diff --git a/.github/actions/install_package/action.yml b/.github/actions/install_package/action.yml index 30ab638..2e63751 100644 --- a/.github/actions/install_package/action.yml +++ b/.github/actions/install_package/action.yml @@ -26,5 +26,5 @@ runs: - name: Install Dependencies shell: bash run: | - uv sync + uv sync --refresh echo "python-version=${{ steps.setup_python.outputs.python-version }}" >> "$GITHUB_OUTPUT" diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index a75af93..dd59cdf 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,6 +1,6 @@ repos: - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v5.0.0 + rev: v6.0.0 hooks: - id: check-yaml - id: end-of-file-fixer @@ -10,14 +10,14 @@ repos: - repo: https://github.com/astral-sh/uv-pre-commit # uv version. - rev: "0.5.27" + rev: "0.9.18" hooks: # Update the uv lockfile - id: uv-lock - repo: https://github.com/astral-sh/ruff-pre-commit # Ruff version. - rev: v0.9.4 + rev: v0.14.10 hooks: # Run the linter. - id: ruff @@ -26,7 +26,13 @@ repos: - id: ruff-format - repo: https://github.com/pycqa/flake8 - rev: 7.1.1 # pick a git hash / tag to point to + rev: 7.3.0 # pick a git hash / tag to point to hooks: - id: flake8 args: ["--config=.flake8"] + + - repo: https://github.com/commitizen-tools/commitizen + rev: v4.9.1 + hooks: + - id: commitizen + stages: [commit-msg] diff --git a/CHANGELOG.md b/CHANGELOG.md index 144e2cf..55cc192 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,3 +1,14 @@ +## v0.2.12 (2025-12-24) + +### Fix + +- **numpy**: handle percentile/quantile API changes + +### Refactor + +- **ufuncs**: streamline matmul implementation and update NODE_SHELF +- **trapz**: rename function to trapezoid and update implementation to use numpy.trapezoid conditionally + ## v0.2.11 (2025-07-09) ### Refactor diff --git a/cz.toml b/cz.toml new file mode 100644 index 0000000..e1d8a7b --- /dev/null +++ b/cz.toml @@ -0,0 +1,6 @@ +[tool.commitizen] +name = "cz_conventional_commits" +tag_format = "$version" +version_scheme = "pep440" +version_provider = "uv" +update_changelog_on_bump = true diff --git a/pyproject.toml b/pyproject.toml index fd71b6f..901eaf2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,21 +1,21 @@ [project] name = "funcnodes-numpy" -version = "0.2.11" +version = "0.2.12" description = "implementations of numpy for funcnodes" readme = "README.md" classifiers = [ "License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)",] -dependencies = [ "funcnodes", "numpy",] +dependencies = [ "funcnodes>=1.2", "funcnodes-core>=2.3.1", "numpy",] requires-python = ">=3.11" [[project.authors]] name = "Julian Kimmig" email = "julian.kimmig@gmx.net" [dependency-groups] -dev = [ "pytest", "pre-commit", "funcnodes-module>=0.2.8",] +dev = [ "pytest", "pre-commit", "funcnodes-module>=0.2.8", "pytest-funcnodes>=1.1.0",] [build-system] -requires = [ "setuptools>=42",] -build-backend = "setuptools.build_meta" +requires = [ "hatchling",] +build-backend = "hatchling.build" [project.license] text = "AGPL-3.0" @@ -26,19 +26,22 @@ source = "https://github.com/Linkdlab/funcnodes_numpy" tracker = "https://github.com/Linkdlab/funcnodes_numpy/issues" download = "https://pypi.org/project/funcnodes-numpy/#files" -[tool.setuptools.package-dir] -"" = "src" - - [tool.commitizen] name = "cz_conventional_commits" tag_format = "v$version" version_scheme = "pep440" version_provider = "uv" update_changelog_on_bump = true + [project.entry-points."funcnodes.module"] module = "funcnodes_numpy" shelf = "funcnodes_numpy:NODE_SHELF" +[tool.setuptools.package-dir] +"" = "src" + [tool.setuptools.packages.find] where = [ "src",] + +[tool.hatch.build.targets.wheel] +packages = [ "src/funcnodes_numpy",] diff --git a/src/funcnodes_numpy/_core/__init__.py b/src/funcnodes_numpy/_core/__init__.py index 775cea2..592bdbb 100644 --- a/src/funcnodes_numpy/_core/__init__.py +++ b/src/funcnodes_numpy/_core/__init__.py @@ -24,6 +24,7 @@ from ._defchararray import * # noqa from ._datetime import * # noqa from .ufuncs import * # noqa +from .._version import np_version @fn.NodeDecorator( @@ -913,7 +914,7 @@ def reshape( ): # params ['a', 'newshape'] ['order'] [] res = numpy.reshape( a, - newshape=newshape, + newshape, # order=order, ) return res @@ -1960,37 +1961,6 @@ def outer( return res -@fn.NodeDecorator( - node_id="np.matmul", - name="matmul", - outputs=[{"name": "y", "type": "ndarray"}], -) -@wraps(numpy.matmul, wrapper_attribute="__fnwrapped__") -def