/usr/lib/python2.7/test/test_random.py is in libpython2.7-testsuite 2.7.6-8.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 | import unittest
import random
import time
import pickle
import warnings
from math import log, exp, pi, fsum, sin
from functools import reduce
from test import test_support
class TestBasicOps(unittest.TestCase):
# Superclass with tests common to all generators.
# Subclasses must arrange for self.gen to retrieve the Random instance
# to be tested.
def randomlist(self, n):
"""Helper function to make a list of random numbers"""
return [self.gen.random() for i in xrange(n)]
def test_autoseed(self):
self.gen.seed()
state1 = self.gen.getstate()
time.sleep(0.1)
self.gen.seed() # diffent seeds at different times
state2 = self.gen.getstate()
self.assertNotEqual(state1, state2)
def test_saverestore(self):
N = 1000
self.gen.seed()
state = self.gen.getstate()
randseq = self.randomlist(N)
self.gen.setstate(state) # should regenerate the same sequence
self.assertEqual(randseq, self.randomlist(N))
def test_seedargs(self):
for arg in [None, 0, 0L, 1, 1L, -1, -1L, 10**20, -(10**20),
3.14, 1+2j, 'a', tuple('abc')]:
self.gen.seed(arg)
for arg in [range(3), dict(one=1)]:
self.assertRaises(TypeError, self.gen.seed, arg)
self.assertRaises(TypeError, self.gen.seed, 1, 2)
self.assertRaises(TypeError, type(self.gen), [])
def test_jumpahead(self):
self.gen.seed()
state1 = self.gen.getstate()
self.gen.jumpahead(100)
state2 = self.gen.getstate() # s/b distinct from state1
self.assertNotEqual(state1, state2)
self.gen.jumpahead(100)
state3 = self.gen.getstate() # s/b distinct from state2
self.assertNotEqual(state2, state3)
with test_support.check_py3k_warnings(quiet=True):
self.assertRaises(TypeError, self.gen.jumpahead) # needs an arg
self.assertRaises(TypeError, self.gen.jumpahead, 2, 3) # too many
def test_jumpahead_produces_valid_state(self):
# From http://bugs.python.org/issue14591.
self.gen.seed(199210368)
self.gen.jumpahead(13550674232554645900)
for i in range(500):
val = self.gen.random()
self.assertLess(val, 1.0)
def test_sample(self):
# For the entire allowable range of 0 <= k <= N, validate that
# the sample is of the correct length and contains only unique items
N = 100
population = xrange(N)
for k in xrange(N+1):
s = self.gen.sample(population, k)
self.assertEqual(len(s), k)
uniq = set(s)
self.assertEqual(len(uniq), k)
self.assertTrue(uniq <= set(population))
self.assertEqual(self.gen.sample([], 0), []) # test edge case N==k==0
def test_sample_distribution(self):
# For the entire allowable range of 0 <= k <= N, validate that
# sample generates all possible permutations
n = 5
pop = range(n)
trials = 10000 # large num prevents false negatives without slowing normal case
def factorial(n):
return reduce(int.__mul__, xrange(1, n), 1)
for k in xrange(n):
expected = factorial(n) // factorial(n-k)
perms = {}
for i in xrange(trials):
perms[tuple(self.gen.sample(pop, k))] = None
if len(perms) == expected:
break
else:
self.fail()
def test_sample_inputs(self):
# SF bug #801342 -- population can be any iterable defining __len__()
self.gen.sample(set(range(20)), 2)
self.gen.sample(range(20), 2)
self.gen.sample(xrange(20), 2)
self.gen.sample(str('abcdefghijklmnopqrst'), 2)
self.gen.sample(tuple('abcdefghijklmnopqrst'), 2)
def test_sample_on_dicts(self):
self.gen.sample(dict.fromkeys('abcdefghijklmnopqrst'), 2)
# SF bug #1460340 -- random.sample can raise KeyError
a = dict.fromkeys(range(10)+range(10,100,2)+range(100,110))
self.gen.sample(a, 3)
