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A Simple Text Cleaning Package For cleaning text during NLP

Project description

textify

A Simple Text Cleaning and Normalization Package For NLP

Installation

pip install textify

Usage

Clean Text

  • Clean text by removing emails,numbers,etc
>>> from textify import TextCleaner
>>> docx = TextCleaner()
>>> docx.text = "your text goes here"
>>> docx.clean_text()

Remove Emails,Numbers,Phone Numbers

>>> docx.remove_emails()
>>> docx.remove_numbers()
>>> docx.remove_phone_numbers()

Remove Special Characters

>>> docx.remove_special_characters()

Replace Emails,Numbers,Phone Numbers

>>> docx.replace_emails()
>>> docx.replace_numbers()
>>> docx.replace_phone_numbers()

Using TextExtractor

  • To Extract emails,phone numbers,numbers from text
>>> from textify import TextExtractor
>>> docx = TextExtractor()
>>> docx.text = "your text with example@gmail.com goes here"
>>> docx.extract_emails()

By

  • Jesse E.Agbe(JCharis)
  • Jesus Saves @JCharisTech

NB

  • Contributions Are Welcomed
  • Notice a bug, please let us know.
  • Thanks A lot

Project details


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Files for textify, version 0.0.1
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