Python语句x=x+1是如何实现的？

Question

In C, a statement x=x+1 will change the content at the same memory that is allocated for x. But in Python, since a variable can have different types, x at the left and right side of = may be of different types, which means they may refer to different pieces of memory. If so, after x changes its reference from the old memory to the new memory, the old memory can be reclaimed by the garbage collection mechanism. If it is the case, the following code may trigger the garbage collection process many times thus is very low efficient:

for i in range(1000000000)
    i=i+1

Is my guess correct?

Update:

I need to correct the typo in the code to make the question clearer:

x=0
for i in range(1000000000)
    x=x+1

@SvenMarnach, do you mean the integers 0,1,2,...,999999999 (which the label x once referred to) all exist in memory if garbage collection is not activated?

Answer 1

id can be used to track the 'allocation' of memory to objects. It should be used with caution, but here I think it's illuminating. id is a bit like a c pointer - that is, some how related to 'where' the object is located in memory.

In [18]: for i in range(0,1000,100): 
    ...:     print(i,id(i)) 
    ...:     i = i+1 
    ...:     print(i,id(i)) 
    ...:                                                                        
0 10914464
1 10914496
100 10917664
101 10917696
200 10920864
201 10920896
300 140186080959760
301 140185597404720
400 140186080959760
401 140185597404720
...
900 140186080959760
901 140185597404720
In [19]: id(1)                                                                  
Out[19]: 10914496

Small integers (<256) are cached - that is, integer 1 , once created is 'reused'.

In [20]: id(202)                                                                
Out[20]: 10920928     # same id as in the loop
In [21]: id(302)                                                                
Out[21]: 140185451618128   # different id
In [22]: id(901)                                                                
Out[22]: 140185597404208
In [23]: id(i)                                                                  
Out[23]: 140185597404720   #  = 901, but different id 

In this loop, the first few iterations create or reuse small integers. But it appears that when creating larger integers, it is 'reusing' memory. It may not be full blown garbage collection, but the code is somehow optimized to avoid unnecessary memory use.

Generally as Python programmers don't focus on those details. Write clean reliable Python code. In this example, modifying an iteration variable in the loop is poor practice (even if it is just an example).

Answer 2

You are mostly correct, though I think a few clarifications may help.

First, the concept of variables in C in Python is rather different. In C, a variable generally references a fixed location in memory, as you stated yourself. In Python, a variable is just a label that can be attached to any object. An object could have multiple such labels, or none at all, and labels can be freely moved between objects. An assignment in C copies a new value to a memory location, while an assignment in Python attaches a new label to an object.

Integers are also very different in both languages. In C, an integer has a fixed size, and stores an integer value in a format native to the hardware. In Python, integers have arbitrary precision. They are stored as array of "digits" (usually 30-bit integers in CPython) together with a Python type header storing type information. Bigger integers will occupy more memory than smaller integers.

Moreover, integer objects in Python are immutable – they can't be changed once created. This means every arithmetic operation creates a new integer object. So the loop in your code indeed creates a new integer object in each iteration.

However, this isn't the only overhead. It also creates a new integer object for i in each iteration, which is dropped at the end of the loop body. And the arithmetic operation is dynamic – Python needs to look up the type of x and its __add__() method in each iteration to figure out how to add objects of this type. And function call overhead in Python is rather high.

Garbage collection and memory allocation on the other hand are rather fast in CPython. Garbage collection for integers relies completely on reference counting (no reference cycles possible here), which is fast. And for allocation, CPython uses an arena allocator for small objects that can quickly reuse memory slots without calling the system allocator.

So in summary, yes, compared to the same code in C, this code will run awfully slow in Python. A modern C compiler would simply compute the result of this loop at compile time and load the result to a register, so it would finish basically immediately. If raw speed for integer arithmetic is what you want, don't write that code in Python.