matmul( - x1: array_like, - x2: array_like, - # out: Optional[ndarray] = None, - # casting: casting_literal = "same_kind", - # order: OrderKACF = "K", - dtype: Optional[DTYPE_ENUM] = None, - # subok: bool = True, - # signature: Any = None, - # extobj: Any = None, -): # params ['x1', 'x2'] ['out', 'casting', 'order'] [] - res = numpy.matmul( - x1, - x2, - # out=out, - # casting=casting, - # order=order, - dtype=dtype_from_name(dtype), - # subok=subok, - # signature=signature, - # extobj=extobj, - ) - return res - - @fn.NodeDecorator( node_id="np.tensordot", name="tensordot", @@ -2692,19 +2662,22 @@ def cross( return res +_trapz = numpy.trapezoid if np_version["major_int"] >= 2 else numpy.trapz + + @fn.NodeDecorator( node_id="np.trapz", - name="trapz", + name="trapezoid", outputs=[{"name": "trapz", "type": "ndarray_or_scalar"}], ) -@wraps(numpy.trapz, wrapper_attribute="__fnwrapped__") +@wraps(_trapz, wrapper_attribute="__fnwrapped__") def trapz( y: array_like, x: Optional[array_like] = None, dx: Optional[scalar] = 1.0, axis: Optional[int] = -1, ): # params ['y'] ['x', 'dx', 'axis'] [] - res = numpy.trapz( + res = _trapz( y=y, x=x, dx=dx, @@ -3030,6 +3003,36 @@ def ptp( return res +if ( + np_version["major_int"] <= 1 and np_version["minor_int"] < 22 +): # smaller than numpy 1.22 + _ST_122 = True + percentile_methods = Literal[ + "linear", + "lower", + "higher", + "midpoint", + "nearest", + ] +else: + _ST_122 = False + percentile_methods = Literal[ + "inverted_cdf", + "averaged_inverted_cdf", + "closest_observation", + "interpolated_inverted_cdf", + "hazen", + "weibull", + "linear", + "median_unbiased", + "normal_unbiased", + "lower", + "higher", + "midpoint", + "nearest", + ] + + @fn.NodeDecorator( node_id="np.percentile", name="percentile", @@ -3042,20 +3045,29 @@ def percentile( axis: Optional[axis_like] = None, # out: Optional[ndarray] = None, overwrite_input: Optional[bool] = False, - method: Optional[str] = "linear", + method: percentile_methods = "linear", keepdims: Optional[bool] = False, - interpolation: Optional[str] = None, ): # params ['a', 'q'] ['axis', 'out'] [] - res = numpy.percentile( - a=a, - q=q, - axis=axis, - # out=out, - overwrite_input=overwrite_input, - method=method, - keepdims=keepdims, - interpolation=interpolation, - ) + if _ST_122: + res = numpy.percentile( + a=a, + q=q, + axis=axis, + # out=out, + overwrite_input=overwrite_input, + interpolation=method, + keepdims=keepdims, + ) + else: + res = numpy.percentile( + a=a, + q=q, + axis=axis, + # out=out, + overwrite_input=overwrite_input, + method=method, + keepdims=keepdims, + ) return res @@ -3071,20 +3083,29 @@ def nanpercentile( axis: Optional[axis_like] = None, # out: Optional[ndarray] = None, overwrite_input: Optional[bool] = False, - method: Optional[str] = "linear", + method: percentile_methods = "linear", keepdims: Optional[bool] = NoValue, - interpolation: Optional[str] = None, ): # params ['a', 'q'] ['axis', 'out'] [] - res = numpy.nanpercentile( - a=a, - q=q, - axis=axis, - # out=out, - overwrite_input=overwrite_input, - method=method, - keepdims=keepdims, - interpolation=interpolation, - ) + if _ST_122: + res = numpy.nanpercentile( + a=a, + q=q, + axis=axis, + # out=out, + overwrite_input=overwrite_input, + interpolation=method, + keepdims=keepdims, + ) + else: + res = numpy.nanpercentile( + a=a, + q=q, + axis=axis, + # out=out, + overwrite_input=overwrite_input, + method=method, + keepdims=keepdims, + ) return res @@ -3100,20 +3121,29 @@ def quantile( axis: Optional[axis_like] = None, # out: Optional[ndarray] = None, overwrite_input: Optional[bool] = False, - method: Optional[str] = "linear", + method: percentile_methods = "linear", keepdims: Optional[bool] = False, - interpolation: Optional[str] = None, ): # params ['a', 'q'] ['axis', 'out', 'overwrite_input'] [] - res = numpy.quantile( - a=a, - q=q, - axis=axis, - # out=out, - overwrite_input=overwrite_input, - method=method, - keepdims=keepdims, - interpolation=interpolation, - ) + if _ST_122: + res = numpy.quantile( + a=a, + q=q, + axis=axis, + # out=out, + overwrite_input=overwrite_input, + interpolation=method, + keepdims=keepdims, + ) + else: + res = numpy.quantile( + a=a, + q=q, + axis=axis, + # out=out, + overwrite_input=overwrite_input, + method=method, + keepdims=keepdims, + ) return res @@ -3129,20 +3159,30 @@ def nanquantile( axis: Optional[axis_like] = None, # out: Optional[ndarray] = None, overwrite_input: Optional[bool] = False, - method: Optional[str] = "linear", + method: percentile_methods = "linear", keepdims: Optional[bool] = NoValue, - interpolation: Optional[str] = None, ): # params ['a', 'q'] ['axis', 'out'] [] - res = numpy.nanquantile( - a=a, - q=q, - axis=axis, - # out=out, - overwrite_input=overwrite_input, - method=method, - keepdims=keepdims, - interpolation=interpolation, - ) + if _ST_122: + res = numpy.nanquantile( + a=a, + q=q, + axis=axis, + # out=out, + overwrite_input=overwrite_input, + interpolation=method, + keepdims=keepdims, + ) + + else: + res = numpy.nanquantile( + a=a, + q=q, + axis=axis, + # out=out, + overwrite_input=overwrite_input, + method=method, + keepdims=keepdims, + ) return res diff --git a/src/funcnodes_numpy/_core/ufuncs.py b/src/funcnodes_numpy/_core/ufuncs.py index 7759b0c..a3ffa6d 100644 --- a/src/funcnodes_numpy/_core/ufuncs.py +++ b/src/funcnodes_numpy/_core/ufuncs.py @@ -1993,6 +1993,37 @@ def logical_xor( return res +@fn.NodeDecorator( + node_id="np.matmul", + name="matmul", + outputs=[{"name": "y", "type": "ndarray"}], +) +@wraps(numpy.matmul, wrapper_attribute="__fnwrapped__") +def matmul( + x1: array_like, + x2: array_like, + # out: Optional[ndarray] = None, + # casting: casting_literal = "same_kind", + # order: OrderKACF = "K", + dtype: Optional[DTYPE_ENUM] = None, + # subok: bool = True, + # signature: Any = None, + # extobj: Any = None, +): # params ['x1', 'x2'] ['out', 'casting', 'order'] [] + res = numpy.matmul( + x1, + x2, + # out=out, + # casting=casting, + # order=order, + dtype=dtype_from_name(dtype), + # subok=subok, + # signature=signature, + # extobj=extobj, + ) + return res + + @fn.NodeDecorator( node_id="np.maximum", name="maximum", @@ -3073,6 +3104,7 @@ def vecmat( logical_or, logical_xor, maximum, + matmul, minimum, mod, modf, diff --git a/src/funcnodes_numpy/_ndarray.py b/src/funcnodes_numpy/_ndarray.py index 6a5fb68..6629f21 100644 --- a/src/funcnodes_numpy/_ndarray.py +++ b/src/funcnodes_numpy/_ndarray.py @@ -321,12 +321,14 @@ def item( name="itemset", outputs=[{"name": "out", "type": "ndarray"}], ) -@wraps(numpy.ndarray.itemset, wrapper_attribute="__fnwrapped__") def itemset( a: ndarray, pos: axis_like, value: float, ): + """ + insert scalar into an array (scalar is cast to array's dtype, if possible) + """ arr = numpy.atleast_1d(a).copy() arr = numpy.array(a) arr[pos] = value @@ -382,11 +384,11 @@ def min( name="newbyteorder", outputs=[{"name": "out", "type": "ndarray"}], ) -@wraps(numpy.ndarray.newbyteorder, wrapper_attribute="__fnwrapped__") def newbyteorder( a: ndarray, new_order: Literal["S", "<", ">", "=", "|"] = "S", ): + """new byte order of an array""" return a.view(a.dtype.newbyteorder(new_order)).copy() @@ -648,6 +650,7 @@ def tolist( res = a.tolist() return res + @fn.NodeDecorator( node_id="np.a.trace", name="trace", diff --git a/tests/all_nodes_test_base.py b/tests/all_nodes_test_base.py deleted file mode 100644 index b34115d..0000000 --- a/tests/all_nodes_test_base.py +++ /dev/null @@ -1,171 +0,0 @@ -# this is an autogenerated file, do not edit it directly or your changes might be lost. -import unittest -from funcnodes_numpy import NODE_SHELF # noqa -from functools import wraps -from typing import List -import funcnodes as fn -import asyncio - - -def passfunc(self, *args, **kwargs): - pass - - -async def async_passfunc(self, *args, **kwargs): - pass - - -def add_subclass_tests(cls): - # Dynamically add test methods from sub_test_classes - if not hasattr(cls, "sub_test_classes"): - return - for testcase in cls.sub_test_classes: - if hasattr(testcase, "setUp"): - inner_setup = testcase.setUp - else: - inner_setup = passfunc - - if hasattr(testcase, "asyncSetUp"): - inner_async_setup = testcase.asyncSetUp - else: - inner_async_setup = async_passfunc - - if hasattr(testcase, "tearDown"): - inner_teardown = testcase.tearDown - else: - inner_teardown = passfunc - - if hasattr(testcase, "asyncTearDown"): - inner_async_teardown = testcase.asyncTearDown - else: - inner_async_teardown = async_passfunc - - for attr_name in dir(testcase): - if attr_name.startswith("test_"): - # Retrieve the test method from the subclass - test_method = getattr(testcase, attr_name) - - # Create a new test method that wraps the original test method - def make_new_test_method( - test_method=test_method, - inner_setup=inner_setup, - inner_teardown=inner_teardown, - inner_async_setup=inner_async_setup, - inner_async_teardown=inner_async_teardown, - ): - if asyncio.iscoroutinefunction(test_method): - - async def test_method_wrapper(self, *args, **kwargs): - # Call the inner setup method - inner_setup(self) - await inner_async_setup(self) - # Call the test method - await test_method(self, *args, **kwargs) - print(f"Test {test_method.