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LRU Dict

A fixed size dict like container which evicts Least Recently Used (LRU) items once size limit is exceeded. There are many python implementations available which does similar things. This is a fast and efficient C implementation. LRU maximum capacity can be modified at run-time. If you are looking for pure python version, look else where <http://www.google.com/search?q=python+lru+dict>_.

Usage

This can be used to build a LRU cache. Usage is almost like a dict.

.. code:: python

from lru import LRU l = LRU(5) # Create an LRU container that can hold 5 items

print l.peek_first_item(), l.peek_last_item() #return the MRU key and LRU key

Would print None None

for i in range(5): l[i] = str(i) print l.items() # Prints items in MRU order

Would print [(4, '4'), (3, '3'), (2, '2'), (1, '1'), (0, '0')]

print l.peek_first_item(), l.peek_last_item() #return the MRU key and LRU key

Would print (4, '4') (0, '0')

l[5] = '5' # Inserting one more item should evict the old item print l.items()

Would print [(5, '5'), (4, '4'), (3, '3'), (2, '2'), (1, '1')]

l[3] # Accessing an item would make it MRU print l.items()

Would print [(3, '3'), (5, '5'), (4, '4'), (2, '2'), (1, '1')]

Now 3 is in front

l.keys() # Can get keys alone in MRU order

Would print [3, 5, 4, 2, 1]

del l[4] # Delete an item print l.items()

Would print [(3, '3'), (5, '5'), (2, '2'), (1, '1')]

print l.get_size()

Would print 5

l.set_size(3) print l.items()

Would print [(3, '3'), (5, '5'), (2, '2')]

print l.get_size()

Would print 3

print l.has_key(5)

Would print True

print 2 in l

Would print True

l.get_stats()

Would print (1, 0)

l.update(5='0') # Update an item print l.items()

Would print [(5, '0'), (3, '3'), (2, '2')]

l.clear() print l.items()

Would print []

def evicted(key, value): print "removing: %s, %s" % (key, value)

l = LRU(1, callback=evicted)

l[1] = '1' l[2] = '2'

callback would print removing: 1, 1

l[2] = '3'

doesn't call the evicted callback

print l.items()

would print [(2, '3')]

del l[2]

doesn't call the evicted callback

print l.items()

would print []

Install

::

pip install lru-dict

or

::

easy_install lru_dict

When to use this

Like mentioned above there are many python implementations of an LRU. Use this if you need a faster and memory efficient alternative. It is implemented with a dict and associated linked list to keep track of LRU order. See code for a more detailed explanation. To see an indicative comparison with a pure python module, consider a benchmark <https://gist.github.com/amitdev/5773979>_ against pylru <https://pypi.python.org/pypi/pylru/>_ (just chosen at random, it should be similar with other python implementations as well).

::

$ python bench.py pylru.lrucache Time : 3.31 s, Memory : 453672 Kb $ python bench.py lru.LRU Time : 0.23 s, Memory : 124328 Kb