demo + utils venv
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@@ -0,0 +1,367 @@
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from __future__ import division, absolute_import, print_function
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import sys
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import pytest
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import weakref
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import numpy as np
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from numpy.ctypeslib import ndpointer, load_library, as_array
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from numpy.distutils.misc_util import get_shared_lib_extension
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from numpy.testing import assert_, assert_array_equal, assert_raises, assert_equal
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try:
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import ctypes
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except ImportError:
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ctypes = None
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else:
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cdll = None
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test_cdll = None
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if hasattr(sys, 'gettotalrefcount'):
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try:
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cdll = load_library('_multiarray_umath_d', np.core._multiarray_umath.__file__)
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except OSError:
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pass
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try:
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test_cdll = load_library('_multiarray_tests', np.core._multiarray_tests.__file__)
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except OSError:
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pass
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if cdll is None:
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cdll = load_library('_multiarray_umath', np.core._multiarray_umath.__file__)
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if test_cdll is None:
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test_cdll = load_library('_multiarray_tests', np.core._multiarray_tests.__file__)
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c_forward_pointer = test_cdll.forward_pointer
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@pytest.mark.skipif(ctypes is None,
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reason="ctypes not available in this python")
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@pytest.mark.skipif(sys.platform == 'cygwin',
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reason="Known to fail on cygwin")
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class TestLoadLibrary(object):
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def test_basic(self):
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try:
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# Should succeed
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load_library('_multiarray_umath', np.core._multiarray_umath.__file__)
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except ImportError as e:
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msg = ("ctypes is not available on this python: skipping the test"
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" (import error was: %s)" % str(e))
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print(msg)
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def test_basic2(self):
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# Regression for #801: load_library with a full library name
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# (including extension) does not work.
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try:
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try:
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so = get_shared_lib_extension(is_python_ext=True)
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# Should succeed
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load_library('_multiarray_umath%s' % so, np.core._multiarray_umath.__file__)
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except ImportError:
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print("No distutils available, skipping test.")
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except ImportError as e:
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msg = ("ctypes is not available on this python: skipping the test"
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" (import error was: %s)" % str(e))
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print(msg)
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class TestNdpointer(object):
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def test_dtype(self):
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dt = np.intc
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p = ndpointer(dtype=dt)
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assert_(p.from_param(np.array([1], dt)))
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dt = '<i4'
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p = ndpointer(dtype=dt)
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assert_(p.from_param(np.array([1], dt)))
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dt = np.dtype('>i4')
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p = ndpointer(dtype=dt)
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p.from_param(np.array([1], dt))
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assert_raises(TypeError, p.from_param,
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np.array([1], dt.newbyteorder('swap')))
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dtnames = ['x', 'y']
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dtformats = [np.intc, np.float64]
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dtdescr = {'names': dtnames, 'formats': dtformats}
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dt = np.dtype(dtdescr)
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p = ndpointer(dtype=dt)
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assert_(p.from_param(np.zeros((10,), dt)))
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samedt = np.dtype(dtdescr)
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p = ndpointer(dtype=samedt)
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assert_(p.from_param(np.zeros((10,), dt)))
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dt2 = np.dtype(dtdescr, align=True)
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if dt.itemsize != dt2.itemsize:
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assert_raises(TypeError, p.from_param, np.zeros((10,), dt2))
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else:
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assert_(p.from_param(np.zeros((10,), dt2)))
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def test_ndim(self):
