unicode-segmentation-rs

Python bindings for the Rust unicode-segmentation, unicode-linebreak, and unicode-width crates, providing Unicode text segmentation and width calculation according to Unicode standards.

Features

Grapheme Cluster Segmentation: Split text into user-perceived characters
Word Segmentation: Split text into words according to Unicode rules
Sentence Segmentation: Split text into sentences
Line-Break Segmentation: Find legal wrapping opportunities according to Unicode Standard Annex #14
Display Width Calculation: Get the display width of text (for terminal/monospace display)
Gettext PO Wrapping: Wrap text for gettext PO files with proper handling of escape sequences and CJK characters

Installation

From PyPI

uv pip install unicode-segmentation-rs

From source

# Install maturin
pip install maturin

# Build and install the package
maturin develop --release

Usage

import unicode_segmentation_rs

# Grapheme clusters (user-perceived characters)
text = "Hello 👨‍👩‍👧‍👦 World"
clusters = unicode_segmentation_rs.graphemes(text, is_extended=True)
print(clusters)  # ['H', 'e', 'l', 'l', 'o', ' ', '👨‍👩‍👧‍👦', ' ', 'W', 'o', 'r', 'l', 'd']

# Get grapheme clusters with their byte indices
indices = unicode_segmentation_rs.grapheme_indices(text, is_extended=True)
print(indices)  # [(0, 'H'), (1, 'e'), ...]

# Word boundaries (includes punctuation and whitespace)
text = "Hello, world!"
words = unicode_segmentation_rs.split_word_bounds(text)
print(words)  # ['Hello', ',', ' ', 'world', '!']

# Unicode words (excludes punctuation and whitespace)
words = unicode_segmentation_rs.unicode_words(text)
print(words)  # ['Hello', 'world']

# Word indices
indices = unicode_segmentation_rs.split_word_bound_indices(text)
print(indices)  # [(0, 'Hello'), (5, ','), ...]

# Sentence segmentation
text = "Hello world. How are you? I'm fine."
sentences = unicode_segmentation_rs.unicode_sentences(text)
print(sentences)  # ['Hello world. ', 'How are you? ', "I'm fine."]

# Line-break opportunities use UTF-8 byte offsets
text = "你好世界"
breaks = unicode_segmentation_rs.line_breaks(text)
print(breaks)  # [(3, False), (6, False), (9, False), (12, True)]
units = unicode_segmentation_rs.line_break_units(text)
print(units)  # ['你', '好', '世', '界']

# Display width calculation
text = "Hello 世界"
width = unicode_segmentation_rs.text_width(text)
print(width)  # 10 (Hello=5, space=1, 世=2, 界=2, but depends on terminal)

# Character width
print(unicode_segmentation_rs.text_width('A'))    # 1
print(unicode_segmentation_rs.text_width('世'))   # 2
print(unicode_segmentation_rs.text_width('\t'))   # 1

Examples

Grapheme Cluster Segmentation

import unicode_segmentation_rs

# Complex emojis and combining characters
text = "Hello 👨‍👩‍👧‍👦 नमस्ते"
print(f"Text: {text}")
print(f"Graphemes: {unicode_segmentation_rs.graphemes(text, is_extended=True)}")
print(f"Length (graphemes): {len(unicode_segmentation_rs.graphemes(text, is_extended=True))}")
print(f"Length (chars): {len(text)}")

# With indices
print("Grapheme indices:")
for idx, cluster in unicode_segmentation_rs.grapheme_indices(text, is_extended=True):
    print(f"  {idx:3d}: {cluster!r}")

Word Segmentation

text = "Hello, world! How are you?"
print(f"Text: {text}")
print(f"Word bounds: {unicode_segmentation_rs.split_word_bounds(text)}")
print(f"Unicode words: {unicode_segmentation_rs.unicode_words(text)}")

# With indices
print("Word boundary indices:")
for idx, word in unicode_segmentation_rs.split_word_bound_indices(text):
    print(f"  {idx:3d}: {word!r}")

Sentence Segmentation

text = "Hello world. How are you? I'm fine, thanks! What about you?"
print(f"Text: {text}")
sentences = unicode_segmentation_rs.unicode_sentences(text)
print("Sentences:")
for i, sentence in enumerate(sentences, 1):
    print(f"  {i}. {sentence!r}")

