blocks|key|335626|text|an+earlier+question对此的建议是使用sys.getsizeof()，引用：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|335627|>>>+import+sys
>>>+x+=+2
>>>+sys.getsizeof(x)
14
>>>+sys.getsizeof(sys.getsizeof)
32
>>>+sys.getsizeof('this')
38
>>>+sys.getsizeof('this+also')
48|code-block|syntax|javascript|335628|您可以采用这种方法：|335629|>>>+import+sys
>>>+import+decimal
>>>+
>>>+d+=+{
...+++++"int":+0,
...+++++"float":+0.0,
...+++++"dict":+dict(),
...+++++"set":+set(),
...+++++"tuple":+tuple(),
...+++++"list":+list(),
...+++++"str":+"a",
...+++++"unicode":+u"a",
...+++++"decimal":+decimal.Decimal(0),
...+++++"object":+object(),
...+}
>>>+for+k,+v+in+sorted(d.iteritems()):
...+++++print+k,+sys.getsizeof(v)
...
decimal+40
dict+140
float+16
int+12
list+36
object+8
set+116
str+25
tuple+28
unicode+28|335630|335631|2012-09-30|335632|python+2.7+(linux，32位)：|335633|decimal+36
dict+136
float+16
int+12
list+32
object+8
set+112
str+22
tuple+24
unicode+32|335634|python+3.3+(linux，32位)|335635|decimal+52
dict+144
float+16
int+14
list+32
object+8
set+112
str+26
tuple+24
unicode+26|335636|335637|2016-08-01|335638|OSX，Python+2.7.10+(默认，Oct+23+2015，19:19:21)在darwin上，GCC+4.2.1兼容Apple+LLVM+7.0.0+(clang-700.0.59.5)|335639|decimal+80
dict+280
float+24
int+24
list+72
object+16
set+232
str+38
tuple+56
unicode+52|335640|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/449560/how-do-i-determine-the-size-of-an-object-in-python|1|http://docs.python.org/library/sys.html#sys.getsizeof^0|0|J|0|R|F|1|0|0|0|0|0|0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|1E|8|@]|9|@$A|1F|B|1G|1|1H]|$A|1I|B|1J|1|1K]]|C|$]]|$1|D|3|E|5|F|7|1L|8|@]|9|@]|C|$G|H]]|$1|I|3|J|5|6|7|1M|8|@]|9|@]|C|$]]|$1|K|3|L|5|F|7|1N|8|@]|9|@]|C|$G|H]]|$1|M|3|-4|5|6|7|1O|8|@]|9|@]|C|$]]|$1|N|3|O|5|6|7|1P|8|@]|9|@]|C|$]]|$1|P|3|Q|5|6|7|1Q|8|@]|9|@]|C|$]]|$1|R|3|S|5|F|7|1R|8|@]|9|@]|C|$G|H]]|$1|T|3|U|5|6|7|1S|8|@]|9|@]|C|$]]|$1|V|3|W|5|F|7|1T|8|@]|9|@]|C|$G|H]]|$1|X|3|-4|5|6|7|1U|8|@]|9|@]|C|$]]|$1|Y|3|Z|5|6|7|1V|8|@]|9|@]|C|$]]|$1|10|3|11|5|6|7|1W|8|@]|9|@]|C|$]]|$1|12|3|13|5|F|7|1X|8|@]|9|@]|C|$G|H]]|$1|14|3|-4|5|6|7|1Y|8|@]|9|@]|C|$]]]|15|$16|$5|17|18|19|C|$1A|1B]]|1C|$5|17|18|19|C|$1A|1D]]]]

The recommendation from <a href="https://stackoverflow.com/questions/449560/how-do-i-determine-the-size-of-an-object-in-python">an earlier question</a> on this was to use <a href="http://docs.python.org/library/sys.html#sys.getsizeof" rel="noreferrer">sys.getsizeof()</a>, quoting:

<pre><code>&gt;&gt;&gt; import sys
&gt;&gt;&gt; x = 2
&gt;&gt;&gt; sys.getsizeof(x)
14
&gt;&gt;&gt; sys.getsizeof(sys.getsizeof)
32
&gt;&gt;&gt; sys.getsizeof('this')
38
&gt;&gt;&gt; sys.getsizeof('this also')
48
</code></pre>

