6 Best Python Trie Data Structure Libraries

Here are the best open-source Python Trie data structure for your applications. You can use these libraries to build smartphone and web applications that efficiently store and search large collections of strings. 

Python Trie data structure libraries are an essential tool for many text-based applications. There are several libraries available in Python that provide Trie functionality such as spell-checking, auto-completion, and searching large text corpora. Certain libraries enable simple Trie implementation for Python, providing a basic set of operations for building and searching Tries. Also, some high-performance Trie libraries in Python support fast key lookups and memory-efficient storage. In addition to basic Trie functionality, Trie libraries also provide specialized functions like Trie-based spell-checking and auto-completion. Also, some libraries offer a Trie-based filter for text data. 

We have handpicked the top and tending open-source Python libraries that efficiently store and search extensive collections of strings in your applications. 

PyTrie:

• Used to implement the mapping interface, usually strings over an alphabet.
• Offers a pure Python 3 implementation of a Trie data structure. 
• Supports the standard operations of a Trie, such as insert, search, and delete. 
• Optimized for memory usage and performance.

Marisa-Trie:

• Used in Artificial Intelligence, Natural Language Processing applications.
• It is a high-performance Trie library for Python.
• Supports fast key lookups and memory-efficient storage.
• Provides a compact binary format for serializing Tries.

datrie:

• Used for its fast, efficiently stored Trie function for Python.
• Based on the Double-Array Trie structure and uses libraries.
• Supports Unicode strings, efficient memory usage, and fast key lookups.

TriePy:

• Used for its easy to implement and understand Python Tri functions.
• It’s a simple Trie implementation for Python.
• Provides a basic set of operations for building and searching Tries. 

Trie-Dictionary:

• Used for its dictionary-like interface.
• Supports fast key lookups, efficient memory usage,
• Provides a compact binary format for serializing Tries.

PyDawg:

Used for Directed Acyclic Word Graph (DAWG) data structure.

Provides fast key lookups, memory-efficient storage,

Offers a compact binary format for serializing Tries.