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p = ndpointer(ndim=0)
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assert_(p.from_param(np.array(1)))
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assert_raises(TypeError, p.from_param, np.array([1]))
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p = ndpointer(ndim=1)
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assert_raises(TypeError, p.from_param, np.array(1))
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assert_(p.from_param(np.array([1])))
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p = ndpointer(ndim=2)
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assert_(p.from_param(np.array([[1]])))
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def test_shape(self):
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p = ndpointer(shape=(1, 2))
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assert_(p.from_param(np.array([[1, 2]])))
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assert_raises(TypeError, p.from_param, np.array([[1], [2]]))
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p = ndpointer(shape=())
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assert_(p.from_param(np.array(1)))
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def test_flags(self):
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x = np.array([[1, 2], [3, 4]], order='F')
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p = ndpointer(flags='FORTRAN')
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assert_(p.from_param(x))
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p = ndpointer(flags='CONTIGUOUS')
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assert_raises(TypeError, p.from_param, x)
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p = ndpointer(flags=x.flags.num)
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assert_(p.from_param(x))
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assert_raises(TypeError, p.from_param, np.array([[1, 2], [3, 4]]))
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def test_cache(self):
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assert_(ndpointer(dtype=np.float64) is ndpointer(dtype=np.float64))
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# shapes are normalized
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assert_(ndpointer(shape=2) is ndpointer(shape=(2,)))
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# 1.12 <= v < 1.16 had a bug that made these fail
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assert_(ndpointer(shape=2) is not ndpointer(ndim=2))
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assert_(ndpointer(ndim=2) is not ndpointer(shape=2))
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@pytest.mark.skipif(ctypes is None,
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reason="ctypes not available on this python installation")
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class TestNdpointerCFunc(object):
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def test_arguments(self):
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""" Test that arguments are coerced from arrays """
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c_forward_pointer.restype = ctypes.c_void_p
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c_forward_pointer.argtypes = (ndpointer(ndim=2),)
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c_forward_pointer(np.zeros((2, 3)))
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# too many dimensions
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assert_raises(
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ctypes.ArgumentError, c_forward_pointer, np.zeros((2, 3, 4)))
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@pytest.mark.parametrize(
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'dt', [
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float,
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np.dtype(dict(
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formats=['<i4', '<i4'],
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names=['a', 'b'],
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offsets=[0, 2],
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itemsize=6
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))
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], ids=[
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'float',
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'overlapping-fields'
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]
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)
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def test_return(self, dt):
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""" Test that return values are coerced to arrays """
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arr = np.zeros((2, 3), dt)
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ptr_type = ndpointer(shape=arr.shape, dtype=arr.dtype)
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c_forward_pointer.restype = ptr_type
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c_forward_pointer.argtypes = (ptr_type,)
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# check that the arrays are equivalent views on the same data
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arr2 = c_forward_pointer(arr)
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assert_equal(arr2.dtype, arr.dtype)
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assert_equal(arr2.shape, arr.shape)
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assert_equal(
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arr2.__array_interface__['data'],
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arr.__array_interface__['data']
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)
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def test_vague_return_value(self):
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""" Test that vague ndpointer return values do not promote to arrays """
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arr = np.zeros((2, 3))
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ptr_type = ndpointer(dtype=arr.dtype)
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c_forward_pointer.restype = ptr_type
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c_forward_pointer.argtypes = (ptr_type,)
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ret = c_forward_pointer(arr)
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assert_(isinstance(ret, ptr_type))
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@pytest.mark.skipif(ctypes is None,
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reason="ctypes not available on this python installation")
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class TestAsArray(object):
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def test_array(self):
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from ctypes import c_int
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pair_t = c_int * 2
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a = as_array(pair_t(1, 2))
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assert_equal(a.shape, (2,))
