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bpo-37798: Test both Python and C versions in test_statistics.py (GH-15453)
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‎Lib/test/test_statistics.py‎

Lines changed: 73 additions & 33 deletions
Original file line numberDiff line numberDiff line change
@@ -18,6 +18,7 @@
1818

1919
from decimal import Decimal
2020
from fractions import Fraction
21+
from test import support
2122

2223

2324
# Module to be tested.
@@ -178,6 +179,23 @@ class _DoNothing:
178179
# We prefer this for testing numeric values that may not be exactly equal,
179180
# and avoid using TestCase.assertAlmostEqual, because it sucks :-)
180181

182+
py_statistics = support.import_fresh_module('statistics', blocked=['_statistics'])
183+
c_statistics = support.import_fresh_module('statistics', fresh=['_statistics'])
184+
185+
186+
class TestModules(unittest.TestCase):
187+
func_names = ['_normal_dist_inv_cdf']
188+
189+
def test_py_functions(self):
190+
for fname in self.func_names:
191+
self.assertEqual(getattr(py_statistics, fname).__module__, 'statistics')
192+
193+
@unittest.skipUnless(c_statistics, 'requires _statistics')
194+
def test_c_functions(self):
195+
for fname in self.func_names:
196+
self.assertEqual(getattr(c_statistics, fname).__module__, '_statistics')
197+
198+
181199
class NumericTestCase(unittest.TestCase):
182200
"""Unit test class for numeric work.
183201
@@ -2314,7 +2332,7 @@ def test_error_cases(self):
23142332
quantiles([10, None, 30], n=4) # data is non-numeric
23152333

23162334

2317-
class TestNormalDist(unittest.TestCase):
2335+
class TestNormalDist:
23182336

23192337
# General note on precision: The pdf(), cdf(), and overlap() methods
23202338
# depend on functions in the math libraries that do not make
@@ -2324,35 +2342,35 @@ class TestNormalDist(unittest.TestCase):
23242342
# implementing our own implementations from scratch.
23252343

23262344
def test_slots(self):
2327-
nd = statistics.NormalDist(300, 23)
2345+
nd = self.module.NormalDist(300, 23)
23282346
with self.assertRaises(TypeError):
23292347
vars(nd)
23302348
self.assertEqual(tuple(nd.__slots__), ('_mu', '_sigma'))
23312349

23322350
def test_instantiation_and_attributes(self):
2333-
nd = statistics.NormalDist(500, 17)
2351+
nd = self.module.NormalDist(500, 17)
23342352
self.assertEqual(nd.mean, 500)
23352353
self.assertEqual(nd.stdev, 17)
23362354
self.assertEqual(nd.variance, 17**2)
23372355

23382356
# default arguments
2339-
nd = statistics.NormalDist()
2357+
nd = self.module.NormalDist()
23402358
self.assertEqual(nd.mean, 0)
23412359
self.assertEqual(nd.stdev, 1)
23422360
self.assertEqual(nd.variance, 1**2)
23432361

23442362
# error case: negative sigma
2345-
with self.assertRaises(statistics.StatisticsError):
2346-
statistics.NormalDist(500, -10)
2363+
with self.assertRaises(self.module.StatisticsError):
2364+
self.module.NormalDist(500, -10)
23472365

23482366
# verify that subclass type is honored
2349-
class NewNormalDist(statistics.NormalDist):
2367+
class NewNormalDist(self.module.NormalDist):
23502368
pass
23512369
nnd = NewNormalDist(200, 5)
23522370
self.assertEqual(type(nnd), NewNormalDist)
23532371

23542372
def test_alternative_constructor(self):
2355-
NormalDist = statistics.NormalDist
2373+
NormalDist = self.module.NormalDist
23562374
data = [96, 107, 90, 92, 110]
23572375
# list input
23582376
self.assertEqual(NormalDist.from_samples(data), NormalDist(99, 9))
@@ -2361,9 +2379,9 @@ def test_alternative_constructor(self):
23612379
# iterator input
23622380
self.assertEqual(NormalDist.from_samples(iter(data)), NormalDist(99, 9))
23632381
# error cases
2364-
with self.assertRaises(statistics.StatisticsError):
2382+
with self.assertRaises(self.module.StatisticsError):
23652383
NormalDist.from_samples([]) # empty input
2366-
with self.assertRaises(statistics.StatisticsError):
2384+
with self.assertRaises(self.module.StatisticsError):
23672385
NormalDist.from_samples([10]) # only one input
23682386

23692387
# verify that subclass type is honored
@@ -2373,15 +2391,15 @@ class NewNormalDist(NormalDist):
23732391
self.assertEqual(type(nnd), NewNormalDist)
23742392