# A followup to bug #1460340: sampling from a dict could return
# a subset of its keys or of its values, depending on the size of
# the subset requested.
N = 30
d = dict((i, complex(i, i)) for i in xrange(N))
for k in xrange(N+1):
samp = self.gen.sample(d, k)
# Verify that we got ints back (keys); the values are complex.
for x in samp:
self.assertTrue(type(x) is int)
samp.sort()
self.assertEqual(samp, range(N))
def test_gauss(self):
# Ensure that the seed() method initializes all the hidden state. In
# particular, through 2.2.1 it failed to reset a piece of state used
# by (and only by) the .gauss() method.
for seed in 1, 12, 123, 1234, 12345, 123456, 654321:
self.gen.seed(seed)
x1 = self.gen.random()
y1 = self.gen.gauss(0, 1)
self.gen.seed(seed)
x2 = self.gen.random()
y2 = self.gen.gauss(0, 1)
self.assertEqual(x1, x2)
self.assertEqual(y1, y2)
def test_pickling(self):
state = pickle.dumps(self.gen)
origseq = [self.gen.random() for i in xrange(10)]
newgen = pickle.loads(state)
restoredseq = [newgen.random() for i in xrange(10)]
self.assertEqual(origseq, restoredseq)
def test_bug_1727780(self):
# verify that version-2-pickles can be loaded
# fine, whether they are created on 32-bit or 64-bit
# platforms, and that version-3-pickles load fine.
files = [("randv2_32.pck", 780),
("randv2_64.pck", 866),
("randv3.pck", 343)]
for file, value in files:
f = open(test_support.findfile(file),"rb")
r = pickle.load(f)
f.close()
self.assertEqual(r.randrange(1000), value)
class WichmannHill_TestBasicOps(TestBasicOps):
gen = random.WichmannHill()
def test_setstate_first_arg(self):
self.assertRaises(ValueError, self.gen.setstate, (2, None, None))
def test_strong_jumpahead(self):
# tests that jumpahead(n) semantics correspond to n calls to random()
N = 1000
s = self.gen.getstate()
self.gen.jumpahead(N)
r1 = self.gen.random()
# now do it the slow way
self.gen.setstate(s)
for i in xrange(N):
self.gen.random()
r2 = self.gen.random()
self.assertEqual(r1, r2)
def test_gauss_with_whseed(self):
# Ensure that the seed() method initializes all the hidden state. In
# particular, through 2.2.1 it failed to reset a piece of state used
# by (and only by) the .gauss() method.
for seed in 1, 12, 123, 1234, 12345, 123456, 654321:
self.gen.whseed(seed)
x1 = self.gen.random()
y1 = self.gen.gauss(0, 1)
self.gen.whseed(seed)
x2 = self.gen.random()
y2 = self.gen.gauss(0, 1)
self.assertEqual(x1, x2)
self.assertEqual(y1, y2)
def test_bigrand(self):
# Verify warnings are raised when randrange is too large for random()
with warnings.catch_warnings():
warnings.filterwarnings("error", "Underlying random")
self.assertRaises(UserWarning, self.gen.randrange, 2**60)
class SystemRandom_TestBasicOps(TestBasicOps):
gen = random.SystemRandom()
def test_autoseed(self):
# Doesn't need to do anything except not fail
self.gen.seed()
def test_saverestore(self):
self.assertRaises(NotImplementedError, self.gen.getstate)
self.assertRaises(NotImplementedError, self.gen.setstate, None)
def test_seedargs(self):
# Doesn't need to do anything except not fail
self.gen.seed(100)
def test_jumpahead(self):
# Doesn't need to do anything except not fail
self.gen.jumpahead(100)
def test_gauss(self):
self.gen.gauss_next = None
self.gen.seed(100)
self.assertEqual(self.gen.gauss_next, None)
def test_pickling(self):
self.assertRaises(NotImplementedError, pickle.dumps, self.gen)
def test_53_bits_per_float(self):