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assert_array_equal(a, np.array([1, 2]))
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a = as_array((pair_t * 3)(pair_t(1, 2), pair_t(3, 4), pair_t(5, 6)))
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assert_equal(a.shape, (3, 2))
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assert_array_equal(a, np.array([[1, 2], [3, 4], [5, 6]]))
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def test_pointer(self):
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from ctypes import c_int, cast, POINTER
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p = cast((c_int * 10)(*range(10)), POINTER(c_int))
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a = as_array(p, shape=(10,))
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assert_equal(a.shape, (10,))
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assert_array_equal(a, np.arange(10))
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a = as_array(p, shape=(2, 5))
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assert_equal(a.shape, (2, 5))
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assert_array_equal(a, np.arange(10).reshape((2, 5)))
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# shape argument is required
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assert_raises(TypeError, as_array, p)
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def test_struct_array_pointer(self):
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from ctypes import c_int16, Structure, pointer
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class Struct(Structure):
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_fields_ = [('a', c_int16)]
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Struct3 = 3 * Struct
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c_array = (2 * Struct3)(
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Struct3(Struct(a=1), Struct(a=2), Struct(a=3)),
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Struct3(Struct(a=4), Struct(a=5), Struct(a=6))
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)
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expected = np.array([
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[(1,), (2,), (3,)],
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[(4,), (5,), (6,)],
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], dtype=[('a', np.int16)])
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def check(x):
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assert_equal(x.dtype, expected.dtype)
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assert_equal(x, expected)
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# all of these should be equivalent
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check(as_array(c_array))
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check(as_array(pointer(c_array), shape=()))
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check(as_array(pointer(c_array[0]), shape=(2,)))
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check(as_array(pointer(c_array[0][0]), shape=(2, 3)))
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def test_reference_cycles(self):
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# related to gh-6511
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import ctypes
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# create array to work with
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# don't use int/long to avoid running into bpo-10746
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N = 100
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a = np.arange(N, dtype=np.short)
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# get pointer to array
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pnt = np.ctypeslib.as_ctypes(a)
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with np.testing.assert_no_gc_cycles():
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# decay the array above to a pointer to its first element
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newpnt = ctypes.cast(pnt, ctypes.POINTER(ctypes.c_short))
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# and construct an array using this data
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b = np.ctypeslib.as_array(newpnt, (N,))
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# now delete both, which should cleanup both objects
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del newpnt, b
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def test_segmentation_fault(self):
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arr = np.zeros((224, 224, 3))
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c_arr = np.ctypeslib.as_ctypes(arr)
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arr_ref = weakref.ref(arr)
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del arr
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# check the reference wasn't cleaned up
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assert_(arr_ref() is not None)
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# check we avoid the segfault
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c_arr[0][0][0]
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@pytest.mark.skipif(ctypes is None,
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reason="ctypes not available on this python installation")
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class TestAsCtypesType(object):
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""" Test conversion from dtypes to ctypes types """
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def test_scalar(self):
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dt = np.dtype('<u2')
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ct = np.ctypeslib.as_ctypes_type(dt)
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assert_equal(ct, ctypes.c_uint16.__ctype_le__)
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dt = np.dtype('>u2')
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ct = np.ctypeslib.as_ctypes_type(dt)
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assert_equal(ct, ctypes.c_uint16.__ctype_be__)
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dt = np.dtype('u2')
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ct = np.ctypeslib.as_ctypes_type(dt)
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assert_equal(ct, ctypes.c_uint16)
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def test_subarray(self):
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dt = np.dtype((np.int32, (2, 3)))
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ct = np.ctypeslib.as_ctypes_type(dt)
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assert_equal(ct, 2 * (3 * ctypes.c_int32))
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def test_structure(self):
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dt = np.dtype([
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('a', np.uint16),
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('b', np.uint32),
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])