23752393
def test_sample_generation(self):
2376-
NormalDist = statistics.NormalDist
2394+
NormalDist = self.module.NormalDist
23772395
mu, sigma = 10_000, 3.0
23782396
X = NormalDist(mu, sigma)
23792397
n = 1_000
23802398
data = X.samples(n)
23812399
self.assertEqual(len(data), n)
23822400
self.assertEqual(set(map(type, data)), {float})
23832401
# mean(data) expected to fall within 8 standard deviations
2384-
xbar = statistics.mean(data)
2402+
xbar = self.module.mean(data)
23852403
self.assertTrue(mu - sigma*8 <= xbar <= mu + sigma*8)
23862404

23872405
# verify that seeding makes reproducible sequences
@@ -2395,7 +2413,7 @@ def test_sample_generation(self):
23952413
self.assertNotEqual(data1, data2)
23962414

23972415
def test_pdf(self):
2398-
NormalDist = statistics.NormalDist
2416+
NormalDist = self.module.NormalDist
23992417
X = NormalDist(100, 15)
24002418
# Verify peak around center
24012419
self.assertLess(X.pdf(99), X.pdf(100))
@@ -2426,15 +2444,15 @@ def test_pdf(self):
24262444
self.assertAlmostEqual(Z.pdf(-x / 100.0), px, places=4)
24272445
# Error case: variance is zero
24282446
Y = NormalDist(100, 0)
2429-
with self.assertRaises(statistics.StatisticsError):
2447+
with self.assertRaises(self.module.StatisticsError):
24302448
Y.pdf(90)
24312449
# Special values
24322450
self.assertEqual(X.pdf(float('-Inf')), 0.0)
24332451
self.assertEqual(X.pdf(float('Inf')), 0.0)
24342452
self.assertTrue(math.isnan(X.pdf(float('NaN'))))
24352453

24362454
def test_cdf(self):
2437-
NormalDist = statistics.NormalDist
2455+
NormalDist = self.module.NormalDist
24382456
X = NormalDist(100, 15)
24392457
cdfs = [X.cdf(x) for x in range(1, 200)]
24402458
self.assertEqual(set(map(type, cdfs)), {float})
@@ -2456,7 +2474,7 @@ def test_cdf(self):
24562474
self.assertAlmostEqual(Z.cdf(-z), 1.0 - cum_prob, places=5)
24572475
# Error case: variance is zero
24582476
Y = NormalDist(100, 0)
2459-
with self.assertRaises(statistics.StatisticsError):
2477+
with self.assertRaises(self.module.StatisticsError):
24602478
Y.cdf(90)
24612479
# Special values
24622480
self.assertEqual(X.cdf(float('-Inf')), 0.0)
@@ -2465,7 +2483,7 @@ def test_cdf(self):
24652483

24662484
@support.skip_if_pgo_task
24672485
def test_inv_cdf(self):
2468-
NormalDist = statistics.NormalDist
2486+
NormalDist = self.module.NormalDist
24692487

24702488
# Center case should be exact.
24712489
iq = NormalDist(100, 15)
@@ -2513,23 +2531,23 @@ def test_inv_cdf(self):
25132531
self.assertAlmostEqual(iq.inv_cdf(iq.cdf(x)), x, places=5)
25142532

25152533
# Error cases:
2516-
with self.assertRaises(statistics.StatisticsError):
2534+
with self.assertRaises(self.module.StatisticsError):
25172535
iq.inv_cdf(0.0) # p is zero
2518-
with self.assertRaises(statistics.StatisticsError):
2536+
with self.assertRaises(self.module.StatisticsError):
25192537
iq.inv_cdf(-0.1) # p under zero
2520-
with self.assertRaises(statistics.StatisticsError):
2538+
with self.assertRaises(self.module.StatisticsError):
25212539
iq.inv_cdf(1.0) # p is one
2522-
with self.assertRaises(statistics.StatisticsError):
2540+
with self.assertRaises(self.module.StatisticsError):
25232541
iq.inv_cdf(1.1) # p over one
2524-
with self.assertRaises(statistics.StatisticsError):
2542+
with self.assertRaises(self.module.StatisticsError):
25252543
iq = NormalDist(100, 0) # sigma is zero
25262544
iq.inv_cdf(0.5)
25272545

25282546
# Special values
25292547
self.assertTrue(math.isnan(Z.inv_cdf(float('NaN'))))
25302548

25312549
def test_overlap(self):
2532-
NormalDist = statistics.NormalDist
2550+
NormalDist = self.module.NormalDist
25332551

