R

Regex Patterns

regex-patterns

Practical regex patterns across languages and use cases. Use when validating input (email, URL, IP), parsing log lines, extracting data from text, refactoring code with search-and-replace, or debugging why a regex doesn't match.

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关于 Regex Patterns

--- name: regex-patterns description: Practical regex patterns across languages and use cases. Use when validating input (email, URL, IP), parsing log lines, extracting data from text, refactoring code with search-and-replace, or debugging why a regex doesn't match. metadata: {"clawdbot":{"emoji":"🔤","requires":{"anyBins":["grep","python3","node"]},"os":["linux","darwin","win32"]}} ---

Regex Patterns

Practical regular expression cookbook. Patterns for validation, parsing, extraction, and refactoring across JavaScript, Python, Go, and command-line tools.

When to Use

Validating user input (email, URL, IP, phone, dates)
Parsing log lines or structured text
Extracting data from strings (IDs, numbers, tokens)
Search-and-replace in code (rename variables, update imports)
Filtering lines in files or command output
Debugging regexes that don't match as expected

Quick Reference

Metacharacters

| Pattern | Matches | Example | |---|---|---| | . | Any character (except newline) | a.c matches abc, a1c | | \d | Digit [0-9] | \d{3} matches 123 | | \w | Word char [a-zA-Z0-9_] | \w+ matches hello_123 | | \s | Whitespace [ \t\n\r\f] | \s+ matches spaces/tabs | | \b | Word boundary | \bcat\b matches cat not scatter | | ^ | Start of line | ^Error matches line starting with Error | | $ | End of line | \.js$ matches line ending with .js | | \D, \W, \S | Negated: non-digit, non-word, non-space | |

Quantifiers

| Pattern | Meaning | |---|---| | * | 0 or more (greedy) | | + | 1 or more (greedy) | | ? | 0 or 1 (optional) | | {3} | Exactly 3 | | {2,5} | Between 2 and 5 | | {3,} | 3 or more | | *?, +? | Lazy (match as few as possible) |

Groups and Alternation

| Pattern | Meaning | |---|---| | (abc) | Capture group | | (?:abc) | Non-capturing group | | (?Pabc) | Named group (Python) | | (?abc) | Named group (JS/Go) | | a\|b | Alternation (a or b) | | [abc] | Character class (a, b, or c) | | [^abc] | Negated class (not a, b, or c) | | [a-z] | Range |

Lookahead and Lookbehind

| Pattern | Meaning | |---|---| | (?=abc) | Positive lookahead (followed by abc) | | (?!abc) | Negative lookahead (not followed by abc) | | (?<=abc) | Positive lookbehind (preceded by abc) | | (? | Negative lookbehind (not preceded by abc) |


Validation Patterns
Email
# Basic (covers 99% of real emails)
^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$

# Stricter (no consecutive dots, no leading/trailing dots in local part)
^[a-zA-Z0-9]([a-zA-Z0-9._%+-]*[a-zA-Z0-9])?@[a-zA-Z0-9]([a-zA-Z0-9-]*[a-zA-Z0-9])?(\.[a-zA-Z]{2,})+$
URL
# HTTP/HTTPS URLs
https?://[a-zA-Z0-9]([a-zA-Z0-9-]*[a-zA-Z0-9])?(\.[a-zA-Z0-9]([a-zA-Z0-9-]*[a-zA-Z0-9])?)*(/[^\s]*)?

# With optional port and query
https?://[^\s/]+(/[^\s?]*)?(\?[^\s#]*)?(#[^\s]*)?
IP Addresses
# IPv4
\b(?:(?:25[0-5]|2[0-4]\d|[01]?\d\d?)\.){3}(?:25[0-5]|2[0-4]\d|[01]?\d\d?)\b

# IPv4 (simple, allows invalid like 999.999.999.999)
\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b

# IPv6 (simplified)
(?:[0-9a-fA-F]{1,4}:){7}[0-9a-fA-F]{1,4}
Phone Numbers
# US phone (various formats)
(?:\+1[-.\s]?)?\(?\d{3}\)?[-.\s]?\d{3}[-.\s]?\d{4}
# Matches: +1 (555) 123-4567, 555.123.4567, 5551234567