Line-Break Segmentation

# Find legal wrapping opportunities without measuring or reformatting text
text = "Hello 世界"
print(unicode_segmentation_rs.line_breaks(text))
print(unicode_segmentation_rs.line_break_units(text))  # ['Hello ', '世', '界']

# A soft hyphen is preserved in the unit before its discretionary break
text = "foo\u00adbar"
print(unicode_segmentation_rs.line_break_units(text))  # ['foo\u00ad', 'bar']

Line-break segmentation reports opportunities only. The caller remains responsible for measuring widths, trimming whitespace for display, and rendering a visible hyphen when selecting a soft-hyphen break.

The underlying unicode-linebreak crate treats complex-context (SA) characters as ordinary alphabetic characters rather than performing dictionary-based segmentation. Consequently, scripts such as Thai, Lao, and Khmer do not receive language-specific word break opportunities.

Multilingual Examples

# Arabic
arabic = "مرحبا بك. كيف حالك؟"
print(f"Arabic: {arabic}")
print(f"Sentences: {unicode_segmentation_rs.unicode_sentences(arabic)}")

# Japanese
japanese = "こんにちは。お元気ですか？"
print(f"Japanese: {japanese}")
print(f"Sentences: {unicode_segmentation_rs.unicode_sentences(japanese)}")

# Mixed languages
mixed = "Hello世界! This is a test文章."
print(f"Mixed: {mixed}")
print(f"Words: {unicode_segmentation_rs.unicode_words(mixed)}")

Display Width Calculation

examples = [
    "Hello",
    "世界",
    "Hello 世界",
    "こんにちは",
    "🎉🎊",
    "Tab\there",
]

for text in examples:
    width = unicode_segmentation_rs.text_width(text)
    print(f"Text: {text!r:20} Width: {width:2} Chars: {len(text):2}")

# Character widths
chars = ['a', 'A', '1', ' ', '世', '界', 'あ', '🎉', '\t', '\n']
for c in chars:
    w = unicode_segmentation_rs.text_width(c)
    print(f"  {c!r:6} width: {w:2}")

Gettext PO File Wrapping

# Wrap text for PO files (default width is 77 characters)
text = "This is a long translation string that needs to be wrapped appropriately for a gettext PO file"
lines = unicode_segmentation_rs.gettext_wrap(text, 77)
for i, line in enumerate(lines, 1):
    print(f"Line {i}: {line}")

# Wrapping with CJK characters
text = "This translation contains 中文字符 (Chinese characters) and should wrap correctly"
lines = unicode_segmentation_rs.gettext_wrap(text, 40)
for line in lines:
    width = unicode_segmentation_rs.text_width(line)
    print(f"[{width:2d} cols] {line}")

# Escape sequences are preserved
text = "This has\\nline breaks\\tand tabs"
lines = unicode_segmentation_rs.gettext_wrap(text, 20)
print(lines)

API Reference

`graphemes(text: str, is_extended: bool) -> list[str]`

Split a string into grapheme clusters. Set is_extended=True for extended grapheme clusters (recommended).

`grapheme_indices(text: str, is_extended: bool) -> list[tuple[int, str]]`

Split a string into grapheme clusters with their byte indices.

`split_word_bounds(text: str) -> list[str]`

Split a string at word boundaries (includes punctuation and whitespace).

`split_word_bound_indices(text: str) -> list[tuple[int, str]]`

Split a string at word boundaries with byte indices.

`unicode_words(text: str) -> list[str]`

Get Unicode words from a string (excludes punctuation and whitespace).

`unicode_sentences(text: str) -> list[str]`

Split a string into sentences according to Unicode rules.

`line_breaks(text: str) -> list[tuple[int, bool]]`

Return every allowed or mandatory Unicode line-break opportunity as (utf8_byte_offset, mandatory). The boolean is True only for mandatory breaks. Non-empty input includes the mandatory end-of-text opportunity.

`line_break_units(text: str) -> list[str]`

Split a string at every allowed or mandatory Unicode line-break opportunity. Every input code point is preserved exactly, and the mandatory end-of-text opportunity does not add an empty unit.

`text_width(text: str) -> int`

Get the display width of a string in columns (as it would appear in a terminal). East Asian characters typically take 2 columns.

