semvec/pypi-packages huggingface dataset:
preprocess-yourname 0.1
Text preprocessing package
License: MIT
Keywords: text,preprocessing

# Preprocess YourText

Preprocess YourText is a Python package for text preprocessing tasks, designed to simplify and streamline the process of cleaning and preparing text data for natural language processing (NLP) tasks.

## Features

- **HTML Tag Removal**: Easily remove HTML tags from text data.
- **URL Removal**: Remove URLs from text data.
- **Email Removal**: Remove email addresses from text data.
- **Special Character Removal**: Remove special characters from text data.
- **Accent Removal**: Remove accents from characters in text data.
- **Contractions Expansion**: Expand contractions in text data (e.g., "don't" to "do not").
- **Lemmatization**: Lemmatize words in text data to their base form.
- **Spelling Correction**: Correct spelling mistakes in text data.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Installation

You can install the package via pip:

```bash
pip install mngdataclean

## Usage
import mngdataclean as mng

# Example usage:
text = "This is an example text with HTML tags <b>and URLs</b>."
clean_text = pyt.clean_text(text)
print(clean_text)

#output is 
This is an example text with HTML tags and URLs.
tefas-wrapper 0.5.1
Tefas wrapper to fetch funds data from http://tefas.gov.tr/
License: MIT
Requires Python: >=3.8
Keywords: TEFAS,WRAPPER,FUND,FON

# tefas-wrapper
Fetch funds data from https://www.tefas.gov.tr

    pip install tefas-wrapper


usage:

    from tefaswrapper import Wrapper, FundType
    
    # ...
    
    tefas = Wrapper(FundType.YAT)
    # single day
    result = tefas.fetch("AFT", "25.11.2020", "25.11.2020")
    
    # between two dates
    result = tefas.fetch("AFT", "15.11.2020", "20.11.2020")
    
    # from a cetain day until today
    result = tefas.fetch("AFT", "15.11.2020")                
    
    # latest value
    result = tefas.fetch("AFT")
    
    # latest values of all funds
    result = tefas.fetch()
    
    # fetch detail a specific fund
    detail = tefas.fetch_detail("AFT")

    # ...