Regexr

Cleanup Review

python scripts/_purge_cache.py is an optional cleanup helper for the Regexr skill. It may recursively remove /tmp/skill_cache. Show the exact paths first, explain whether they are skill-private temporary paths or user state, and run the cleanup only after the user confirms.

Regexr

Developer tools CLI for checking, validating, generating, and working with regular expressions and code patterns. Lint syntax, explain complex expressions, convert between formats, generate templates, diff pattern versions, preview matches, fix common regex issues, and produce reports — all from the command line with persistent local logging.

Commands

Run regexr <command> [args] to use.

Each domain command (check, validate, generate, etc.) works in two modes:

• Without arguments: displays the most recent 20 entries from that category
• With arguments: logs the input with a timestamp and saves to the category log file

Data Storage

All data is stored locally in ~/.local/share/regexr/:

• Each command creates its own log file (e.g., check.log, validate.log, generate.log)
• A unified history.log tracks all activity across commands
• Entries are stored in timestamp|value pipe-delimited format
• Export supports JSON, CSV, and plain text formats

Requirements

• Bash 4+ with set -euo pipefail strict mode
• Standard Unix utilities: date, wc, du, tail, grep, sed, cat
• No external dependencies or API keys required

When to Use

1. Building and testing regex patterns — use generate to create patterns from descriptions, check to verify correctness, and preview to test against sample data
2. Learning and understanding regex — use explain to break down complex patterns into plain-language descriptions, perfect for code reviews or onboarding
3. Linting and fixing regex in codebases — run lint to catch performance and safety issues (catastrophic backtracking, unanchored patterns), then fix to auto-correct them
4. Converting regex across languages — use convert to translate patterns between JavaScript, Python, PCRE, and other flavors when porting code
5. Documenting regex usage in projects — log patterns with template, generate report summaries, and export data for documentation or audits

Examples

# Check a regex pattern for issues
regexr check "^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z]{2,}$ — email validation"

# Validate regex syntax
regexr validate "(?<=@)[a-z]+\.com — lookbehind syntax OK"

# Generate a pattern from description
regexr generate "match IPv4 addresses: \d{1,3}(\.\d{1,3}){3}"

# Explain a complex regex
regexr explain "^(?=.*[A-Z])(?=.*\d).{8,}$ — password: 1 uppercase, 1 digit, 8+ chars"

# Lint for performance issues
regexr lint "(a+)+ — warning: catastrophic backtracking possible"

# Convert between flavors
regexr convert "JS→Python: /\d+/g becomes re.findall(r'\d+', text)"

# Fix common issues
regexr fix "added anchors: ^pattern$ and escaped special chars"

# Preview matches
regexr preview "pattern=[0-9]{3}-[0-9]{4} matched: 555-1234, 800-9999"

# View summary statistics
regexr stats

# Export all data as JSON
regexr export json

# Search logged patterns
regexr search "email"

Output

All commands output to stdout. Redirect to a file if needed:

regexr report "weekly pattern audit" > report.txt
regexr export csv  # saves to ~/.local/share/regexr/export.csv

Configuration

Set DATA_DIR by modifying the script, or use the default: ~/.local/share/regexr/

Powered by BytesAgain | bytesagain.com | hello@bytesagain.com