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.
Open a persistent dictionary. The filename specified is the base filename for the underlying database. As a side-effect, an extension may be added to the filename and more than one file may be created. By default, the underlying database file is opened for reading and writing. The optional flag parameter has the same interpretation as the flag parameter of anydbm.open().
By default, version 0 pickles are used to serialize values. The version of the pickle protocol can be specified with the protocol parameter.
Changed in version 2.3: The protocol parameter was added.
Because of Python semantics, a shelf cannot know when a mutable persistent-dictionary entry is modified. By default modified objects are written only when assigned to the shelf (see Example). If the optional writeback parameter is set to True, all entries accessed are cached in memory, and written back on sync() and close(); this can make it handier to mutate mutable entries in the persistent dictionary, but, if many entries are accessed, it can consume vast amounts of memory for the cache, and it can make the close operation very slow since all accessed entries are written back (there is no way to determine which accessed entries are mutable, nor which ones were actually mutated).
Note
Do not rely on the shelf being closed automatically; always call close() explicitly when you don’t need it any more, or use a with statement with contextlib.closing().
Shelf objects support all methods supported by dictionaries. This eases the transition from dictionary based scripts to those requiring persistent storage.
Two additional methods are supported:
See also
Persistent dictionary recipe with widely supported storage formats and having the speed of native dictionaries.
A subclass of UserDict.DictMixin which stores pickled values in the dict object.
By default, version 0 pickles are used to serialize values. The version of the pickle protocol can be specified with the protocol parameter. See the pickle documentation for a discussion of the pickle protocols.
Changed in version 2.3: The protocol parameter was added.
If the writeback parameter is True, the object will hold a cache of all entries accessed and write them back to the dict at sync and close times. This allows natural operations on mutable entries, but can consume much more memory and make sync and close take a long time.
To summarize the interface (key is a string, data is an arbitrary object):
import shelve
d = shelve.open(filename) # open -- file may get suffix added by low-level
# library
d[key] = data # store data at key (overwrites old data if
# using an existing key)
data = d[key] # retrieve a COPY of data at key (raise KeyError if no
# such key)
del d[key] # delete data stored at key (raises KeyError
# if no such key)
flag = d.has_key(key) # true if the key exists
klist = d.keys() # a list of all existing keys (slow!)
# as d was opened WITHOUT writeback=True, beware:
d['xx'] = range(4) # this works as expected, but...
d['xx'].append(5) # *this doesn't!* -- d['xx'] is STILL range(4)!
# having opened d without writeback=True, you need to code carefully:
temp = d['xx'] # extracts the copy
temp.append(5) # mutates the copy
d['xx'] = temp # stores the copy right back, to persist it
# or, d=shelve.open(filename,writeback=True) would let you just code
# d['xx'].append(5) and have it work as expected, BUT it would also
# consume more memory and make the d.close() operation slower.
d.close() # close it
See also