Easily dump python objects to files, and then load them back.
Project description
pickle-warehouse makes it easy to save Python objects to files with meaningful identifiers.
How to use
pickle-warehouse provides a dictionary-like object that is associated with a particular directory on your computer.
from pickle_warehouse import Warehouse warehouse = Warehouse(‘/tmp/a-directory’)
The keys correspond to files, and the values get pickled to the files.
warehouse['filename'] = range(100) import pickle range(100) == pickle.load(open('/tmp/a-directory/filename', 'rb'))
You can also read and delete things.
# Read range(100) == warehouse['filename'] # Delete del(warehouse['filename'])
The coolest part is that the key gets interpreted in a fancy way. Aside from strings and string-like objects, you can use iterables of strings; all of these indices refer to the file /tmp/a-directory/foo/bar/baz:
warehouse[('foo','bar','baz')] warehouse[['foo','bar','baz']]
If you pass a URL, it will get broken up in a reasonable way.
# /tmp/a-directory/http/thomaslevine.com/!/?foo=bar#baz warehouse['http://thomaslevine.com/!/?foo=bar#baz'] # /tmp/a-directory/thomaslevine.com/!?foo=bar#baz warehouse['thomaslevine.com/!?foo=bar#baz']
Dates and datetimes get converted to YYYY-MM-DD format.
import datetime # /tmp/a-directory/2014-02-26 warehouse[datetime.date(2014,2,26)] warehouse[datetime.datetime(2014,2,26,13,6,42)]
And you can mix these formats!
# /tmp/a-directory/http/thomaslevine.com/open-data/2014-02-26 warehouse[('http://thomaslevine.com/open-data', datetime.date(2014,2,26))]
It also has typical dictionary methods like keys, values, items, and update.
When to use
Use this when you want a persistant store of Python objects. If you want an in-memory pickle store, look at _pickleDB: https://pythonhosted.org/pickleDB/.
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