# This should pass whenever a C double has 53 bit precision.
span = 2 ** 53
cum = 0
for i in xrange(100):
cum |= int(self.gen.random() * span)
self.assertEqual(cum, span-1)
def test_bigrand(self):
# The randrange routine should build-up the required number of bits
# in stages so that all bit positions are active.
span = 2 ** 500
cum = 0
for i in xrange(100):
r = self.gen.randrange(span)
self.assertTrue(0 <= r < span)
cum |= r
self.assertEqual(cum, span-1)
def test_bigrand_ranges(self):
for i in [40,80, 160, 200, 211, 250, 375, 512, 550]:
start = self.gen.randrange(2 ** (i-2))
stop = self.gen.randrange(2 ** i)
if stop <= start:
continue
self.assertTrue(start <= self.gen.randrange(start, stop) < stop)
def test_rangelimits(self):
for start, stop in [(-2,0), (-(2**60)-2,-(2**60)), (2**60,2**60+2)]:
self.assertEqual(set(range(start,stop)),
set([self.gen.randrange(start,stop) for i in xrange(100)]))
def test_genrandbits(self):
# Verify ranges
for k in xrange(1, 1000):
self.assertTrue(0 <= self.gen.getrandbits(k) < 2**k)
# Verify all bits active
getbits = self.gen.getrandbits
for span in [1, 2, 3, 4, 31, 32, 32, 52, 53, 54, 119, 127, 128, 129]:
cum = 0
for i in xrange(100):
cum |= getbits(span)
self.assertEqual(cum, 2**span-1)
# Verify argument checking
self.assertRaises(TypeError, self.gen.getrandbits)
self.assertRaises(TypeError, self.gen.getrandbits, 1, 2)
self.assertRaises(ValueError, self.gen.getrandbits, 0)
self.assertRaises(ValueError, self.gen.getrandbits, -1)
self.assertRaises(TypeError, self.gen.getrandbits, 10.1)
def test_randbelow_logic(self, _log=log, int=int):
# check bitcount transition points: 2**i and 2**(i+1)-1
# show that: k = int(1.001 + _log(n, 2))
# is equal to or one greater than the number of bits in n
for i in xrange(1, 1000):
n = 1L << i # check an exact power of two
numbits = i+1
k = int(1.00001 + _log(n, 2))
self.assertEqual(k, numbits)
self.assertTrue(n == 2**(k-1))
n += n - 1 # check 1 below the next power of two
k = int(1.00001 + _log(n, 2))
self.assertIn(k, [numbits, numbits+1])
self.assertTrue(2**k > n > 2**(k-2))
n -= n >> 15 # check a little farther below the next power of two
k = int(1.00001 + _log(n, 2))
self.assertEqual(k, numbits) # note the stronger assertion
self.assertTrue(2**k > n > 2**(k-1)) # note the stronger assertion
class MersenneTwister_TestBasicOps(TestBasicOps):
gen = random.Random()
def test_setstate_first_arg(self):
self.assertRaises(ValueError, self.gen.setstate, (1, None, None))
def test_setstate_middle_arg(self):
# Wrong type, s/b tuple
self.assertRaises(TypeError, self.gen.setstate, (2, None, None))
# Wrong length, s/b 625
self.assertRaises(ValueError, self.gen.setstate, (2, (1,2,3), None))
# Wrong type, s/b tuple of 625 ints
self.assertRaises(TypeError, self.gen.setstate, (2, ('a',)*625, None))
# Last element s/b an int also
self.assertRaises(TypeError, self.gen.setstate, (2, (0,)*624+('a',), None))
def test_referenceImplementation(self):
# Compare the python implementation with results from the original
# code. Create 2000 53-bit precision random floats. Compare only
# the last ten entries to show that the independent implementations
# are tracking. Here is the main() function needed to create the
# list of expected random numbers:
# void main(void){
# int i;
# unsigned long init[4]={61731, 24903, 614, 42143}, length=4;
# init_by_array(init, length);
# for (i=0; i<2000; i++) {
# printf("%.15f ", genrand_res53());
# if (i%5==4) printf("\n");
# }
# }
expected = [0.45839803073713259,
0.86057815201978782,
0.92848331726782152,
0.35932681119782461,
0.081823493762449573,
0.14332226470169329,
0.084297823823520024,
0.53814864671831453,
0.089215024911993401,
0.78486196105372907]
self.gen.seed(61731L + (24903L<<32) + (614L<<64) + (42143L<<96))
actual = self.randomlist(2000)[-10:]
for a, e in zip(actual, expected):
self.assertAlmostEqual(a,e,places=14)
def test_strong_reference_implementation(self):
