模块层级关系:
----:
|->AA.py
|->BB.py
|->CC.py
AA.py
from BB import BB
class AA:
def sub(self, x):
bb = BB()
bb.print_name()
return x def print_name(self):
print("AA")
BB.py
引入方法一:在文件头部直接引入,算是全局引入吧。
引入方法二:在函数内引入,算是局部引入吧。
##引入方式一
from AA import AA
class BB:
def add(self,x):
##引入方式二
from AA import AA
aa = AA()
aa.print_name()
return x def print_name(self):
print("BB")
CC.py
from AA import AA if __name__ == '__main__':
aa = AA()
aa.sub(1)
运行模块CC:
如果在BB模块中
使用引入方法一:
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" 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如果使用引入方法二:
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" alt="" />
个人注解:
不知道原因。。。。暂时只是知道如果出现这种情况下,该怎么弄。