WordTrie: a simple trie (prefix tree) for word and phrase matching
Project description
WordTrie
Example
Create a new trie:
from wordtrie import WordTrie
trie = WordTrie()
Words and their values are added to the trie with the add()
method:
trie.add("She", 1)
trie.add("sea", 2)
Exact matches in the trie are found with the match()
method:
print(trie.match("She"))
# 1
print(trie.match("sells"))
# None
print(trie.match("She sells"))
# None
All matches in a stream of words can be found with the search()
method:
print(trie.search("She sells sea shells by the sea shore."))
# [1, 2, 2]
Phrases can be added too and will be split into a list of words:
trie.add("sea shells", 3)
# same as trie.add(["sea", "shells"], 3)
Matching is greedy and will match the maximal length phrase:
print(trie.match("sea shells"))
# 3
print(trie.search("She sells sea shells by the sea shore."))
# [1, 3, 2]
In addition to the values, you can return the trie nodes that were
matched with return_nodes=True
:
print(trie.search("She sells sea shells by the sea shore.", return_nodes=True))
# [(['She'], 1), (['sea', 'shells'], 3), (['sea'], 2)]
The trie can be written to a JSON file with:
trie.to_json("sea.json")
# {
# "She": {
# "#": 1
# },
# "sea": {
# "#": 2,
# "shells": {
# "#": 3
# }
# }
# }
Or restored from a JSON file with:
trie.from_json("sea.json")
print(trie.match("sea"))
# 2
The reserved key #
is used to store the value in the JSON structure. You can still add a word that starts with #
to the trie, and it will be protected with an additional prepended #
:
trie.add("#She", 4)
trie.to_json("sea.json")
# {
# "##She": {
# ...
print(trie.match("#She"))
# 4
When a node does not yet exist in the trie, the value specified in the add()
method is used as the initial value. If the node already exists, then an aggregator function can be called to modify the value based on the old and new values. The default aggregator is to replace the old value with the new value. However, a custom aggregator can be defined as a function with signature aggregator(old, new)
and passed to the add()
call:
def sum_aggregator(old, new):
return old + new
trie.add("She", 100, aggregator=sum_aggregator)
print(trie.search("She sells sea shells by the sea shore."))
# [101, 3, 2]
Testing
Run the example above as a basic regression test with:
# grep "^ " README.md | sed 's/ //' | python
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