Whitespace Remover

Remove all whitespace characters including spaces, tabs, and line breaks.

Input

Output

Examples

Example 1

Hello World From Istanbul

Example 2

Code    with   multiple   spaces

How Whitespace Removal Works

Whitespace removal strips all characters classified as whitespace: spaces, tabs, newlines, carriage returns, and other Unicode space characters. 'Hello World' becomes 'HelloWorld', and multi-line text collapses to a single continuous string.

The process targets all whitespace varieties, not just visible spaces. Tabs (\t), line feeds (\n), carriage returns (\r), and non-breaking spaces (\u00A0) all get removed, ensuring complete whitespace elimination regardless of origin.

Character preservation maintains all non-whitespace content in original order. 'user name' becomes 'username', and code 'if (x > 5)' becomes 'if(x>5)'—spacing disappears but letter sequences and punctuation remain intact.

Practical Uses for Whitespace Removal

Data validation requires spaceless strings for certain identifiers. Credit card numbers, phone numbers, and reference codes often prohibit spaces—removing whitespace converts '1234 5678 9012 3456' to '1234567890123456' for system processing.

URL-safe strings cannot contain spaces. Converting 'My Document' to 'MyDocument' (with additional processing) creates valid identifiers for filenames, slugs, or parameters that will be URL-encoded.

Code minification removes whitespace to reduce file size. JavaScript 'function sum(a, b) { return a + b; }' becomes 'function sum(a,b){return a+b;}' saving bytes for faster transmission and smaller storage.

Token generation for authentication or IDs requires compact strings. Removing whitespace from formatted tokens ensures they work in systems expecting continuous strings without embedded spaces.

Whitespace Removal Challenges

Readability loss makes output unsuitable for human consumption. 'Hello World' → 'HelloWorld' is manageable, but removing spaces from paragraphs creates unreadable walls of characters. Use only when machines process the result.

Programming language syntax breaks when whitespace matters. Python indentation, YAML structure, and Markdown formatting all depend on whitespace—removing it destroys document structure and code functionality.

Natural language processing fails on spaceless text. 'thequickbrownfox' cannot be tokenized into words for analysis or search. Whitespace removal makes text unsearchable and incompatible with NLP tools.

Reversibility is impossible without context. 'username' could have been 'user name', 'us ername', or 'usern ame'—once spaces are removed, original formatting cannot be restored reliably.

Best Practices for Removing Whitespace

Preserve originals before removing whitespace: Keep the formatted version for display or reference. Use the spaceless version only for system processing where whitespace prohibition is explicit.

Combine with other formatting: Removing whitespace alone creates compact but potentially ambiguous strings. Add delimiters or convert to specific formats (camelCase, underscores) for structured identifiers.

Validate context before removal: Ensure whitespace is truly unnecessary. Code comments, formatted output, and human-readable content all require spaces—verify the target system actually demands spaceless input.

Consider partial whitespace normalization instead: Collapse multiple spaces to single spaces, trim leading/trailing whitespace, or remove only newlines. Complete whitespace removal is extreme—lighter normalization often suffices.

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