[Python-checkins] bpo-37798: Test both Python and C versions in test_statistics.py (GH-15453) (GH-15467)
Raymond Hettinger
webhook-mailer at python.org
Sat Aug 24 14:14:25 EDT 2019
https://github.com/python/cpython/commit/d5a66bc56f68d0f7cc3470722a31d7f731754af6
commit: d5a66bc56f68d0f7cc3470722a31d7f731754af6
branch: 3.8
author: Miss Islington (bot) <31488909+miss-islington at users.noreply.github.com>
committer: Raymond Hettinger <rhettinger at users.noreply.github.com>
date: 2019-08-24T11:14:20-07:00
summary:
bpo-37798: Test both Python and C versions in test_statistics.py (GH-15453) (GH-15467)
(cherry picked from commit 8ad22a42267d4ecb1c080d420933680cc126363e)
Co-authored-by: Dong-hee Na <donghee.na92 at gmail.com>
files:
A Misc/NEWS.d/next/Library/2019-08-24-16-54-49.bpo-37798.7mRQCk.rst
M Lib/test/test_statistics.py
diff --git a/Lib/test/test_statistics.py b/Lib/test/test_statistics.py
index 104718ed7db6..23dd96e365a8 100644
--- a/Lib/test/test_statistics.py
+++ b/Lib/test/test_statistics.py
@@ -18,6 +18,7 @@
from decimal import Decimal
from fractions import Fraction
+from test import support
# Module to be tested.
@@ -178,6 +179,23 @@ class _DoNothing:
# We prefer this for testing numeric values that may not be exactly equal,
# and avoid using TestCase.assertAlmostEqual, because it sucks :-)
+py_statistics = support.import_fresh_module('statistics', blocked=['_statistics'])
+c_statistics = support.import_fresh_module('statistics', fresh=['_statistics'])
+
+
+class TestModules(unittest.TestCase):
+ func_names = ['_normal_dist_inv_cdf']
+
+ def test_py_functions(self):
+ for fname in self.func_names:
+ self.assertEqual(getattr(py_statistics, fname).__module__, 'statistics')
+
+ @unittest.skipUnless(c_statistics, 'requires _statistics')
+ def test_c_functions(self):
+ for fname in self.func_names:
+ self.assertEqual(getattr(c_statistics, fname).__module__, '_statistics')
+
+
class NumericTestCase(unittest.TestCase):
"""Unit test class for numeric work.
@@ -2314,7 +2332,7 @@ def test_error_cases(self):
quantiles([10, None, 30], n=4) # data is non-numeric
-class TestNormalDist(unittest.TestCase):
+class TestNormalDist:
# General note on precision: The pdf(), cdf(), and overlap() methods
# depend on functions in the math libraries that do not make
@@ -2324,35 +2342,35 @@ class TestNormalDist(unittest.TestCase):
# implementing our own implementations from scratch.
def test_slots(self):
- nd = statistics.NormalDist(300, 23)
+ nd = self.module.NormalDist(300, 23)
with self.assertRaises(TypeError):
vars(nd)
self.assertEqual(tuple(nd.__slots__), ('_mu', '_sigma'))
def test_instantiation_and_attributes(self):
- nd = statistics.NormalDist(500, 17)
+ nd = self.module.NormalDist(500, 17)
self.assertEqual(nd.mean, 500)
self.assertEqual(nd.stdev, 17)
self.assertEqual(nd.variance, 17**2)
# default arguments
- nd = statistics.NormalDist()
+ nd = self.module.NormalDist()
self.assertEqual(nd.mean, 0)
