Metadata-Version: 2.1
Name: complex-text-tools
Version: 0.2.0
Summary: A package for processing complex text with mixed Chinese and English characters
Home-page: https://github.com/yourusername/complex-text-tools
Author: Your Name
Author-email: Your Name <your.email@example.com>
License: MIT
Project-URL: Homepage, https://github.com/yourusername/complex-text-tools
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Text Processing :: Linguistic
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Provides-Extra: dev
Requires-Dist: pytest>=6.0; extra == "dev"

# Complex Text Tools

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A Python package for processing complex text containing mixed Chinese and English characters, removing extra spaces and counting text length according to specific rules.

## Features

- Remove extra spaces between Chinese characters
- Remove extra spaces between Chinese and English characters
- Handle spacing around punctuation marks correctly
- Count text length according to specific rules (Chinese characters, English words, numbers, equations, etc.)
- Process mixed language texts efficiently

## Installation

```bash
pip install complex-text-tools
```

## Usage

### Remove Extra Spaces

```python
from complex_text_tools import remove_extra_spaces

text = "这 是  中文 测试  文本 ，  mixed  English  text  here ， 还 有   symbols :  ;  !  "
clean_text = remove_extra_spaces(text)
print(clean_text)
# Output: "这是中文测试文本，mixed English text here，还有 symbols:;!"
```

### Count Effective Text Length

```python
from complex_text_tools import count_eff_len

text = "这是一段包含 English words 和 123.45 数字的 mixed 文本"
result = count_eff_len(text)
print(result)
# Output: {"total": 15}
```

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