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ct = np.ctypeslib.as_ctypes_type(dt)
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assert_(issubclass(ct, ctypes.Structure))
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assert_equal(ctypes.sizeof(ct), dt.itemsize)
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assert_equal(ct._fields_, [
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('a', ctypes.c_uint16),
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('b', ctypes.c_uint32),
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])
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def test_structure_aligned(self):
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dt = np.dtype([
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('a', np.uint16),
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('b', np.uint32),
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], align=True)
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ct = np.ctypeslib.as_ctypes_type(dt)
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assert_(issubclass(ct, ctypes.Structure))
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assert_equal(ctypes.sizeof(ct), dt.itemsize)
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assert_equal(ct._fields_, [
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('a', ctypes.c_uint16),
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('', ctypes.c_char * 2), # padding
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('b', ctypes.c_uint32),
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])
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def test_union(self):
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dt = np.dtype(dict(
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names=['a', 'b'],
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offsets=[0, 0],
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formats=[np.uint16, np.uint32]
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))
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ct = np.ctypeslib.as_ctypes_type(dt)
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assert_(issubclass(ct, ctypes.Union))
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assert_equal(ctypes.sizeof(ct), dt.itemsize)
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assert_equal(ct._fields_, [
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('a', ctypes.c_uint16),
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('b', ctypes.c_uint32),
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])
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def test_padded_union(self):
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dt = np.dtype(dict(
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names=['a', 'b'],
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offsets=[0, 0],
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formats=[np.uint16, np.uint32],
|
||||
itemsize=5,
|
||||
))
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||||
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||||
ct = np.ctypeslib.as_ctypes_type(dt)
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assert_(issubclass(ct, ctypes.Union))
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assert_equal(ctypes.sizeof(ct), dt.itemsize)
|
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assert_equal(ct._fields_, [
|
||||
('a', ctypes.c_uint16),
|
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('b', ctypes.c_uint32),
|
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('', ctypes.c_char * 5), # padding
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||||
])
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def test_overlapping(self):
|
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dt = np.dtype(dict(
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names=['a', 'b'],
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offsets=[0, 2],
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formats=[np.uint32, np.uint32]
|
||||
))
|
||||
assert_raises(NotImplementedError, np.ctypeslib.as_ctypes_type, dt)
|
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@@ -0,0 +1,68 @@
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from __future__ import division, absolute_import, print_function
|
||||
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||||
# As we are testing matrices, we ignore its PendingDeprecationWarnings
|
||||
try:
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import pytest
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pytestmark = pytest.mark.filterwarnings(
|
||||
'ignore:the matrix subclass is not:PendingDeprecationWarning')
|
||||
except ImportError:
|
||||
pass
|
||||
|
||||
import numpy as np
|
||||
import numpy.matlib
|
||||
from numpy.testing import assert_array_equal, assert_
|
||||
|
||||
def test_empty():
|
||||
x = numpy.matlib.empty((2,))
|
||||
assert_(isinstance(x, np.matrix))
|
||||
assert_(x.shape, (1, 2))
|
||||
|
||||
def test_ones():
|
||||
assert_array_equal(numpy.matlib.ones((2, 3)),
|
||||
np.matrix([[ 1., 1., 1.],
|
||||
[ 1., 1., 1.]]))
|
||||
|
||||
assert_array_equal(numpy.matlib.ones(2), np.matrix([[ 1., 1.]]))
|
||||
|
||||
def test_zeros():
|
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assert_array_equal(numpy.matlib.zeros((2, 3)),
|
||||
np.matrix([[ 0., 0., 0.],
|
||||
[ 0., 0., 0.]]))
|
||||
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||||
assert_array_equal(numpy.matlib.zeros(2), np.matrix([[ 0., 0.]]))
|
||||
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||||
def test_identity():
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x = numpy.matlib.identity(2, dtype=int)
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assert_array_equal(x, np.matrix([[1, 0], [0, 1]]))
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||||
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||||
def test_eye():
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xc = numpy.matlib.eye(3, k=1, dtype=int)
|
||||
assert_array_equal(xc, np.matrix([[ 0, 1, 0],
|
||||
[ 0, 0, 1],
|
||||
[ 0, 0, 0]]))
|
||||
assert xc.flags.c_contiguous
|
||||
assert not xc.flags.f_contiguous
|
||||
|
||||
xf = numpy.matlib.eye(3, 4, dtype=int, order='F')
|
||||
assert_array_equal(xf, np.matrix([[ 1, 0, 0, 0],
|
||||
[ 0, 1, 0, 0],
|
||||
[ 0, 0, 1, 0]]))
|
||||
assert not xf.flags.c_contiguous
|
||||
assert xf.flags.f_contiguous
|
||||
|
||||
def test_rand():
|
||||
x = numpy.matlib.rand(3)
|
||||
# check matrix type, array would have shape (3,)
|
||||
assert_(x.ndim == 2)
|
||||
|
||||
def test_randn():
|
||||
x = np.matlib.randn(3)
|
||||
# check matrix type, array would have shape (3,)
|
||||
assert_(x.ndim == 2)
|
||||
|
||||
def test_repmat():
|
||||
a1 = np.arange(4)
|
||||
x = numpy.matlib.repmat(a1, 2, 2)
|
||||
y = np.array([[0, 1, 2, 3, 0, 1, 2, 3],
|
||||
[0, 1, 2, 3, 0, 1, 2, 3]])
|
||||
assert_array_equal(x, y)
|
||||
@@ -0,0 +1,19 @@
|
||||
from __future__ import division, absolute_import, print_function
|
||||
|
||||
import re
|
||||
|
||||
import numpy as np
|
||||
from numpy.testing import assert_
|
||||
|
||||
|
||||
def test_valid_numpy_version():
