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Test, debug, and explain regular expressions. Visualize matches, generate patterns from examples, and convert between regex flavors.

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SKILL.md

name regex-tester
description Test, debug, and explain regular expressions. Visualize matches, generate patterns from examples, and convert between regex flavors.

Regex Tester

Test and debug regular expressions with detailed match visualization, plain-English explanations, and pattern generation from examples.

Quick Start

from scripts.regex_tester import RegexTester

# Test pattern
tester = RegexTester()
result = tester.test(r"\d{3}-\d{4}", "Call 555-1234 today")
print(result['matches'])  # ['555-1234']

# Explain pattern
explanation = tester.explain(r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b")
print(explanation)

# Generate pattern from examples
pattern = tester.generate_pattern(["555-1234", "123-4567", "999-0000"])
print(pattern)  # r"\d{3}-\d{4}"

Features

  • Pattern Testing: Test against text with detailed results
  • Match Visualization: See exactly what matched and where
  • Pattern Explanation: Plain-English breakdown of regex
  • Pattern Generation: Create patterns from example matches
  • Find & Replace: Test substitution patterns
  • Common Patterns: Library of pre-built patterns
  • Validation: Check pattern syntax before use

API Reference

Testing

tester = RegexTester()

# Basic test
result = tester.test(r"\d+", "There are 42 items")
# {
#     'pattern': r'\d+',
#     'text': 'There are 42 items',
#     'matches': ['42'],
#     'match_count': 1,
#     'positions': [(10, 12)],  # (start, end)
#     'groups': []
# }

# With flags
result = tester.test(r"hello", "Hello World", ignore_case=True)

# All matches with groups
result = tester.test(r"(\d{3})-(\d{4})", "555-1234 and 999-0000")
# matches: ['555-1234', '999-0000']
# groups: [('555', '1234'), ('999', '0000')]

Explanation

explanation = tester.explain(r"\b\w+@\w+\.\w{2,}\b")
# Returns:
# \b - Word boundary
# \w+ - One or more word characters
# @ - Literal '@'
# \w+ - One or more word characters
# \. - Literal '.'
# \w{2,} - Two or more word characters
# \b - Word boundary

Pattern Generation

# Generate pattern from examples
examples = ["user@test.com", "admin@site.org", "info@company.net"]
pattern = tester.generate_pattern(examples)
# Suggests: r"[a-z]+@[a-z]+\.(com|org|net)"

# With negative examples (what NOT to match)
pattern = tester.generate_pattern(
    positive=["555-1234", "999-0000"],
    negative=["555-12", "12345"]
)

Find & Replace

result = tester.replace(
    pattern=r"(\d{3})-(\d{4})",
    replacement=r"(\1) \2",
    text="Call 555-1234"
)
# "Call (555) 1234"

Validation

# Check if pattern is valid
is_valid, error = tester.validate(r"[invalid")
# is_valid: False
# error: "unterminated character set"

Common Patterns

# Get pre-built patterns
email = tester.patterns['email']
phone = tester.patterns['phone']
url = tester.patterns['url']
ip = tester.patterns['ipv4']

CLI Usage

# Test pattern
python regex_tester.py --pattern "\d+" --text "There are 42 items"

# Test from file
python regex_tester.py --pattern "\w+@\w+\.\w+" --file emails.txt

# Explain pattern
python regex_tester.py --explain "\b[A-Z][a-z]+\b"

# Find and replace
python regex_tester.py --pattern "(\d+)" --replace "[$1]" --text "Item 42"

# Generate pattern
python regex_tester.py --generate "555-1234,999-0000,123-4567"

# Interactive mode
python regex_tester.py --interactive

CLI Arguments

Argument Description Default
--pattern Regex pattern -
--text Text to test against -
--file File to test against -
--explain Explain pattern False
--replace Replacement pattern -
--generate Generate from examples -
--ignore-case Case insensitive False
--multiline Multiline mode False
--interactive Interactive mode False

Examples

Email Validation

tester = RegexTester()

email_pattern = r"^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$"

test_emails = [
    "user@example.com",
    "invalid.email",
    "user@domain",
    "test.user+tag@sub.domain.org"
]

for email in test_emails:
    result = tester.test(email_pattern, email)
    status = "Valid" if result['matches'] else "Invalid"
    print(f"{email}: {status}")

Extract Data from Log

tester = RegexTester()

log_line = '[2024-01-15 14:30:22] ERROR: Connection timeout (192.168.1.100)'
pattern = r'\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2})\] (\w+): (.+) \((\d+\.\d+\.\d+\.\d+)\)'

result = tester.test(pattern, log_line)
if result['groups']:
    timestamp, level, message, ip = result['groups'][0]
    print(f"Time: {timestamp}")
    print(f"Level: {level}")
    print(f"Message: {message}")
    print(f"IP: {ip}")

Phone Number Formatter

tester = RegexTester()

# Normalize various phone formats
phones = ["5551234567", "(555) 123-4567", "555.123.4567"]
pattern = r"[\(\)\.\s-]?"

for phone in phones:
    # Remove all formatting
    clean = tester.replace(r"[\(\)\.\s-]", "", phone)
    # Format consistently
    formatted = tester.replace(
        r"(\d{3})(\d{3})(\d{4})",
        r"(\1) \2-\3",
        clean
    )
    print(f"{phone} -> {formatted}")

Understand Complex Pattern

tester = RegexTester()

# Explain a complex pattern
pattern = r"(?:https?://)?(?:www\.)?([a-zA-Z0-9-]+)\.([a-zA-Z]{2,})(?:/\S*)?"

explanation = tester.explain(pattern)
print(explanation)
# (?:https?://)? - Optional non-capturing group: 'http://' or 'https://'
# (?:www\.)? - Optional non-capturing group: 'www.'
# ([a-zA-Z0-9-]+) - Capturing group 1: domain name
# \. - Literal '.'
# ([a-zA-Z]{2,}) - Capturing group 2: TLD
# (?:/\S*)? - Optional non-capturing group: path

Common Patterns Library

Name Pattern Matches
email Complex user@domain.com
phone_us \d{3}[-.]?\d{3}[-.]?\d{4} 555-123-4567
url Complex https://example.com
ipv4 \d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3} 192.168.1.1
date_iso \d{4}-\d{2}-\d{2} 2024-01-15
time_24h \d{2}:\d{2}(:\d{2})? 14:30:00
hex_color #[0-9A-Fa-f]{6} #FF5733
zipcode_us \d{5}(-\d{4})? 12345-6789

Dependencies

(No external dependencies - uses Python standard library re module)

Limitations

  • Pattern generation is heuristic (may not be optimal)
  • Some advanced regex features are Python-specific
  • Explanation works best with common patterns
  • Very long patterns may have simplified explanations