python - 如何加速数百万对象的python实例初始化？

Question

我定义了一个名为 Edge 的 python class，如下所示:

class Edge:
    def __init__(self):
        self.node1 = 0
        self.node2 = 0
        self.weight = 0

现在我必须使用以下方法创建大约 10^6 到 10^7 个 Edge 实例:

edges= []
for (i,j,w) in ijw:
    edge = Edge()
    edge.node1 = i
    edge.node2 = j
    edge.weight = w
    edges.append(edge)

我在桌面上花了大约 2 秒的时间。有没有更快的方法呢？

Answer 1

你不能让它变得多快，但我肯定会使用 __slots__以节省内存分配。还可以在创建实例时传入属性值:

class Edge:
    __slots__ = ('node1', 'node2', 'weight')
    def __init__(self, node1=0, node2=0, weight=0):
        self.node1 = node1
        self.node2 = node2
        self.weight = weight

通过更新的 __init__，您可以使用列表理解:

edges = [Edge(*args) for args in ijw]

这些一起可以节省大量创建对象的时间，大约需要一半的时间。

比较创建 100 万个对象；设置:

>>> from random import randrange
>>> ijw = [(randrange(100), randrange(100), randrange(1000)) for _ in range(10 ** 6)]
>>> class OrigEdge:
...     def __init__(self):
...         self.node1 = 0
...         self.node2 = 0
...         self.weight = 0
...
>>> origloop = '''\
... edges= []
... for (i,j,w) in ijw:
...     edge = Edge()
...     edge.node1 = i
...     edge.node2 = j
...     edge.weight = w
...     edges.append(edge)
... '''
>>> class SlotsEdge:
...     __slots__ = ('node1', 'node2', 'weight')
...     def __init__(self, node1=0, node2=0, weight=0):
...         self.node1 = node1
...         self.node2 = node2
...         self.weight = weight
...
>>> listcomploop = '''[Edge(*args) for args in ijw]'''

和时间:

>>> from timeit import Timer
>>> count, total = Timer(origloop, 'from __main__ import OrigEdge as Edge, ijw').autorange()
>>> (total / count) * 1000 # milliseconds
722.1121070033405
>>> count, total = Timer(listcomploop, 'from __main__ import SlotsEdge as Edge, ijw').autorange()
>>> (total / count) * 1000 # milliseconds
386.6706900007557

快了将近 2 倍。

将随机输入列表增加到 10^7 项，并且时间差异保持:

>>> ijw = [(randrange(100), randrange(100), randrange(1000)) for _ in range(10 ** 7)]
>>> count, total = Timer(origloop, 'from __main__ import OrigEdge as Edge, ijw').autorange()
>>> (total / count)
7.183759553998243
>>> count, total = Timer(listcomploop, 'from __main__ import SlotsEdge as Edge, ijw').autorange()
>>> (total / count)
3.8709938440006226