压缩内存中的Python对象 [英] Compress Python Object in Memory

问题描述

关于使用Python压缩文件的大多数教程都涉及立即将文件写入磁盘，而中间没有经过压缩的python对象。我想知道如何腌制然后压缩内存中的python对象，而无需写入磁盘或从磁盘读取数据。

Most tutorials on compressing a file in Python involve immediately writing that file to disk with no intervening compressed python object. I want to know how to pickle and then compress a python object in memory without ever writing to or reading from disk.

推荐答案

我用它在一个地方保存内存：

I use this to save memory in one place:

import cPickle
import zlib

# Compress:
compressed = zlib.compress(cPickle.dumps(obj))

# Get it back:
obj = cPickle.loads(zlib.decompress(compressed))

如果 obj 引用了许多小对象，则可以减少很多内存的使用。由于每个对象的内存开销以及内存碎片，Python中的许多小对象加起来了。

If obj has references to a number of small objects, this can reduce the amount of memory used by a lot. A lot of small objects in Python add up because of per-object memory overhead as well as memory fragmentation.

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