Regex Replace Online
Find and replace text using regular expressions (regex) with advanced pattern matching. Supports case-sensitive search, whole word matching, and complex regex patterns.
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Why Use Find and Replace?
Our free find and replace tool is essential for developers, content writers, and data analysts who need to perform bulk text transformations instantly without manual editing. Whether you're refactoring code variable names, updating brand terminology across documentation, fixing typos in large datasets, or standardizing formatting in CSV files, this tool handles hundreds or thousands of replacements in milliseconds. Manual find-and-replace through word processors requires opening files individually and lacks the advanced pattern matching capabilities needed for complex text operations.
With advanced features like regex pattern matching, case-sensitive search, and whole-word matching, you can perform surgical text replacements that traditional tools can't handle. Replace phone number formats across thousands of entries, update URL structures in HTML exports, standardize date formats in log files, or swap programming syntax between languages. The live replacement counter shows exactly how many matches exist before you commit changes, preventing accidental over-replacement that could corrupt data or break code functionality.
Common Use Cases
💻 Code Refactoring & Variable Renaming
When refactoring code, developers need to rename variables, functions, or class names consistently across entire files. Manual search-and-replace in IDEs can miss instances or accidentally replace partial matches (changing "userName" when you only wanted "user"). Using whole-word matching ensures only exact matches are replaced, while case-sensitive mode preserves camelCase or snake_case conventions critical to code functionality.
After refactoring code, use Remove Empty Lines to clean up spacing, then Sort Lines to organize import statements or configuration arrays alphabetically.
✏️ Content Editing & Brand Updates
Marketing teams frequently need to update product names, company names, or terminology across hundreds of pages of documentation, blog posts, or help articles. When brands rebrand or product names change, manually updating every instance creates inconsistencies and typos. Find and replace ensures every mention updates simultaneously—"Acme Corp" becomes "Acme Technologies" across all content in seconds.
After updating brand terms, use Case Converter to ensure consistent capitalization, then Word Counter to verify article length requirements remain met.
📊 Data Cleaning & Formatting
CSV exports from databases often contain inconsistent formatting—phone numbers as "(555) 123-4567", "555-123-4567", or "5551234567". Before importing to new systems, standardizing format is essential. Use regex patterns to find all phone number variations and replace with a single format. Similarly, standardize date formats from "MM/DD/YYYY" to "YYYY-MM-DD" for database compatibility or international standards.
For comprehensive data cleanup, combine with Trim Lines to remove extra spaces, then CSV Safe to escape special characters before spreadsheet imports.
🔗 URL Updates & Link Management
When migrating websites or restructuring URLs, you need to update hundreds of internal links in documentation, sitemaps, or content. Changing "http://oldsite.com" to "https://newsite.com" across thousands of URLs manually is error-prone and time-consuming. Find and replace with regex patterns ensures all URL variations update correctly, including query parameters and anchor links that simple search might miss.
After updating URLs, use Remove Duplicates to clean duplicate links, then Character Counter to verify URL lengths meet platform requirements.
How Find and Replace Works
Our find and replace tool uses JavaScript's powerful string matching engine to locate patterns in your text. Basic mode performs simple string matching—searching for "apple" finds every occurrence of those exact five characters. Case-sensitive mode distinguishes between "Apple" and "apple", essential when working with proper nouns, code variables, or brand names where capitalization matters for meaning or functionality.
Whole word matching ensures you only replace complete words, not partial matches. Searching for "cat" with whole-word mode won't match "category" or "scatter", preventing accidental corruption of larger words. Regex mode unlocks advanced pattern matching using regular expressions—match phone numbers, email addresses, dates, URLs, or any complex text pattern that traditional search can't handle with flexible wildcards and character classes.
The live match counter displays how many instances will be replaced before you commit, helping prevent errors. If you expect 50 matches but see 500, you can adjust your search pattern before replacing. All processing happens instantly in your browser—no server upload required, ensuring complete privacy for sensitive code, customer data, or proprietary documents. The tool handles large texts (up to 5MB) and can process millions of characters with thousands of replacements in under a second.
Tips for Best Results
- 1.For code refactoring, always enable both case-sensitive and whole-word matching to prevent accidental partial replacements. Replacing "id" without whole-word mode will corrupt "grid", "valid", and "solid" throughout your code. After replacement, use Text Statistics to verify code length and complexity.
- 2.When using regex patterns, start with simple patterns and test on small text samples. Complex regex can match unexpected patterns—verify the match counter shows the expected number before processing large datasets. Use Character Counter to check pattern lengths.
- 3.For brand name updates, perform multiple passes with different variations: "Acme Corp", "ACME CORP", "acme corp". After all replacements, use Case Converter to standardize capitalization across your updated content.
- 4.Before data cleaning operations, use Trim Lines to remove hidden spaces that prevent matches. A search for "John Smith" won't find "John Smith" (double space). Clean whitespace first for accurate replacement counts.