patricia-trie 2

Installation

pip install patricia-trie

Usage

>>> from patricia import trie
>>> T = trie(1, key='value', king='kong') # a root value and two pairs
>>> '' in T # check if the value exits (note: the [empty] root is '')
True
>>> 'kong' in T
False
>>> T['king'] # get the value for an exact key
'kong'
>>> T['kong'] # error from non-existing keys
Traceback (most recent call last):
    ...
KeyError: 'kong'
>>> len(T) # count keys ("terminals") in the tree
3
>>> sorted(T.keys()) # "traditional stuff": keys(), values(), and items()
['', 'key', 'king']
>>> # scanning a text S with key(S), value(S), and item(S):
>>> S = 'keys and kewl stuff'
>>> T.key(S) # report the (longest) key that is a prefix of S
'key'
>>> T.value(S[1:]) # remember: the empty root always matches!
1
>>> del T[''] # interlude: deleting keys
>>> T.item(S[9:]) # raise error if no key is a prefix of S
Traceback (most recent call last):
    ...
KeyError: 'k'
>>> # info: the error string above contains the matched path so far
>>> T.item(S[1:], None) # avoid the error by specifying a default
>>> # iterate all matching content with keys(S), values(S), and items(S):
>>> list(T.items(S))
[('key', 'value')]

Note that deletion is a “half-supported” operation only. The key seems “removed”, but the trie is not actually changed, only the node state is changed from terminal to non-terminal. I.e., if you frequently delete keys, the compaction will become fragmented and less efficient. To mitigate this effect, make a copy of the trie (using a copy constructor idiom):

T = trie(**T)

Copyright

Copyright 2013, Florian Leitner, All rights reserved.

License

Apache License v2