def test_sequence_less_than_dice_sides(self, capsys, monkeypatch):
# Test to see whether we can use a n-sided die to choose from
# a sequence with less than n items
src = RealDiceRandomSource(None)
src.dice_sides = 6
# A length of 1 requires no rolls
self.fake_input_values(["1"], monkeypatch)
picked = src.choice([1])
out, err = capsys.readouterr()
assert "roll" not in out
assert picked == 1
# A length of 2,3 only requires 1 roll
for choice_length in (2, 3):
self.fake_input_values(["1"], monkeypatch)
picked = src.choice(range(1, choice_length + 1))
out, err = capsys.readouterr()
assert "roll 1 dice" in out
assert picked == 1
# A length of 4,5 requires 2 rolls
for choice_length in (4, 5):
self.fake_input_values(["1", "1"], monkeypatch)
picked = src.choice(range(1, choice_length + 1))
out, err = capsys.readouterr()
assert "roll 2 dice" in out
assert picked == 1
def test_pre_check_warn_if_not_all_seq_items_used(self, capsys):
# we issue a warning if not all sequence items will be used
src = RealDiceRandomSource(None)
src.dice_sides = 10
src.pre_check(1, list(range(10)))
out, err = capsys.readouterr()
assert "entropy is reduced" not in out
src.pre_check(1, list(range(11)))
out, err = capsys.readouterr()
assert "entropy is reduced" in out
def test_pre_check_warn_if_not_all_seq_items_used(self, capsys):
# we issue a warning if not all sequence items will be used
src = RealDiceRandomSource(None)
src.dice_sides = 10
src.pre_check(1, list(range(10)))
out, err = capsys.readouterr()
assert "entropy is reduced" not in out
src.pre_check(1, list(range(11)))
out, err = capsys.readouterr()
assert "entropy is reduced" in out
def test_choice_distributes_equally_on_long_seq(self, fake_input):
# we distribute nearly equally over sequences longer than
# dice_sides**n
src = RealDiceRandomSource(None)
src.dice_sides = 2
dist = [0, 0, 0]
fake_input(["1", "1", "1", "2", "2", "1", "2", "2"])
for x in range(8):
picked = src.choice([1, 2, 3])
dist[picked - 1] += 1
assert dist == [4, 4, 0]
def test_choice_distributes_equally(self, fake_input):
# we distribute nearly equally over sequences sized
# dice_sides**n
src = RealDiceRandomSource(None)
src.dice_sides = 3
dist = [0, 0, 0]
fake_input(["1", "2", "3"])
for x in range(3):
picked = src.choice([1, 2, 3])
dist[picked - 1] += 1
assert dist == [1, 1, 1]
def test_choice_distributes_equally_on_long_seq(self, fake_input):
# we distribute nearly equally over sequences longer than
# dice_sides**n
src = RealDiceRandomSource(None)
src.dice_sides = 2
dist = [0, 0, 0]
fake_input(["1", "1", "1", "2", "2", "1", "2", "2"])
for x in range(8):
picked = src.choice([1, 2, 3])
dist[picked - 1] += 1
assert dist == [4, 4, 0]
def test_choice_distributes_equally(self, fake_input):
# we distribute nearly equally over sequences sized
# dice_sides**n
src = RealDiceRandomSource(None)
src.dice_sides = 3
dist = [0, 0, 0]
fake_input(["1", "2", "3"])
for x in range(3):
picked = src.choice([1, 2, 3])
dist[picked - 1] += 1
assert dist == [1, 1, 1]
def test_choice_prints_hint_on_repeated_rolls(self, capsys, fake_input):
# on short sequences (shorter than number of dice sides)
# we give users hints to repeat dice rolls
src = RealDiceRandomSource(None)
src.dice_sides = 4
fake_input(["2", "3"]) # no value out of bounds (> 3)
picked = src.choice([1, 2, 3])
out, err = capsys.readouterr()
assert picked == 2
assert out.count("Please roll dice again") == 0
fake_input(["4", "4", "1"])
picked = src.choice([1, 2, 3])
out, err = capsys.readouterr()
assert picked == 1
assert out.count("Please roll dice again") == 2
def test_choice_prints_hint_on_repeated_rolls(self, capsys, fake_input):
# on short sequences (shorter than number of dice sides)
# we give users hints to repeat dice rolls
src = RealDiceRandomSource(None)
src.dice_sides = 4
fake_input(["2", "3"]) # no value out of bounds (> 3)
picked = src.choice([1, 2, 3])
out, err = capsys.readouterr()
assert picked == 2
assert out.count("Please roll dice again") == 0
fake_input(["4", "4", "1"])
picked = src.choice([1, 2, 3])
out, err = capsys.readouterr()
assert picked == 1
assert out.count("Please roll dice again") == 2
def test_choice_distributes_equally_on_short_seq(self, fake_input):
# we distribute equally over sequences shorter than
# dice_sides**n
src = RealDiceRandomSource(None)
src.dice_sides = 4
dist = [0, 0, 0]
# a list of pairs in a row: 4-4 - 4-3 - 4-2 - ... - 1-3 - 1-2 - 1-1
rolled_values = list(
chain.from_iterable(product(["4", "3", "2", "1"], repeat=2)))
# 4 is not a valid roll value, must do a new roll then
num_valid = len(rolled_values) - rolled_values.count("4")
fake_input(rolled_values)
for x in range(num_valid):
picked = src.choice([1, 2, 3])
dist[picked - 1] += 1
assert dist == [8, 8, 8]
def test_choice_distributes_equally_on_short_seq(self, fake_input):
# we distribute equally over sequences shorter than
# dice_sides**n
src = RealDiceRandomSource(None)
src.dice_sides = 4
dist = [0, 0, 0]
# a list of pairs in a row: 4-4 - 4-3 - 4-2 - ... - 1-3 - 1-2 - 1-1
rolled_values = list(chain.from_iterable(
product(["4", "3", "2", "1"], repeat=2)))
# 4 is not a valid roll value, must do a new roll then
num_valid = len(rolled_values) - rolled_values.count("4")
fake_input(rolled_values)
for x in range(num_valid):
picked = src.choice([1, 2, 3])
dist[picked - 1] += 1
assert dist == [8, 8, 8]
def test_choice_copes_with_small_sequences(self, capsys, fake_input):
# We handle sequences correctly, that have less elements than the used
# dice sides.
src = RealDiceRandomSource(None)
src.dice_sides = 6
# A length of 2,3 only requires 1 roll
for choice_length in (2, 3):
fake_input(["1"])
picked = src.choice(range(1, choice_length + 1))
out, err = capsys.readouterr()
assert "roll 1 dice" in out
assert picked == 1
# A length of 4,5 requires 2 rolls
for choice_length in (4, 5):
fake_input(["1", "2"])
picked = src.choice(range(1, choice_length + 1))
out, err = capsys.readouterr()
assert "roll 1 dice" in out
assert picked == 1
def test_choice_copes_with_small_sequences(self, capsys, fake_input):
# We handle sequences correctly, that have less elements than the used
# dice sides.
src = RealDiceRandomSource(None)
src.dice_sides = 6
# A length of 2,3 only requires 1 roll
for choice_length in (2, 3):
fake_input(["1"])
picked = src.choice(range(1, choice_length + 1))
out, err = capsys.readouterr()
assert "roll 1 dice" in out
assert picked == 1
# A length of 4,5 requires 2 rolls
for choice_length in (4, 5):
fake_input(["1", "2"])
picked = src.choice(range(1, choice_length + 1))
out, err = capsys.readouterr()
assert "roll 1 dice" in out
assert picked == 1
