semvec/pypi-packages huggingface dataset:
terminalcolor 1.0.3
Change the Python terminal text color.
Requires Python: >=3.6

# TerminalColor
![Python_Version](https://img.shields.io/pypi/pyversions/terminalcolor?label=Python%20Version&logo=python&logoColor=white&style=flat-square)
![License](https://img.shields.io/github/license/cheongwoli/PythonTerminalTextColor?label=License&logo=github&logoColor=white&style=flat-square)

![Pypi_Version](https://img.shields.io/pypi/v/terminalcolor?logo=pypi&logoColor=white&style=flat-square)
![Pypi_Package](https://img.shields.io/pypi/format/terminalcolor?label=package&logo=pypi&logoColor=white&style=flat-square)

> TerminalColor is used to change the color of the text displayed on the Python terminal.

-----

#### Brightnesses(3/4bit) and Bit modes(8bit, 24bit)
- dark
- light

- 8bit
- 24bit or rgb

#### Colors(3/4bit)
- red
- green
- yellow
- blue
- magenta
- cyan

#### Text Types
- bold
- italic
- underline

-----

3/4bit color mode
> ctext(color="brightness-color_name")

8bit color mode
> ctext(color="8bit-color_code")

24bit color mode
> ctext(color="24bit-r;g;b")

> ctext(color="rgb-r;g;b")

-----

#### Example Code
```python
from terminalcolor import ctext, cprint

"""
ctext
"""

# color
print(ctext(text="example", color="dark-blue"))
# background color
print(ctext(text="example", bg_color="light-blue"))
# single text type
print(ctext(text="example", text_type="bold"))
# multiple text type
print(ctext(text="example", text_type=["italic", "underline"]))

# 8bit color mode
print(ctext(text="example", color="8bit-231"))
# 24bit color mode
print(ctext(text="example", color="24bit-91;92;239"))
print(ctext(text="example", color="rgb-91;92;239"))

"""
cprint
"""

cprint(text="example", color="light-yellow", bg_color="dark-blue", text_type="bold")
```
tweetprocessor-1 1.0.0
This is my text processor that will process text using 10 NLP processing tehcniques for the ML SPECIALIZATION
Requires Python: ==3.12

# TextPreprocessor

## Overview
The TextPreprocessor is a Python class designed for comprehensive text preprocessing. It facilitates tasks like removing links, hashtags, special characters, emojis, numbers, and stopwords. Additionally, it provides functionality for converting text to lowercase.

## Installation
Ensure you have NLTK installed. You can install NLTK via pip:

pip install nltk




## Usage
```python
### Import the TextPreprocessor class
from text_preprocessor import TextPreprocessor
# Initialize the preprocessor with default settings
preprocessor = TextPreprocessor()

# Customize the preprocessor by setting flags
preprocessor = TextPreprocessor(
    remove_links=True,
    remove_hashtags=True,
    remove_characters=True,
    convert_to_lowercase=True,
    remove_emojis=True,
    remove_numbers=True,
    remove_stopwords_flag=True
)



text = "Your text goes here..."


processed_text = preprocessor.preprocess_text(text)

```
## Available Methods
1. preprocess_text(text): Preprocesses the input text based on the initialized flags.
2. Other methods in the class can be used individually for specific preprocessing steps (e.g., remove_links, remove_stopwords, etc.).
# Examples
```python

text = "Hello! This is an example text with #hashtags and links: https://example.com"



# Initialize preprocessor
preprocessor = TextPreprocessor(remove_links=True, remove_hashtags=True)

# Preprocess text
processed_text = preprocessor.preprocess_text(text)
print(processed_text)
Output: "Hello This is an example text with and links"

```

# License

This project is licensed under the MIT License - see the LICENSE file for details.