__name__} passed") - # Call the inner teardown method - inner_teardown(self) - await inner_async_teardown(self) - - else: - - def test_method_wrapper(self, *args, **kwargs): - # Call the inner setup method - inner_setup(self) - # Call the test method - test_method(self, *args, **kwargs) - print(f"Test {test_method.__name__} passed") - # Call the inner teardown method - inner_teardown(self) - - return test_method_wrapper - - # Create a unique name for the test method in this class - new_test_name = f"test_{testcase.__name__}_{attr_name}" - # Add the test method to this class - setattr( - cls, - new_test_name, - make_new_test_method( - test_method=test_method, - inner_setup=inner_setup, - inner_teardown=inner_teardown, - inner_async_setup=inner_async_setup, - inner_async_teardown=inner_async_teardown, - ), - ) - - -class TestAllNodesBase(unittest.IsolatedAsyncioTestCase): - # if you tests your nodes with in other test classes, add them here - # this will automtically extend this test class with the tests in the other test classes - # but this will also mean if you run all tests these tests might run multiple times - # also the correspondinig setups and teardowns will not be called, so the tests should be - # independently callable - sub_test_classes: List[unittest.IsolatedAsyncioTestCase] = [] - - # if you have specific nodes you dont want to test, add them here - # But why would you do that, it will ruin the coverage?! - # a specific use case would be ignore nodes that e.g. load a lot of data, but there we would recommend - # to write tests with patches and not ignore them. - ignore_nodes: List[fn.Node] = [] - - def __init_subclass__(cls) -> None: - super().__init_subclass__() - add_subclass_tests(cls) - return cls - - @classmethod - def setUpClass(cls): - def get_all_nodes_classes(shelf: fn.Shelf, current=None): - if current is None: - current = [] - for node in shelf.nodes: - if node not in current: - current.append(node) - - for subshelf in shelf.subshelves: - get_all_nodes_classes(subshelf, current) - - return current - - all_nodes = fn.flatten_shelf(NODE_SHELF)[0] - nodes_to_test = all_nodes.copy() - - for node in cls.ignore_nodes: - if node in nodes_to_test: - nodes_to_test.remove(node) - - # monkey patching the async func method in the nodeclasses that if they are called the nodeclass - # is removed from the NODES_TO_TEST list - def monkey_patch_func(node_class): - ofunc = node_class.func - node_class.TestAllNodes_func = ofunc - - @wraps(ofunc) - async def func(self, *args, **kwargs): - res = await ofunc(self, *args, **kwargs) - if node_class in nodes_to_test: - nodes_to_test.remove(node_class) - return res - - node_class.func = func - - for node_class in all_nodes: - monkey_patch_func(node_class) - - cls.all_nodes = all_nodes - cls.nodes_to_test = nodes_to_test - - @classmethod - def tearDownClass(cls): - # undo the monkey patching - for node_class in cls.all_nodes: - if hasattr(node_class, "TestAllNodes_func"): - node_class.func = node_class.TestAllNodes_func - del node_class.TestAllNodes_func - - # Final assertion to ensure all nodes were tested - if cls.nodes_to_test: - raise AssertionError( - f"These nodes were not tested ({len(cls.nodes_to_test)}): {cls.nodes_to_test}" - ) diff --git a/tests/test_all_nodes.py b/tests/test_all_nodes.py index c66a05f..9e6bfa5 100644 --- a/tests/test_all_nodes.py +++ b/tests/test_all_nodes.py @@ -1,9 +1,9 @@ -from all_nodes_test_base import TestAllNodesBase import numpy as np import funcnodes_numpy as fnp import funcnodes as fn -import unittest +import pytest_funcnodes +import pytest samplemap = { "ndarray": lambda: [ @@ -97,6 +97,32 @@ "str", ], "Union[Literal['big', 'little'], None]": lambda: ["big", "little", None], + "Literal['linear', 'lower', 'higher', 'midpoint', 'nearest']": lambda: [ + "linear", + "lower", + "higher", + "midpoint", + "nearest", + ], + ( + "Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', " + "'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', " + "'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest']" + ): lambda: [ + "inverted_cdf", + "averaged_inverted_cdf", + "closest_observation", + "interpolated_inverted_cdf", + "hazen", + "weibull", + "linear", + "median_unbiased", + "normal_unbiased", + "lower", + "higher", + "midpoint", + "nearest", + ], "Union[None, int, ndarray]": lambda: [ None, 1, @@ -146,6 +172,7 @@ np.array([1, 2, 3]), ], np.arange(25).reshape(1, 5, 5), + np.arange(25).reshape(5, 5), ], "typing.Callable": lambda: [lambda x: x], "funcnodes_numpy._dtypes.DTYPE_ENUM": lambda: ["f", bool], @@ -163,7 +190,8 @@ np.array([1, 2, 3, 4]).reshape(2, 2), np.array([1, 2, 3]), "str", - ] + ], + [np.arange(25).reshape(5, 5)], ], "Union[float, int]": lambda: [1.0, 1], "bool": lambda: [True, False], @@ -173,12 +201,28 @@ "Sequence[ndarray]": lambda: [ [np.array([1, 2, 3, 4]).reshape(2, 2), np.array([1, 2, 3])], [np.array([4, 3, 2]), np.array([1, 2, 3])], + [ + np.random.random((10000, 100)), + np.random.random((100, 1000)), + ], ], "Literal['L', 'U']": lambda: ["L", "U"], "builtins.object": lambda: [object(), np.array([1, 2, 3])], "Literal['raise', 'wrap', 'clip']": lambda: ["raise", "wrap", "clip"], "Sequence[Union[bool, complex, float, int, ndarray, str]]": lambda: [ - [True, 1j, 1.0, 1, np.array([1, 2, 3]), "str"] + [ + True, + 1j, + 1.0, + 1, + np.array([1, 2, 3]), + "str", + ], + [ + np.random.random((10000, 100)), + np.random.random((100, 1000)), + ], + [np.array([1, 2, 3]), np.array([4, 5, 6])], ], "Union[List[Tuple[int, int]], Tuple[int, int], int]": lambda: [ [(1, 2), (3, 4)], @@ -215,7 +259,7 @@ "wrap", "empty", ], - "str": lambda: ["str", "ii", "ij,jk,kl->il", "2005-02-25"], + "str": lambda: ["str", "ii", "ij,jk,kl->il", "2005-02-25", "1, 2"], "Union[int, List[int], None]": lambda: [1, [1, 2, 3], None], "Union[ndarray, int, List[int]]": lambda: [ np.array([1, 2, 3]), @@ -299,6 +343,12 @@ [[[1, 2, 3]]], "str", ], + "Union[_SupportsArray, _NestedSequence, str, _NestedSequence]": lambda: [ + np.array([1, 2, 3]), + [[1, 2, 3]], + [[[1, 2, 3]]], + "str", + ], "bytes": lambda: [ b"\x93NUMPY\x01\x00v\x00{'descr': ' 0, f"{node.node_name} has no outputs" + assert len(ins.inputs) > 0, f"{node.node_name} has no inputs" diff --git a/tests/test_all_nodes_pytest.py b/tests/test_all_nodes_pytest.py new file mode 100644 index 0000000..3a55d1b --- /dev/null +++ b/tests/test_all_nodes_pytest.py @@ -0,0 +1,6 @@ +from pytest_funcnodes import all_nodes_tested +import funcnodes_numpy as fnmodule # noqa + + +def test_all_nodes_tested(all_nodes): + all_nodes_tested(all_nodes, fnmodule.NODE_SHELF, ignore=[]) diff --git a/tests/test_general.py b/tests/test_general.py index 6622373..ec818db 100644 --- a/tests/test_general.py +++ b/tests/test_general.py @@ -1,4 +1,4 @@ -import unittest +import pytest import funcnodes_numpy as fnp import funcnodes as fn @@ -12,61 +12,66 @@ def get_module_nodes(module): return nodes -class TestGeneral(unittest.IsolatedAsyncioTestCase): - def test_main_shelf(self): - shelf = fnp.NODE_SHELF - self.assertEqual(shelf.name, "numpy") - self.assertEqual(len(shelf.nodes), 0) - self.assertEqual(len(shelf.subshelves), 16) - - def test_all_nodes(self): - nodes = get_module_nodes(fnp) - exp = 307 - exp_shelfnodes = 374 - if fnp.np_version["major_int"] < 2: - exp -= 1 - exp_shelfnodes -= 1 - if fnp.np_version["major_int"] >= 2 and fnp.np_version["minor_int"] >= 2: - exp += 3 - exp_shelfnodes += 3 - self.assertEqual(len(nodes) + 1, exp) - for node in nodes: - print(node.node_name) - - shelvenodes, _ = fn.flatten_shelf(fnp.NODE_SHELF) - missing_shelvenodes = set(nodes) - (set(shelvenodes)) - self.assertEqual( - len(missing_shelvenodes), 1, [n.node_name for n in missing_shelvenodes] - ) - - self.assertEqual(len(shelvenodes), exp_shelfnodes) - - async def test_ndarray_shelve(self): - shelf = fnp._ndarray.NODE_SHELF - shelve_nodes, _ = fn.flatten_shelf(shelf) - module_nodes = get_module_nodes(fnp._ndarray) - self.assertEqual(len(shelve_nodes), len(module_nodes)) - self.assertEqual(len(shelve_nodes), 49) - - async def test_linalg_shelve(self): - shelf = fnp._linalg.NODE_SHELF - shelve_nodes, _ = fn.flatten_shelf(shelf) - module_nodes = get_module_nodes(fnp._linalg) - self.assertEqual(len(shelve_nodes), len(module_nodes)) - self.assertEqual(len(shelve_nodes), 20) - - async def test_emath_shelve(self): - shelf = fnp._lib.EMATH_NODE_SHELF - shelve_nodes, _ = fn.flatten_shelf(shelf) - module_nodes = get_module_nodes(fnp._lib.scimath) - self.assertEqual(len(shelve_nodes), len(module_nodes)) - self.assertEqual(len(shelve_nodes), 9) - - async def test_core_shelve(self): - exp_nodes = 261 - if