You could take this approach:

<pre><code>&gt;&gt;&gt; import sys
&gt;&gt;&gt; import decimal
&gt;&gt;&gt; 
&gt;&gt;&gt; d = {
... "int": 0,
... "float": 0.0,
... "dict": dict(),
... "set": set(),
... "tuple": tuple(),
... "list": list(),
... "str": "a",
... "unicode": u"a",
... "decimal": decimal.Decimal(0),
... "object": object(),
... }
&gt;&gt;&gt; for k, v in sorted(d.iteritems()):
... print k, sys.getsizeof(v)
...
decimal 40
dict 140
float 16
int 12
list 36
object 8
set 116
str 25
tuple 28
unicode 28
</code></pre>

<hr>

2012-09-30

python 2.7 (linux, 32-bit):

<pre><code>decimal 36
dict 136
float 16
int 12
list 32
object 8
set 112
str 22
tuple 24
unicode 32
</code></pre>

python 3.3 (linux, 32-bit)

<pre><code>decimal 52
dict 144
float 16
int 14
list 32
object 8
set 112
str 26
tuple 24
unicode 26
</code></pre>

<hr>

2016-08-01

OSX, Python 2.7.10 (default, Oct 23 2015, 19:19:21) [GCC 4.2.1 Compatible Apple LLVM 7.0.0 (clang-700.0.59.5)] on darwin

<pre><code>decimal 80
dict 280
float 24
int 24
list 72
object 16
set 232
str 38
tuple 56
unicode 52
</code></pre>

blocks|key|3094029|text|我一直很高兴地使用pympler来完成这些任务。它与许多版本的Python兼容--特别是asizeof模块回到了2.2版本！|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|3094030|例如，使用hughdbrown的示例，但开头是from+pympler+import+asizeof，结尾是print+asizeof.asizeof(v)，我看到(+MacOSX+10.5上的system+Python2.5)：|3094031|$+python+pymp.py+
set+120
unicode+32
tuple+32
int+16
decimal+152
float+16
list+40
object+0
dict+144
str+32|code-block|syntax|javascript|3094032|显然，这里有一些近似值，但我发现它对于内存占用分析和调优非常有用。|3094033|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/pympler/pympler^0|18|7|9|7|0|0|N|R|1I|O|0|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@$9|X|A|Y|B|C]]|D|@$9|Z|A|10|1|11]]|E|$]]|$1|F|3|G|5|6|7|12|8|@$9|13|A|14|B|C]|$9|15|A|16|B|C]]|D|@]|E|$]]|$1|H|3|I|5|J|7|17|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|18|8|@]|D|@]|E|$]]|$1|O|3|-4|5|6|7|19|8|@]|D|@]|E|$]]]|P|$Q|$5|R|S|T|E|$U|V]]]]

I've been happily using <a href="https://github.com/pympler/pympler" rel="nofollow noreferrer">pympler</a> for such tasks. It's compatible with many versions of Python -- the <code>asizeof</code> module in particular goes back to 2.2!
For example, using hughdbrown's example but with <code>from pympler import asizeof</code> at the start and <code>print asizeof.asizeof(v)</code> at the end, I see (system Python 2.5 on MacOSX 10.5):
<pre><code>$ python pymp.py 
set 120
unicode 32
tuple 32
int 16
decimal 152
float 16
list 40
object 0
dict 144
str 32
</code></pre>
Clearly there is some approximation here, but I've found it very useful for footprint analysis and tuning.

blocks|key|333351|text|尝试使用内存分析器。memory+profiler|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|333352|Line+#++++Mem+usage++Increment+++Line+Contents
==============================================
+++++3+++++++++++++++++++++++++++@profile
+++++4++++++5.97+MB++++0.00+MB+++def+my_func():
+++++5+++++13.61+MB++++7.64+MB+++++++a+=+[1]+*+(10+**+6)
+++++6++++166.20+MB++152.59+MB+++++++b+=+[2]+*+(2+*+10+**+7)
+++++7+++++13.61+MB+-152.59+MB+++++++del+b
+++++8+++++13.61+MB++++0.00+MB+++++++return+a|code-block|syntax|javascript|333353|entityMap|0|LINK|mutability|MUTABLE|url|http://pypi.python.org/pypi/memory_profiler^0|A|F|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@$A|R|B|S|1|T]]|C|$]]|$1|D|3|E|5|F|7|U|8|@]|9|@]|C|$G|H]]|$1|I|3|-4|5|6|7|V|8|@]|9|@]|C|$]]]|J|$K|$5|L|M|N|C|$O|P]]]]

