Python RegEx Tester

Test and debug Python regular expressions online with instant match highlighting

RegEx Tester

Regular Expression Pattern

Ignore Case (re.IGNORECASE)

Multiline (re.MULTILINE)

Dot All (re.DOTALL)

Test String Contact us at john@example.com or support@qodex.ai for assistance. You can also reach out to admin@testsite.org.

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Python Regular Expressions Guide

What is Python Regex?

Python Regular Expressions (RegEx) are powerful pattern-matching tools used to search, match, and manipulate text strings. They provide a concise and flexible way to identify specific patterns within text data.

RegEx is particularly useful for:

• Email validation
• Password strength checking
• Phone number formatting
• Data extraction and cleaning
• Text parsing and validation

Core Components

Python RegEx consists of several key components that work together to create powerful pattern matching capabilities:

import re # Basic pattern matching pattern = r"\d+" text = "I have 25 apples" matches = re.findall(pattern, text)

Metacharacters

Special characters with specific meanings in regex patterns:

• . Matches any character except newline
• ^ Matches start of string
• $ Matches end of string
• * Matches 0 or more repetitions
• + Matches 1 or more repetitions
• ? Matches 0 or 1 repetition

Character Classes

Define sets of characters to match:

• [abc] Matches a, b, or c
• [a-z] Matches any lowercase letter
• [A-Z] Matches any uppercase letter
• [0-9] Matches any digit
• [^abc] Matches anything except a, b, or c

Predefined Classes

Shorthand for common character sets:

• \d Matches any digit [0-9]
• \D Matches any non-digit
• \w Matches any word character [a-zA-Z0-9_]
• \W Matches any non-word character
• \s Matches any whitespace character
• \S Matches any non-whitespace character

Quantifiers

Specify how many times a pattern should repeat:

• {3} Exactly 3 times
• {3,} 3 or more times
• {3,6} Between 3 and 6 times
• *? Non-greedy: matches as few as possible
• +? Non-greedy: matches as few as possible

Groups & Capturing

Group parts of patterns and capture matched text:

• (abc) Capturing group
• (?:abc) Non-capturing group
• (?P<name>abc) Named capturing group
• \1 Backreference to group 1

Common Examples

Practical regex patterns for everyday use:

# Email validation r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$' # Phone number (US format) r'^\(\d{3}\)\s\d{3}-\d{4}$' # Strong password r'^(?=.*[a-z])(?=.*[A-Z])(?=.*\d)(?=.*[@$!%*?&])[A-Za-z\d@$!%*?&]{8,}$' # URL validation r'^https?://(?:[-\w.])+(?:[:\d]+)?(?:/(?:[\w/_.])*(?:\?(?:[\w&=%.])*)?(?:#(?:\w*))?)?$'

How It Works

1

Enter Your Pattern

Input your regular expression pattern in the designated field. Use Python regex syntax including metacharacters, character classes, and quantifiers.

2

Configure Flags

Select optional flags like case-insensitive matching, multiline mode, or dot-all mode to modify how your pattern behaves.

3

Add Test String

Paste or type the text you want to test your regular expression against. This can be single or multiple lines of text.

4

Analyze Results

View highlighted matches, detailed match information, capture groups, and statistics. The tool provides comprehensive analysis of your regex performance.

5

Refine & Iterate

Use the results to refine your pattern. The real-time feedback helps you perfect your regex for your specific use case.

Feature	Details
Price	Free
Rendering	Client-Side Rendering
Language	JavaScript
Paywall	No

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