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-rw-r--r--Lib/test/test_random.py78
1 files changed, 78 insertions, 0 deletions
diff --git a/Lib/test/test_random.py b/Lib/test/test_random.py
index e80ed17a8c..4d5a8749c7 100644
--- a/Lib/test/test_random.py
+++ b/Lib/test/test_random.py
@@ -7,6 +7,7 @@ import warnings
from functools import partial
from math import log, exp, pi, fsum, sin
from test import support
+from fractions import Fraction
class TestBasicOps:
# Superclass with tests common to all generators.
@@ -141,6 +142,83 @@ class TestBasicOps:
def test_sample_on_dicts(self):
self.assertRaises(TypeError, self.gen.sample, dict.fromkeys('abcdef'), 2)
+ def test_choices(self):
+ choices = self.gen.choices
+ data = ['red', 'green', 'blue', 'yellow']
+ str_data = 'abcd'
+ range_data = range(4)
+ set_data = set(range(4))
+
+ # basic functionality
+ for sample in [
+ choices(data, k=5),
+ choices(data, range(4), k=5),
+ choices(k=5, population=data, weights=range(4)),
+ choices(k=5, population=data, cum_weights=range(4)),
+ ]:
+ self.assertEqual(len(sample), 5)
+ self.assertEqual(type(sample), list)
+ self.assertTrue(set(sample) <= set(data))
+
+ # test argument handling
+ with self.assertRaises(TypeError): # missing arguments
+ choices(2)
+
+ self.assertEqual(choices(data, k=0), []) # k == 0
+ self.assertEqual(choices(data, k=-1), []) # negative k behaves like ``[0] * -1``
+ with self.assertRaises(TypeError):
+ choices(data, k=2.5) # k is a float
+
+ self.assertTrue(set(choices(str_data, k=5)) <= set(str_data)) # population is a string sequence
+ self.assertTrue(set(choices(range_data, k=5)) <= set(range_data)) # population is a range
+ with self.assertRaises(TypeError):
+ choices(set_data, k=2) # population is not a sequence
+
+ self.assertTrue(set(choices(data, None, k=5)) <= set(data)) # weights is None
+ self.assertTrue(set(choices(data, weights=None, k=5)) <= set(data))
+ with self.assertRaises(ValueError):
+ choices(data, [1,2], k=5) # len(weights) != len(population)
+ with self.assertRaises(TypeError):
+ choices(data, 10, k=5) # non-iterable weights
+ with self.assertRaises(TypeError):
+ choices(data, [None]*4, k=5) # non-numeric weights
+ for weights in [
+ [15, 10, 25, 30], # integer weights
+ [15.1, 10.2, 25.2, 30.3], # float weights
+ [Fraction(1, 3), Fraction(2, 6), Fraction(3, 6), Fraction(4, 6)], # fractional weights
+ [True, False, True, False] # booleans (include / exclude)
+ ]:
+ self.assertTrue(set(choices(data, weights, k=5)) <= set(data))
+
+ with self.assertRaises(ValueError):
+ choices(data, cum_weights=[1,2], k=5) # len(weights) != len(population)
+ with self.assertRaises(TypeError):
+ choices(data, cum_weights=10, k=5) # non-iterable cum_weights
+ with self.assertRaises(TypeError):
+ choices(data, cum_weights=[None]*4, k=5) # non-numeric cum_weights
+ with self.assertRaises(TypeError):
+ choices(data, range(4), cum_weights=range(4), k=5) # both weights and cum_weights
+ for weights in [
+ [15, 10, 25, 30], # integer cum_weights
+ [15.1, 10.2, 25.2, 30.3], # float cum_weights
+ [Fraction(1, 3), Fraction(2, 6), Fraction(3, 6), Fraction(4, 6)], # fractional cum_weights
+ ]:
+ self.assertTrue(set(choices(data, cum_weights=weights, k=5)) <= set(data))
+
+ # Test weight focused on a single element of the population
+ self.assertEqual(choices('abcd', [1, 0, 0, 0]), ['a'])
+ self.assertEqual(choices('abcd', [0, 1, 0, 0]), ['b'])
+ self.assertEqual(choices('abcd', [0, 0, 1, 0]), ['c'])
+ self.assertEqual(choices('abcd', [0, 0, 0, 1]), ['d'])
+
+ # Test consistency with random.choice() for empty population
+ with self.assertRaises(IndexError):
+ choices([], k=1)
+ with self.assertRaises(IndexError):
+ choices([], weights=[], k=1)
+ with self.assertRaises(IndexError):
+ choices([], cum_weights=[], k=5)
+
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