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AiTechWorlds
AiTechWorlds
Insert and search words in a trie with shared-prefix nodes, end-of-word markers, and an animated search path.
class Trie:
def __init__(self):
self.children = {}
self.end = False
def insert(self, word):
cur = self
for ch in word:
cur = cur.children.setdefault(ch, Trie())
cur.end = TrueA trie (prefix tree) stores strings character by character along paths from the root. Words that share a prefix share nodes, making prefix lookups and autocomplete very fast. Insert and search take O(L) time, where L is the word length, independent of how many words are stored.
| Insert / Search | O(L) |
| Prefix query | O(L) |
| Space | O(total chars) |
The Trie Visualizer lets you insert and search words in a prefix tree and see how words sharing a prefix share nodes. A trie stores strings character by character along paths from the root, with end-of-word markers. Insert and search run in O(L) time, where L is the word length, independent of the number of stored words — which makes tries ideal for autocomplete and prefix queries.
Insert words
Type a lowercase word and click Insert; shared prefixes reuse existing nodes.
Search a word
Type a word and click Search to animate the path and see if it is a full word or only a prefix.
Inspect the structure
Green nodes mark the end of a word; the search path highlights in yellow.
Read the code
See the trie class in C++, Java, Python, or JavaScript and copy it.
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Last reviewed on June 14, 2026 by the AiTechWorlds Tools Team. All processing runs locally in your browser.