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
Release history Release notifications
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
| Filename, size | File type | Python version | Upload date | Hashes |
|---|---|---|---|---|
| Filename, size textify-0.0.1-py3-none-any.whl (3.5 kB) | File type Wheel | Python version py3 | Upload date | Hashes View hashes |
| Filename, size textify-0.0.1.tar.gz (3.4 kB) | File type Source | Python version None | Upload date | Hashes View hashes |
