Matcher Python Bindings (PyO3)

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Python bindings for the Matcher library — a high-performance matcher designed to solve LOGICAL and TEXT VARIATIONS problems in word matching, implemented in Rust via PyO3.

For detailed implementation, see the Design Document.

Features

  • Text Transformation:
    • VariantNorm: CJK variant normalization. Example: 測試 -> 测试
    • Delete: Remove specific characters. Example: *Fu&*iii&^%%*&kkkk -> Fuiiikkkk
    • Normalize: Normalize special characters to identifiable characters. Example: ＡＢⅣ①℉ -> ab41°f
    • Romanize: Convert CJK characters to space-separated romanized form (Pinyin, Romaji, RR) for fuzzy matching. Example: 西安 -> xi an, matches 洗按 -> xi an, but not 先 -> xian
    • RomanizeChar: Convert CJK characters to romanized form without boundary spaces. Example: 西安 -> xian, matches 洗按 and 先 -> xian
    • EmojiNorm: Convert emoji to English words (CLDR short names) and strip modifiers. Example: 👍🏽 -> thumbs_up, 🔥 -> fire
  • AND OR NOT Word Matching:
    • Takes into account the number of repetitions of words.
    • & (AND): hello&world matches hello world and world,hello
    • | (OR): color|colour matches color and colour
    • ~ (NOT): hello~helloo~hhello matches hello but not helloo and hhello
    • \b (word boundary): \bcat\b matches "the cat" but not "concatenate"
    • Repeated segments: 无&法&无&天 matches 无无法天 (because 无 is repeated twice), but not 无法天
    • Combined: color|colour&bright~dark matches "bright color" but not "dark colour"
  • Pickle Support: SimpleMatcher instances can be pickled and unpickled for serialization.

Installation

Use pip

pip install matcher_py

Build from source

Requires the Rust nightly toolchain.

git clone https://github.com/Lips7/Matcher.git
cd Matcher/matcher_py

# Option 1: Using uv (recommended for development)
pip install uv
uv sync

# Option 2: Using maturin directly
pip install maturin
maturin develop --release

Usage

All relevant types are defined in matcher_py.pyi.

Text Process Usage

Here’s an example of how to use the reduce_text_process and text_process functions:

from matcher_py import ProcessType, reduce_text_process, text_process

# Combine and reduce multiple transformations
print(reduce_text_process(ProcessType.DELETE_NORMALIZE, "hello, world!"))
# Perform a single transformation
print(text_process(ProcessType.DELETE, "hello, world!"))

Simple Matcher — Builder (recommended)

from matcher_py import ProcessType, SimpleMatcherBuilder

builder = SimpleMatcherBuilder()
builder.add_word(ProcessType.NONE, 1, "hello&world")
builder.add_word(ProcessType.NONE, 2, "word&word~hello")
builder.add_word(ProcessType.DELETE, 3, "hallo")
matcher = builder.build()

assert matcher.is_match("hello^&!#*#&!^#*()world")
result = matcher.process("hello,world,word,word,hallo")
print(result)

Simple Matcher — JSON constructor

You can also construct from JSON bytes if you already have them:

import json

from matcher_py import ProcessType, SimpleMatcher

matcher = SimpleMatcher(
    json.dumps(
        {
            ProcessType.NONE: {
                1: "hello&world",
                2: "word&word~hello"
            },
            ProcessType.DELETE: {
                3: "hallo"
            }
        }
    ).encode()
)
assert matcher.is_match("hello^&!#*#&!^#*()world")

OR, NOT, and Word Boundary

from matcher_py import ProcessType, SimpleMatcherBuilder

builder = SimpleMatcherBuilder()
builder.add_word(ProcessType.NONE, 1, "color|colour")                     # OR
builder.add_word(ProcessType.NONE, 2, "banana~peel")                      # NOT
builder.add_word(ProcessType.NONE, 3, r"\bcat\b")                         # word boundary
builder.add_word(ProcessType.NONE, 4, r"bright&color|colour~\bdark\b")    # combined
matcher = builder.build()

assert matcher.is_match("nice colour")            # OR
assert matcher.is_match("banana split")            # NOT (no veto)
assert not matcher.is_match("banana peel")         # NOT (vetoed)
assert matcher.is_match("the cat sat")             # word boundary
assert not matcher.is_match("concatenate")         # "cat" is substring
assert matcher.is_match("bright colour")           # combined: AND + OR
assert not matcher.is_match("bright dark color")   # combined: vetoed by \bdark\b
assert matcher.is_match("bright darken color")     # "darken" ≠ \bdark\b

Explanation of the configuration

  • SimpleMatcher's configuration is defined by the SimpleTable = Dict[ProcessType, Dict[int, str]] type, the value Dict[int, str]'s key is called word_id, word_id is required to be globally unique.

ProcessType

  • NONE: No transformation.
  • VARIANT_NORM: CJK variant normalization. Based on VARIANT_NORM.
    • 測試 -> 测试
    • 現⾝ -> 现身
  • DELETE: Delete all punctuation, special characters, separator characters, and configured control/format codepoints. Based on TEXT_DELETE.
    • hello, world! -> helloworld
    • 《你∷好》 -> 你好
  • NORMALIZE: Normalize all English character variations and number variations to basic characters. Based on NORM and NUM_NORM.
    • ＡＢⅣ①℉ -> ab41°f
    • ⅠⅡⅢ -> 123
  • ROMANIZE: Convert CJK characters to space-separated romanization (Pinyin, Romaji, RR). Based on ROMANIZE.
    • 你好 -> ni hao
    • 西安 -> xi an
  • ROMANIZE_CHAR: Convert CJK characters to romanized form without boundary spaces. Based on ROMANIZE.
    • 你好 -> nihao
    • 西安 -> xian
  • EMOJI_NORM: Convert emoji to English words (CLDR short names) and strip modifiers. Based on EMOJI_NORM.
    • 👍🏽 -> thumbs_up
    • 🔥 -> fire

You can combine these transformations as needed. Pre-defined combinations like DELETE_NORMALIZE and VARIANT_NORM_DELETE_NORMALIZE are provided for convenience.

Be careful combining ROMANIZE and ROMANIZE_CHAR: they preserve different word boundaries, so the same input can behave like xi + an in one pipeline and xian in the other.

Error Handling

  • Construction (SimpleMatcher(bytes)): raises ValueError if the JSON is malformed or contains invalid ProcessType values. This is the only operation that can fail.
  • Matching (is_match, process, batch_*): infallible once the matcher is built. These methods never raise exceptions.

Contributing

Contributions to matcher_py are welcome! If you find a bug or have a feature request, please open an issue on the GitHub repository. If you would like to contribute code, please fork the repository and submit a pull request.

License

matcher_py is licensed under the MIT OR Apache-2.0 license.

More Information

For more details, visit the GitHub repository.

Project links

Key dates

PyPI data
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  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for lippsapple7 from gravatar.com lippsapple7

Credits

Data verified by PyPI on Apr 17, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI. Confirms that the provided email matches a verified, public email address on a PyPI user account associated with the project.

Author: Foster Guo

License

Apache Software License, MIT License

Requires

Python >=3.8

Classifiers

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