爱站程序员基地目录
- 1、跳过迭代对象的开头
- 2、避免数据复制
- 3、避免变量中间变量
- 4、循环优化
- 5、使用numba.jit
1、跳过迭代对象的开头
string_from_file = \"\"\" // Wooden: ... // LaoLi: ... // // Whole: ... Wooden LaoLi... \"\"\" import itertools for line in itertools.dropwhile(lambda line: line.startswith(\"//\"), string_from_file.split(\" \")): print(line)
2、避免数据复制
# 不推荐写法，代码耗时：6.5秒def main(): size = 10000 for _ in range(size): value = range(size) value_list = [x for x in value] square_list = [x * x for x in value_list] main()
# 推荐写法，代码耗时：4.8秒def main(): size = 10000 for _ in range(size): value = range(size) square_list = [x * x for x in value] # 避免无意义的复制
3、避免变量中间变量
# 不推荐写法，代码耗时：0.07秒def main(): size = 1000000 for _ in range(size): a = 3 b = 5 temp = a a = b b = temp main()
# 推荐写法，代码耗时：0.06秒def main(): size = 1000000 for _ in range(size): a = 3 b = 5 a, b = b, a # 不借助中间变量 main()
4、循环优化
# 不推荐写法。代码耗时：6.7秒def computeSum(size: int) -> int: sum_ = 0 i = 0 while i < size: sum_ += i i += 1 return sum_ def main(): size = 10000 for _ in range(size): sum_ = computeSum(size) main()
# 推荐写法。代码耗时：4.3秒def computeSum(size: int) -> int: sum_ = 0 for i in range(size): # for 循环代替 while 循环 sum_ += i return sum_ def main(): size = 10000 for _ in range(size): sum_ = computeSum(size) main()
隐式for循环代替显式for循环
# 推荐写法。代码耗时：1.7秒def computeSum(size: int) -> int: return sum(range(size)) # 隐式 for 循环代替显式 for 循环 def main(): size = 10000 for _ in range(size): sum = computeSum(size) main()
5、使用numba.jit
# 推荐写法。代码耗时：0.62秒# numba可以将 Python 函数 JIT 编译为机器码执行，大大提高代码运行速度。import numba @numba.jitdef computeSum(size: float) -> int: sum = 0 for i in range(size): sum += i return sum def main(): size = 10000 for _ in range(size): sum = computeSum(size) main()
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