Python assignment and copy

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Variables and Assignment

In Python, everything is an object, and objects are referenced through "variable names". "Variable names" are more accurately called "names". Just like each of us has our own name, we use The name refers to a person, and the code refers to an object through the name.

Variable assignment is to bind a name to the object. Assignment does not copy the object. Just like our parents give us a name when we are born, giving someone a nickname does not create an extra person, it just creates an extra name.

There are two ways to compare two objects, namely: is and ==. is compares whether the two objects are the same. Whether they are the same object can be identified through the ID value of the object. == compares Is the value of the two objects equal?

>>> x1 = [1,2]
>>> x2 = [1,2]
>>> x1 is x2
False
>>> id(x1)
4338854088
>>> id(x2)
4338904392
>>> x1 == x2
True

Although the values ​​​​of x1 and x2 are the same, they are two independent and different objects in the memory, occupying different The memory space is like two identical apples placed on the table, but they are actually two different objects.

>>> x3 = x2
>>> x3 is x2
True
>>> id(x3)
4338904392

As mentioned before, assignment is to bind a name to the object. Here we just bind a new name to the object corresponding to x2. x3, this is like putting an apple on the table, initially labeling it x2, and later adding a label x3. It is essentially the same apple, so x2 and x3 actually refer to same object.

When the object is modified through x2, x3 will also change accordingly, because essentially they are the same object. This is just like when Zhang San and Xiao Zhang are the same person, Adding clothes to Zhang San is actually adding clothes to Xiao Zhang.

>>> x2.append(3)
>>> x2
[1, 2, 3]
>>> x3
[1, 2, 3]

However, when I reassign a value to x2, it means that x2 no longer refers to the previous object, but refers to the new object, and x3 still refers to the previous object. . For example, a big apple on the table has two labels: x2 and x3. Reassigning a value to x2 is equivalent to attaching the x2 label to another apple, but x3 is still attached to the old apple.

>>> x2 = [3, 4]
>>> x3
[1, 2, 3]

Object copy

In business Sometimes we need to copy an object, but we don’t want to have side effects on the original object. This cannot be solved by assigning it to a new variable (because assignment is not copying the object), so Python specifically provides a copy mechanism to quickly create based on the original object. Produces an object containing the same value. This functionality is provided by the copy module.

Copy is divided into shallow copy and deep copy.

>>> s = [1,2,3]>>> sc = copy.copy(s) # 浅拷贝>>> sc[1, 2, 3]
>>> sdc = copy.deepcopy(s) # 深拷贝
>>> sdc
[1, 2, 3]

The copied objects only have the same value, but are actually different objects

>>> s == sc == sdc 
True
>>> s is sc 
False
>>> s is sdc
False

So what is the difference between shallow copy and deep copy?

For immutable objects, such as integers, strings, tuples, and collection objects composed of these immutable objects, there is no difference between shallow copy and deep copy, both copy a new object

The difference between the two is that when the combined object is copied, for example, when there is a list in the list, and there is a dictionary or list in the dictionary, the shallow copy only copies the outer shell, and the elements inside are not copied, while the deep copy It makes a new copy of the shell and the elements inside.

Let’s look at an example:

>>> x = [2, 3]
>>> y = [7, 11]
>>> z = [x, y]
>>> a = copy.copy(z) # 浅拷贝
>>> a[0] is z[0]
True

The elements in the copied object a refer to x and y, when you change the value of x, a will also change.

>>> b = copy.deepcopy(z) # 深拷贝
>>> b[0] is z[0]
False

#For deep copy, the elements inside are also copied again, one copy with x and y For two elements of equal value, modifying the values ​​of x and y will not affect b

Copying the slice of the list z[:] or calling the copy method list.copy() of the object are both shallow copy. For custom objects, we can also implement the __copy__ method and __deepcopy__ method ourselves

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