self.assertEqual(nd.stdev, 1)
self.assertEqual(nd.variance, 1**2)
# error case: negative sigma
- with self.assertRaises(statistics.StatisticsError):
- statistics.NormalDist(500, -10)
+ with self.assertRaises(self.module.StatisticsError):
+ self.module.NormalDist(500, -10)
# verify that subclass type is honored
- class NewNormalDist(statistics.NormalDist):
+ class NewNormalDist(self.module.NormalDist):
pass
nnd = NewNormalDist(200, 5)
self.assertEqual(type(nnd), NewNormalDist)
def test_alternative_constructor(self):
- NormalDist = statistics.NormalDist
+ NormalDist = self.module.NormalDist
data = [96, 107, 90, 92, 110]
# list input
self.assertEqual(NormalDist.from_samples(data), NormalDist(99, 9))
@@ -2361,9 +2379,9 @@ def test_alternative_constructor(self):
# iterator input
self.assertEqual(NormalDist.from_samples(iter(data)), NormalDist(99, 9))
# error cases
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
NormalDist.from_samples([]) # empty input
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
NormalDist.from_samples([10]) # only one input
# verify that subclass type is honored
@@ -2373,7 +2391,7 @@ class NewNormalDist(NormalDist):
self.assertEqual(type(nnd), NewNormalDist)
def test_sample_generation(self):
- NormalDist = statistics.NormalDist
+ NormalDist = self.module.NormalDist
mu, sigma = 10_000, 3.0
X = NormalDist(mu, sigma)
n = 1_000
@@ -2381,7 +2399,7 @@ def test_sample_generation(self):
self.assertEqual(len(data), n)
self.assertEqual(set(map(type, data)), {float})
# mean(data) expected to fall within 8 standard deviations
- xbar = statistics.mean(data)
+ xbar = self.module.mean(data)
self.assertTrue(mu - sigma*8 <= xbar <= mu + sigma*8)
# verify that seeding makes reproducible sequences
@@ -2395,7 +2413,7 @@ def test_sample_generation(self):
self.assertNotEqual(data1, data2)
def test_pdf(self):
- NormalDist = statistics.NormalDist
+ NormalDist = self.module.NormalDist
X = NormalDist(100, 15)
# Verify peak around center
self.assertLess(X.pdf(99), X.pdf(100))
@@ -2426,7 +2444,7 @@ def test_pdf(self):
self.assertAlmostEqual(Z.pdf(-x / 100.0), px, places=4)
# Error case: variance is zero
Y = NormalDist(100, 0)
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
Y.pdf(90)
# Special values
self.assertEqual(X.pdf(float('-Inf')), 0.0)
@@ -2434,7 +2452,7 @@ def test_pdf(self):
self.assertTrue(math.isnan(X.pdf(float('NaN'))))
def test_cdf(self):
- NormalDist = statistics.NormalDist
+ NormalDist = self.module.NormalDist
X = NormalDist(100, 15)
cdfs = [X.cdf(x) for x in range(1, 200)]
self.assertEqual(set(map(type, cdfs)), {float})
@@ -2456,7 +2474,7 @@ def test_cdf(self):
self.assertAlmostEqual(Z.cdf(-z), 1.0 - cum_prob, places=5)
# Error case: variance is zero
Y = NormalDist(100, 0)
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
Y.cdf(90)
# Special values
self.assertEqual(X.cdf(float('-Inf')), 0.0)
@@ -2465,7 +2483,7 @@ def test_cdf(self):
@support.skip_if_pgo_task
def test_inv_cdf(self):