# International (E.164)
\+[1-9]\d{6,14}
Dates and Times
# ISO 8601 date
\d{4}-(?:0[1-9]|1[0-2])-(?:0[1-9]|[12]\d|3[01])

# ISO 8601 datetime
\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}(?:\.\d+)?(?:Z|[+-]\d{2}:\d{2})

# US date (MM/DD/YYYY)
(?:0[1-9]|1[0-2])/(?:0[1-9]|[12]\d|3[01])/\d{4}

# Time (HH:MM:SS, 24h)
(?:[01]\d|2[0-3]):[0-5]\d:[0-5]\d
Passwords (Strength Check)
# At least 8 chars, 1 upper, 1 lower, 1 digit, 1 special
^(?=.*[a-z])(?=.*[A-Z])(?=.*\d)(?=.*[!@#$%^&*()_+=-]).{8,}$
UUIDs
[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}
Semantic Version
\bv?(\d+)\.(\d+)\.(\d+)(?:-([\w.]+))?(?:\+([\w.]+))?\b
# Captures: major, minor, patch, prerelease, build
# Matches: 1.2.3, v1.0.0-beta.1, 2.0.0+build.123
Parsing Patterns
Log Lines
# Apache/Nginx access log
# Format: IP - - [date] "METHOD /path HTTP/x.x" status size
grep -oP '(\S+) - - \[([^\]]+)\] "(\w+) (\S+) \S+" (\d+) (\d+)' access.log

# Extract IP and status code
grep -oP '^\S+|"\s\K\d{3}' access.log

# Syslog format
# Format: Mon DD HH:MM:SS hostname process[pid]: message
grep -oP '^\w+\s+\d+\s[\d:]+\s(\S+)\s(\S+)\[(\d+)\]:\s(.*)' syslog

# JSON log — extract a field
grep -oP '"level"\s*:\s*"\K[^"]+' app.log
grep -oP '"message"\s*:\s*"\K[^"]+' app.log
Code Patterns
# Find function definitions (JavaScript/TypeScript)
grep -nP '(?:function\s+\w+|(?:const|let|var)\s+\w+\s*=\s*(?:async\s*)?\([^)]*\)\s*=>|(?:async\s+)?function\s*\()' src/*.ts

# Find class definitions
grep -nP 'class\s+\w+(?:\s+extends\s+\w+)?' src/*.ts

# Find import statements
grep -nP '^import\s+.*\s+from\s+' src/*.ts

# Find TODO/FIXME/HACK comments
grep -rnP '(?:TODO|FIXME|HACK|XXX|WARN)(?:\([^)]+\))?:?\s+' src/

# Find console.log left in code
grep -rnP 'console\.(log|debug|info|warn|error)\(' src/ --include='*.ts' --include='*.js'
Data Extraction
# Extract all email addresses from a file
grep -oP '[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}' file.txt

# Extract all URLs
grep -oP 'https?://[^\s<>"]+' file.html

# Extract all quoted strings
grep -oP '"[^"\\]*(?:\\.[^"\\]*)*"' file.json

# Extract numbers (integer and decimal)
grep -oP '-?\d+\.?\d*' data.txt

# Extract key-value pairs (key=value)
grep -oP '\b(\w+)=([^\s&]+)' query.txt

# Extract hashtags
grep -oP '#\w+' posts.txt

# Extract hex colors
grep -oP '#[0-9a-fA-F]{3,8}\b' styles.css
Language-Specific Usage
JavaScript
// Test if a string matches
const emailRegex = /^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$/;
emailRegex.test('[email protected]'); // true

// Extract with capture groups
const match = '2026-02-03T12:30:00Z'.match(/(\d{4})-(\d{2})-(\d{2})/);
// match[1] = '2026', match[2] = '02', match[3] = '03'

// Named groups
const m = 'John Doe, age 30'.match(/(?<name>[A-Za-z ]+), age (?<age>\d+)/);
// m.groups.name = 'John Doe', m.groups.age = '30'