# Like test_referenceImplementation, but checks for exact bit-level
# equality. This should pass on any box where C double contains
# at least 53 bits of precision (the underlying algorithm suffers
# no rounding errors -- all results are exact).
from math import ldexp
expected = [0x0eab3258d2231fL,
0x1b89db315277a5L,
0x1db622a5518016L,
0x0b7f9af0d575bfL,
0x029e4c4db82240L,
0x04961892f5d673L,
0x02b291598e4589L,
0x11388382c15694L,
0x02dad977c9e1feL,
0x191d96d4d334c6L]
self.gen.seed(61731L + (24903L<<32) + (614L<<64) + (42143L<<96))
actual = self.randomlist(2000)[-10:]
for a, e in zip(actual, expected):
self.assertEqual(long(ldexp(a, 53)), e)
def test_long_seed(self):
# This is most interesting to run in debug mode, just to make sure
# nothing blows up. Under the covers, a dynamically resized array
# is allocated, consuming space proportional to the number of bits
# in the seed. Unfortunately, that's a quadratic-time algorithm,
# so don't make this horribly big.
seed = (1L << (10000 * 8)) - 1 # about 10K bytes
self.gen.seed(seed)
def test_53_bits_per_float(self):
# This should pass whenever a C double has 53 bit precision.
span = 2 ** 53
cum = 0
for i in xrange(100):
cum |= int(self.gen.random() * span)
self.assertEqual(cum, span-1)
def test_bigrand(self):
# The randrange routine should build-up the required number of bits
# in stages so that all bit positions are active.
span = 2 ** 500
cum = 0
for i in xrange(100):
r = self.gen.randrange(span)
self.assertTrue(0 <= r < span)
cum |= r
self.assertEqual(cum, span-1)
def test_bigrand_ranges(self):
for i in [40,80, 160, 200, 211, 250, 375, 512, 550]:
start = self.gen.randrange(2 ** (i-2))
stop = self.gen.randrange(2 ** i)
if stop <= start:
continue
self.assertTrue(start <= self.gen.randrange(start, stop) < stop)
def test_rangelimits(self):
for start, stop in [(-2,0), (-(2**60)-2,-(2**60)), (2**60,2**60+2)]:
self.assertEqual(set(range(start,stop)),
set([self.gen.randrange(start,stop) for i in xrange(100)]))
def test_genrandbits(self):
# Verify cross-platform repeatability
self.gen.seed(1234567)
self.assertEqual(self.gen.getrandbits(100),
97904845777343510404718956115L)
# Verify ranges
for k in xrange(1, 1000):
self.assertTrue(0 <= self.gen.getrandbits(k) < 2**k)
# Verify all bits active
getbits = self.gen.getrandbits
for span in [1, 2, 3, 4, 31, 32, 32, 52, 53, 54, 119, 127, 128, 129]:
cum = 0
for i in xrange(100):
cum |= getbits(span)
self.assertEqual(cum, 2**span-1)
# Verify argument checking
self.assertRaises(TypeError, self.gen.getrandbits)
