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Remove --ci option
And move meta tests to top-level meta_tests folder
1 parent 6a9f809 commit b7cd5ce

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+33
-84
lines changed

.github/workflows/numpy.yml

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@@ -28,4 +28,4 @@ jobs:
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env:
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ARRAY_API_TESTS_MODULE: numpy.array_api
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run: |
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pytest -v -rxXfE --ci --skips-file numpy-skips.txt
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pytest -v -rxXfE --skips-file numpy-skips.txt array_api_tests/

README.md

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@@ -161,12 +161,6 @@ You can specify the API version to use when testing via the
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array module's `__array_api_version__` value, and if that attribute doesn't
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exist then we fallback to `"2021.12"`.
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#### CI flag
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Use the `--ci` flag to run only the primary and special cases tests. You can
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ignore the other test cases as they are redundant for the purposes of checking
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compliance.
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#### Data-dependent shapes
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Use the `--disable-data-dependent-shapes` flag to skip testing functions which have

conftest.py renamed to array_api_tests/conftest.py

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@@ -54,11 +54,6 @@ def pytest_addoption(parser):
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help="disable testing functions with output shapes dependent on input",
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)
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# CI
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parser.addoption(
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"--ci",
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action="store_true",
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help="run just the tests appropriate for CI",
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)
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parser.addoption(
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"--skips-file",
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action="store",
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config.addinivalue_line(
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"markers", "data_dependent_shapes: output shapes are dependent on inputs"
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)
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config.addinivalue_line("markers", "ci: primary test")
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config.addinivalue_line(
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"markers",
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"min_version(api_version): run when greater or equal to api_version",
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disabled_exts = config.getoption("--disable-extension")
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disabled_dds = config.getoption("--disable-data-dependent-shapes")
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ci = config.getoption("--ci")
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for item in items:
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markers = list(item.iter_markers())
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mark.skip(reason="disabled via --disable-data-dependent-shapes")
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)
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break
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# skip if test not appropriate for CI
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if ci:
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ci_mark = next((m for m in markers if m.name == "ci"), None)
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if ci_mark is None:
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item.add_marker(mark.skip(reason="disabled via --ci"))
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# skip if test is for greater api_version
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ver_mark = next((m for m in markers if m.name == "min_version"), None)
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if ver_mark is not None:

array_api_tests/test_array_object.py

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from . import xp as _xp
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from .typing import DataType, Index, Param, Scalar, ScalarType, Shape
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pytestmark = pytest.mark.ci
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def scalar_objects(
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dtype: DataType, shape: Shape

array_api_tests/test_constants.py

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from . import xp
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from .typing import Array
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pytestmark = pytest.mark.ci
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def assert_scalar_float(name: str, c: Any):
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assert isinstance(c, SupportsFloat), f"{name}={c!r} does not look like a float"

array_api_tests/test_creation_functions.py

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from itertools import count
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from typing import Iterator, NamedTuple, Union
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import pytest
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from hypothesis import assume, given, note
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from hypothesis import strategies as st
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from . import xps
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from .typing import DataType, Scalar
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pytestmark = pytest.mark.ci
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2017

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class frange(NamedTuple):
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start: float

array_api_tests/test_data_type_functions.py

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from . import xp as _xp
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from .typing import DataType
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pytestmark = pytest.mark.ci
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# TODO: test with complex dtypes
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def non_complex_dtypes():

array_api_tests/test_fft.py

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from . import xp
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pytestmark = [
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pytest.mark.ci,
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pytest.mark.xp_extension("fft"),
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pytest.mark.min_version("2022.12"),
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]

array_api_tests/test_has_names.py

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from .stubs import (array_attributes, array_methods, category_to_funcs,
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extension_to_funcs, EXTENSIONS)
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pytestmark = pytest.mark.ci
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has_name_params = []
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for ext, stubs in extension_to_funcs.items():
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for stub in stubs:

array_api_tests/test_indexing_functions.py

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from . import shape_helpers as sh
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from . import xps
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pytestmark = pytest.mark.ci
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@pytest.mark.min_version("2022.12")
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@given(

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