lexrs
Efficient lexicon data structures — Trie and DAWG (Directed Acyclic Word Graph) — backed by Rust for 10–100× faster insertion and search compared to pure Python.
lexrs is the successor to lexpy. It exposes the same API, so existing code requires minimal changes.
Install
pip install pylexrs
API
Both Trie and DAWG expose the same interface:
| Method | Description |
|---|---|
add(word, count) |
Insert a word with an optional frequency count |
add_all(words) |
Insert from any iterable |
add_from_file(path) |
Insert words from a file (one per line) |
contains(word) |
Exact membership test |
contains_prefix(prefix) |
Check if any word starts with the given prefix |
search(pattern) |
Wildcard search (* = zero or more chars, ? = exactly one) |
search(pattern, with_count=True) |
Like search, but returns (word, count) pairs |
search_with_prefix(prefix) |
All words beginning with the prefix |
search_with_prefix(prefix, with_count=True) |
Like above, with counts |
search_within_distance(word, dist) |
Levenshtein fuzzy search |
search_within_distance(word, dist, with_count=True) |
Like above, with counts |
get_word_count() |
Number of words stored |
len(t) |
Number of nodes in the structure |
Usage
from lexrs import Trie, DAWG
# ── Trie ──────────────────────────────────────────────────────────────────────
t = Trie()
t.add("hello", 5) # word + optional frequency count
t.add_all(["world", "foo"])
t.add_from_file("words.txt")
"hello" in t # True
t.contains_prefix("wor") # True
t.get_word_count() # total words stored
len(t) # total nodes
t.search("h*") # wildcard → list of words
t.search("h*", with_count=True) # → list of (word, count)
t.search_with_prefix("wo") # prefix completion
t.search_with_prefix("wo", with_count=True) # with counts
t.search_within_distance("helo", 1) # fuzzy, Levenshtein ≤ 1
t.search_within_distance("helo", 1, with_count=True)
# ── DAWG ──────────────────────────────────────────────────────────────────────
# DAWG compresses shared suffixes — fewer nodes for large lexicons.
# Words are sorted automatically by add_all.
d = DAWG()
d.add_all(["apple", "apply", "apt"])
"apple" in d # True
d.search("ap*") # wildcard
d.search_within_distance("aple", 1) # fuzzy
Wildcard syntax
| Pattern | Meaning |
|---|---|
* |
Zero or more characters |
? |
Exactly one character |
h* |
All words starting with h |
?at |
Three-letter words ending in at |
a?* |
Words of two or more characters starting with a |
Consecutive wildcards are normalized (** → *, ?* → *).
Migrating from lexpy
# lexpy 1.x
from lexpy.trie import Trie
from lexpy.dawg import DAWG
# lexrs
from lexrs import Trie, DAWG
The API is otherwise identical.
More
Full documentation, the production HTTP server (reader/writer), Docker Compose setup, and benchmarks are available at github.com/aosingh/lexrs.
Metadata
Release files for pylexrs 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pylexrs-1.0.0.tar.gz | 32.4 kB | Details |
Built distributions (wheels)
Total release size: 6.9 MB
Release files / pylexrs-1.0.0.tar.gz
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