xarray_dataclasses/datamodel.py b/xarray_dataclasses/datamodel.py new file mode 100644 index 0000000..3c583f9 --- /dev/null +++ b/xarray_dataclasses/datamodel.py @@ -0,0 +1,291 @@ +"""Submodule for data expression inside the package.""" + +__all__ = ["DataModel"] + + +# standard library +from dataclasses import dataclass, field, is_dataclass +from typing import ( + Any, + Dict, + Hashable, + List, + Literal, + Optional, + Tuple, + Type, + Union, + cast, +) + +# dependencies +import numpy as np +import xarray as xr +from typing_extensions import ParamSpec, get_type_hints + +# submodules +from .typing import ( + AnyDType, + AnyField, + AnyXarray, + DataClass, + Dims, + Role, + get_annotated, + get_dataclass, + get_dims, + get_dtype, + get_name, + get_role, +) + +# type hints +PInit = ParamSpec("PInit") +AnyDataClass = Union[Type[DataClass[PInit]], DataClass[PInit]] +AnyEntry = Union["AttrEntry", "DataEntry"] + + +# runtime classes +class MissingType: + """Singleton that indicates missing data.""" + + _instance = None + + def __new__(cls) -> "MissingType": + if cls._instance is None: + cls._instance = super().__new__(cls) + + return cls._instance + + def __repr__(self) -> str: + return "" + + +MISSING = MissingType() + + +@dataclass(frozen=True) +class AttrEntry: + """Entry of an attribute (i.e. metadata).""" + + name: Hashable + """Name that the attribute is accessed by.""" + + tag: Literal["attr", "name"] + """Function of the attribute (either attr or name).""" + + type: Any = None + """Type or type hint of the attribute.""" + + value: Any = MISSING + """Actual value of the attribute.""" + + cast: bool = False + """Whether the value is cast to the type.""" + + def __call__(self) -> Any: + """Create an object according to the entry.""" + if self.value is MISSING: + raise ValueError("Value is missing.") + + return self.value + + +@dataclass(frozen=True) +class DataEntry: + """Entry of a data variable.""" + + name: Hashable + """Name that the attribute is accessed by.""" + + tag: Literal["coord", "data"] + """Function of the data (either coord or data).""" + + dims: Dims = cast(Dims, None) + """Dimensions of the DataArray that the data is cast to.""" + + dtype: Optional[AnyDType] = None + """Data type of the DataArray that the data is cast to.""" + + base: Optional[Type[DataClass[Any]]] = None + """Base dataclass that converts the data to a DataArray.""" + + value: Any = MISSING + """Actual value of the data.""" + + cast: bool = True + """Whether the value is cast to the data type.""" + + def __post_init__(self) -> None: + """Update the entry if a base dataclass exists.""" + if self.base is None: + return + + model = DataModel.from_dataclass(self.base) + + setattr = object.__setattr__ + setattr(self, "dims", model.data_vars[0].dims) + setattr(self, "dtype", model.data_vars[0].dtype) + + if model.names: + setattr(self, "name", model.names[0].value) + + def __call__(self, reference: Optional[AnyXarray] = None) -> xr.DataArray: + """Create a DataArray object according to the entry.""" + from .dataarray import asdataarray + + if self.value is MISSING: + raise ValueError("Value is missing.") + + if self.base is None: + return get_typedarray(self.value, self.dims, self.dtype, reference) + + if is_dataclass(self.value): + return asdataarray(self.value, reference) + else: + return asdataarray(self.base(self.value), reference) + + +@dataclass(frozen=True) +class DataModel: + """Data representation (data model) inside the package.""" + + entries: Dict[str, AnyEntry] = field(default_factory=dict[str, AnyEntry]) + """Entries of data variable(s) and attribute(s).""" + + @property + def attrs(self) -> List[AttrEntry]: + """Return a list of attribute entries.""" + return [v for v in self.entries.values() if v.tag == "attr"] + + @property + def coords(self) -> List[DataEntry]: + """Return a list of coordinate entries.""" + return [v for v in self.entries.values() if v.tag == "coord"] + + @property + def data_vars(self) -> List[DataEntry]: + """Return a list of data variable entries.""" + return [v for v in self.entries.values() if v.tag == "data"] + + @property + def data_vars_items(self) -> List[Tuple[str, DataEntry]]: + """Return a list of data variable entries with keys.""" + return [(k, v) for k, v in self.entries.items() if v.tag == "data"] + + @property + def names(self) -> List[AttrEntry]: + """Return a list of name entries.""" + return [v for v in self.entries.values() if v.tag == "name"] + + @classmethod + def from_dataclass(cls, dataclass: AnyDataClass[PInit]) -> "DataModel": + """Create a data model from a dataclass or its object.""" + model = cls() + eval_dataclass(dataclass) + + for field in dataclass.