Pympler包的asizeof模块可以做到这一点。

使用方法如下:

from pympler import asizeof
asizeof.asizeof(my_object)

不像系统。Getsizeof，它适用于你自己创建的对象。它甚至可以与numpy一起工作。

>>> asizeof.asizeof(tuple('bcd'))
200
>>> asizeof.asizeof({'foo': 'bar', 'baz': 'bar'})
400
>>> asizeof.asizeof({})
280
>>> asizeof.asizeof({'foo':'bar'})
360
>>> asizeof.asizeof('foo')
40
>>> asizeof.asizeof(Bar())
352
>>> asizeof.asizeof(Bar().__dict__)
280
>>> A = rand(10)
>>> B = rand(10000)
>>> asizeof.asizeof(A)
176
>>> asizeof.asizeof(B)
80096

正如前面提到的,

可以通过设置option code=True来包含类、函数、方法、模块等对象的(字节)代码大小。

如果你需要实时数据的其他视图，请选择Pympler

模块muppy用于在线监控Python应用程序 和模块类跟踪器提供的生命周期的离线分析 选择Python对象。

下面是我根据之前对所有变量的列表大小的回答编写的一个快速脚本

for i in dir():
    print (i, sys.getsizeof(eval(i)) )

对于numpy数组，getsizeof不起作用-对我来说，它总是出于某种原因返回40:

from pylab import *
from sys import getsizeof
A = rand(10)
B = rand(10000)

然后(在ipython中):

In [64]: getsizeof(A)
Out[64]: 40

In [65]: getsizeof(B)
Out[65]: 40

不过令人高兴的是,:

In [66]: A.nbytes
Out[66]: 80

In [67]: B.nbytes
Out[67]: 80000

我用这个技巧…May在小对象上不准确，但我认为对于复杂对象(如pygame surface)比sys.getsizeof()更准确。

import pygame as pg
import os
import psutil
import time


process = psutil.Process(os.getpid())
pg.init()    
vocab = ['hello', 'me', 'you', 'she', 'he', 'they', 'we',
         'should', 'why?', 'necessarily', 'do', 'that']

font = pg.font.SysFont("monospace", 100, True)

dct = {}

newMem = process.memory_info().rss  # don't mind this line
Str = f'store ' + f'Nothing \tsurface use about '.expandtabs(15) + \
      f'0\t bytes'.expandtabs(9)  # don't mind this assignment too

usedMem = process.memory_info().rss

for word in vocab:
    dct[word] = font.render(word, True, pg.Color("#000000"))

    time.sleep(0.1)  # wait a moment

    # get total used memory of this script:
    newMem = process.memory_info().rss
    Str = f'store ' + f'{word}\tsurface use about '.expandtabs(15) + \
          f'{newMem - usedMem}\t bytes'.expandtabs(9)

    print(Str)
    usedMem = newMem

在我的windows 10, python 3.7.3，输出是:

store hello          surface use about 225280    bytes
store me             surface use about 61440     bytes
store you            surface use about 94208     bytes
store she            surface use about 81920     bytes
store he             surface use about 53248     bytes
store they           surface use about 114688    bytes
store we             surface use about 57344     bytes
store should         surface use about 172032    bytes
store why?           surface use about 110592    bytes
store necessarily    surface use about 311296    bytes
store do             surface use about 57344     bytes
store that           surface use about 110592    bytes

If you don't need the exact size of the object but roughly to know how big it is, one quick (and dirty) way is to let the program run, sleep for an extended period of time, and check the memory usage (ex: Mac's activity monitor) by this particular python process. This would be effective when you are trying to find the size of one single large object in a python process. For example, I recently wanted to check the memory usage of a new data structure and compare it with that of Python's set data structure. First I wrote the elements (words from a large public domain book) to a set, then checked the size of the process, and then did the same thing with the other data structure. I found out the Python process with a set is taking twice as much memory as the new data structure. Again, you wouldn't be able to exactly say the memory used by the process is equal to the size of the object. As the size of the object gets large, this becomes close as the memory consumed by the rest of the process becomes negligible compared to the size of the object you are trying to monitor.

使用以下函数获取python对象的实际大小:

import sys
import gc

def actualsize(input_obj):
    memory_size = 0
    ids = set()
    objects = [input_obj]
    while objects:
        new = []
        for obj in objects:
            if id(obj) not in ids:
                ids.add(id(obj))
                memory_size += sys.getsizeof(obj)
                new.append(obj)
        objects = gc.get_referents(*new)
    return memory_size

actualsize([1, 2, [3, 4, 5, 1]])

参考:https://towardsdatascience.com/the-strange-size-of-python-objects-in-memory-ce87bdfbb97f