fnp.np_version["major_int"] < 2: - exp_nodes -= 1 - if fnp.np_version["major_int"] >= 2 and fnp.np_version["minor_int"] >= 2: - exp_nodes += 3 - module_nodes = get_module_nodes(fnp._core) - self.assertEqual(len(module_nodes), exp_nodes) +def test_main_shelf(): + shelf = fnp.NODE_SHELF + assert shelf.name == "numpy" + assert len(shelf.nodes) == 0 + assert len(shelf.subshelves) == 16 + + +def test_all_nodes(): + nodes = get_module_nodes(fnp) + exp = 307 + exp_shelfnodes = 374 + if fnp.np_version["major_int"] < 2: + exp -= 1 + exp_shelfnodes -= 1 + if fnp.np_version["major_int"] >= 2 and fnp.np_version["minor_int"] >= 2: + exp += 3 + exp_shelfnodes += 3 + assert len(nodes) + 1 == exp + for node in nodes: + print(node.node_name) + + shelvenodes, _ = fn.flatten_shelf(fnp.NODE_SHELF) + missing_shelvenodes = set(nodes) - (set(shelvenodes)) + assert len(missing_shelvenodes) == 1, [n.node_name for n in missing_shelvenodes] + assert len(shelvenodes) == exp_shelfnodes + + +@pytest.mark.asyncio +async def test_ndarray_shelve(): + shelf = fnp._ndarray.NODE_SHELF + shelve_nodes, _ = fn.flatten_shelf(shelf) + module_nodes = get_module_nodes(fnp._ndarray) + assert len(shelve_nodes) == len(module_nodes) + assert len(shelve_nodes) == 49 + + +@pytest.mark.asyncio +async def test_linalg_shelve(): + shelf = fnp._linalg.NODE_SHELF + shelve_nodes, _ = fn.flatten_shelf(shelf) + module_nodes = get_module_nodes(fnp._linalg) + assert len(shelve_nodes) == len(module_nodes) + assert len(shelve_nodes) == 20 + + +@pytest.mark.asyncio +async def test_emath_shelve(): + shelf = fnp._lib.EMATH_NODE_SHELF + shelve_nodes, _ = fn.flatten_shelf(shelf) + module_nodes = get_module_nodes(fnp._lib.scimath) + assert len(shelve_nodes) == len(module_nodes) + assert len(shelve_nodes) == 9 + + +@pytest.mark.asyncio +async def test_core_shelve(): + exp_nodes = 261 + if fnp.np_version["major_int"] < 2: + exp_nodes -= 1 + if fnp.np_version["major_int"] >= 2 and fnp.np_version["minor_int"] >= 2: + exp_nodes += 3 + module_nodes = get_module_nodes(fnp._core) + assert len(module_nodes) == exp_nodes diff --git a/tests/test_lib.py b/tests/test_lib.py index 80a14f9..7b6389a 100644 --- a/tests/test_lib.py +++ b/tests/test_lib.py @@ -1,4 +1,3 @@ -import unittest import funcnodes_numpy as fnp import funcnodes as fn import numpy as np @@ -14,46 +13,39 @@ def _testf(): return 1 -class TestNumpyLib(unittest.TestCase): - def test_ufunc_completness(self): - nodes, _ = fn.flatten_shelf(fnp.NODE_SHELF) - node_names = sorted([node.node_name for node in nodes]) - all_funcs = fnp.ufuncs.get_numpy_ufucs() - print(all_funcs) - self.assertIn("add", all_funcs) - self.assertIn("subtract", all_funcs) - self.assertIn("sin", all_funcs) - self.assertIn("cos", all_funcs) - self.assertIn("sqrt", all_funcs) - self.assertIn("exp", all_funcs) - - for f in all_funcs: - self.assertIn(f, node_names) - - for f in all_funcs: - for node in nodes: - if node.node_name == f: - srcf = inspect.getsourcefile(unwrap(node.func)) - bdir = os.path.dirname(os.path.dirname(inspect.getsourcefile(fn))) - memdata = "\n ".join( - [ - str( - ( - inspect.getsourcefile(v).replace(bdir, ""), - hasattr(v, "__wrapped__"), - ) +def test_ufunc_completness(): + nodes, _ = fn.flatten_shelf(fnp.NODE_SHELF) + node_names = sorted([node.node_name for node in nodes]) + all_funcs = fnp.ufuncs.get_numpy_ufucs() + print(all_funcs) + assert "add" in all_funcs + assert "subtract" in all_funcs + assert "sin" in all_funcs + assert "cos" in all_funcs + assert "sqrt" in all_funcs + assert "exp" in all_funcs + + for f in all_funcs: + assert f in node_names + + for f in all_funcs: + for node in nodes: + if node.node_name == f: + srcf = inspect.getsourcefile(unwrap(node.func)) + bdir = os.path.dirname(os.path.dirname(inspect.getsourcefile(fn))) + memdata = "\n ".join( + [ + str( + ( + inspect.getsourcefile(v).replace(bdir, ""), + hasattr(v, "__wrapped__"), ) - for v in unwrap(node.func, return_memo=True)[1].values() - ] - ) - self.assertTrue( - srcf.endswith("ufuncs.py") - or srcf.endswith("scimath.py") - or srcf.endswith("_ndarray.py"), - f"souce file for {f} is {srcf} not ufuncs.py, [\n {memdata}\n]", - ) - - def test_calls(self): - import inspect - - print(inspect.getsource(_testf)) + ) + for v in unwrap(node.func, return_memo=True)[1].values() + ] + ) + assert ( + srcf.endswith("ufuncs.py") + or srcf.endswith("scimath.py") + or srcf.endswith("_ndarray.py") + ), f"souce file for {f} is {srcf} not