pickledir 0.1.2

File-based key-value storage. Keys are strings, values are objects pickle serializable.

File-based key-value storage.

Keys can be any string. Objects must be pickle serializable.

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Unit-tested with Python 3.6-3.9 on macOS, Ubuntu and Windows.

Install

$ pip3 install pickledir

Use

Save, read, delete

from pickledir import PickleDir

cache = PickleDir('/tmp/my_cache_dir')

# saving data to files
cache['a'] = 'hello, user!'
cache['b'] = 1
cache['c'] = [1, 2, 3, 4, 5]

# reading files
print(cache['a'])
print(cache['b'])
print(cache['c'])

# delete item
del cache['b']

Read all values

for key, value in cache.items():
    print(key, value)

Set expiration time on writing

The expired items will be removed from the storage.

cache.set('a', 1000, max_age = datetime.timedelta(seconds=1))
print(cache.get('a'))  # 1000
time.sleep(2)     
print(cache.get('a'))  # None (and removed from storage)

Set expiration time on reading

The expired items will not be returned, but kept in the storage.

cache['b'] = 1000
time.sleep(2)
cache.get('b' max_age = datetime.timedelta(seconds=1)) # None
cache.get('b' max_age = datetime.timedelta(seconds=9)) # 1000

Set data version

cache = PickleDir('/tmp/my_cache', version=1)
cache['a'] = 'some_data'

You can read all stored data while the version value is 1.

cache = PickleDir('/tmp/my_cache', version=1)
print(cache.get('a'))  # 'some_data'

If you decide that all the data in the cache is out of date, just pass the constructor a version number that you haven't used before.

cache = PickleDir('/tmp/my_cache', version=2)
print(cache.get('a'))  # None

Now all that is saved with version 2 is actual data. Any other version is considered obsolete and will be gradually removed.

Do not create the PickleDir with an old version number. It will make the data unpredictable.

cacheV1 = PickleDir('/tmp/my_cache', version=1)  # ok
cacheV1['a'] = 'old A'
cacheV1['b'] = 'old B'

cacheV2 = PickleDir('/tmp/my_cache', version=2)  # ok
cacheV2['a'] = 'new A'

cacheV1 = PickleDir('/tmp/my_cache', version=1)  # don't do this
print(cacheV1.get('b'))  # Schrödinger's data ('old B' or None)

Under the hood

The implementation is deliberately naive. Each file stores a pickled dictionary (dict_in_file: Dict). dict_in_file[key] keeps the value of the item associated with key.

With a small number of items, each item is stored in a separate file (in a dictionary with a single item). With a larger number of items, some files will store dictionaries with multiple items. There will be a maximum of 4096 files in total. The string keys of two items generate the same hash, the items are stored in the same file.

This solution is extremely simple and universally compatible.

However, with a large number or size of items, disadvantages also appear. Reading and modifying files that contain multiple items is predictably slower: we will read and save the whole dictionary each time.