📦 prefix_tree

A lightweight, pure-Python prefix tree (trie) implementation for fast in-memory prefix search, autocomplete, and filtering based on metadata. Useful for building autocomplete engines, suggestion systems, and efficient word lookups.

✨ Features

• In-memory key-value storage using a prefix tree (trie)
• Fast search by prefix
• Sortable results by dictionary key
• Query filtering by field values (exact match)
• Pure Python, no dependencies
• Compatible with Python 3.10+

📅 Installation

pip install prefix-tree==0.0.7

🚀 Usage Example

from prefix_tree import Trie

# Create a new trie
trie = Trie()

# Insert words with associated metadata
trie.insert("hello", {"name": "hello", "amount": 10, "gender": "t", "type": "t"})
trie.insert("help", {"name": "help", "amount": 5, "gender": "f", "type": "f"})
trie.insert("hell", {"name": "hell", "amount": 7, "gender": "t", "type": "f"})

# Search by prefix and sort by amount (descending)
results = trie.get_by_prefix_sort_desc_by("hel", "amount")
print(results)
# Output:
# [{'name': 'hello', 'amount': 10, ...}, {'name': 'hell', 'amount': 7, ...}, {'name': 'help', 'amount': 5, ...}]

# Search by prefix and filter by query
filtered = trie.get_by_prefix_and_query("hel", {"gender": "t"})
print(filtered)
# Output:
# [{'name': 'hello', 'amount': 10, ...}, {'name': 'hell', 'amount': 7, ...}]

🔧 Build & Upload to PyPI

python3 -m build
twine upload dist/*

🧠 Use Cases

• Autocomplete and typeahead suggestions
• Named entity lookup with filters
• Efficient in-memory keyword searches
• Building simple text-based databases

🔗 Related Projects

• autocomplete-full-name (GitHub)

📚 Keywords

autocomplete, trie, prefix search, in-memory database, suggestions, python trie, word search, autocompletion, fast lookup, filtering

📝 License

MIT License (see LICENSE for details)

✨ Author

Created by ilia iakhin