// Find all matches (matchAll returns iterator)
const text = 'Call 555-1234 or 555-5678';
const matches = [...text.matchAll(/\d{3}-\d{4}/g)];
// [{0: '555-1234', index: 5}, {0: '555-5678', index: 18}]

// Replace with callback
'hello world'.replace(/\b\w/g, c => c.toUpperCase());
// 'Hello World'

// Replace with named groups
'2026-02-03'.replace(/(?<y>\d{4})-(?<m>\d{2})-(?<d>\d{2})/, '$<m>/$<d>/$<y>');
// '02/03/2026'

// Split with regex
'one, two;  three'.split(/[,;]\s*/);
// ['one', 'two', 'three']
Python
import re

# Match (anchored to start)
m = re.match(r'^(\w+)@(\w+)\.(\w+)$', '[email protected]')
if m:
    print(m.group(1))  # 'user'

# Search (find first match anywhere)
m = re.search(r'\d{3}-\d{4}', 'Call 555-1234 today')
print(m.group())  # '555-1234'

# Find all matches
emails = re.findall(r'[\w.+-]+@[\w.-]+\.\w{2,}', text)

# Named groups
m = re.match(r'(?P<name>\w+)\s+(?P<age>\d+)', 'Alice 30')
print(m.group('name'))  # 'Alice'

# Substitution
result = re.sub(r'\bfoo\b', 'bar', 'foo foobar foo')
# 'bar foobar bar'

# Sub with callback
result = re.sub(r'\b\w', lambda m: m.group().upper(), 'hello world')
# 'Hello World'

# Compile for reuse (faster in loops)
pattern = re.compile(r'\d{4}-\d{2}-\d{2}')
dates = pattern.findall(log_text)

# Multiline and DOTALL
re.findall(r'^ERROR.*$', text, re.MULTILINE)  # ^ and $ match line boundaries
re.search(r'start.*end', text, re.DOTALL)      # . matches newlines

...

`Prompt 示例`

安装 Regex Patterns 后，可以对 AI 说这些话来触发它

UHelp me get started with Regex Patterns

AExplains what Regex Patterns does, walks through the setup, and runs a quick demo based on your current project

UUse Regex Patterns to practical regex patterns across languages and use cases

AInvokes Regex Patterns with the right parameters and returns the result directly in the conversation

UWhat can I do with Regex Patterns in my developer & devops workflow?

ALists the top use cases for Regex Patterns, with example commands for each scenario

`常见问题`

如何安装 Regex Patterns？▾

将技能文件夹放到 ~/.claude/skills/regex-patterns/ 目录（个人级，所有项目可用），或 .claude/skills/regex-patterns/（项目级）。重启 AI 客户端后，用 /regex-patterns 主动调用，或让 AI 根据上下文自动发现并使用。

Regex Patterns 支持哪些 AI 平台？▾

Regex Patterns 支持 Claude、Cursor、OpenClaw，可与这些 AI 平台无缝集成，扩展其能力。

Regex Patterns 是免费的吗？▾

Regex Patterns 可免费安装使用。请查阅仓库了解许可证信息。

Regex Patterns 有什么功能？▾

Practical regex patterns across languages and use cases. Use when validating input (email, URL, IP), parsing log lines, extracting data from text, refactoring code with search-and-replace, or debugging why a regex doesn't match.

Regex Patterns 属于哪个分类？▾

Regex Patterns 属于「Developer & DevOps」分类，该分类的技能帮助 AI 智能体在此领域执行专业任务。

`使用场景`

Getting Started with Regex Patterns→Automate Developer & DevOps Workflows with Regex Patterns→Team Collaboration with Regex Patterns→

Regex Patterns

安装

关于 Regex Patterns

Regex Patterns

When to Use

Quick Reference

Metacharacters

Quantifiers

Groups and Alternation

Lookahead and Lookbehind

Validation Patterns

Email

URL

IP Addresses

Phone Numbers

Dates and Times

Passwords (Strength Check)

UUIDs

Semantic Version

Parsing Patterns

Log Lines

Code Patterns

Data Extraction

Language-Specific Usage

JavaScript

Python

`Prompt 示例`

`常见问题`

`使用场景`

`同类技能推荐`

Github

Browser Use

Browser Automation

Playwright MCP