ufuncs.py, [\n {memdata}\n]" diff --git a/tests/test_types.py b/tests/test_types.py index 5f4f79a..4d23516 100644 --- a/tests/test_types.py +++ b/tests/test_types.py @@ -1,4 +1,3 @@ -import unittest import funcnodes_numpy as fnp from typing import Union, List, Literal, TYPE_CHECKING import numpy as np @@ -19,178 +18,176 @@ def flatten_shelves(shelf: fn.Shelf) -> list[fn.Node]: return set(nodes) -class TestTypes(unittest.TestCase): - def test_typestrings(self): - shelf = fnp.NODE_SHELF - nodes, _ = fn.flatten_shelf(shelf) +def test_typestrings(): + shelf = fnp.NODE_SHELF + nodes, _ = fn.flatten_shelf(shelf) - def _test_typestring(t): - if isinstance(t, str): - self.assertEqual(type_to_string(string_to_type(t)), t) - elif isinstance(t, dict): - if "anyOf" in t: - for _t in t["anyOf"]: - _test_typestring(_t) - elif "allOf" in t: - for _t in t["allOf"]: - _test_typestring(_t) - elif "type" in t: - if t["type"] == "array": - _test_typestring(t["items"]) - elif t["type"] == "enum": - return - else: - raise ValueError(f"{t}, ({type(t)})") + def _test_typestring(t): + if isinstance(t, str): + assert type_to_string(string_to_type(t)) == t + elif isinstance(t, dict): + if "anyOf" in t: + for _t in t["anyOf"]: + _test_typestring(_t) + elif "allOf" in t: + for _t in t["allOf"]: + _test_typestring(_t) + elif "type" in t: + if t["type"] == "array": + _test_typestring(t["items"]) + elif t["type"] == "enum": + return else: raise ValueError(f"{t}, ({type(t)})") else: raise ValueError(f"{t}, ({type(t)})") + else: + raise ValueError(f"{t}, ({type(t)})") - for node in nodes: - ins: fn.Node = node() - for ipname, ip in ins.inputs.items(): - t = json.loads( - json.dumps(ip.serialize_class()["type"], cls=fn.JSONEncoder) - ) - try: - _test_typestring(t) + for node in nodes: + ins: fn.Node = node() + for ipname, ip in ins.inputs.items(): + t = json.loads(json.dumps(ip.serialize_class()["type"], cls=fn.JSONEncoder)) + try: + _test_typestring(t) - except Exception as e: - raise ValueError( - f"failed typestring test for {node.node_name} input: {ipname}, {t}" - ) from e - for ipname, ip in ins.outputs.items(): - t = ip.serialize_class()["type"] - try: - _test_typestring(t) - except Exception as e: - print(_TYPE_GETTER) - raise ValueError( - f"failed typestring test for {node.node_name} output: {ipname}" - ) from e + except Exception as e: + raise ValueError( + f"failed typestring test for {node.node_name} input: {ipname}, {t}" + ) from e + for ipname, ip in ins.outputs.items(): + t = ip.serialize_class()["type"] + try: + _test_typestring(t) + except Exception as e: + print(_TYPE_GETTER) + raise ValueError( + f"failed typestring test for {node.node_name} output: {ipname}" + ) from e - def test_types_to_string(self): - for i, (src, exp, exps) in enumerate( - [ - ( - fnp.DTYPE_ENUM, - fnp.DTYPE_ENUM, - "funcnodes_numpy._dtypes.DTYPE_ENUM", - ), # 0 - (fnp._types.scalar, Union[float, int], "Union[float, int]"), # 1 - ( - fnp._types.number, - Union[complex, float, int], - "Union[complex, float, int]", - ), # 2 - ( - fnp._types.ndarray_or_scalar, - Union[ - fnp._types.scalar, - np.ndarray, - ], - "Union[float, int, ndarray]", - ), # 3 - ( - fnp._types.ndarray_or_number, - Union[fnp._types.number, np.ndarray], - "Union[complex, float, int, ndarray]", - ), # 4 - ( - fnp._types.indices_or_sections, - Union[int, List[int]], - "Union[int, List[int]]", - ), # 5 - ( - fnp._types.shape_like, - Union[np.ndarray, int, List[int]], - "Union[ndarray, int, List[int]]", - ), # 6 - ( - fnp._types.axis_like, - Union[int, List[int]], - "Union[int, List[int]]", - ), # 7 - (fnp._types.ndarray, np.ndarray, "ndarray"), # 8 - ( - fnp._types.array_like, - Union[float, int, complex, str, bool, np.ndarray], - "Union[float, int, complex, str, bool, ndarray]", - ), # 9 - (fnp._types.int_array, np.ndarray, "ndarray"), # 10 - (fnp._types.bool_array, np.ndarray, "ndarray"), # 11 - (fnp._types.bitarray, np.ndarray, "ndarray"), # 12 - ( - fnp._types.bool_or_bool_array, - Union[bool, fnp._types.bool_array], - "Union[bool, ndarray]", - ), # 13 - ( - fnp._types.int_bool_array, - Union[fnp._types.int_array, fnp._types.bool_array], - "ndarray", - ), # 14 - ( - fnp._types.int_or_int_array, - Union[int, fnp._types.int_array], - "Union[int, ndarray]", - ), # 15 - (fnp._types.real_array, np.ndarray, "ndarray"), # 16 - (fnp._types.matrix, np.ndarray, "ndarray"), # 17 - ( - fnp._types.OrderCF, - Literal[None, "C", "F"], - "Literal[None, 'C', 'F']", - ), # 18 - ( - fnp._types.OrderKACF, - Literal[None, "K", "A", "C", "F"], - "Literal[None, 'K', 'A', 'C', 'F']", - ), # 19 - ( - fnp._types.OrderACF, - Literal[None, "A", "C", "F"], - "Literal[None, 'A', 'C', 'F']", - ), # 20 - ( - fnp._types.buffer_like, - Union[bytes, bytearray, memoryview, np.ndarray], - "Union[bytes, bytearray, memoryview, ndarray]", - ), # 21 - ( - fnp._types.str_array, - np._ArrayLikeStr_co - if TYPE_CHECKING - else np._typing._ArrayLikeStr_co, - "Union[numpy._typing._array_like._SupportsArray, numpy._typing._nested_sequence._NestedSequence, " - "str, numpy._typing._nested_sequence._NestedSequence]", - ), # 22 - (fnp._types.NoValue, np._NoValue, ""), # 23 - ( - fnp._types.casting_literal, - Literal["no", "equiv", "safe", "same_kind", "unsafe"], - "Literal['no', 'equiv', 'safe', 'same_kind', 'unsafe']", - ), # 24 - ] - ): - self.assertEqual(type_to_string(src), type_to_string(exp), (i, src, exp)) - self.assertEqual(type_to_string(src), exps, (i, src, exps)) - def test_enum_options(self): - node = fnp.astype() +def test_types_to_string(): + for i, (src, exp, exps) in enumerate( + [ + ( + fnp.DTYPE_ENUM, + fnp.DTYPE_ENUM, + "funcnodes_numpy._dtypes.DTYPE_ENUM", + ), # 0 + (fnp._types.scalar, Union[float, int], "Union[float, int]"), # 1 + ( + fnp._types.number, + Union[complex, float, int], + "Union[complex, float, int]", + ), # 2 + ( + fnp._types.ndarray_or_scalar, + Union[ + fnp._types.scalar, + np.ndarray, + ], + "Union[float, int, ndarray]", + ), # 3 + ( + fnp._types.ndarray_or_number, + Union[fnp._types.number, np.ndarray], + "Union[complex, float, int, ndarray]", + ), # 4 + ( + fnp._types.indices_or_sections, + Union[int, List[int]], + "Union[int, List[int]]", + ), # 5 + ( + fnp._types.shape_like, + Union[np.ndarray, int, List[int]], + "Union[ndarray, int, List[int]]", + ), # 6 + ( + fnp._types.axis_like, + Union[int, List[int]], + "Union[int, List[int]]", + ), # 7 + (fnp._types.ndarray, np.ndarray, "ndarray"), # 8 + ( + fnp._types.array_like, + Union[float, int, complex, str, bool, np.ndarray], + "Union[float, int, complex, str, bool, ndarray]", + ), # 9 + (fnp._types.int_array, np.ndarray, "ndarray"), # 10 + (fnp._types.bool_array, np.ndarray, "ndarray"), # 11 + (fnp._types.bitarray, np.ndarray, "ndarray"), # 12 + ( + fnp._types.bool_or_bool_array, + Union[bool, fnp._types.bool_array], + "Union[bool, ndarray]", + ), # 13 + ( + fnp._types.int_bool_array, + Union[fnp._types.int_array, fnp._types.bool_array], + "ndarray", + ), # 14 + ( + fnp._types.int_or_int_array, + Union[int, fnp._types.int_array], + "Union[int, ndarray]", + ), # 15 + (fnp._types.real_array, np.ndarray, "ndarray"), # 16 + (fnp._types.matrix, np.ndarray, "ndarray"), # 17 + ( + fnp._types.OrderCF, + Literal[None, "C", "F"], + "Literal[None, 'C', 'F']", + ), # 18 + ( + fnp._types.OrderKACF, + Literal[None, "K", "A", "C", "F"], + "Literal[None, 'K', 'A', 'C', 'F']", + ), # 19 + ( + fnp._types.OrderACF, + Literal[None, "A", "C", "F"], + "Literal[None, 'A', 'C', 'F']", + ), # 20 + ( + fnp._types.buffer_like, + Union[bytes, bytearray, memoryview, np.ndarray], + "Union[bytes, bytearray, memoryview, ndarray]", + ), # 21 + ( + fnp._types.str_array, + np._ArrayLikeStr_co if TYPE_CHECKING else np._typing._ArrayLikeStr_co, + "Union[_SupportsArray, _NestedSequence, str, _NestedSequence]", + ), # 22 + (fnp._types.NoValue, np._NoValue, ""), # 23 + ( + fnp._types.casting_literal, + Literal["no", "equiv", "safe", "same_kind", "unsafe"], + "Literal['no', 'equiv', 'safe', 'same_kind', 'unsafe']", + ), # 24 + ] + ): + assert type_to_string(src) == type_to_string(exp), (i, src, exp) + assert type_to_string(src) == exps, (i, src, exps) - self.assertEqual( - node.get_input("dtype").value_options["options"]["keys"], - [i.name for i in fnp.DTYPE_ENUM], - ) - self.assertEqual( - node.get_input("dtype").value_options["options"]["values"], - [i.value for i in fnp.DTYPE_ENUM], - ) - def test_literal_options(self): - node = fnp.newbyteorder() - self.assertEqual( - node.get_input("new_order").value_options["options"]["values"], - ["S", "<", ">", "=", "|"], - ) +def test_enum_options(): + node = fnp.astype() + + assert node["dtype"].value_options["options"]["keys"] == [ + i.name for i in fnp.DTYPE_ENUM + ] + assert node["dtype"].value_options["options"]["values"] == [ + i.value for i in fnp.DTYPE_ENUM + ] + + +def test_literal_options(): + node = fnp.newbyteorder() + assert 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