25342552
# Match examples from Imman and Bradley
25352553
for X1, X2, published_result in [
@@ -2586,26 +2604,26 @@ def overlap_numeric(X, Y, *, steps=8_192, z=5):
25862604
X.overlap(X, X) # too may arguments
25872605
with self.assertRaises(TypeError):
25882606
X.overlap(None) # right operand not a NormalDist
2589-
with self.assertRaises(statistics.StatisticsError):
2607+
with self.assertRaises(self.module.StatisticsError):
25902608
X.overlap(NormalDist(1, 0)) # right operand sigma is zero
2591-
with self.assertRaises(statistics.StatisticsError):
2609+
with self.assertRaises(self.module.StatisticsError):
25922610
NormalDist(1, 0).overlap(X) # left operand sigma is zero
25932611

25942612
def test_properties(self):
2595-
X = statistics.NormalDist(100, 15)
2613+
X = self.module.NormalDist(100, 15)
25962614
self.assertEqual(X.mean, 100)
25972615
self.assertEqual(X.stdev, 15)
25982616
self.assertEqual(X.variance, 225)
25992617

26002618
def test_same_type_addition_and_subtraction(self):
2601-
NormalDist = statistics.NormalDist
2619+
NormalDist = self.module.NormalDist
26022620
X = NormalDist(100, 12)
26032621
Y = NormalDist(40, 5)
26042622
self.assertEqual(X + Y, NormalDist(140, 13)) # __add__
26052623
self.assertEqual(X - Y, NormalDist(60, 13)) # __sub__
26062624

26072625
def test_translation_and_scaling(self):
2608-
NormalDist = statistics.NormalDist
2626+
NormalDist = self.module.NormalDist
26092627
X = NormalDist(100, 15)
26102628
y = 10
26112629
self.assertEqual(+X, NormalDist(100, 15)) # __pos__
@@ -2621,7 +2639,7 @@ def test_translation_and_scaling(self):
26212639
y / X
26222640

26232641
def test_unary_operations(self):
2624-
NormalDist = statistics.NormalDist
2642+
NormalDist = self.module.NormalDist
26252643
X = NormalDist(100, 12)
26262644
Y = +X
26272645
self.assertIsNot(X, Y)
@@ -2633,7 +2651,7 @@ def test_unary_operations(self):
26332651
self.assertEqual(X.stdev, Y.stdev)
26342652

26352653
def test_equality(self):
2636-
NormalDist = statistics.NormalDist
2654+
NormalDist = self.module.NormalDist
26372655
nd1 = NormalDist()
26382656
nd2 = NormalDist(2, 4)
26392657
nd3 = NormalDist()
@@ -2673,7 +2691,7 @@ def __init__(self, mu, sigma):
26732691
self.assertNotEqual(nd, lnd)
26742692

26752693
def test_pickle_and_copy(self):
2676-
nd = statistics.NormalDist(37.5, 5.625)
2694+
nd = self.module.NormalDist(37.5, 5.625)
26772695
nd1 = copy.copy(nd)
26782696
self.assertEqual(nd, nd1)
26792697
nd2 = copy.deepcopy(nd)
@@ -2682,14 +2700,36 @@ def test_pickle_and_copy(self):
26822700
self.assertEqual(nd, nd3)
26832701

26842702
def test_hashability(self):
2685-
ND = statistics.NormalDist
2703+
ND = self.module.NormalDist
26862704
s = {ND(100, 15), ND(100.0, 15.0), ND(100, 10), ND(95, 15), ND(100, 15)}
26872705
self.assertEqual(len(s), 3)
26882706

26892707
def test_repr(self):
2690-
nd = statistics.NormalDist(37.5, 5.625)
2708+
nd = self.module.NormalDist(37.5, 5.625)
26912709
self.assertEqual(repr(nd), 'NormalDist(mu=37.5, sigma=5.625)')
26922710

2711+
# Swapping the sys.modules['statistics'] is to solving the
2712+
# _pickle.PicklingError:
2713+
# Can't pickle <class 'statistics.NormalDist'>:
2714+
# it's not the same object as statistics.NormalDist
2715+
class TestNormalDistPython(unittest.TestCase, TestNormalDist):
2716+
module = py_statistics
2717+
def setUp(self):
2718+
sys.modules['statistics'] = self.module
2719+
2720+
def tearDown(self):
2721+
sys.modules['statistics'] = statistics
2722+
2723+
2724+
@unittest.skipUnless(c_statistics, 'requires _statistics')
2725+
class TestNormalDistC(unittest.TestCase, TestNormalDist):
2726+
module = c_statistics
2727+
def setUp(self):
2728+
sys.modules['statistics'] = self.module
2729+
2730+
def tearDown(self):
2731+
sys.modules['statistics'] = statistics
2732+
26932733

26942734
# === Run tests ===
26952735

‎Misc/NEWS.d/next/Library/2019-08-24-16-54-49.bpo-37798.7mRQCk.rst‎

Lines changed: 2 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,2 @@
1+
Update test_statistics.py to verify that the statistics module works well
2+
for both C and Python implementations. Patch by Dong-hee Na

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