Common use-cases for pickle in Python

Some uses that I have come across:

1) saving a program's state data to disk so that it can carry on where it left off when restarted (persistence)

2) sending python data over a TCP connection in a multi-core or distributed system (marshalling)

3) storing python objects in a database

4) converting an arbitrary python object to a string so that it can be used as a dictionary key (e.g. for caching & memoization).

There are some issues with the last one - two identical objects can be pickled and result in different strings - or even the same object pickled twice can have different representations. This is because the pickle can include reference count information.

To emphasise @lunaryorn's comment - you should never unpickle a string from an untrusted source, since a carefully crafted pickle could execute arbitrary code on your system. For example see https://blog.nelhage.com/2011/03/exploiting-pickle/

Minimal roundtrip example..

>>> import pickle>>> a = Anon()>>> a.foo = 'bar'>>> pickled = pickle.dumps(a)>>> unpickled = pickle.loads(pickled)>>> unpickled.foo'bar'

Edit: but as for the question of real-world examples of pickling, perhaps the most advanced use of pickling (you'd have to dig quite deep into the source) is ZODB:http://svn.zope.org/

Otherwise, PyPI mentions several:http://pypi.python.org/pypi?:action=search&term=pickle&submit=search

I have personally seen several examples of pickled objects being sent over the network as an easy to use network transfer protocol.

I have used it in one of my projects. If the app was terminated during it's working (it did a lengthy task and processed lots of data), I needed to save the whole data structure and reload it after the app was run again. I used cPickle for this, as speed was a crucial thing and the size of data was really big.