Strings can easily be written to and read from a file. Numbers take a bit more effort, since the read() method only returns strings, which will have to be passed to a function like string.atoi(), which takes a string like '123' and returns its numeric value 123. However, when you want to save more complex data types like lists, dictionaries, or class instances, things get a lot more complicated.
Rather than have users be constantly writing and debugging code to save complicated data types, Python provides a standard module called pickle. This is an amazing module that can take almost any Python object (even some forms of Python code!), and convert it to a string representation; this process is called pickling. Reconstructing the object from the string representation is called unpickling. Between pickling and unpickling, the string representing the object may have been stored in a file or data, or sent over a network connection to some distant machine.
If you have an object x, and a file object f that's been opened for writing, the simplest way to pickle the object takes only one line of code:
To unpickle the object again, if f is a file object which has been opened for reading:
x = pickle.load(f)
(There are other variants of this, used when pickling many objects or when you don't want to write the pickled data to a file; consult the complete documentation for pickle in the Library Reference.)
pickle is the standard way to make Python objects which can be stored and reused by other programs or by a future invocation of the same program; the technical term for this is a persistent object. Because pickle is so widely used, many authors who write Python extensions take care to ensure that new data types such as matrices can be properly pickled and unpickled.