python weak references

The following code is very helpful in the [python standard library: def all_nodes(self): yield self n = self.other while n and n.name != self.name: yield n n = n.other if n is self: yield

A piece of code seen in the [python standard library] is very helpful: def all_nodes(self): yield self n = self.other while n and n.name != self.name: yield n n = n.other if n is self:

The following code is very helpful in the [python standard library: = n n.name !== n Yield at the beginning and end of the cycle graph is returned only once, as the starting point and ending point of the cycle graph, and n as the potential node of

How does python manage memory in loop references? python references In python, junk objects are recycled by reference counting. In some ring data structures (tree, graph ......), There is a circular reference between objects. For example, if the

Transferred from: http://www.jianshu.com/p/1e375fb40506first, an overview, the second part of the picture is very serious.Garbage collection (GC)Today's high-level languages such as java,c# have adopted a garbage collection mechanism, rather than a

Garbage collection 1. Small integer Object poolIntegers are used extensively in programs, and in order to optimize speed, Python uses a small integer pool of objects to avoid frequent application and destruction of memory space for integers.Python

Python memory management is implemented by reference counting. When the object's reference count is 0 o'clock, it is reclaimed by the GC.To explore the storage of objects in memory, we can resort to Python's built-in function ID (). It is used to

[Pyhton] weakref weak reference   Interpretation in wiki: in computer programming, weak references, compared with strong references, mean that the referenced objects cannot be referenced by the garbage collector. If an object is referenced by a weak

Explanation in the document: https://docs.python.org/2/library/weakref.html Interpretation in wiki: in computer programming, weak references, compared with strong references, mean that the referenced objects cannot be referenced by the garbage

1. A simple exampleLet's start with a simple example that contains two files foo.py and demo.py[foo.py]def add (A, B):Return a + b[demo.py]Import FooA = [1, ' Python ']A = ' A string 'def func ():A = 1b = 257Print (A + B)Print (a)if __name__ = = ' __