mayank gupta <mooniitk <at> gmail.com> writes:
>
> After a little analysis, I found out that in general it uses about
> 1.4 kb of memory for each node!!
How did you measure memory use? Python objects are not very compact, but 1.4KB
per object seems a bit too much (I would expect more about 150-200 bytes/object
in 32-bit mode, or 300-400 bytes/object in 64-bit mode).
One of the solutions is to use __slots__ as already suggested. Another, which
will have similar benefits, is to use a namedtuple. Both suppress the instance
dictionnary (`instance`.__dict__), which is a major contributor to memory
consumption. Illustration (64-bit mode, by the way):
>>> import sys
>>> from collections import namedtuple
# First a normal class
>>> class Node(object): pass
...
>>> o = Node()
>>> o.value = 1
>>> o.children = ()
>>>
>>> sys.getsizeof(o)
64
>>> sys.getsizeof(o.__dict__)
280
# The object seems to take a mere 64 bytes, but the attribute dictionnary
# adds a whoppy 280 bytes and bumps actual size to 344 bytes!
# Now a namedtuple (a tuple subclass with property accessors for the various
# tuple items)
>>> Node = namedtuple("Node", "value children")
>>>
>>> o = Node(value=1, children=())
>>> sys.getsizeof(o)
72
>>> sys.getsizeof(o.__dict__)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'Node' object has no attribute '__dict__'
# The object doesn't have a __dict__, so 72 bytes is its real total size.
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