|
||||
# Verify that the numpy version is a valid one (no .post suffix or other
|
||||
# nonsense). See gh-6431 for an issue caused by an invalid version.
|
||||
version_pattern = r"^[0-9]+\.[0-9]+\.[0-9]+(|a[0-9]|b[0-9]|rc[0-9])"
|
||||
dev_suffix = r"(\.dev0\+([0-9a-f]{7}|Unknown))"
|
||||
if np.version.release:
|
||||
res = re.match(version_pattern, np.__version__)
|
||||
else:
|
||||
res = re.match(version_pattern + dev_suffix, np.__version__)
|
||||
|
||||
assert_(res is not None, np.__version__)
|
||||
@@ -0,0 +1,89 @@
|
||||
from __future__ import division, absolute_import, print_function
|
||||
|
||||
import sys
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
try:
|
||||
import ctypes
|
||||
except ImportError:
|
||||
ctypes = None
|
||||
|
||||
def check_dir(module, module_name=None):
|
||||
"""Returns a mapping of all objects with the wrong __module__ attribute."""
|
||||
if module_name is None:
|
||||
module_name = module.__name__
|
||||
results = {}
|
||||
for name in dir(module):
|
||||
item = getattr(module, name)
|
||||
if (hasattr(item, '__module__') and hasattr(item, '__name__')
|
||||
and item.__module__ != module_name):
|
||||
results[name] = item.__module__ + '.' + item.__name__
|
||||
return results
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
sys.version_info[0] < 3,
|
||||
reason="NumPy exposes slightly different functions on Python 2")
|
||||
def test_numpy_namespace():