`gettext_wrap(text: str, width: int) -> list[str]`

Wrap text for gettext PO files. This function follows gettext's wrapping behavior:

Never breaks escape sequences (\n, \", etc.)
Prefers breaking after spaces
Handles CJK characters with proper width calculation
Breaks long words only when necessary

Building for Distribution

# Build wheel
maturin build --release

# Build and publish to PyPI
maturin publish

Running Tests

# Install test dependencies
pip install pytest

# Run tests
pytest tests/

License

This project is licensed under the Apache License 2.0.

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SHA256	`16b6c41791858589907d17144c92917e3ff5d552b7ed57b8dd4659b87b2e1b81`
MD5	`747e20cfc9e66eb10c3313be7ca99829`
BLAKE2b-256	`2820ebe648c1f6b261aeab8ff0e6ee750dcef967b1d2c62f0ca9e2aafcb83010`

Algorithm	Hash digest
SHA256	`25da168f2577f3477cfa490b13a209287e5aa3e1daa2e749ff365e7b9b895472`
MD5	`283a617ef81ff683e67b651c0bda12b6`
BLAKE2b-256	`ded8f5e0f95eb402763e1e3db21e695dac9b48357fe018bdccff5f3070383c6b`

Algorithm	Hash digest
SHA256	`a0b700484240687ac92fb9c8320b6ab1a0184a9bc32892c83749bbf79ea298c7`
MD5	`6daf615e267475b99519ac6e5f817be7`
BLAKE2b-256	`50c82ff0f229a7dfd6dbc7d60a5eb45448a4c3b4834186ce9067cfd216c72645`

Algorithm	Hash digest
SHA256	`08bf49b2147576ed60c6d590e5b59cbc4ddaae00a5f9f795ae47fdc962d03def`
MD5	`e9161499daebb1af123d521a4df40c86`
BLAKE2b-256	`c54aa8f3a64631b69e1934712640016d61d9702a4e573448976da375fda5c59e`

Algorithm	Hash digest
SHA256	`4a1cc2cb64371b8e414c588c46555bd874389cba6386c86b54199ac4c37d3db3`
MD5	`e6647c0a675bb82e93807a263c32440e`
BLAKE2b-256	`f7e95908bffaae4af7406fd8be91cb1f73880ada90fd32d745aff7858d4c8921`

Algorithm	Hash digest
SHA256	`07a6eb8c0ac2c0d598162f59910b881d512ee3c9a8c8579ad1a757e8075d18c7`
MD5	`20572fd332852a81ec120694ef5d89dd`
BLAKE2b-256	`95c864f431dc441c8d3c38de755a8db25c73659ca1e1a50bd271a7be108ba639`

Algorithm	Hash digest
SHA256	`e9dd0982da46ca28f6eeafe74cc76bc48a967d4a6466a517b77304aa56e3d836`
MD5	`f54004a4c040c76b3092881ccacd9486`
BLAKE2b-256	`61b3ec5f939b0de2307df0f5d2ee0d9624afaaf33bfd3d4438c6fc008286dd9d`

unicode-segmentation-rs 0.3.2

unicode-segmentation-rs

Features

Installation

From PyPI

From source

Usage

Examples

Grapheme Cluster Segmentation

Word Segmentation

Sentence Segmentation

Line-Break Segmentation

Multilingual Examples

Display Width Calculation

Gettext PO File Wrapping

API Reference

graphemes(text: str, is_extended: bool) -> list[str]

grapheme_indices(text: str, is_extended: bool) -> list[tuple[int, str]]

split_word_bounds(text: str) -> list[str]

split_word_bound_indices(text: str) -> list[tuple[int, str]]

unicode_words(text: str) -> list[str]

unicode_sentences(text: str) -> list[str]

line_breaks(text: str) -> list[tuple[int, bool]]

line_break_units(text: str) -> list[str]

text_width(text: str) -> int

gettext_wrap(text: str, width: int) -> list[str]

Building for Distribution

Running Tests

License

Project links

Key dates

Owner

Credits

GitHub Statistics

Requires

Classifiers

Download files

Source Distribution

Built Distributions

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`graphemes(text: str, is_extended: bool) -> list[str]`

