From a6391c08a36ff036ab82cf4c1ab6e6e4d8c5155c Mon Sep 17 00:00:00 2001 From: sneakers-the-rat Date: Wed, 3 Apr 2024 20:52:33 -0700 Subject: [PATCH] numpy interface and type stub generation --- .gitignore | 3 +- pdm.lock | 1155 +++++++++++++++++++++++- pyproject.toml | 9 +- src/numpydantic/__init__.py | 7 +- src/numpydantic/exceptions.py | 6 + src/numpydantic/interface/__init__.py | 4 + src/numpydantic/interface/dask.py | 0 src/numpydantic/interface/hdf5.py | 0 src/numpydantic/interface/interface.py | 125 +++ src/numpydantic/interface/numpy.py | 45 + src/numpydantic/interface/xarray.py | 0 src/numpydantic/interface/zarr.py | 0 src/numpydantic/meta.py | 39 + src/numpydantic/ndarray.py | 71 +- src/numpydantic/types.py | 28 + tests/test_meta.py | 29 + tests/test_ndarray.py | 6 +- 17 files changed, 1470 insertions(+), 57 deletions(-) create mode 100644 src/numpydantic/exceptions.py create mode 100644 src/numpydantic/interface/__init__.py create mode 100644 src/numpydantic/interface/dask.py create mode 100644 src/numpydantic/interface/hdf5.py create mode 100644 src/numpydantic/interface/interface.py create mode 100644 src/numpydantic/interface/numpy.py create mode 100644 src/numpydantic/interface/xarray.py create mode 100644 src/numpydantic/interface/zarr.py create mode 100644 src/numpydantic/meta.py create mode 100644 src/numpydantic/types.py create mode 100644 tests/test_meta.py diff --git a/.gitignore b/.gitignore index 6769ec3..3b0fc39 100644 --- a/.gitignore +++ b/.gitignore @@ -158,4 +158,5 @@ cython_debug/ # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ -.pdm-python \ No newline at end of file +.pdm-python +ndarray.pyi \ No newline at end of file diff --git a/pdm.lock b/pdm.lock index c398836..69484ac 100644 --- a/pdm.lock +++ b/pdm.lock @@ -2,28 +2,116 @@ # It is not intended for manual editing. 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ignore = [ - "ANN101", "ANN102" + "ANN101", "ANN102", "ANN401", + # builtin type annotations + "UP006", "UP035", + # docstrings for __init__ + "D107", ] fixable = ["ALL"] diff --git a/src/numpydantic/__init__.py b/src/numpydantic/__init__.py index 9abd141..f8fd847 100644 --- a/src/numpydantic/__init__.py +++ b/src/numpydantic/__init__.py @@ -2,10 +2,11 @@ # ruff: noqa: F401 # ruff: noqa: I001 from numpydantic.monkeypatch import apply_patches + apply_patches() from numpydantic.ndarray import NDArray -__all__ = [ - "NDArray" -] \ No newline at end of file +from numpydantic.meta import update_ndarray_stub + +update_ndarray_stub() diff --git a/src/numpydantic/exceptions.py b/src/numpydantic/exceptions.py new file mode 100644 index 0000000..ba195a0 --- /dev/null +++ b/src/numpydantic/exceptions.py @@ -0,0 +1,6 @@ +class DtypeError(TypeError): + """Exception raised for invalid dtypes""" + + +class ShapeError(ValueError): + """Exception raise for invalid shapes""" diff --git a/src/numpydantic/interface/__init__.py b/src/numpydantic/interface/__init__.py new file mode 100644 index 0000000..fce5b1f --- /dev/null +++ b/src/numpydantic/interface/__init__.py @@ -0,0 +1,4 @@ +from numpydantic.interface.interface import Interface +from numpydantic.interface.numpy import NumpyInterface + +__all__ = ["Interface", "NumpyInterface"] diff --git a/src/numpydantic/interface/dask.py b/src/numpydantic/interface/dask.py new file mode 100644 index 0000000..e69de29 diff --git a/src/numpydantic/interface/hdf5.py b/src/numpydantic/interface/hdf5.py new file mode 100644 index 0000000..e69de29 diff --git a/src/numpydantic/interface/interface.py b/src/numpydantic/interface/interface.py new file mode 100644 index 0000000..d7b496d --- /dev/null +++ b/src/numpydantic/interface/interface.py @@ -0,0 +1,125 @@ +from abc import ABC, abstractmethod +from operator import attrgetter +from typing import Any, Generic, List, Type, TypeVar, Tuple + +from nptyping.shape_expression import check_shape + +from numpydantic.exceptions import DtypeError, ShapeError +from numpydantic.types import DtypeType, NDArrayType, ShapeType + +T = TypeVar("T", bound=NDArrayType) + + +class Interface(ABC, Generic[T]): + """ + Abstract parent class for interfaces to different array formats + """ + + return_type: Type[T] + priority: int = 0 + + def __init__(self, shape: ShapeType, dtype: DtypeType) -> None: + self.shape = shape + self.dtype = dtype + + def validate(self, array: Any) -> T: + """ + Validate input, returning final array type + """ + array = self.before_validation(array) + array = self.validate_dtype(array) + array = self.validate_shape(array) + array = self.after_validation(array) + return array + + def before_validation(self, array: Any) -> NDArrayType: + """ + Optional step pre-validation that coerces the input into a type that can be + validated for shape and dtype + + Default method is a no-op + """ + return array + + def validate_dtype(self, array: NDArrayType) -> NDArrayType: + """ + Validate the dtype of the given array, returning it unmutated. + + Raises: + :class:`~numpydantic.exceptions.DtypeError` + """ + if self.dtype is Any: + return array + if not array.dtype == self.dtype: + raise DtypeError(f"Invalid dtype! expected {self.dtype}, got {array.dtype}") + return array + + def validate_shape(self, array: NDArrayType) -> NDArrayType: + """ + Validate the shape of the given array, returning it unmutated + + Raises: + :class:`~numpydantic.exceptions.ShapeError` + """ + if self.shape is Any: + return array + if not check_shape(array.shape, self.shape): + raise ShapeError( + f"Invalid shape! expected shape {self.shape.prepared_args}, got shape {array.shape}" + ) + return array + + def after_validation(self, array: NDArrayType) -> T: + """ + Optional step post-validation that coerces the intermediate array type into the return type + + Default method is a no-op + """ + return array + + @classmethod + @abstractmethod + def check(cls, array: Any) -> bool: + """ + Method to check whether a given input applies to this interface + """ + + @classmethod + @abstractmethod + def enabled(cls) -> bool: + """ + Check whether this array interface can be used (eg. its dependent packages are installed, etc.) + """ + + @classmethod + def interfaces(cls) -> Tuple[Type["Interface"], ...]: + """ + Enabled interface subclasses + """ + return tuple( + sorted( + [i for i in Interface.__subclasses__() if i.enabled()], + key=attrgetter("priority"), + reverse=True, + ) + ) + + @classmethod + def array_types(cls) -> Tuple[NDArrayType, ...]: + """Return types for all enabled interfaces""" + return tuple([i.return_type for i in cls.interfaces()]) + + @classmethod + def match(cls, array: Any) -> Type["Interface"]: + """ + Find the interface that should be used for this array + """ + matches = [i for i in cls.interfaces() if i.check(array)] + if len(matches) > 1: + msg = f"More than one interface matches input {array}:\n" + msg += "\n".join([f" - {i}" for i in matches]) + raise ValueError(msg) + elif len(matches) == 0: + raise ValueError(f"No matching interfaces found for input {array}") + else: + return matches[0] diff --git a/src/numpydantic/interface/numpy.py b/src/numpydantic/interface/numpy.py new file mode 100644 index 0000000..5bea417 --- /dev/null +++ b/src/numpydantic/interface/numpy.py @@ -0,0 +1,45 @@ +from typing import Any + +from numpydantic.interface.interface import Interface + +try: + from numpy import ndarray + + ENABLED = True + +except ImportError: + ENABLED = False + ndarray = None + + +class NumpyInterface(Interface): + """ + Numpy :class:`~numpy.ndarray` s! + """ + + return_type = ndarray + + @classmethod + def check(cls, array: Any) -> bool: + """Check that this is in fact a numpy ndarray or something that can be coerced to one""" + if isinstance(array, ndarray): + return True + else: + try: + _ = ndarray(array) + return True + except TypeError: + return False + + def before_validation(self, array: Any) -> ndarray: + """ + Coerce to an ndarray. We have already checked if coercion is possible in :meth:`.check` + """ + if not isinstance(array, ndarray): + array = ndarray(array) + return array + + @classmethod + def enabled(cls) -> bool: + """Check that numpy is present in the environment""" + return ENABLED diff --git a/src/numpydantic/interface/xarray.py b/src/numpydantic/interface/xarray.py new file mode 100644 index 0000000..e69de29 diff --git a/src/numpydantic/interface/zarr.py b/src/numpydantic/interface/zarr.py new file mode 100644 index 0000000..e69de29 diff --git a/src/numpydantic/meta.py b/src/numpydantic/meta.py new file mode 100644 index 0000000..27e242d --- /dev/null +++ b/src/numpydantic/meta.py @@ -0,0 +1,39 @@ +""" +Metaprogramming functions for numpydantic to modify itself :) +""" + +from pathlib import Path + +from numpydantic.interface import Interface + + +def generate_ndarray_stub() -> str: + """ + Make a stub file based on the array interfaces that are available + """ + + import_strings = [ + f"from {arr.