Plane is a tool for shaping wood using muscle power to force the cutting blade over the wood surface.
from Wikipedia
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.
Python 3.x only.
pip install plane
python setup.py install
- 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
Use regex to extract
or replace
:
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='<Email>')
replace(text, EMAIL) # replace(text, Regex, repl), if repl is not provided, Regex.repl will be used
>>> '<Email> & <Email>'
replace(text, EMAIL, '')
>>> ' & '
Regex
is a namedtuple with 3 items:
name
pattern
: Regular Expressionrepl
: replacement tag, this will replace matched regex when usingreplace
function
# create new pattern
from plane import build_new_regex
custom_regex = build_new_regex('my_regex', regex=r'(\d{4})', repl='<my-replacement-tag>')
Also, you can build new pattern from default patterns.
Attention: this should only be used for language range.
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
URL
: only ASCIIEMAIL
: local-part@domainTELEPHONE
: like xxx-xxxx-xxxxSPACE
:\t
,\n
,\r
,\f
,\v
HTML
: HTML tags, Script part and CSS partASCII_WORD
: English word, numbers,<tag>
and so on.CHINESE
: all Chinese characters (only Han and punctuations)CJK
: all Chinese, Japanese, Korean(CJK) characters and punctuationsTHAI
: all Thai and punctuationsVIETNAMESE
: all Vietnames and punctuationsENGLISH
: all English chars and punctuationsNUMBER
: 0-9
Regex name | replace |
---|---|
URL | '<URL>' |
'<Email>' |
|
TELEPHONE | '<Telephone>' |
SPACE | ' ' |
HTML | ' ' |
ASCII_WORD | ' ' |
CHINESE | ' ' |
CJK | ' ' |
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']
.
from plane import segment
segment('你看起来guaiguai的。<EOS>')
>>> ['你', '看', '起', '来', 'guaiguai', '的', '。', '<EOS>']
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.
from plane import punc
text = 'Hello world!'
punc.remove(text)
>>> 'Hello world '
# replace punctuation with special string
punc.remove(text, '<P>')
>>> 'Hello world<P>'
# 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.'
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.
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', '<Email>', '.']
p.update('My email is [email protected].').extract(EMAIL).values
>>> [Token(name='Email', value='[email protected]', start=12, end=24)]
You can use Pipeline
if you like.
segment
and extract
can only present in the end.
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', '.']