Python wrong title set

Knowing and wrong can change 1. Set the variable a=2, the variable b=a, and then set the A=3, and then look at B will also be equal to 3

• The answer resolves:

Variable a=2, b=a, and then a=3, the result of viewing a at this time is 3, but the result of B is still 2, because B=a actually does not point the B variable to a, but the value of B is pointed to the value of a variable point, if a after a change to the 3,python interpreter will open a new memory space and the value Save As 3, then a memory pointer points to 3 of the address, but 2 of the memory address is the same, since B points to the address of 2, so the value of B is still 2

总结：+=对于可变对象（dict,list）来说，以最小动作为基础，是在原处修改的= 另外的是生成了一个新的对象

Knowledge Point: Garbage collection 1. Small integer Object pool

Integers 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 defines small integers as [-5, 257] These integer objects are set up well in advance and are not garbage collected. In a Python program, all integers that are in this range use the same object.

Similarly, a single letter is the same.

However, when you define 2 identical strings, the reference count is 0, which triggers a garbage collection

2. Large integer Object pool

A new object is created for each large integer.

3. Intern mechanism

A1 = "HelloWorld"
A2 = "HelloWorld"
a3 = "HelloWorld"
a4 = "HelloWorld"
A5 = "HelloWorld"
A6 = "HelloWorld"
A7 = "HelloWorld"
A8 = "HelloWorld"
A9 = "HelloWorld"
Will python create 9 objects? Will it open up 9 "HelloWorld" of memory space in memory? Think about it, if this is the case, we write 10,000 objects, such as a1= "HelloWorld" ... a1000= "HelloWorld", then he did not open up 1000 "HelloWorld" occupied the memory space? If so, does the memory explode? So python has such a mechanism--intern mechanism, so that he only occupies a "HelloWorld" occupies the memory space. By reference counting to maintain when to release.

Summary: Garbage collection

• Small integer [-5,257) Common object, Resident memory
• Single character shared object, resident memory
• Single word, non-modifiable, default turn on intern mechanism, common object, reference count is 0, destroy word garbage collection
• string (containing spaces), non-modifiable, no intern mechanism, no shared object, reference count 0, destroy
• Large integers do not share memory, reference count is 0, destroy large integer garbage collection
• numeric types and string types are immutable in Python, which means that you cannot modify the value of this object, and each time you modify a variable, you are actually creating a new object that is not mutable

Python wrong title set