__module__} import {arr.__name__}" + for arr in Interface.array_types() + ] + import_string = "\n".join(import_strings) + + class_names = [arr.__name__ for arr in Interface.array_types()] + class_union = " | ".join(class_names) + ndarray_type = "NDArray = " + class_union + + stub_string = "\n".join([import_string, ndarray_type]) + return stub_string + + +def update_ndarray_stub() -> None: + """ + Update the ndarray.pyi string in the numpydantic file + """ + from numpydantic import ndarray + + stub_string = generate_ndarray_stub() + + pyi_file = Path(ndarray.__file__).with_suffix(".pyi") + with open(pyi_file, "w") as pyi: + pyi.write(stub_string) diff --git a/src/numpydantic/ndarray.py b/src/numpydantic/ndarray.py index 57cc46b..f4d51ee 100644 --- a/src/numpydantic/ndarray.py +++ b/src/numpydantic/ndarray.py @@ -8,14 +8,11 @@ import base64 import sys from collections.abc import Callable from copy import copy -from typing import Any +from typing import Any, Tuple, TypeVar, cast, Union import blosc2 import nptyping.structure import numpy as np - -# TODO: conditional import of dask, remove from required dependencies -from dask.array.core import Array as DaskArray from nptyping import Shape from nptyping.ndarray import NDArrayMeta as _NDArrayMeta from nptyping.nptyping_type import NPTypingType @@ -23,9 +20,11 @@ from nptyping.shape_expression import check_shape from pydantic_core import core_schema from pydantic_core.core_schema import ListSchema +from numpydantic.interface import Interface from numpydantic.maps import np_to_python -from numpydantic.proxy import NDArrayProxy +# from numpydantic.proxy import NDArrayProxy +from numpydantic.types import DtypeType, NDArrayType, ShapeType COMPRESSION_THRESHOLD = 16 * 1024 """ @@ -33,8 +32,6 @@ Arrays larger than this size (in bytes) will be compressed and b64 encoded when serializing to JSON. """ -ARRAY_TYPES = np.ndarray | DaskArray | NDArrayProxy - def list_of_lists_schema(shape: Shape, array_type_handler: dict) -> ListSchema: """Make a pydantic JSON schema for an array as a list of lists.""" @@ -68,7 +65,7 @@ def list_of_lists_schema(shape: Shape, array_type_handler: dict) -> ListSchema: return list_schema -def jsonize_array(array: ARRAY_TYPES) -> list | dict: +def jsonize_array(array: NDArrayType) -> list | dict: """ Render an array to base python types that can be serialized to JSON @@ -80,12 +77,13 @@ def jsonize_array(array: ARRAY_TYPES) -> list | dict: Args: array (:class:`np.ndarray`, :class:`dask.DaskArray`): Array to render as a list! """ - if isinstance(array, DaskArray): - arr = array.__array__() - elif isinstance(array, NDArrayProxy): - arr = array[:] - else: - arr = array + # if isinstance(array, DaskArray): + # arr = array.__array__() + # elif isinstance(array, NDArrayProxy): + # arr = array[:] + # else: + # arr = array + arr = array # If we're larger than 16kB then compress array! if sys.getsizeof(arr) > COMPRESSION_THRESHOLD: @@ -117,21 +115,18 @@ def get_validate_shape(shape: Shape) -> Callable: return validate_shape -def get_validate_dtype(dtype: np.dtype) -> Callable: +def get_validate_interface(shape: ShapeType, dtype: DtypeType) -> Callable: """ - Get a closure around a dtype validation function that includes the dtype definition + Validate using a matching :class:`.Interface` class using its :meth:`.Interface.validate` method """ - def validate_dtype(value: np.ndarray) -> np.ndarray: - if dtype is Any: - return value - - assert ( - value.dtype == dtype - ), f"Invalid dtype! expected {dtype}, got {value.dtype}" + def validate_interface(value: Any, info) -> NDArrayType: + interface_cls = Interface.match(value) + interface = interface_cls(shape, dtype) + value = interface.validate(value) return value - return validate_dtype + return validate_interface def coerce_list(value: