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Manage shelves of pickled objects.

A "shelf" is a persistent, dictionary-like object.  The difference
with dbm databases is that the values (not the keys!) in a shelf can
be essentially arbitrary Python objects -- anything that the "pickle"
module can handle.  This includes most class instances, recursive data
types, and objects containing lots of shared sub-objects.  The keys
are ordinary strings.

To summarize the interface (key is a string, data is an arbitrary
object):

        import shelve
        d = shelve.open(filename) # open, with (g)dbm filename -- no suffix

        d[key] = data   # store data at key (overwrites old data if
                        # using an existing key)
        data = d[key]   # retrieve a COPY of the data at key (raise
                        # KeyError if no such key) -- NOTE that this
                        # access returns a *copy* of the entry!
        del d[key]      # delete data stored at key (raises KeyError
                        # if no such key)
        flag = key in d # true if the key exists
        list = d.keys() # a list of all existing keys (slow!)

        d.close()       # close it

Dependent on the implementation, closing a persistent dictionary may
or may not be necessary to flush changes to disk.

Normally, d[key] returns a COPY of the entry.  This needs care when
mutable entries are mutated: for example, if d[key] is a list,
        d[key].append(anitem)
does NOT modify the entry d[key] itself, as stored in the persistent
mapping -- it only modifies the copy, which is then immediately
discarded, so that the append has NO effect whatsoever.  To append an
item to d[key] in a way that will affect the persistent mapping, use:
        data = d[key]
        data.append(anitem)
        d[key] = data

To avoid the problem with mutable entries, you may pass the keyword
argument writeback=True in the call to shelve.open.  When you use:
        d = shelve.open(filename, writeback=True)
then d keeps a cache of all entries you access, and writes them all back
to the persistent mapping when you call d.close().  This ensures that
such usage as d[key].append(anitem) works as intended.

However, using keyword argument writeback=True may consume vast amount
of memory for the cache, and it may make d.close() very slow, if you
access many of d's entries after opening it in this way: d has no way to
check which of the entries you access are mutable and/or which ones you
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