|
||||
# None of these objects are publicly documented.
|
||||
undocumented = {
|
||||
'Tester': 'numpy.testing._private.nosetester.NoseTester',
|
||||
'_add_newdoc_ufunc': 'numpy.core._multiarray_umath._add_newdoc_ufunc',
|
||||
'add_docstring': 'numpy.core._multiarray_umath.add_docstring',
|
||||
'add_newdoc': 'numpy.core.function_base.add_newdoc',
|
||||
'add_newdoc_ufunc': 'numpy.core._multiarray_umath._add_newdoc_ufunc',
|
||||
'byte_bounds': 'numpy.lib.utils.byte_bounds',
|
||||
'compare_chararrays': 'numpy.core._multiarray_umath.compare_chararrays',
|
||||
'deprecate': 'numpy.lib.utils.deprecate',
|
||||
'deprecate_with_doc': 'numpy.lib.utils.<lambda>',
|
||||
'disp': 'numpy.lib.function_base.disp',
|
||||
'fastCopyAndTranspose': 'numpy.core._multiarray_umath._fastCopyAndTranspose',
|
||||
'get_array_wrap': 'numpy.lib.shape_base.get_array_wrap',
|
||||
'get_include': 'numpy.lib.utils.get_include',
|
||||
'int_asbuffer': 'numpy.core._multiarray_umath.int_asbuffer',
|
||||
'mafromtxt': 'numpy.lib.npyio.mafromtxt',
|
||||
'maximum_sctype': 'numpy.core.numerictypes.maximum_sctype',
|
||||
'ndfromtxt': 'numpy.lib.npyio.ndfromtxt',
|
||||
'recfromcsv': 'numpy.lib.npyio.recfromcsv',
|
||||
'recfromtxt': 'numpy.lib.npyio.recfromtxt',
|
||||
'safe_eval': 'numpy.lib.utils.safe_eval',
|
||||
'set_string_function': 'numpy.core.arrayprint.set_string_function',
|
||||
'show_config': 'numpy.__config__.show',
|
||||
'who': 'numpy.lib.utils.who',
|
||||
}
|
||||
# These built-in types are re-exported by numpy.
|
||||
builtins = {
|
||||
'bool': 'builtins.bool',
|
||||
'complex': 'builtins.complex',
|
||||
'float': 'builtins.float',
|
||||
'int': 'builtins.int',
|
||||
'long': 'builtins.int',
|
||||
'object': 'builtins.object',
|
||||
'str': 'builtins.str',
|
||||
'unicode': 'builtins.str',
|
||||
}
|
||||
whitelist = dict(undocumented, **builtins)
|
||||
bad_results = check_dir(np)
|
||||
# pytest gives better error messages with the builtin assert than with
|
||||
# assert_equal
|
||||
assert bad_results == whitelist
|
||||
|
||||
|
||||
def test_numpy_linalg():
|
||||
bad_results = check_dir(np.linalg)
|
||||
assert bad_results == {}
|
||||
|
||||
|
||||
def test_numpy_fft():
|
||||
bad_results = check_dir(np.fft)
|
||||
assert bad_results == {}
|
||||
|
||||
@pytest.mark.skipif(ctypes is None,
|
||||
reason="ctypes not available in this python")
|
||||
def test_NPY_NO_EXPORT():
|
||||
cdll = ctypes.CDLL(np.core._multiarray_tests.__file__)
|
||||
# Make sure an arbitrary NPY_NO_EXPORT function is actually hidden
|
||||
f = getattr(cdll, 'test_not_exported', None)
|
||||
assert f is None, ("'test_not_exported' is mistakenly exported, "
|
||||
"NPY_NO_EXPORT does not work")
|
||||
@@ -0,0 +1,38 @@
|
||||
from __future__ import division, absolute_import, print_function
|
||||
|
||||
import sys
|
||||
|
||||
from numpy.testing import assert_raises, assert_, assert_equal
|
||||
from numpy.core.numeric import pickle
|
||||
|
||||
if sys.version_info[:2] >= (3, 4):
|
||||
from importlib import reload
|
||||
else:
|
||||
from imp import reload
|
||||
|
||||
def test_numpy_reloading():
|
||||
# gh-7844. Also check that relevant globals retain their identity.
|
||||
import numpy as np
|
||||
import numpy._globals
|
||||
|
||||
_NoValue = np._NoValue
|
||||
VisibleDeprecationWarning = np.VisibleDeprecationWarning
|
||||
ModuleDeprecationWarning = np.ModuleDeprecationWarning
|
||||
|
||||
reload(np)
|
||||
assert_(_NoValue is np._NoValue)
|
||||
assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
|
||||
assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
|
||||
|
||||
assert_raises(RuntimeError, reload, numpy._globals)
|
||||
reload(np)
|
||||
assert_(_NoValue is np._NoValue)
|
||||
assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
|
||||
assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
|
||||
|
||||
def test_novalue():
|
||||
import numpy as np
|
||||
for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
|
||||
assert_equal(repr(np._NoValue), '<no value>')
|
||||
assert_(pickle.loads(pickle.dumps(np._NoValue,
|
||||
protocol=proto)) is np._NoValue)
|
||||
@@ -0,0 +1,49 @@
|
||||
""" Test scripts
|
||||
|
||||
Test that we can run executable scripts that have been installed with numpy.
|
||||
"""
|
||||
from __future__ import division, print_function, absolute_import
|
||||
|
||||
import sys
|
||||
import os
|
||||
import pytest
|
||||
from os.path import join as pathjoin, isfile, dirname
|
||||
import subprocess
|
||||
|
||||
import numpy as np
|
||||
from numpy.compat.py3k import basestring
|
||||
from numpy.testing import assert_, assert_equal
|
||||
|
||||
is_inplace = isfile(pathjoin(dirname(np.__file__), '..', 'setup.py'))
|
||||
|
||||
|
||||
def find_f2py_commands():
|
||||
if sys.platform == 'win32':
|
||||
exe_dir = dirname(sys.executable)
|
||||
if exe_dir.endswith('Scripts'): # virtualenv
|
||||
return [os.path.join(exe_dir, 'f2py')]
|
||||
else:
|
||||
return [os.path.join(exe_dir, "Scripts", 'f2py')]
|
||||
else:
