RegExp Tester

Test Regular Expressions

RegExp Quick Reference

Common Patterns

Character Meaning
. Any character except newline
\w Word character [A-Za-z0-9_]
\d Digit [0-9]
\s Whitespace (space, tab, newline)
[abc] Any character a, b, or c
[^abc] Any character except a, b, or c
^ Start of string or line
$ End of string or line
\b Word boundary

Quantifiers

Pattern Meaning
* 0 or more
+ 1 or more
? 0 or 1
{n} Exactly n times
{n,} n or more times
{n,m} Between n and m times
*? 0 or more (non-greedy)
+? 1 or more (non-greedy)

About RegExp Tester

Regular expressions (RegExp) are powerful tools used to search, match, and manipulate text based on patterns. Whether validating user input, parsing log files, or extracting specific data from large datasets, regular expressions provide a flexible way to work with text efficiently.

Developers, data analysts, and system administrators frequently use regular expressions for text processing in programming languages like JavaScript, Python, and Java. Testing expressions manually can be time-consuming, but a dedicated tool makes it easy to visualize and troubleshoot patterns.

Core Capabilities

  • Real-Time Pattern Matching: Instantly highlights matches within the input text.
  • Syntax Highlighting: Differentiates regex components for better readability.
  • Flags and Modifiers: Supports global, case-insensitive, and multiline search options.
  • Error Detection: Identifies syntax issues to prevent incorrect expressions.
  • Cross-Language Compatibility: Works with common regex implementations in JavaScript, Python, PHP, and more.

Common Use Cases

Validating User Input

Regular expressions help enforce rules for forms and user-generated content, such as email validation or password complexity checks.

Example
Regex for Email Validation:
/^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$/

Matches: [email protected], [email protected]

Does Not Match: invalid@com, @missinguser.com

Extracting Data from Logs or Files

System logs and large text files often contain valuable information, but finding specific patterns manually is inefficient. A regex tester allows users to refine expressions for accurate searches.

Example
Regex for Extracting IP Addresses:
/\b(?:\d{1,3}\.){3}\d{1,3}\b/

Matches: 192.168.1.1, 10.0.0.255

Does Not Match: 300.500.700.900

Searching and Replacing Text

Many text-processing tasks involve searching for specific patterns and replacing them. Regular expressions make this process more dynamic and efficient.

Example
Regex for Replacing Multiple Spaces with a Single Space:
/\s+/g

Input: This is a test.

Output: This is a test.

Troubleshooting & Best Practices

Escape Special Characters

If searching for special characters like . or *, use a backslash (\. or \*).

Use Anchors (^ and $)

Define start and end positions in patterns to avoid partial matches.

Optimize Performance

Avoid overly complex patterns that slow down processing, especially in large datasets.

Test with Different Inputs

Validate expressions with multiple samples to ensure accuracy.

Check for Greedy vs. Lazy Matching

Use .*? for non-greedy matches when needed.