About

Data sanitation creates significant friction during software integration. Legacy databases often export strings with inconsistent capitalization or unwanted whitespace that causes parser failures in modern applications. This utility provides a centralized interface for normalizing text data into strict coding conventions. Developers can instantly align variable names with project standards like CamelCase or Snake_Case without manual editing. Content creators also utilize this system to bypass plain text limitations on social platforms. The engine processes input through rigorous regular expressions to ensure structural integrity is maintained. It handles multi-byte Unicode characters correctly to prevent data corruption during transformation.

Formulas

Text transformation relies on specific algorithmic mappings rather than algebraic formulas. However, the logic for converting a string S into Camel Case can be defined structurally.

Let S be a sequence of words separated by delimiters _, -, or space.

{

lowercase(w₀)capitalize(w_i) for i > 0

The final string C is the concatenation of these transformed segments.

For Unicode Styling, the tool utilizes a direct character mapping function map where Latin characters are replaced by their Mathematical Alphanumeric Symbols block equivalents.

U_style = n∑i=0 lookup(S_i, Table_style)

Reference Data

Transformation Mode	Input Sample	Output Result	Primary Context
Upper Case	user_id	USER_ID	SQL Keywords
Lower Case	PageTitle	pagetitle	URL Slugs
Title Case	war and peace	War And Peace	Headlines
Sentence Case	hello world. how are you?	Hello world. How are you?	Prose
Camel Case	api_response_data	apiResponseData	JavaScript / Java
Pascal Case	make_user	MakeUser	C# Classes
Snake Case	customerID	customer_id	Python / Ruby
Kebab Case	NavBar	nav-bar	CSS Classes
Constant Case	maxRetries	MAX_RETRIES	Environment Variables
Dot Case	obj property	obj.property	Object Access
Path Case	user profile	user/profile	File Systems
Strip HTML	<b>Bold</b>	Bold	Data Cleaning
Trim Whitespace	Text	Text	Form Input
Unicode Bold	Important	𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭	Social Media
Unicode Italic	Emphasis	𝐸𝑚𝑝ℎ𝑎𝑠𝑖𝑠	Design

Frequently Asked Questions

Conversion logic relies on identifying word boundaries. If an input string uses ambiguous delimiters or lacks separation entirely (e.g., 'somewordhere'), the algorithm treats it as a single token. Pre-processing the text by adding spaces or underscores usually resolves this identification issue.

No. The HTML strip function is designed to remove only the tags themselves (e.g., <div> or </span>) while preserving the inner text node. This is useful for extracting readable content from web scrapers or rich text editors.

Generally, no. The "Bold" and "Italic" text generators use mathematical alphanumeric symbols, not actual font weights. Screen readers often interpret these as individual mathematical variables (e.g., 'Mathematical Bold Capital A'). Use these styles sparingly for decorative headers, not for critical information.

The regex engine is Unicode-aware. When applying Upper or Lower case transformations, emojis and symbols remain unchanged because they do not have case variants. However, some aggressive "Cleanup" modes might remove non-alphanumeric characters if selected.

The tool runs entirely in your browser's memory. While there is no hard-coded limit, pasting text files larger than 5MB (approximately 500,000 words) may cause temporary UI lag during complex regex operations.

Yes. The underlying JavaScript normalization methods support full Unicode sets. Transformations like Upper Case will correctly convert characters like "é" to "É" or "ñ" to "Ñ" without corrupting the encoding.