def test_random_distinct():
prime = 11
num = 7
random_values = random.get_distinct_positive_random_ints_in_field(num, prime)
assert len(random_values) == num and \
len([value for value in random_values if value < prime]) == num and \
len(random_values) == len(set(random_values)) # check distinct
def test_random_small_multiple():
prime = 2**3 - 1
num = 5
random_values = random.get_distinct_positive_random_ints_in_field(num, prime)
assert len(random_values) == num and \
len([value for value in random_values if value < prime]) == 5 and \
len(random_values) == len(set(random_values)) # check distinct
def test_random_small_single():
prime = 2**3 - 1
random_values = random.get_distinct_positive_random_ints_in_field(1, prime)
assert len(random_values) == 1 and \
random_values[0] < prime and\
random_values[0].bit_length > 0 and \
len(random_values) == len(set(random_values)) # check distinct
def _share_secret_int(num_players, reconstruction_threshold, max_secret_length, secret):
'''
Args:
num_players, the number of shares to be distributed
reconstruction_threshold, the number of shares needed for reconstruction
any collection of fewer shares will reveal no information about the secret
max_secret_length, the maximum length of the secret represented as a bytestring (ie, len(secret))
secret, an integer to be Shamir secret shared
Returns:
a list of tuples of (x, f(x)) values
Raises:
ValueError, the input parameters are invalid
'''
bitlength = max(num_players.bit_length(), max_secret_length * 8)
prime = primes.get_prime_by_bitlength(bitlength)
if not _verify_parameters(num_players, reconstruction_threshold, secret, prime):
raise ValueError("invalid secret sharing parameters")
# fix n distinct points, alpha_1,...,alpha_n in Z_ps (public)
alphas = [i for i in xrange(1, num_players + 1)]
# choose at random t points, a_1,...,a_t in Z_ps (private)
# we will use the a_i values as our coefficients to define the polynomial f(x) = (a_t x^t) + ... + (a_1 x) + s
coefficients = [secret] + random.get_distinct_positive_random_ints_in_field(reconstruction_threshold - 1, prime)
# for values of i from 1 to n, calculate f(alpha_i)
return polynomials.evaluate(coefficients, alphas, prime)
def test_random_positive_distinct():
prime = 3
num = 2
for i in range(1000):
random_values = random.get_distinct_positive_random_ints_in_field(num, prime)
assert 0 not in random_values and \
len(random_values) == num and \
len([value for value in random_values if value < prime]) == num and \
len(random_values) == len(set(random_values)) # check distinct
def get_ids(num_players):
'''
Args:
num_players, the number of players to generate ids for
Returns:
a list of random, unique ids
'''
ids = []
for r in random.get_distinct_positive_random_ints_in_field(num_players, PRIME):
ids.append(str(r))
return ids
def test_random_too_many():
prime = 7
num = 10 # test the case where there are too many requested integers for the prime selected
with pytest.raises(ValueError):
random.get_distinct_positive_random_ints_in_field(num, prime)
def test_random_size_of_field():
prime = 31
num = prime
with pytest.raises(ValueError):
random.get_distinct_positive_random_ints_in_field(num, prime)
def test_random_empty():
prime = 71
random_values = random.get_distinct_positive_random_ints_in_field(0, prime)
assert random_values == []