Any) -> np.ndarray: @@ -152,6 +147,9 @@ class NDArrayMeta(_NDArrayMeta, implementation="NDArray"): """ +T = TypeVar("T") + + class NDArray(NPTypingType, metaclass=NDArrayMeta): """ Constrained array type allowing npytyping syntax for dtype and shape validation and serialization. @@ -167,7 +165,10 @@ class NDArray(NPTypingType, metaclass=NDArrayMeta): - https://docs.pydantic.dev/latest/usage/types/custom/#handling-third-party-types """ - __args__ = (Any, Any) + def __init__(self: T): + pass + + __args__: Tuple[ShapeType, DtypeType] = (Any, Any) @classmethod def __get_pydantic_core_schema__( @@ -176,6 +177,8 @@ class NDArray(NPTypingType, metaclass=NDArrayMeta): _handler: Callable[[Any], core_schema.CoreSchema], ) -> core_schema.CoreSchema: shape, dtype = _source_type.__args__ + shape: ShapeType + dtype: DtypeType # get pydantic core schema for the given specified type if isinstance(dtype, nptyping.structure.StructureMeta): @@ -195,18 +198,8 @@ class NDArray(NPTypingType, metaclass=NDArrayMeta): python_schema=core_schema.chain_schema( [ core_schema.no_info_plain_validator_function(coerce_list), - core_schema.union_schema( - [ - core_schema.is_instance_schema(cls=np.ndarray), - core_schema.is_instance_schema(cls=DaskArray), - core_schema.is_instance_schema(cls=NDArrayProxy), - ] - ), - core_schema.no_info_plain_validator_function( - get_validate_dtype(dtype) - ), - core_schema.no_info_plain_validator_function( - get_validate_shape(shape) + core_schema.with_info_plain_validator_function( + get_validate_interface(shape, dtype) ), ] ), @@ -214,3 +207,7 @@ class NDArray(NPTypingType, metaclass=NDArrayMeta): jsonize_array, when_used="json" ), ) + + +NDArray = cast(Union[np.ndarray, list[int]], NDArray) +# NDArray = cast(Union[Interface.array_types()], NDArray) diff --git a/src/numpydantic/types.py b/src/numpydantic/types.py new file mode 100644 index 0000000..a54d814 --- /dev/null +++ b/src/numpydantic/types.py @@ -0,0 +1,28 @@ +""" +Types for numpydantic + +Note that these are types as in python typing types, not classes. +""" + +from typing import Any, Protocol, Tuple, TypeVar, Union, runtime_checkable + +import numpy as np +from nptyping import DType + + +ShapeType = Tuple[int, ...] | Any +DtypeType = np.dtype | str | type | Any | DType + + +@runtime_checkable +class NDArrayType(Protocol): + + @property + def dtype(self) -> DtypeType: ... + + @property + def shape(self) -> ShapeType: ... + + def __getitem__(self, key: int | slice) -> "NDArrayType": ... + + def __setitem__(self, key: int | slice, value: "NDArrayType"): ... diff --git a/tests/test_meta.py b/tests/test_meta.py new file mode 100644 index 0000000..6d143bd --- /dev/null +++ b/tests/test_meta.py @@ -0,0 +1,29 @@ +import pytest + +from numpydantic import NDArray + +from typing import reveal_type + + +@pytest.mark.skip("TODO") +def test_generate_stub(): + """ + Test that we generate the stub file correctly... + """ + pass + + +@pytest.mark.skip("TODO") +def test_update_stub(): + """ + Test that the update stub file correctly updates the stub stored in the package + """ + pass + + +@pytest.mark.skip("TODO") +def test_stub_revealed_type(): + """ + Check that the revealed type matches the stub + """ + type = reveal_type(NDArray) diff --git a/tests/test_ndarray.py b/tests/test_ndarray.py index 8baa118..61bbaa5 100644 --- a/tests/test_ndarray.py +++ b/tests/test_ndarray.py @@ -8,7 +8,7 @@ from pydantic import BaseModel, ValidationError, Field from nptyping import Shape, Number from numpydantic import NDArray -from numpydantic.proxy import NDArrayProxy +from numpydantic.exceptions import ShapeError, DtypeError # from .fixtures import tmp_output_dir_func @@ -33,7 +33,7 @@ def test_ndarray_type(): with pytest.raises(ValidationError): instance = Model(array=np.zeros((4, 6))) - with pytest.raises(ValidationError): + with pytest.raises(DtypeError): instance = Model(array=np.ones((2, 3), dtype=bool)) instance = Model(array=np.zeros((2, 3)), array_any=np.ones((3, 4, 5))) @@ -77,7 +77,7 @@ def test_ndarray_coercion(): amod = Model(array=[1, 2, 3, 4.5]) assert np.allclose(amod.array, np.array([1, 2, 3, 4.5])) - with pytest.raises(ValidationError): + with pytest.raises(DtypeError): amod = Model(array=["a", "b", "c"])