✨ Textcraft

🧵 A lightweight Python module for text transformation, cleaning, and basic analysis —
beginner-friendly and open source.

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📖 Overview

Textcraft is a simple Python library that provides common text manipulation functions. It's designed to be easy to use and understand, making it perfect for beginners and for quick text processing tasks.

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📦 Installation

Install Textcraft using pip:

pip install textcraft-py

Or clone the repository:

git clone https://github.com/O-sama12/textcraft

then import the module directly:

import textcraft

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🚀 Getting Started

Basic Usage

import textcraft as txt

# Example text to work with
text = "Hello World! This is a TextCraft example."

# Text Case & Format Conversion
print(txt.to_lowercase(text))      # hello world! this is a textcraft example.
print(txt.to_uppercase(text))      # HELLO WORLD! THIS IS A TEXTCRAFT EXAMPLE.
print(txt.to_snake_case(text))     # hello_world!_this_is_a_textcraft_example.
print(txt.to_kebab_case(text))     # hello-world!-this-is-a-textcraft-example.
print(txt.to_camel_case(text))     # helloWorld!ThisIsATextcraftExample.

# Text Cleaning
print(txt.remove_punctuation(text))  # Hello World This is a TextCraft example
print(txt.normalize_spaces(text))    # Hello World! This is a TextCraft example.

# Text Statistics
print(txt.word_count(text))          # 8
print(txt.char_count(text))          # 43 (without spaces: 35)
print(txt.sentence_count(text))      # 1
print(txt.slugify(text))             # hello-world-this-is-a-textcraft-example

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🚀 Features

🔤 Text Case & Format Conversion

• 🔡 to_lowercase(text) - Convert text to lowercase
• 🐫 to_uppercase(text) - Convert text to uppercase
• 🐍 to_snake_case(text) - Transform text into snake_case
• 🔗 to_kebab_case(text) - Convert text into kebab-case
• 🐪 to_camel_case(text) - Convert text into camelCase

🧹 Text Cleaning Utilities

• 🧽 remove_punctuation(text) - Remove all punctuation characters from text
• 📐 normalize_spaces(text) - Normalize multiple spaces into a single space
• 🌐 slugify(text) - Generate URL-friendly slugs

📊 Basic Text Statistics

• 🧮 word_count(text) - Count number of words in text
• 🔢 char_count(text, include_spaces=True/False) - Count characters (with or without spaces)
• 📑 sentence_count(text) - Count number of sentences

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🧪 Common Use Cases

1. Preparing text for processing

raw_text = "  This   text   has   extra   spaces.  "
clean_text = txt.normalize_spaces(raw_text)  # "This text has extra spaces."

2. Creating URL-friendly strings

title = "My Blog Post: An Introduction!"
slug = txt.slugify(title)  # "my-blog-post-an-introduction"

3. Formatting text for different contexts

function_name = "my function name"
snake_case = txt.to_snake_case(function_name)  # "my_function_name"
kebab_case = txt.to_kebab_case(function_name)  # "my-function-name"

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📝 Examples with Input → Output

Function	Input	Output
to_lowercase()	"Hello World!"	"hello world!"
to_uppercase()	"Hello World!"	"HELLO WORLD!"
to_snake_case()	"Hello World"	"hello_world"
to_camel_case()	"hello world"	"helloWorld"
remove_punctuation()	"Hello, World!"	"Hello World"
word_count()	"Hello World"	2
slugify()	"Hello, World!"	"hello-world"

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⚠️ Edge Cases & Notes

• Empty strings will return empty strings for most functions
• to_camel_case() handles various separators and converts them appropriately
• sentence_count() recognizes ., !, and ? as sentence terminators
• char_count() can optionally include or exclude spaces
• slugify() removes punctuation and replaces spaces with hyphens

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🤝 Contributing

This project is beginner-friendly and welcomes:

• 🐞 Bug reports
• 💡 Feature suggestions
• 🔧 Pull requests

Before contributing, please take a moment to read the CONTRIBUTING.md file.

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📄 License

This project is licensed under the
MIT License.