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This article mainly explains "Python assigns all objects to how to understand", interested friends may wish to take a look. The method introduced in this paper is simple, fast and practical. Let's let Xiaobian take you to learn "Python assigns all objects to be addressed"!

Python assigns all objects to be addressed. In programming language assignment operations, there are passing references, passing values, etc., but there is only one way to pass addresses in Python. For example:

>>> s = [1,2,3]>>> t = s>>> t.reverse()

The values of s and t both become [3, 2, 1], and look again:

>>> s = [1,2,3]>>> t = s[::-1]

The value of s is [1, 2, 3], and the value of t is [3, 2, 1], so the question arises, is the assignment operation passed by value or address in Python?

Python is all about objects. Assignment is always addressed. All variables are addresses that hold objects. The first case in the example above assigns s to t, where s and t point to the same object. So when reverse is executed, the object itself is changed. Because s and t point to the same object, you output the same object that has been reversed whether you output s or t. The second case is when a slicing operation is performed on s. In this case, s[::-1] itself does not return the object itself pointed to by s, but an object regenerated from the operation in memory, so t points to the address of a new object generated by s[::-1]. And s still points to the original object, since s[::-1] does not change the value of the original object, so the value of s does not change.

Extended reading:

In Python, even integer types are treated as objects. For example, a=1 does not assign 1 to a, but assigns the address of an integer object 1 to a. Due to Python's special treatment of small integers, all small integers within a certain range are uniformly used as "small integer object pool". That is, all small integers, such as 1, use the same object in the object pool. However, the pool of small integer objects is finite, and the range is [-5, 257) Note that the left is closed and the right is open. So integers beyond this range are, strictly speaking, required to generate such an object. So, here's what happens.

>>> a = 1>>> b = 1>>> id(a) == id(b)True>>> c = 1000000>>> d = 1000000>>> id(c) == id(d)False

Integer objects are immutable, meaning that once you generate an integer object of 257, the number you hold in that object cannot be changed. So when we add integers, what is the relationship between the result and the original object? The answer is, it doesn't matter, and the result is a whole new object based on the sum. Even if the new object has the same value as the original, it is still a different object (unless the number is in the pool of small integer objects). For example:

>>> e = c + 0>>> id(c) == id(e)False>>> f = a + 0>>> id(a) == id(f)True

The list type is a variable type. It provides methods for changing objects in-place without generating new objects, such as s.reverse(). But at the same time, you can also generate a new object to store the desired result, such as s[::-1], or reversed(s). PS: Note the difference between reverse() and reversed

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