Try memory profiler.
<a href="http://pypi.python.org/pypi/memory_profiler" rel="noreferrer">memory profiler</a>

<pre><code>Line # Mem usage Increment Line Contents
==============================================
 3 @profile
 4 5.97 MB 0.00 MB def my_func():
 5 13.61 MB 7.64 MB a = [1] * (10 ** 6)
 6 166.20 MB 152.59 MB b = [2] * (2 * 10 ** 7)
 7 13.61 MB -152.59 MB del b
 8 13.61 MB 0.00 MB return a
</code></pre>

blocks|key|330540|text|你也可以使用guppy模块。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|330541|>>>+from+guppy+import+hpy;+hp=hpy()
>>>+hp.heap()
Partition+of+a+set+of+25853+objects.+Total+size+=+3320992+bytes.
+Index++Count+++%25+++++Size+++%25+Cumulative++%25+Kind+(class+/+dict+of+class)
+++++0++11731++45+++929072++28++++929072++28+str
+++++1+++5832++23+++469760++14+++1398832++42+tuple
+++++2++++324+++1+++277728+++8+++1676560++50+dict+(no+owner)
+++++3+++++70+++0+++216976+++7+++1893536++57+dict+of+module
+++++4++++199+++1+++210856+++6+++2104392++63+dict+of+type
+++++5+++1627+++6+++208256+++6+++2312648++70+types.CodeType
+++++6+++1592+++6+++191040+++6+++2503688++75+function
+++++7++++199+++1+++177008+++5+++2680696++81+type
+++++8++++124+++0+++135328+++4+++2816024++85+dict+of+class
+++++9+++1045+++4++++83600+++3+++2899624++87+__builtin__.wrapper_descriptor
<90+more+rows.+Type+e.g.+'_.more'+to+view.>|code-block|syntax|javascript|330542|和：|330543|>>>+hp.iso(1,+[1],+"1",+(1,),+{1:1},+None)
Partition+of+a+set+of+6+objects.+Total+size+=+560+bytes.
+Index++Count+++%25+++++Size+++%25+Cumulative++%25+Kind+(class+/+dict+of+class)
+++++0++++++1++17++++++280++50+++++++280++50+dict+(no+owner)
+++++1++++++1++17++++++136++24+++++++416++74+list
+++++2++++++1++17+++++++64++11+++++++480++86+tuple
+++++3++++++1++17+++++++40+++7+++++++520++93+str
+++++4++++++1++17+++++++24+++4+++++++544++97+int
+++++5++++++1++17+++++++16+++3+++++++560+100+types.NoneType|330544|entityMap|0|LINK|mutability|MUTABLE|url|https://pypi.python.org/pypi/guppy/^0|6|5|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@]|9|@$A|V|B|W|1|X]]|C|$]]|$1|D|3|E|5|F|7|Y|8|@]|9|@]|C|$G|H]]|$1|I|3|J|5|6|7|Z|8|@]|9|@]|C|$]]|$1|K|3|L|5|F|7|10|8|@]|9|@]|C|$G|H]]|$1|M|3|-4|5|6|7|11|8|@]|9|@]|C|$]]]|N|$O|$5|P|Q|R|C|$S|T]]]]

Also you can use <a href="https://pypi.python.org/pypi/guppy/" rel="noreferrer">guppy</a> module.