__dataclass_fields__.values(): + value = getattr(dataclass, field.name, MISSING) + entry = get_entry(field, value) + + if entry is not None: + model.entries[field.name] = entry + + return model + + +# runtime functions +def eval_dataclass(dataclass: AnyDataClass[PInit]) -> None: + """Evaluate field types of a dataclass.""" + if not is_dataclass(dataclass): + raise TypeError("Not a dataclass or its object.") + + fields = dataclass.__dataclass_fields__.values() + + # do nothing if field types are already evaluated + if not any(isinstance(field.type, str) for field in fields): + return + + # otherwise, replace field types with evaluated types + if not isinstance(dataclass, type): + dataclass = type(dataclass) + + types = get_type_hints(dataclass, include_extras=True) + + for field in fields: + field.type = types[field.name] + + +def get_entry(field: AnyField, value: Any) -> Optional[AnyEntry]: + """Create an entry from a field and its value.""" + role = get_role(field.type) + name = get_name(field.type, field.name) + + if role is Role.ATTR or role is Role.NAME: + return AttrEntry( + name=name, + tag=role.value, + value=value, + type=get_annotated(field.type), + ) + + if role is Role.COORD or role is Role.DATA: + try: + return DataEntry( + name=name, + tag=role.value, + base=get_dataclass(field.type), + value=value, + ) + except TypeError: + return DataEntry( + name=name, + tag=role.value, + dims=get_dims(field.type), + dtype=get_dtype(field.type), + value=value, + ) + + +def get_typedarray( + data: Any, + dims: Dims, + dtype: Optional[AnyDType], + reference: Optional[AnyXarray] = None, +) -> xr.DataArray: + """Create a DataArray object with given dims and dtype. + + Args: + data: Data to be converted to the DataArray object. + dims: Dimensions of the DataArray object. + dtype: Data type of the DataArray object. + reference: DataArray or Dataset object as a reference of shape. + + Returns: + DataArray object with given dims and dtype. + + """ + try: + data.__array__ + except AttributeError: + data = np.asarray(data) + + if dtype is not None: + data = data.astype(dtype, copy=False) + + if data.ndim == len(dims): + dataarray = xr.DataArray(data, dims=dims) + elif data.ndim == 0 and reference is not None: + dataarray = xr.DataArray(data) + else: + raise ValueError( + "Could not create a DataArray object from data. " + f"Mismatch between shape {data.shape} and dims {dims}." + ) + + if reference is None: + return dataarray + else: + ddims = set(reference.dims) - set(dims) + reference = reference.isel({dim: 0 for dim in ddims}) + return dataarray.broadcast_like(reference) diff --git a/xarray_dataclasses/dataoptions.py b/xarray_dataclasses/dataoptions.py new file mode 100644 index 0000000..a8a6f5c --- /dev/null +++ b/xarray_dataclasses/dataoptions.py @@ -0,0 +1,23 @@ +"""Submodule for customization of DataArray or Dataset creation.""" + +__all__ = ["DataOptions"] + + +# standard library +from dataclasses import dataclass +from typing import Callable, Generic, TypeVar + +# submodules +from .typing import AnyXarray + +# type hints +TAnyXarray = TypeVar("TAnyXarray", bound=AnyXarray) + + +# dataclasses +@dataclass(frozen=True) +class DataOptions(Generic[TAnyXarray]): + """Options for DataArray or Dataset creation.""" + + factory: Callable[..., TAnyXarray] + """Factory function for DataArray or Dataset.""" diff --git a/xarray_dataclasses/dataset.py b/xarray_dataclasses/dataset.py new file mode 100644 index 0000000..658ed1d --- /dev/null +++ b/xarray_dataclasses/dataset.py @@ -0,0 +1,354 @@ +"""Submodule for Dataset creation.""" + +__all__ = ["AsDataset", "asdataset"] + + +# standard library +from functools import partial +from inspect import signature +from types import MethodType +from typing import Any, Callable, Dict, Optional, Protocol, Type, TypeVar, overload + +# dependencies +import numpy as np +import xarray as xr +from typing_extensions import ParamSpec + +# submodules +from .datamodel import DataModel +from .dataoptions import DataOptions +from .typing import AnyArray, AnyXarray, DataClass, Order, Shape, Sizes + +# type hints +PInit = ParamSpec("PInit") +TDataset = TypeVar("TDataset", bound=xr.Dataset) + + +class OptionedClass(DataClass[PInit], Protocol[PInit, TDataset]): + """Type hint for dataclass objects with options.""" + + __dataoptions__: DataOptions[TDataset] + + +# runtime functions and classes +@overload +def asdataset( + dataclass: OptionedClass[PInit, TDataset], + reference: Optional[AnyXarray] = None, + dataoptions: None = None, +) -> TDataset: ... + + +@overload +def asdataset( + dataclass: DataClass[PInit], + reference: Optional[AnyXarray] = None, + dataoptions: None = None, +) -> xr.Dataset: ... + + +@overload +def asdataset( + dataclass: Any, + reference: Optional[AnyXarray] = None, + dataoptions: DataOptions[TDataset] = DataOptions(xr.Dataset), +) -> TDataset: ... + + +def asdataset( + dataclass: Any, + reference: Optional[AnyXarray] = None, + dataoptions: Any = None, +) -> Any: + """Create a Dataset object from a dataclass object. + + Args: + dataclass: Dataclass object that defines typed Dataset. + reference: DataArray or Dataset object as a reference of shape. + dataoptions: Options for Dataset creation. + + Returns: + Dataset object created from the dataclass object. + + """ + if dataoptions is None: + try: + dataoptions = dataclass.__dataoptions__ + except AttributeError: + dataoptions = DataOptions(xr.Dataset) + + model = DataModel.from_dataclass(dataclass) + dataset = dataoptions.factory() + + for entry in model.data_vars: + dataset[entry.name] = entry(reference) + + for entry in model.coords: + if entry.name in dataset.dims: + dataset.coords[entry.name] = entry(dataset) + + for entry in model.coords: + if entry.name not in dataset.dims: + dataset.coords[entry.name] = entry(dataset) + + for entry in model.attrs: + dataset.attrs[entry.name] = entry() + + return dataset + + +# runtime classes +class classproperty: + """Class property only for AsDataset.new(). + + As a classmethod and a property can be chained together since Python 3.9, + this class will be removed when the support for Python 3.7 and 3.8 ends. + + """ + + def __init__(self, func: Callable[..., Any]) -> None: + self.__func__ = func + + @overload + def __get__( + self, + obj: Any, + cls: Type[OptionedClass[PInit, TDataset]], + ) -> Callable[PInit, TDataset]: ... + + @overload + def __get__( + self, + obj: Any, + cls: Type[DataClass[PInit]], + ) -> Callable[PInit, xr.Dataset]: ... + + def __get__(self, obj: Any, cls: Any) -> Any: + return self.__func__(cls) + + +class AsDataset: + """Mix-in class that provides shorthand methods.""" + + @classproperty + def new(cls: Any) -> Any: + """Create a Dataset object from dataclass parameters.""" + + sig = signature(cls.__init__) # type: ignore + sig = sig.replace(return_annotation=TDataset) + + def new(cls: Any, *args: Any, **kwargs: Any) -> Any: + return asdataset(cls(*args, **kwargs)) + + setattr(new, "__doc__", cls.__init__.__doc__) + setattr(new, "__signature__", sig) + return MethodType(new, cls) + + @overload + @classmethod + def shaped( + cls: Type[OptionedClass[PInit, TDataset]], + func: Callable[[Shape], AnyArray], + sizes: Sizes, + **kwargs: Any, + ) -> TDataset: ... + + @overload + @classmethod + def shaped( + cls: Type[DataClass[PInit]], + func: Callable[[Shape], AnyArray], + sizes: Sizes, + **kwargs: Any, + ) -> xr.Dataset: ... + + @classmethod + def shaped( + cls: Any, + func: Callable[[Shape], AnyArray], + sizes: Sizes, + **kwargs: Any, + ) -> Any: + """Create a Dataset object from a shaped function. + + Args: + func: Function to create an array with given shape. + sizes: Sizes of the new Dataset object. + kwargs: Args of the Dataset class except for data