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https://github.com/kemingy/plane
A text processing tool including tag(HTML, URL, Email) extraction and removing, punctuation normalization, simple segmentation, and so on.
https://github.com/kemingy/plane
chinese-nlp data-cleaning nlp preprocess regex tokenization tokenizer
Last synced: 24 days ago
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A text processing tool including tag(HTML, URL, Email) extraction and removing, punctuation normalization, simple segmentation, and so on.
- Host: GitHub
- URL: https://github.com/kemingy/plane
- Owner: kemingy
- License: mit
- Created: 2018-02-27T09:13:34.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2022-10-13T00:46:45.000Z (about 2 years ago)
- Last Synced: 2024-10-15T18:37:59.340Z (about 1 month ago)
- Topics: chinese-nlp, data-cleaning, nlp, preprocess, regex, tokenization, tokenizer
- Language: Python
- Homepage: https://kemingy.github.io/Plane/
- Size: 2.83 MB
- Stars: 11
- Watchers: 2
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
- Code of conduct: CODE_OF_CONDUCT.md
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README
# Plane
[](https://github.com/kemingy/plane/actions)
[](https://pypi.python.org/pypi/plane)
[](https://github.com/kemingy/plane)
[](https://kemingy.github.io/plane/)
> **Plane** is a tool for shaping wood using muscle power to force the cutting blade over the wood surface.
> *from [Wikipedia](https://en.wikipedia.org/wiki/Plane_(tool))*
This package is used for extracting or replacing specific parts from text, like URL, Email, HTML tags, telephone numbers and so on. Also supports punctuation normalization and removement.
See the full [Documents](https://kemingy.github.io/Plane/).
## Install
Python **3.x** only.
### pip
```python
pip install plane
```
### Install from source
```sh
python setup.py install
```
## Features
* no other dependencies
* build-in regex patterns: `plane.pattern.Regex`
* custom regex patterns
* pattern combination
* extract, replace patterns
* segment sentence
* chain function calls: `plane.plane.Plane`
* pipeline: `plane.Pipeline`
## Usage
### Quick start
Use regex to `extract` or `replace`:
```python
from plane import EMAIL, extract, replace
text = '[email protected] & [email protected]'
emails = extract(text, EMAIL) # this return a generator object
for e in emails:
print(e)
>>> Token(name='Email', value='[email protected]', start=0, end=11)
>>> Token(name='Email', value='[email protected]', start=14, end=34)
print(EMAIL)
>>> Regex(name='Email', pattern='([a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\\.[a-zA-Z0-9-]+)', repl='')
replace(text, EMAIL) # replace(text, Regex, repl), if repl is not provided, Regex.repl will be used
>>> ' & '
replace(text, EMAIL, '')
>>> ' & '
```
### pattern
`Regex` is a namedtuple with 3 items:
* `name`
* `pattern`: Regular Expression
* `repl`: replacement tag, this will replace matched regex when using `replace` function
```python
# create new pattern
from plane import build_new_regex
custom_regex = build_new_regex('my_regex', regex=r'(\d{4})', repl='')
```
Also, you can build new pattern from default patterns.
**Attention**: this should only be used for language range.
```python
from plane import extract, build_new_regex, CHINESE_WORDS
ASCII = build_new_regex('ascii', regex=r'[a-zA-Z0-9]+', repl=' ')
WORDS = ASCII + CHINESE_WORDS
print(WORDS)
>>> Regex(name='ascii_Chinese_words', pattern='[a-zA-Z0-9]+|[\\U00004E00-\\U00009FFF\\U00003400-\\U00004DBF\\U00020000-\\U0002A6DF\\U0002A700-\\U0002B73F\\U0002B740-\\U0002B81F\\U0002B820-\\U0002CEAF\\U0002CEB0-\\U0002EBEF]+', repl=' ')
text = "自然语言处理太难了！who can help me? (╯▔🔺▔)╯"
print(' '.join([t.value for t in list(extract(text, WORDS))]))
>>> "自然语言处理太难了 who can help me"
from plane import CHINESE, ENGLISH, NUMBER
CN_EN_NUM = sum([CHINESE, ENGLISH, NUMBER])
text = "佛是虚名，道亦妄立。एवं मया श्रुतम्। 1999 is not the end of the world. "
print(' '.join([t.value for t in extract(text, CN_EN_NUM)]))
>>> "佛是虚名，道亦妄立。 1999 is not the end of the world."
```
Default Regex: [Details](https://github.com/Momingcoder/Plane/blob/master/plane/pattern.py)
* `URL`: only ASCII
* `EMAIL`: local-part@domain
* `TELEPHONE`: like xxx-xxxx-xxxx
* `SPACE`: ` `, `\t`, `\n`, `\r`, `\f`, `\v`
* `HTML`: HTML tags, Script part and CSS part
* `ASCII_WORD`: English word, numbers, `` and so on.
* `CHINESE`: all Chinese characters (only Han and punctuations)
* `CJK`: all Chinese, Japanese, Korean(CJK) characters and punctuations
* `THAI`: all Thai and punctuations
* `VIETNAMESE`: all Vietnames and punctuations
* `ENGLISH`: all English chars and punctuations
* `NUMBER`: 0-9
Regex name | replace
-----------|---------
URL | `''`
EMAIL | `''`
TELEPHONE | `''`
SPACE | `' '`
HTML | `' '`
ASCII_WORD | `' '`
CHINESE | `' '`
CJK | `' '`
### segment
`segment` can be used to segment sentence, English and Numbers like 'PS4' will be keeped and others like Chinese '中文' will be split to single word format `['中', '文']`.
```python
from plane import segment
segment('你看起来guaiguai的。')
>>> ['你', '看', '起', '来', 'guaiguai', '的', '。', '']
```
### punctuation
`punc.remove` will replace all unicode punctuations to `' '` or something you send to this function as paramter `repl`. `punc.normalize` will normalize some Unicode punctuations to English punctuations.
**Attention**: '+', '^', '$', '~' and some chars are not punctuation.
```python
from plane import punc
text = 'Hello world!'
punc.remove(text)
>>> 'Hello world '
# replace punctuation with special string
punc.remove(text, '
')
>>> 'Hello world
'
# normalize punctuations
punc.normalize('你读过那本《边城》吗？什么编程？！人生苦短，我用 Python。')
>>> '你读过那本(边城)吗?什么编程?!人生苦短,我用 Python.'
```
### Chain function
`Plane` contains `extract`, `replace`, `segment` and `punc.remove`, `punc.normalize`, and these methods can be called in chain. Since `segment` returns list, it can only be called in the end of the chain.
`Plane.text` saves the result of processed text and `Plane.values` saves the result of extracted strings.
```python
from plane import Plane
from plane.pattern import EMAIL
p = Plane()
p.update('My email is [email protected].').replace(EMAIL, '').text # update() will init Plane.text and Plane.values
>>> 'My email is .'
p.update('My email is [email protected].').replace(EMAIL).segment()
>>> ['My', 'email', 'is', '', '.']
p.update('My email is [email protected].').extract(EMAIL).values
>>> [Token(name='Email', value='[email protected]', start=12, end=24)]
```
### Pipeline
You can use `Pipeline` if you like.
`segment` and `extract` can only present in the end.
```python
from plane import Pipeline, replace, segment
from plane.pattern import URL
pipe = Pipeline()
pipe.add(replace, URL, '')
pipe.add(segment)
pipe('http://www.guokr.com is online.')
>>> ['is', 'online', '.']