<pre><code>&gt;&gt;&gt; from guppy import hpy; hp=hpy()
&gt;&gt;&gt; hp.heap()
Partition of a set of 25853 objects. Total size = 3320992 bytes.
 Index Count % Size % Cumulative % Kind (class / dict of class)
 0 11731 45 929072 28 929072 28 str
 1 5832 23 469760 14 1398832 42 tuple
 2 324 1 277728 8 1676560 50 dict (no owner)
 3 70 0 216976 7 1893536 57 dict of module
 4 199 1 210856 6 2104392 63 dict of type
 5 1627 6 208256 6 2312648 70 types.CodeType
 6 1592 6 191040 6 2503688 75 function
 7 199 1 177008 5 2680696 81 type
 8 124 0 135328 4 2816024 85 dict of class
 9 1045 4 83600 3 2899624 87 __builtin__.wrapper_descriptor
&lt;90 more rows. Type e.g. '_.more' to view.&gt;
</code></pre>

And:

<pre><code>&gt;&gt;&gt; hp.iso(1, [1], "1", (1,), {1:1}, None)
Partition of a set of 6 objects. Total size = 560 bytes.
 Index Count % Size % Cumulative % Kind (class / dict of class)
 0 1 17 280 50 280 50 dict (no owner)
 1 1 17 136 24 416 74 list
 2 1 17 64 11 480 86 tuple
 3 1 17 40 7 520 93 str
 4 1 17 24 4 544 97 int
 5 1 17 16 3 560 100 types.NoneType
</code></pre>

blocks|key|330546|text|这些答案都收集了浅层次的信息。我怀疑这个问题的访问者最终会在这里回答这个问题，“这个复杂的对象在内存中有多大？”|type|unstyled|depth|inlineStyleRanges|entityRanges|data|330547|这里有一个很好的答案：https://goshippo.com/blog/measure-real-size-any-python-object/|offset|length|330548|笑点是：|330549|import+sys

def+get_size(obj,+seen=None):
++++"""Recursively+finds+size+of+objects"""
++++size+=+sys.getsizeof(obj)
++++if+seen+is+None:
++++++++seen+=+set()
++++obj_id+=+id(obj)
++++if+obj_id+in+seen:
++++++++return+0
++++#+Important+mark+as+seen+*before*+entering+recursion+to+gracefully+handle
++++#+self-referential+objects
++++seen.add(obj_id)
++++if+isinstance(obj,+dict):
++++++++size+%2B=+sum([get_size(v,+seen)+for+v+in+obj.values()])
++++++++size+%2B=+sum([get_size(k,+seen)+for+k+in+obj.keys()])
++++elif+hasattr(obj,+'__dict__'):
++++++++size+%2B=+get_size(obj.__dict__,+seen)
++++elif+hasattr(obj,+'__iter__')+and+not+isinstance(obj,+(str,+bytes,+bytearray)):
++++++++size+%2B=+sum([get_size(i,+seen)+for+i+in+obj])
++++return+size|code-block|syntax|javascript|330550|如下所示：|330551|In+[1]:+get_size(1)
Out[1]:+24

In+[2]:+get_size([1])
Out[2]:+104

In+[3]:+get_size([[1]])
Out[3]:+184|330552|如果您想更深入地了解Python的内存模型，这里有一篇很棒的文章，它有一个类似的“总大小”代码片段，作为更长的解释的一部分：https://code.tutsplus.com/tutorials/understand-how-much-memory-your-python-objects-use--cms-25609|330553|entityMap|0|LINK|mutability|MUTABLE|url|https://goshippo.com/blog/measure-real-size-any-python-object/|1|https://code.tutsplus.com/tutorials/understand-how-much-memory-your-python-objects-use--cms-25609^0|0|B|1Q|0|0|0|0|0|0|1Q|2P|1|0^^$0|@$1|2|3|4|5|6|7|12|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|13|8|@]|9|@$D|14|E|15|1|16]]|A|$]]|$1|F|3|G|5|6|7|17|8|@]|9|@]|A|$]]|$1|H|3|I|5|J|7|18|8|@]|9|@]|A|$K|L]]|$1|M|3|N|5|6|7|19|8|@]|9|@]|A|$]]|$1|O|3|P|5|J|7|1A|8|@]|9|@]|A|$K|L]]|$1|Q|3|R|5|6|7|1B|8|@]|9|@$D|1C|E|1D|1|1E]]|A|$]]|$1|S|3|-4|5|6|7|1F|8|@]|9|@]|A|$]]]|T|$U|$5|V|W|X|A|$Y|Z]]|10|$5|V|W|X|A|$Y|11]]]]

These answers all collect shallow size information. I suspect that visitors to this question will end up here looking to answer the question, "How big is this complex object in memory?"