vars. + + Returns: + Dataset object created from the shaped function. + + """ + model = DataModel.from_dataclass(cls) + data_vars: Dict[str, AnyArray] = {} + + for key, entry in model.data_vars_items: + shape = tuple(sizes[dim] for dim in entry.dims) + data_vars[key] = func(shape) + + return asdataset(cls(**data_vars, **kwargs)) + + @overload + @classmethod + def empty( + cls: Type[OptionedClass[PInit, TDataset]], + sizes: Sizes, + order: Order = "C", + **kwargs: Any, + ) -> TDataset: ... + + @overload + @classmethod + def empty( + cls: Type[DataClass[PInit]], + sizes: Sizes, + order: Order = "C", + **kwargs: Any, + ) -> xr.Dataset: ... + + @classmethod + def empty( + cls: Any, + sizes: Sizes, + order: Order = "C", + **kwargs: Any, + ) -> Any: + """Create a Dataset object without initializing data vars. + + Args: + sizes: Sizes of the new Dataset object. + order: Whether to store data in row-major (C-style) + or column-major (Fortran-style) order in memory. + kwargs: Args of the Dataset class except for data vars. + + Returns: + Dataset object without initializing data vars. + + """ + func = partial(np.empty, order=order) + return cls.shaped(func, sizes, **kwargs) + + @overload + @classmethod + def zeros( + cls: Type[OptionedClass[PInit, TDataset]], + sizes: Sizes, + order: Order = "C", + **kwargs: Any, + ) -> TDataset: ... + + @overload + @classmethod + def zeros( + cls: Type[DataClass[PInit]], + sizes: Sizes, + order: Order = "C", + **kwargs: Any, + ) -> xr.Dataset: ... + + @classmethod + def zeros( + cls: Any, + sizes: Sizes, + order: Order = "C", + **kwargs: Any, + ) -> Any: + """Create a Dataset object whose data vars are filled with zeros. + + Args: + sizes: Sizes of the new Dataset object. + order: Whether to store data in row-major (C-style) + or column-major (Fortran-style) order in memory. + kwargs: Args of the Dataset class except for data vars. + + Returns: + Dataset object whose data vars are filled with zeros. + + """ + func = partial(np.zeros, order=order) + return cls.shaped(func, sizes, **kwargs) + + @overload + @classmethod + def ones( + cls: Type[OptionedClass[PInit, TDataset]], + sizes: Sizes, + order: Order = "C", + **kwargs: Any, + ) -> TDataset: ... + + @overload + @classmethod + def ones( + cls: Type[DataClass[PInit]], + sizes: Sizes, + order: Order = "C", + **kwargs: Any, + ) -> xr.Dataset: ... + + @classmethod + def ones( + cls: Any, + sizes: Sizes, + order: Order = "C", + **kwargs: Any, + ) -> Any: + """Create a Dataset object whose data vars are filled with ones. + + Args: + sizes: Sizes of the new Dataset object. + order: Whether to store data in row-major (C-style) + or column-major (Fortran-style) order in memory. + kwargs: Args of the Dataset class except for data vars. + + Returns: + Dataset object whose data vars are filled with ones. + + """ + func = partial(np.ones, order=order) + return cls.shaped(func, sizes, **kwargs) + + @overload + @classmethod + def full( + cls: Type[OptionedClass[PInit, TDataset]], + sizes: Sizes, + fill_value: Any, + order: Order = "C", + **kwargs: Any, + ) -> TDataset: ... + + @overload + @classmethod + def full( + cls: Type[DataClass[PInit]], + sizes: Sizes, + fill_value: Any, + order: Order = "C", + **kwargs: Any, + ) -> xr.Dataset: ... + + @classmethod + def full( + cls: Any, + sizes: Sizes, + fill_value: Any, + order: Order = "C", + **kwargs: Any, + ) -> Any: + """Create a Dataset object whose data vars are filled with given value. + + Args: + sizes: Sizes of the new Dataset object. + fill_value: Value for data vars of the new Dataset object. + order: Whether to store data in row-major (C-style) + or column-major (Fortran-style) order in memory. + kwargs: Args of the Dataset class except for data vars. + + Returns: + Dataset object whose data vars are filled with given value. + + """ + func = partial(np.full, fill_value=fill_value, order=order) + return cls.shaped(func, sizes, **kwargs) diff --git a/xarray_dataclasses/typing.py b/xarray_dataclasses/typing.py new file mode 100644 index 0000000..bd92d7f --- /dev/null +++ b/xarray_dataclasses/typing.py @@ -0,0 +1,361 @@ +"""Submodule for type hints to define