TinySegmenter

Warnings

• gotcha The project is explicitly stated by its maintainer as not being actively developed, with limited maintenance. New features or rapid bug fixes are unlikely.
  Fix: Be aware of the project's maintenance status. For active development or critical projects, consider forks like 'tinysegmenter3' or more actively maintained Japanese tokenizers.
• gotcha As a 'very compact' tokenizer, TinySegmenter makes trade-offs in accuracy and performance compared to larger, more sophisticated Japanese NLP libraries. While suitable for lightweight tasks, it might not offer the highest precision or speed for complex or large-scale Japanese text processing.
  Fix: For higher accuracy or performance requirements, evaluate alternative Japanese tokenizers such as MeCab, Sudachi, or Janome. Benchmarking with your specific data is recommended.
• gotcha Although the `tinysegmenter` 0.4 package states compatibility with Python 3, a prominent fork named `tinysegmenter3` exists specifically to provide improved Python 3 compatibility and enhanced performance. This implies that the original `tinysegmenter` might not be fully optimized or as robust for modern Python 3 environments as its dedicated Python 3 fork.
  Fix: If working with Python 3, especially for performance-sensitive applications, consider using `tinysegmenter3` (`pip install tinysegmenter3`) or another Python 3 native Japanese tokenizer for potentially better results.

Install

• pip install tinysegmenter Install with pip

Imports

• TinySegmenter

  from tinysegmenter import TinySegmenter

  The class is directly available under the 'tinysegmenter' module, not a nested submodule.

Quickstart

Initialize the TinySegmenter and tokenize a Japanese string into a list of words.

import tinysegmenter

segmenter = tinysegmenter.TinySegmenter()
text = "私の名前は中野です"
tokens = segmenter.tokenize(text)
print(' | '.join(tokens))
# Expected output: 私 | の | 名前 | は | 中野 | です