There's a great answer here: <a href="https://goshippo.com/blog/measure-real-size-any-python-object/" rel="noreferrer">https://goshippo.com/blog/measure-real-size-any-python-object/</a>

The punchline:

<pre class="lang-python prettyprint-override"><code>import sys

def get_size(obj, seen=None):
 """Recursively finds size of objects"""
 size = sys.getsizeof(obj)
 if seen is None:
 seen = set()
 obj_id = id(obj)
 if obj_id in seen:
 return 0
 # Important mark as seen *before* entering recursion to gracefully handle
 # self-referential objects
 seen.add(obj_id)
 if isinstance(obj, dict):
 size += sum([get_size(v, seen) for v in obj.values()])
 size += sum([get_size(k, seen) for k in obj.keys()])
 elif hasattr(obj, '__dict__'):
 size += get_size(obj.__dict__, seen)
 elif hasattr(obj, '__iter__') and not isinstance(obj, (str, bytes, bytearray)):
 size += sum([get_size(i, seen) for i in obj])
 return size
</code></pre>

Used like so:

<pre><code>In [1]: get_size(1)
Out[1]: 24

In [2]: get_size([1])
Out[2]: 104

In [3]: get_size([[1]])
Out[3]: 184
</code></pre>

If you want to know Python's memory model more deeply, there's a great article here that has a similar "total size" snippet of code as part of a longer explanation: <a href="https://code.tutsplus.com/tutorials/understand-how-much-memory-your-python-objects-use--cms-25609" rel="noreferrer">https://code.tutsplus.com/tutorials/understand-how-much-memory-your-python-objects-use--cms-25609</a>

blocks|key|3306741|text|使用dir([object])内置函数时，可以获得内置函数的__sizeof__。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|3306742|>>>+a+=+-1
>>>+a.__sizeof__()
24|code-block|syntax|javascript|3306743|entityMap^0|2|D|U|A|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]|$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|S|8|@]|D|@]|E|$]]]|L|$]]

When you use the <code>dir([object])</code> built-in function, you can get the <code>__sizeof__</code> of the built-in function.

<pre><code>&gt;&gt;&gt; a = -1
&gt;&gt;&gt; a.__sizeof__()
24
</code></pre>

blocks|key|3094105|text|还可以使用Python标准库中的tracemalloc模块。对于其类是用C实现的对象，它似乎工作得很好(例如，与Pympler不同)。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|3094106|entityMap|0|LINK|mutability|MUTABLE|url|https://docs.python.org/3/library/tracemalloc.html^0|G|B|G|B|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@$9|O|A|P|B|C]]|D|@$9|Q|A|R|1|S]]|E|$]]|$1|F|3|-4|5|6|7|T|8|@]|D|@]|E|$]]]|G|$H|$5|I|J|K|E|$L|M]]]]

One can also make use of the <a href="https://docs.python.org/3/library/tracemalloc.html" rel="nofollow noreferrer"><code>tracemalloc</code></a> module from the Python standard library. It seems to work well for objects whose class is implemented in C (unlike Pympler, for instance).

Is there a reference for the memory size of Python data stucture on 32- and 64-bit platforms?

If not, this would be nice to have it on SO. The more exhaustive the better! So how many bytes are used by the following Python structures (depending on the <code>len</code> and the content type when relevant)?

<ul>
<li><code>int</code></li>
<li><code>float</code></li>
<li>reference</li>
<li><code>str</code></li>
<li>unicode string</li>
<li><code>tuple</code></li>
<li><code>list</code></li>
<li><code>dict</code></li>
<li><code>set</code></li>
<li><code>array.array</code></li>
<li><code>numpy.array</code></li>
<li><code>deque</code></li>
<li>new-style classes object</li>
<li>old-style classes object</li>
<li>... and everything I am forgetting!</li>
</ul>

(For containers that keep only references to other objects, we obviously do not want to count the size of the item themselves, since it might be shared.)

Furthermore, is there a way to get the memory used by an object at runtime (recursively or not)?

In-memory size of a Python structure

数据结构

容器

Python

32位和64位平台上的Python数据结构的内存大小有没有参考？如果没有，这将是一件很好的事情。越详尽越好！那么，下面的Python结构使用了多少字节(取决于相关的len和内容类型)？intfloatreferencestrunicode stringtuplelistdictsetarray.arraynumpy.a...

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