|
||||
# Three scripts are installed in Unix-like systems:
|
||||
# 'f2py', 'f2py{major}', and 'f2py{major.minor}'. For example,
|
||||
# if installed with python3.7 the scripts would be named
|
||||
# 'f2py', 'f2py3', and 'f2py3.7'.
|
||||
version = sys.version_info
|
||||
major = str(version.major)
|
||||
minor = str(version.minor)
|
||||
return ['f2py', 'f2py' + major, 'f2py' + major + '.' + minor]
|
||||
|
||||
|
||||
@pytest.mark.skipif(is_inplace, reason="Cannot test f2py command inplace")
|
||||
@pytest.mark.xfail(reason="Test is unreliable")
|
||||
@pytest.mark.parametrize('f2py_cmd', find_f2py_commands())
|
||||
def test_f2py(f2py_cmd):
|
||||
# test that we can run f2py script
|
||||
stdout = subprocess.check_output([f2py_cmd, '-v'])
|
||||
assert_equal(stdout.strip(), b'2')
|
||||
|
||||
|
||||
def test_pep338():
|
||||
stdout = subprocess.check_output([sys.executable, '-mnumpy.f2py', '-v'])
|
||||
assert_equal(stdout.strip(), b'2')
|
||||
@@ -0,0 +1,78 @@
|
||||
"""
|
||||
Tests which scan for certain occurrences in the code, they may not find
|
||||
all of these occurrences but should catch almost all.
|
||||
"""
|
||||
from __future__ import division, absolute_import, print_function
|
||||
|
||||
import sys
|
||||
import pytest
|
||||
|
||||
if sys.version_info >= (3, 4):
|
||||
from pathlib import Path
|
||||
import ast
|
||||
import tokenize
|
||||
import numpy
|
||||
|
||||
class ParseCall(ast.NodeVisitor):
|
||||
def __init__(self):
|
||||
self.ls = []
|
||||
|
||||
def visit_Attribute(self, node):
|
||||
ast.NodeVisitor.generic_visit(self, node)
|
||||
self.ls.append(node.attr)
|
||||
|
||||
def visit_Name(self, node):
|
||||
self.ls.append(node.id)
|
||||
|
||||
|
||||
class FindFuncs(ast.NodeVisitor):
|
||||
def __init__(self, filename):
|
||||
super().__init__()
|
||||
self.__filename = filename
|
||||
|
||||
def visit_Call(self, node):
|
||||
p = ParseCall()
|
||||
p.visit(node.func)
|
||||
ast.NodeVisitor.generic_visit(self, node)
|
||||
|
||||
if p.ls[-1] == 'simplefilter' or p.ls[-1] == 'filterwarnings':
|
||||
if node.args[0].s == "ignore":
|
||||
raise AssertionError(
|
||||
"ignore filter should not be used; found in "
|
||||
"{} on line {}".format(self.__filename, node.lineno))
|
||||
|
||||
if p.ls[-1] == 'warn' and (
|
||||
len(p.ls) == 1 or p.ls[-2] == 'warnings'):
|
||||
|
||||
if "testing/tests/test_warnings.py" is self.__filename:
|
||||
# This file
|
||||
return
|
||||
|
||||
# See if stacklevel exists:
|
||||
if len(node.args) == 3:
|
||||
return
|
||||
args = {kw.arg for kw in node.keywords}
|
||||
if "stacklevel" in args:
|
||||
return
|
||||
raise AssertionError(
|
||||
"warnings should have an appropriate stacklevel; found in "
|
||||
"{} on line {}".format(self.__filename, node.lineno))
|
||||
|
||||
|
||||
@pytest.mark.slow
|
||||
def test_warning_calls():
|
||||
# combined "ignore" and stacklevel error
|
||||
base = Path(numpy.__file__).parent
|
||||
|
||||
for path in base.rglob("*.py"):
|
||||
if base / "testing" in path.parents:
|
||||
continue
|
||||
if path == base / "__init__.py":
|
||||
continue
|
||||
if path == base / "random" / "__init__.py":
|
||||
continue
|
||||
# use tokenize to auto-detect encoding on systems where no
|
||||
# default encoding is defined (e.g. LANG='C')
|
||||
with tokenize.open(str(path)) as file:
|
||||
tree = ast.parse(file.read())
|
||||
FindFuncs(path).visit(tree)
|
||||
Reference in New Issue
Block a user