self.assertRaises(TypeError, self.gen.getrandbits, 'a')
self.assertRaises(TypeError, self.gen.getrandbits, 1, 2)
self.assertRaises(ValueError, self.gen.getrandbits, 0)
self.assertRaises(ValueError, self.gen.getrandbits, -1)
def test_randbelow_logic(self, _log=log, int=int):
# check bitcount transition points: 2**i and 2**(i+1)-1
# show that: k = int(1.001 + _log(n, 2))
# is equal to or one greater than the number of bits in n
for i in xrange(1, 1000):
n = 1L << i # check an exact power of two
numbits = i+1
k = int(1.00001 + _log(n, 2))
self.assertEqual(k, numbits)
self.assertTrue(n == 2**(k-1))
n += n - 1 # check 1 below the next power of two
k = int(1.00001 + _log(n, 2))
self.assertIn(k, [numbits, numbits+1])
self.assertTrue(2**k > n > 2**(k-2))
n -= n >> 15 # check a little farther below the next power of two
k = int(1.00001 + _log(n, 2))
self.assertEqual(k, numbits) # note the stronger assertion
self.assertTrue(2**k > n > 2**(k-1)) # note the stronger assertion
def test_randrange_bug_1590891(self):
start = 1000000000000
stop = -100000000000000000000
step = -200
x = self.gen.randrange(start, stop, step)
self.assertTrue(stop < x <= start)
self.assertEqual((x+stop)%step, 0)
def gamma(z, sqrt2pi=(2.0*pi)**0.5):
# Reflection to right half of complex plane
if z < 0.5:
return pi / sin(pi*z) / gamma(1.0-z)
# Lanczos approximation with g=7
az = z + (7.0 - 0.5)
return az ** (z-0.5) / exp(az) * sqrt2pi * fsum([
0.9999999999995183,
676.5203681218835 / z,
-1259.139216722289 / (z+1.0),
771.3234287757674 / (z+2.0),
-176.6150291498386 / (z+3.0),
12.50734324009056 / (z+4.0),
-0.1385710331296526 / (z+5.0),
0.9934937113930748e-05 / (z+6.0),
0.1659470187408462e-06 / (z+7.0),
])
class TestDistributions(unittest.TestCase):
def test_zeroinputs(self):
# Verify that distributions can handle a series of zero inputs'
g = random.Random()
x = [g.random() for i in xrange(50)] + [0.0]*5
g.random = x[:].pop; g.uniform(1,10)
g.random = x[:].pop; g.paretovariate(1.0)
g.random = x[:].pop; g.expovariate(1.0)
g.random = x[:].pop; g.weibullvariate(1.0, 1.0)
g.random = x[:].pop; g.vonmisesvariate(1.0, 1.0)
g.random = x[:].pop; g.normalvariate(0.0, 1.0)
g.random = x[:].pop; g.gauss(0.0, 1.0)
g.random = x[:].pop; g.lognormvariate(0.0, 1.0)
g.random = x[:].pop; g.vonmisesvariate(0.0, 1.0)
g.random = x[:].pop; g.gammavariate(0.01, 1.0)
g.random = x[:].pop; g.gammavariate(1.0, 1.0)
g.random = x[:].pop; g.gammavariate(200.0, 1.0)
g.random = x[:].pop; g.betavariate(3.0, 3.0)
g.random = x[:].pop; g.triangular(0.0, 1.0, 1.0/3.0)
def test_avg_std(self):