`grapheme_indices(text: str, is_extended: bool) -> list[tuple[int, str]]`

`split_word_bounds(text: str) -> list[str]`

`split_word_bound_indices(text: str) -> list[tuple[int, str]]`

`unicode_words(text: str) -> list[str]`

`unicode_sentences(text: str) -> list[str]`

`line_breaks(text: str) -> list[tuple[int, bool]]`

`line_break_units(text: str) -> list[str]`

`text_width(text: str) -> int`

`gettext_wrap(text: str, width: int) -> list[str]`

Algorithm	Hash digest
SHA256	`a9ae59277bee1b76e9393e86f362150cb38007dfb6749c96c46c93d354e203b0`
MD5	`65d3bb76dee72ea6fe9c0f402b35d10c`
BLAKE2b-256	`52f5388d61cb8df5b1b52abd9ae1444a0429ef94a6f1fc546e3ca0b2acb7f7f6`

Algorithm	Hash digest
SHA256	`5a31902842ddefbc9fc24ee3cf5861eefa9aa91c59f6849a57ad2a661227bdd5`
MD5	`c18e010e13477111deca16d30e5347f2`
BLAKE2b-256	`2f653506b1e89e566bcf0baa5b8e31ec0fd6ed952ddaac9f95f9bfe7ac5687aa`

Algorithm	Hash digest
SHA256	`16b2017c7b263083bdf80055aca2c6374530a34117b6858c188c9a9d2f0d1033`
MD5	`2937f50f9653133cd80f6d809ed2e3ba`
BLAKE2b-256	`dcb009f33a95f2bd955d80e5e14d0d72fb816d69aaa3ce122a48dfeed781bc5b`

Algorithm	Hash digest
SHA256	`478f4cc90e1722ba0722d487768dc2e55c0f60a64116fd2034c1d7780033bc86`
MD5	`c8e9a9c20ef12446e72684b9a63d4fdf`
BLAKE2b-256	`4caf93de2ed02c3c30239ef4d842ccf3d7d90dbe86e52a0db1a1501d67923780`

Algorithm	Hash digest
SHA256	`a87350117eab030dca6c672f4bc39705f1af8b988f66a4a58a6263277398031f`
MD5	`179e8b526d661dfa7ea3817b5374b5da`
BLAKE2b-256	`ef68034645447ecc411eafdc81b624d7e0aca4bc36434a8f7322dcdfbdfb0b41`

Algorithm	Hash digest
SHA256	`936148f1accf9e484bd1f1fed4f3e32fe4f5fc8265ac1ec00f2f0bfa14c82d6e`
MD5	`26c910938e00cfd4515c295b292a9d14`
BLAKE2b-256	`a3886a9c17cd9dbb2f874f3786c13cb47a4cf60fae649ccd1f1948b9d6bb8902`

Algorithm	Hash digest
SHA256	`fbba7195018560c47a5d7421b0c9a2b1cf5aee24ba6246c0f1ebb898d68fe856`
MD5	`647729331523ae604a22c68af951676c`
BLAKE2b-256	`d4f930cf997056aa27ffc8843b6b3386065b750260a730523b1bff73f2a3007c`

Algorithm	Hash digest
SHA256	`9cbe7231bbbb50051d85fd93fdc020783e3104fcc96554597e413fd8771a8a97`
MD5	`b54e3dbfac0a85ab816fb5c2d7815b3d`
BLAKE2b-256	`da11843224db0bcbbddf92f1da3c53fc72c2b19007f822cb73d91964dc66e0d6`

Algorithm	Hash digest
SHA256	`317c5b5892b6906f9a48a53f230c4c8737a0ce5e3abec7de6d810548cb82b2e3`
MD5	`f709e19d8a28a25985975e221d319c36`
BLAKE2b-256	`9065cc9647898a0ab1fccf843077e4d2ca61b00c91c7bfffbec7b913ec64222c`

Algorithm	Hash digest
SHA256	`37730584f85261dbe0e873c8513efa54c71e30f4afebb722e8a228981da2cd53`
MD5	`5c7a20b6a213d0e175ef5003af5436c0`
BLAKE2b-256	`f6a3bbe763124504e978849fe8ff4eb7ce2e7cc4c6c46dba79d64a6b6b8bd3ae`