mafan 0.3.1

A toolbox for working with the Chinese language in Python

[](https://travis-ci.org/hermanschaaf/mafan)

===========
Mafan - Toolkit for working with Chinese in Python
===========

Mafan is a collection of Python tools for making your life working with Chinese so much less 麻烦 (mafan, i.e. troublesome).

Contained in here is an ever-growing collection of loosely-related tools, broken down into several files. These are:

installation
===========

Install through pip:

pip install mafan

encodings
===========

`encodings` contains functions for converting files from any number of 麻烦 character encodings to something more sane (utf-8, by default). For example:

```python
from mafan import encoding

filename = 'ugly_big5.txt' # name or path of file as string
encoding.convert(filename) # creates a file with name 'ugly_big5_utf-8.txt' in glorious utf-8 encoding
```


text
===========

`text` contains some functions for working with strings. Things like detecting english in a string, whether a string has Chinese punctuation, etc. Check out `text.py` for all the latest goodness. It also contains a handy wrapper for the jianfan package for converting between simplified and traditional:

```python
>>> from mafan import simplify, tradify
>>> string = u'这是麻烦啦'
>>> print tradify(string) # convert string to traditional
這是麻煩啦
>>> print simplify(tradify(string)) # convert back to simplified
这是麻烦啦
```

The `has_punctuation` and `contains_latin` functions are useful for knowing whether you are really dealing with Chinese, or Chinese characters:

```python
>>> from mafan import text
>>> text.has_punctuation(u'这是麻烦啦') # check for any Chinese punctuation (full-stops, commas, quotation marks, etc)
False
>>> text.has_punctuation(u'这是麻烦啦.')
False
>>> text.has_punctuation(u'这是麻烦啦。')
True
>>> text.contains_latin(u'这是麻烦啦。')
False
>>> text.contains_latin(u'You are麻烦啦。')
True
```

You can also test whether sentences or documents use simplified characters, traditional characters, both or neither:

```python
>>> import mafan
>>> from mafan import text
>>> text.is_simplified(u'这是麻烦啦')
True
>>> text.is_traditional(u'Hello,這是麻煩啦') # ignores non-chinese characters
True

# Or done another way:
>>> text.identify(u'这是麻烦啦') is mafan.SIMPLIFIED
True
>>> text.identify(u'這是麻煩啦') is mafan.TRADITIONAL
True
>>> text.identify(u'这是麻烦啦! 這是麻煩啦') is mafan.BOTH
True
>>> text.identify(u'This is so mafan.') is mafan.NEITHER # or None
True
```

The identification functionality is introduced as a very thin wrapper to Thomas Roten's [hanzidentifier](https://github.com/tsroten/hanzidentifier), which is included as part of mafan.

Another function that comes pre-built into Mafan is `split_text`, which tokenizes Chinese sentences into words:

```python
>>> from mafan import split_text
>>> split_text(u"這是麻煩啦")
[u'\u9019', u'\u662f', u'\u9ebb\u7169', u'\u5566']
>>> print ' '.join(split_text(u"這是麻煩啦"))
這 是 麻煩 啦
```

You can also optionally pass the boolean `include_part_of_speech` parameter to get tagged words back:

```python
>>> split_text(u"這是麻煩啦", include_part_of_speech=True)
[(u'\u9019', 'r'), (u'\u662f', 'v'), (u'\u9ebb\u7169', 'x'), (u'\u5566', 'y')]
```

pinyin
===========

`pinyin` contains functions for working with or converting between pinyin. At the moment, the only function in there is one to convert numbered pinyin to the pinyin with correct tone marks. For example:

```python
>>> from mafan import pinyin
>>> print pinyin.decode("ni3hao3")
nǐhǎo
```

traditional characters
===========

If you want to be able to use `split_text` on traditional characters, you can make use of one of two options:

- Either set an environment variable, `MAFAN_DICTIONARY_PATH`, to the absolute path to a local copy of this [dictionary file](https://github.com/fxsjy/jieba/raw/master/extra_dict/dict.txt.big),
- or install the `mafan_traditional` convenience package: `pip install mafan_traditional`. If this package is installed and available, mafan will default to use this extended dictionary file.

Contributors:
-----------
* Herman Schaaf ([IronZebra.com](http://www.ironzebra.com)) (Author)
* Thomas Roten ([Github](https://github.com/tsroten/))
* [JOEWONGLVFS](https://github.com/JOEWONGLVFS)
* Casper CY Chiang ([Github](https://github.com/cychiang))

Any contributions are very welcome!


Sites using this:
-----------
* [ChineseLevel.com](http://www.ChineseLevel.com)