# Use integration to test distribution average and standard deviation.
# Only works for distributions which do not consume variates in pairs
g = random.Random()
N = 5000
x = [i/float(N) for i in xrange(1,N)]
for variate, args, mu, sigmasqrd in [
(g.uniform, (1.0,10.0), (10.0+1.0)/2, (10.0-1.0)**2/12),
(g.triangular, (0.0, 1.0, 1.0/3.0), 4.0/9.0, 7.0/9.0/18.0),
(g.expovariate, (1.5,), 1/1.5, 1/1.5**2),
(g.vonmisesvariate, (1.23, 0), pi, pi**2/3),
(g.paretovariate, (5.0,), 5.0/(5.0-1),
5.0/((5.0-1)**2*(5.0-2))),
(g.weibullvariate, (1.0, 3.0), gamma(1+1/3.0),
gamma(1+2/3.0)-gamma(1+1/3.0)**2) ]:
g.random = x[:].pop
y = []
for i in xrange(len(x)):
try:
y.append(variate(*args))
except IndexError:
pass
s1 = s2 = 0
for e in y:
s1 += e
s2 += (e - mu) ** 2
N = len(y)
self.assertAlmostEqual(s1/N, mu, places=2,
msg='%s%r' % (variate.__name__, args))
self.assertAlmostEqual(s2/(N-1), sigmasqrd, places=2,
msg='%s%r' % (variate.__name__, args))
def test_constant(self):
g = random.Random()
N = 100
for variate, args, expected in [
(g.uniform, (10.0, 10.0), 10.0),
(g.triangular, (10.0, 10.0), 10.0),
#(g.triangular, (10.0, 10.0, 10.0), 10.0),
(g.expovariate, (float('inf'),), 0.0),
(g.vonmisesvariate, (3.0, float('inf')), 3.0),
(g.gauss, (10.0, 0.0), 10.0),
(g.lognormvariate, (0.0, 0.0), 1.0),
(g.lognormvariate, (-float('inf'), 0.0), 0.0),
(g.normalvariate, (10.0, 0.0), 10.0),
(g.paretovariate, (float('inf'),), 1.0),
(g.weibullvariate, (10.0, float('inf')), 10.0),
(g.weibullvariate, (0.0, 10.0), 0.0),
]:
for i in range(N):
self.assertEqual(variate(*args), expected)
def test_von_mises_range(self):
# Issue 17149: von mises variates were not consistently in the
# range [0, 2*PI].
g = random.Random()
N = 100
for mu in 0.0, 0.1, 3.1, 6.2:
for kappa in 0.0, 2.3, 500.0:
for _ in range(N):
sample = g.vonmisesvariate(mu, kappa)
self.assertTrue(
0 <= sample <= random.TWOPI,
msg=("vonmisesvariate({}, {}) produced a result {} out"
" of range [0, 2*pi]").format(mu, kappa, sample))
def test_von_mises_large_kappa(self):
# Issue #17141: vonmisesvariate() was hang for large kappas
random.vonmisesvariate(0, 1e15)
random.vonmisesvariate(0, 1e100)
class TestModule(unittest.TestCase):
def testMagicConstants(self):
self.assertAlmostEqual(random.NV_MAGICCONST, 1.71552776992141)
self.assertAlmostEqual(random.TWOPI, 6.28318530718)
self.assertAlmostEqual(random.LOG4, 1.38629436111989)
self.assertAlmostEqual(random.SG_MAGICCONST, 2.50407739677627)
def test__all__(self):
# tests validity but not completeness of the __all__ list
self.assertTrue(set(random.__all__) <= set(dir(random)))
def test_random_subclass_with_kwargs(self):
# SF bug #1486663 -- this used to erroneously raise a TypeError
class Subclass(random.Random):
def __init__(self, newarg=None):
random.Random.__init__(self)
Subclass(newarg=1)
def test_main(verbose=None):
testclasses = [WichmannHill_TestBasicOps,
MersenneTwister_TestBasicOps,
TestDistributions,
TestModule]
try:
random.SystemRandom().random()
except NotImplementedError:
pass
else:
testclasses.append(SystemRandom_TestBasicOps)
test_support.run_unittest(*testclasses)
# verify reference counting
import sys
if verbose and hasattr(sys, "gettotalrefcount"):
counts = [None] * 5
for i in xrange(len(counts)):
test_support.run_unittest(*testclasses)
counts[i] = sys.gettotalrefcount()
print counts
if __name__ == "__main__":
test_main(verbose=True)
|