fields of dataclasses. + +Note: + The following code is supposed in the examples below:: + + from dataclasses import dataclass + from typing import Literal + from xarray_dataclasses import AsDataArray, AsDataset + from xarray_dataclasses import Attr, Coord, Data, Name + from xarray_dataclasses import Coordof, Dataof + + + X = Literal["x"] + Y = Literal["y"] + +""" + +__all__ = ["Attr", "Coord", "Coordof", "Data", "Dataof", "Name"] + + +# standard library +from dataclasses import Field, is_dataclass +from enum import Enum +from itertools import chain +from typing import ( + Any, + ClassVar, + Collection, + Dict, + Generic, + Hashable, + Iterable, + Literal, + Optional, + Protocol, + Sequence, + Tuple, + Type, + TypeVar, + Union, +) + +# dependencies +import numpy as np +import xarray as xr +from typing_extensions import ( + Annotated, + ParamSpec, + TypeAlias, + get_args, + get_origin, + get_type_hints, +) + +# type hints (private) +PInit = ParamSpec("PInit") +T = TypeVar("T") +TDataClass = TypeVar("TDataClass", bound="DataClass[Any]") +TDims = TypeVar("TDims", covariant=True) +TDType = TypeVar("TDType", covariant=True) +THashable = TypeVar("THashable", bound=Hashable) + +AnyArray: TypeAlias = "np.ndarray[Any, Any]" +AnyDType: TypeAlias = "np.dtype[Any]" +AnyField: TypeAlias = "Field[Any]" +AnyXarray: TypeAlias = "xr.DataArray | xr.Dataset" +Dims = Tuple[str, ...] +Order = Literal["C", "F"] +Shape = Union[Sequence[int], int] +Sizes = Dict[str, int] + + +class DataClass(Protocol[PInit]): + """Type hint for dataclass objects.""" + + def __init__(self, *args: PInit.args, **kwargs: PInit.kwargs) -> None: ... + + __dataclass_fields__: ClassVar[Dict[str, AnyField]] + + +class Labeled(Generic[TDims]): + """Type hint for labeled objects.""" + + pass + + +# type hints (public) +class Role(Enum): + """Annotations for typing dataclass fields.""" + + ATTR = "attr" + """Annotation for attribute fields.""" + + COORD = "coord" + """Annotation for coordinate fields.""" + + DATA = "data" + """Annotation for data (variable) fields.""" + + NAME = "name" + """Annotation for name fields.""" + + OTHER = "other" + """Annotation for other fields.""" + + @classmethod + def annotates(cls, tp: Any) -> bool: + """Check if any role annotates a type hint.""" + if get_origin(tp) is not Annotated: + return False + + return any(isinstance(arg, cls) for arg in get_args(tp)) + + +Attr = Annotated[T, Role.ATTR] +"""Type hint for attribute fields (``Attr[T]``). + +Example: + :: + + @dataclass + class Image(AsDataArray): + data: Data[tuple[X, Y], float] + long_name: Attr[str] = "luminance" + units: Attr[str] = "cd / m^2" + +Hint: + The following field names are specially treated when plotting. + + - ``long_name`` or ``standard_name``: Coordinate name. + - ``units``: Coordinate units. + +Reference: + https://xarray.pydata.org/en/stable/user-guide/plotting.html + +""" + +Coord = Annotated[Union[Labeled[TDims], Collection[TDType], TDType], Role.COORD] +"""Type hint for coordinate fields (``Coord[TDims, TDType]``). + +Example: + :: + + @dataclass + class Image(AsDataArray): + data: Data[tuple[X, Y], float] + mask: Coord[tuple[X, Y], bool] + x: Coord[X, int] = 0 + y: Coord[Y, int] = 0 + +Hint: + A coordinate field whose name is the same as ``TDims`` + (e.g. ``x: Coord[X, int]``) can define a dimension. + +""" + +Coordof = Annotated[Union[TDataClass, Any], Role.COORD] +"""Type hint for coordinate fields (``Coordof[TDataClass]``). + +Unlike ``Coord``, it specifies a dataclass that defines a DataArray class. +This is useful when users want to add metadata to dimensions for plotting. + +Example: + :: + + @dataclass + class XAxis: + data: Data[X, int] + long_name: Attr[str] = "x axis" + + + @dataclass + class YAxis: + data: Data[Y, int] + long_name: Attr[str] = "y axis" + + + @dataclass + class Image(AsDataArray): + data: Data[tuple[X, Y], float] + x: Coordof[XAxis] = 0 + y: Coordof[YAxis] = 0 + +Hint: + A class used in ``Coordof`` does not need to inherit ``AsDataArray``. + +""" + +Data = Annotated[Union[Labeled[TDims], Collection[TDType], TDType], Role.DATA] +"""Type hint for data fields (``Coordof[TDims, TDType]``). + +Example: + Exactly one data field is allowed in a DataArray class + (the second and subsequent data fields are just ignored):: + + @dataclass + class Image(AsDataArray): + data: Data[tuple[X, Y], float] + + Multiple data fields are allowed in a Dataset class:: + + @dataclass + class ColorImage(AsDataset): + red: Data[tuple[X, Y], float] + green: Data[tuple[X, Y], float] + blue: Data[tuple[X, Y], float] + +""" + +Dataof = Annotated[Union[TDataClass, Any], Role.DATA] +"""Type hint for data fields (``Coordof[TDataClass]``). + +Unlike ``Data``, it specifies a dataclass that defines a DataArray class. +This is useful when users want to reuse a dataclass in a Dataset class. + +Example: + :: + + @dataclass + class Image: + data: Data[tuple[X, Y], float] + x: Coord[X, int] = 0 + y: Coord[Y, int] = 0 + + + @dataclass + class ColorImage(AsDataset): + red: Dataof[Image] + green: Dataof[Image] + blue: Dataof[Image] + +Hint: + A class used in ``Dataof`` does not need to inherit ``AsDataArray``. + +""" + +Name = Annotated[THashable, Role.NAME] +"""Type hint for name fields (``Name[THashable]``). + +Example: + :: + + @dataclass + class Image(AsDataArray): + data: Data[tuple[X, Y], float] + name: Name[str] = "image" + +""" + + +# runtime functions +def deannotate(tp: Any) -> Any: + """Recursively remove annotations in a type hint.""" + + class Temporary: + __annotations__ = dict(type=tp) + + return get_type_hints(Temporary)["type"] + + +def find_annotated(tp: Any) -> Iterable[Any]: + """Generate all annotated types in a type hint.""" + args = get_args(tp) + + if get_origin(tp) is Annotated: + yield tp + yield from find_annotated(args[0]) + else: + yield from chain(*map(find_annotated, args)) + + +def get_annotated(tp: Any) -> Any: + """Extract the first role-annotated type.""" + for annotated in filter(Role.annotates, find_annotated(tp)): + return deannotate(annotated) + + raise TypeError("Could not find any role-annotated type.") + + +def get_annotations(tp: Any) -> Tuple[Any, ...]: + """Extract annotations of the first role-annotated type.""" + for annotated in filter(Role.annotates, find_annotated(tp)): + return get_args(annotated)[1:] + + raise TypeError("Could not find any role-annotated type.") + + +def get_dataclass(tp: Any) -> Type[DataClass[Any]]: + """Extract a dataclass.""" + try: + dataclass = get_args(get_annotated(tp))[0] + except TypeError: + raise TypeError(f"Could not find any dataclass in {tp!r}.") + + if not is_dataclass(dataclass): + raise TypeError(f"Could not find any dataclass in {tp!r}.") + + return dataclass # type: ignore + + +def get_dims(tp: Any) -> Dims: + """Extract data dimensions (dims).""" + try: + dims = get_args(get_args(get_annotated(tp))[0])[0] + except TypeError: + raise TypeError(f"Could not find any dims in {tp!r}.") + + args = get_args(dims) + origin = get_origin(dims) + + if origin is Literal: + return (str(args[0]),) + + if not (origin is tuple or origin is Tuple): + raise TypeError(f"Could not find any dims in {tp!r}.") + + if args == () or args == ((),): + return () + + if not all(get_origin(arg) is Literal for arg in args): + raise TypeError(f"Could not find any dims in {tp!r}.") + + return tuple(str(get_args(arg)[0]) for arg in args) + + +def get_dtype(tp: Any) -> Optional[AnyDType]: + """Extract a NumPy data type (dtype).""" + try: + dtype = get_args(get_args(get_annotated(tp))[1])[0] + except TypeError: + raise TypeError(f"Could not find any dtype in {tp!r}.") + + if dtype is Any or dtype is type(None): + return + + if get_origin(dtype) is Literal: + dtype = get_args(dtype)[0] + + return np.dtype(dtype) # type: ignore + + +def get_name(tp: Any, default: Hashable = None) -> Hashable: + """Extract a name if found or return given default.""" + try: + annotations = get_annotations(tp)[1:] + except TypeError: + return default + + for annotation in annotations: + if isinstance(annotation, Hashable): + return annotation + + return default + + +def get_role(tp: Any, default: Role = Role.OTHER) -> Role: + """Extract a role if found or return given default.""" + try: + return get_annotations(tp)[0] + except TypeError: + return default