- NormalDist = statistics.NormalDist
+ NormalDist = self.module.NormalDist
# Center case should be exact.
iq = NormalDist(100, 15)
@@ -2513,15 +2531,15 @@ def test_inv_cdf(self):
self.assertAlmostEqual(iq.inv_cdf(iq.cdf(x)), x, places=5)
# Error cases:
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
iq.inv_cdf(0.0) # p is zero
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
iq.inv_cdf(-0.1) # p under zero
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
iq.inv_cdf(1.0) # p is one
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
iq.inv_cdf(1.1) # p over one
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
iq = NormalDist(100, 0) # sigma is zero
iq.inv_cdf(0.5)
@@ -2529,7 +2547,7 @@ def test_inv_cdf(self):
self.assertTrue(math.isnan(Z.inv_cdf(float('NaN'))))
def test_overlap(self):
- NormalDist = statistics.NormalDist
+ NormalDist = self.module.NormalDist
# Match examples from Imman and Bradley
for X1, X2, published_result in [
@@ -2586,26 +2604,26 @@ def overlap_numeric(X, Y, *, steps=8_192, z=5):
X.overlap(X, X) # too may arguments
with self.assertRaises(TypeError):
X.overlap(None) # right operand not a NormalDist
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
X.overlap(NormalDist(1, 0)) # right operand sigma is zero
- with self.assertRaises(statistics.StatisticsError):
+ with self.assertRaises(self.module.StatisticsError):
NormalDist(1, 0).overlap(X) # left operand sigma is zero
def test_properties(self):
- X = statistics.NormalDist(100, 15)
+ X = self.module.NormalDist(100, 15)
self.assertEqual(X.mean, 100)
self.assertEqual(X.stdev, 15)
self.assertEqual(X.variance, 225)
def test_same_type_addition_and_subtraction(self):
- NormalDist = statistics.NormalDist
+ NormalDist = self.module.NormalDist
X = NormalDist(100, 12)
Y = NormalDist(40, 5)
self.assertEqual(X + Y, NormalDist(140, 13)) # __add__
self.assertEqual(X - Y, NormalDist(60, 13)) # __sub__
def test_translation_and_scaling(self):
- NormalDist = statistics.NormalDist
+ NormalDist = self.module.NormalDist
X = NormalDist(100, 15)
y = 10
self.assertEqual(+X, NormalDist(100, 15)) # __pos__
@@ -2621,7 +2639,7 @@ def test_translation_and_scaling(self):
y / X
def test_unary_operations(self):
- NormalDist = statistics.NormalDist
+ NormalDist = self.module.NormalDist
X = NormalDist(100, 12)
Y = +X
self.assertIsNot(X, Y)
@@ -2633,7 +2651,7 @@ def test_unary_operations(self):
self.assertEqual(X.stdev, Y.stdev)
def test_equality(self):
- NormalDist = statistics.NormalDist
+ NormalDist = self.module.NormalDist
nd1 = NormalDist()
nd2 = NormalDist(2, 4)
nd3 = NormalDist()
@@ -2673,7 +2691,7 @@ def __init__(self, mu, sigma):
self.assertNotEqual(nd, lnd)
def test_pickle_and_copy(self):
- nd = statistics.NormalDist(37.5, 5.625)
+ nd = self.module.NormalDist(37.5, 5.625)
nd1 = copy.copy(nd)
self.assertEqual(nd, nd1)
nd2 = copy.deepcopy(nd)
@@ -2682,14 +2700,36 @@ def test_pickle_and_copy(self):
self.assertEqual(nd, nd3)
def test_hashability(self):
- ND = statistics.NormalDist
+ ND = self.module.NormalDist
s = {ND(100, 15), ND(100.0, 15.0), ND(100, 10), ND(95, 15), ND(100, 15)}
self.assertEqual(len(s), 3)
def test_repr(self):
- nd = statistics.NormalDist(37.5, 5.625)
+ nd = self.module.NormalDist(37.5, 5.625)
self.assertEqual(repr(nd), 'NormalDist(mu=37.5, sigma=5.625)')
+# Swapping the sys.modules['statistics'] is to solving the
+# _pickle.PicklingError:
+# Can't pickle <class 'statistics.NormalDist'>:
+# it's not the same object as statistics.NormalDist
+class TestNormalDistPython(unittest.TestCase, TestNormalDist):
+ module = py_statistics
+ def setUp(self):
+ sys.modules['statistics'] = self.module
+
+ def tearDown(self):
+ sys.modules['statistics'] = statistics
+
+
+ at unittest.skipUnless(c_statistics, 'requires _statistics')
+class TestNormalDistC(unittest.TestCase, TestNormalDist):
+ module = c_statistics
+ def setUp(self):
+ sys.modules['statistics'] = self.module
+
+ def tearDown(self):
+ sys.modules['statistics'] = statistics
+
# === Run tests ===
diff --git a/Misc/NEWS.d/next/Library/2019-08-24-16-54-49.bpo-37798.7mRQCk.rst b/Misc/NEWS.d/next/Library/2019-08-24-16-54-49.bpo-37798.7mRQCk.rst
new file mode 100644
index 000000000000..25cfa0047886
--- /dev/null
+++ b/Misc/NEWS.d/next/Library/2019-08-24-16-54-49.bpo-37798.7mRQCk.rst
@@ -0,0 +1,2 @@
+Update test_statistics.py to verify that the statistics module works well
+for both C and Python implementations. Patch by Dong-hee Na
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