What does this tool do
The Regex Cleaner removes or replaces text using regular expressions. Enter one or more regex patterns; each pattern is applied in order (output of pattern 1 becomes input to pattern 2). Choose to remove matches or replace them with custom text. Validates each pattern before applying; invalid regex shows an inline error under the failing rule. Defaults to the global flag so all matches are processed. Useful for cleaning data, stripping unwanted characters, or bulk text transformation.
How to use it
- Enter text — Paste or type the text to process.
- Add patterns — Type a regular expression (e.g.
\d+for digits,\s+for whitespace). Use "Add pattern" to chain multiple rules. - Replace (optional) — Leave empty to remove matches, or enter replacement text for each pattern.
- Set flags — Toggle global (g), case-insensitive (i), etc. Shared across all patterns.
- Apply — Click to run (or use Live mode). The result appears; invalid pattern shows an error under the rule that failed.
How it works
Each pattern is validated with new RegExp() before use. Patterns are applied sequentially: the output of rule N becomes the input to rule N+1. If any pattern is invalid, the chain stops and shows partial output with the error under the failing rule. The global (g) flag is the default so all occurrences are replaced in one pass per rule. All processing runs client-side.
All computation runs entirely in your browser. No data is sent to any server.
Use cases & examples
- Clean data — Remove extra spaces, newlines, or special characters.
- Extract — Use capture groups to extract and replace (e.g. reformat dates).
- Normalise — Replace variants (e.g. multiple spaces → single space).
- Strip markup — Remove HTML tags or other markup.
- CSV cleanup — Fix delimiters or escape sequences.
Example
- Pattern
\s+, replace - Pattern
\d{3}-\d{3}-\d{4}, replace[REDACTED]→ Hides phone numbers. - Pattern
[^\w\s], replace empty → Removes all punctuation.
Limitations & known constraints
- Pattern validated first — Invalid regex shows an error; no replacement is attempted.
- ReDoS — Extremely complex patterns may cause slow execution; avoid catastrophic backtracking.
- Sequential chains — Multiple patterns are applied in order; each rule processes the output of the previous rule.
- JavaScript regex — Uses JS regex flavour; some PCRE features may differ.