Erb*_*yev 3 python optimization performance simplify python-3.x
我正在使用以下代码在Python中查找模数的原始根:n
码:
def gcd(a,b):
while b != 0:
a, b = b, a % b
return a
def primRoots(modulo):
roots = []
required_set = set(num for num in range (1, modulo) if gcd(num, modulo) == 1)
for g in range(1, modulo):
actual_set = set(pow(g, powers) % modulo for powers in range (1, modulo))
if required_set == actual_set:
roots.append(g)
return roots
if __name__ == "__main__":
p = 17
primitive_roots = primRoots(p)
print(primitive_roots)
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输出:
[3, 5, 6, 7, 10, 11, 12, 14]
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代码片段摘录自: Diffie-Hellman(Github)
该primRoots方法可以在内存使用和性能 /效率方面进行简化或优化吗?
您可以在此处进行的一项快速更改(尚未有效优化)是使用列表和集合推导式:
def primRoots(modulo):
coprime_set = {num for num in range(1, modulo) if gcd(num, modulo) == 1}
return [g for g in range(1, modulo) if coprime_set == {pow(g, powers, modulo)
for powers in range(1, modulo)}]
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现在,您可以在此处进行的一项强大而有趣的算法更改是使用memoization优化您的gcd函数。或者更好的是,您可以简单地使用Python-3.5+ 中的内置函数表单模块或以前版本中的模块:gcdmathfractions
from functools import wraps
def cache_gcd(f):
cache = {}
@wraps(f)
def wrapped(a, b):
key = (a, b)
try:
result = cache[key]
except KeyError:
result = cache[key] = f(a, b)
return result
return wrapped
@cache_gcd
def gcd(a,b):
while b != 0:
a, b = b, a % b
return a
# or just do the following (recommended)
# from math import gcd
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然后:
def primRoots(modulo):
coprime_set = {num for num in range(1, modulo) if gcd(num, modulo) == 1}
return [g for g in range(1, modulo) if coprime_set == {pow(g, powers, modulo)
for powers in range(1, modulo)}]
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如评论中所述,作为您可以使用的更多 pythoinc 优化器方式fractions.gcd(或用于 Python-3.5+ math.gcd)。
根据Pete的评论和Kasramvd的回答,我可以建议:
from math import gcd as bltin_gcd
def primRoots(modulo):
required_set = {num for num in range(1, modulo) if bltin_gcd(num, modulo) }
return [g for g in range(1, modulo) if required_set == {pow(g, powers, modulo)
for powers in range(1, modulo)}]
print(primRoots(17))
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输出:
[3, 5, 6, 7, 10, 11, 12, 14]
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变化:
有关内置gcd的更多信息,请访问: 联合质量检查