ChirpText is a collection of text processing tools for Python 3.
It is not meant to be a powerful tank like the popular NTLK but a small package which you can pip-install anywhere and write a few lines of code to process textual data.
Main features
- Simple file data manipulation using an enhanced
open()function (txt, gz, binary, etc.) - CSV helper functions
- Parse Japanese text with mecab library (Does not require
mecab-python3package even on Windows, only a binary release (i.e.mecab.exe) is required) - Built-in "lite" text annotation formats (
texttaglibTTL/CSV and TTL/JSON) - Helper functions and useful data for processing English, Japanese, Chinese and Vietnamese.
- Application configuration files management which can make educated guess about config files' whereabouts
- Quick text-based report generation
Installation
chirptext is available on PyPI and can be installed using pip
pip install chirptext
Parsing Japanese text
chirptext supports parsing Japanese text using different parsers (mecab, Janome, and igo-python)
>> doc = deko.parse_doc("猫が好きです。\n犬も好きです。") >>> for sent in doc: ... print(sent, sent.tokens.values()) ... 猫が好きです。 ['猫', 'が', '好き', 'です', '。'] 犬も好きです。 ['犬', 'も', '好き', 'です', '。'] ">
>>> from chirptext import deko >>> sent = deko.parse('猫が好きです。') >>> sent.tokens ['`猫`<0:1>', '`が`<1:2>', '`好き`<2:4>', '`です`<4:6>', '`。`<6:7>'] >>> sent.tokens.values() ['猫', 'が', '好き', 'です', '。'] >>> sent[0] `猫`<0:1> >>> sent[0].pos '名詞' >>> sent[1].lemma 'が' >>> sent[2].reading 'スキ' # tokenize >>> deko.tokenize('猫が好きです。') ['猫', 'が', '好き', 'です', '。'] # split sentences >>> deko.tokenize_sent("猫が好きです。\n犬も好きです。") ['猫が好きです。', '犬も好きです。'] # parse a document (i.e. multiple sentences) >>> doc = deko.parse_doc("猫が好きです。\n犬も好きです。") >>> for sent in doc: ... print(sent, sent.tokens.values()) ... 猫が好きです。 ['猫', 'が', '好き', 'です', '。'] 犬も好きです。 ['犬', 'も', '好き', 'です', '。']
Notes: At least one of the following tools must be installed to use chirptext Japanese parsing:
- mecab: http://taku910.github.io/mecab/#download
- Janome: available on PyPI, install with
pip install Janome - igo-python: available on PyPI, install with
pip install igo-python
Convenient IO APIs
>>> from chirptext import chio
>>> chio.write_tsv('data/test.tsv', [['a', 'b'], ['c', 'd']])
>>> chio.read_tsv('data/tes.tsv')
[['a', 'b'], ['c', 'd']]
>>> chio.write_file('data/content.tar.gz', 'Support writing to .tar.gz file')
>>> chio.read_file('data/content.tar.gz')
'Support writing to .tar.gz file'
>>> for row in chio.read_tsv_iter('data/test.tsv'):
... print(row)
...
['a', 'b']
['c', 'd']
Sample TextReport
# a string report
rp = TextReport() # by default, TextReport will write to standard output, i.e. terminal
rp = TextReport(TextReport.STDOUT) # same as above
rp = TextReport('~/tmp/my-report.txt') # output to a file
rp = TextReport.null() # ouptut to /dev/null, i.e. nowhere
rp = TextReport.string() # output to a string. Call rp.content() to get the string
rp = TextReport(TextReport.STRINGIO) # same as above
# TextReport will close the output stream automatically by using the with statement
with TextReport.string() as rp:
rp.header("Lorem Ipsum Analysis", level="h0")
rp.header("Raw", level="h1")
rp.print(LOREM_IPSUM)
rp.header("Top 5 most common letters")
ct.summarise(report=rp, limit=5)
print(rp.content())
Output
+----------------------------------------------------------------------------------
| Lorem Ipsum Analysis
+----------------------------------------------------------------------------------
Raw
------------------------------------------------------------
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
Top 5 most common letters
------------------------------------------------------------
i: 42
e: 37
t: 32
o: 29
a: 29
Useful links
- Documentation: https://chirptext.readthedocs.io
- Source code: https://github.com/letuananh/chirptext/
- PyPI: https://pypi.org/project/chirptext/
194 Nov 19, 2022
13 Aug 27, 2022
2 Dec 14, 2022
1 Oct 23, 2021
2 Feb 18, 2022
1 Jan 29, 2022
1 Jan 11, 2022
5 Oct 2, 2022
2 Jun 30, 2022
64 Dec 25, 2022
1 Jan 30, 2022
3 May 18, 2022
5 Nov 26, 2022
16 Sep 13, 2022
33 Dec 05, 2022
2 Apr 08, 2022
45 Jan 05, 2023
3 Feb 22, 2022
2 Jun 30, 2022
1 Nov 26, 2021
1.3k Jan 04, 2023
59 Oct 10, 2022
26 Dec 17, 2022
2 Feb 05, 2022
574 Dec 20, 2022
14 Oct 14, 2022
2 Oct 12, 2021