textcleaner v0.4.26
Text-Cleaner is a utility library for text-data pre-processing. Use it
before passing the text data to a model.
website <https://yugantm.github.io/textcleaner/>
__ - for more
Features!
-
main_cleaner to do all the below in one call ! or
-
remove unnecessary blank lines
-
stip out a perticular character or default one
-
transfer all characters to lowercase if needed
-
remove numbers, symblos and stop-words from the whole text
-
tokenize the text-data on one call
-
stemming & lemmatization powered by NLTK
The goal is to make basic cleaning of data hassle free. Most of the
developers who are working with text data have faced this situation
where data is not consumable and they end up wasting their time on
these issues rather than fine tunning the model and get better
accuracy. In that scenario this library can be useful and save you a
tone of time.
Tech
textcleaner uses a number of open source projects to work properly:
- `NLTK <https://www.nltk.org/>`__ - for advanced cleaning
- `REGEX <https://pypi.org/project/regex/>`__ - for regular expression
And of course textcleaner itself is open source with a `public
repository <https://github.com/YugantM/textcleaner>`__ on GitHub.
Installation
textcleaner requires Python 3.x <https://www.python.org/downloads/>
__
to run.
Install the dependencies if you have not already installed it!
- NLTK : steps to install
[
documentation <https://www.nltk.org/install.html>
__\ ] - REGEX :
.. code:: sh
pip install regex
.. code:: sh
pip install textcleaner
or
.. code:: sh
pip install textcleaner==0.4.26
Usage
.. code:: python
import textcleaner as tc
tc.main_cleaner('<FILE_NAME>')
#or
tc.document('<FILE_NAME>')
Above command will convert the text file into list of words with
cleaning. Default response of the function is list of list use *op*
argument and set it to 'words' and you will get a flat list of words.
Todos
- more advanced features
- ability to read more formats rather than only .txt
License
MIT
Free Software, Hell Yeah!