When is it appropriate to use pickle
, and when is it appropriate to use shelve
? That is to say, what do they do differently from each other?
From my research, I understood that pickle
can turn every Python object into stream of bytes which can be persisted into a file. Then why do we need shelve
as well? Isn't pickle
faster?
pickle
is for serializing some object (or objects) as a single bytestream in a file.
shelve
builds on top of pickle
and implements a serialization dictionary where objects are pickled, but associated with a key (some string), so you can load your shelved data file and access your pickled objects via keys. This could be more convenient were you to be serializing many objects.
Here is an example of usage between the two. (should work in latest versions of Python 2.7 and Python 3.x).
pickle
Exampleimport pickle
integers = [1, 2, 3, 4, 5]
with open('pickle-example.p', 'wb') as pfile:
pickle.dump(integers, pfile)
This will dump the integers
list to a binary file called pickle-example.p
.
Now try reading the pickled file back.
import pickle
with open('pickle-example.p', 'rb') as pfile:
integers = pickle.load(pfile)
print(integers)
The above should output [1, 2, 3, 4, 5]
.
shelve
Exampleimport shelve
integers = [1, 2, 3, 4, 5]
# If you're using Python 2.7, import contextlib and use
# the line:
# with contextlib.closing(shelve.open('shelf-example', 'c')) as shelf:
with shelve.open('shelf-example', 'c') as shelf:
shelf['ints'] = integers
Notice how you add objects to the shelf via dictionary-like access.
Read the object back in with code like the following:
import shelve
# If you're using Python 2.7, import contextlib and use
# the line:
# with contextlib.closing(shelve.open('shelf-example', 'r')) as shelf:
with shelve.open('shelf-example', 'r') as shelf:
for key in shelf.keys():
print(repr(key), repr(shelf[key]))
The output will be 'ints', [1, 2, 3, 4, 5]
.