plumbrc 1.0.2

High-performance log redaction for Python - Python wrapper for PlumbrC

PlumbrC for Python

High-performance log redaction for Python. Python wrapper for the PlumbrC C library.

Features

• 🚀 Blazing Fast — 500K+ lines/sec powered by C engine
• 📦 702 Built-in Patterns — AWS, GCP, Stripe, GitHub, and more
• 🔒 Security-First — Detect and redact secrets, API keys, passwords, PII
• 💻 Simple API — Pythonic interface to high-performance C library
• 🔧 Zero Dependencies — Pure ctypes wrapper, no external Python packages

Installation

pip install plumbrc

Requirements

• Python 3.7+
• Linux or macOS
• libpcre2 (usually pre-installed)

Quick Start

from plumbrc import Plumbr

# Create redactor with default patterns
p = Plumbr()

# Redact secrets from text
text = "api_key=sk-proj-abc123 password=secret123"
safe = p.redact(text)
print(safe)
# Output: "api_key=[REDACTED:api_key] password=[REDACTED:password]"

# Check loaded patterns
print(f"Loaded {p.pattern_count} patterns")

# Get statistics
print(p.stats)

Usage

Basic Redaction

from plumbrc import Plumbr

p = Plumbr()

# Single line
safe = p.redact("AWS key: AKIAIOSFODNN7EXAMPLE")
# "AWS key: [REDACTED:aws_access_key]"

# Multiple lines
lines = [
    "User login with token: ghp_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
    "Database: postgres://user:pass@localhost:5432/db",
    "Normal log line"
]
redacted = p.redact_lines(lines)

Context Manager

with Plumbr() as p:
    safe = p.redact("secret data")
    print(safe)
# Resources automatically cleaned up

Custom Patterns

# Load custom pattern file
p = Plumbr(pattern_file="my_patterns.txt")

# Load patterns from directory
p = Plumbr(pattern_dir="patterns/")

Statistics

p = Plumbr()
p.redact("api_key=secret123")

stats = p.stats
print(stats)
# {
#     'lines_processed': 1,
#     'lines_modified': 1,
#     'patterns_matched': 1,
#     'bytes_processed': 17,
#     'elapsed_seconds': 0.000123
# }

API Reference

Plumbr

Main redaction class.

Constructor

Plumbr(
    pattern_file: Optional[str] = None,
    pattern_dir: Optional[str] = None,
    num_threads: int = 0,
    quiet: bool = True
)

Parameters:

• pattern_file: Path to custom pattern file
• pattern_dir: Path to directory with pattern files
• num_threads: Number of worker threads (0 = auto)
• quiet: Suppress statistics output

Methods

redact(text: str) -> str

Redact secrets from text.

safe = p.redact("password=secret123")

redact_lines(lines: List[str]) -> List[str]

Redact multiple lines.

safe_lines = p.redact_lines(["line1", "line2"])

Properties

pattern_count: int

Number of loaded patterns.

count = p.pattern_count

stats: Dict[str, int]

Processing statistics.

stats = p.stats

version() -> str (static)

Get PlumbrC library version.

ver = Plumbr.version()

Pattern Categories

PlumbrC includes 702 patterns across 12 categories:

Category	Patterns	Examples
Cloud	109	AWS, GCP, Azure, DigitalOcean
Communication	127	Slack, Discord, Telegram, Twilio
Payment	79	Stripe, Square, PayPal, Braintree
VCS	63	GitHub, GitLab, Bitbucket
Infrastructure	72	Docker, NPM, PyPI, CI/CD
Crypto	54	SSH, SSL/TLS, PGP, JWT
Secrets	52	Generic API keys, passwords
Social	50	Facebook, Twitter, LinkedIn
Database	42	PostgreSQL, MongoDB, MySQL
Analytics	30	Google Analytics, Mixpanel
PII	14	Email, SSN, phone, IP
Auth	10	JWT, OAuth, Bearer tokens

Performance

PlumbrC is built for speed:

• 500K+ lines/sec on modern hardware
• Sub-microsecond per-line latency
• Zero-allocation hot path in C engine
• Parallel processing support

import time
from plumbrc import Plumbr

p = Plumbr()

# Benchmark
lines = ["test line"] * 100000
start = time.time()
p.redact_lines(lines)
elapsed = time.time() - start

print(f"Processed {len(lines)} lines in {elapsed:.2f}s")
print(f"Throughput: {len(lines)/elapsed:.0f} lines/sec")

Examples

Log File Processing

from plumbrc import Plumbr

with Plumbr() as p:
    with open("app.log") as f:
        for line in f:
            safe = p.redact(line)
            print(safe, end="")

Flask Integration

from flask import Flask, request, jsonify
from plumbrc import Plumbr

app = Flask(__name__)
redactor = Plumbr()

@app.route("/api/redact", methods=["POST"])
def redact():
    text = request.json.get("text", "")
    safe = redactor.redact(text)
    return jsonify({"redacted": safe, "stats": redactor.stats})

Batch Processing

from plumbrc import Plumbr
import glob

p = Plumbr()

for log_file in glob.glob("logs/*.log"):
    with open(log_file) as f:
        lines = f.readlines()
    
    redacted = p.redact_lines(lines)
    
    with open(f"redacted/{log_file}", "w") as f:
        f.writelines(redacted)

Development

Building from Source

# Clone repository
git clone https://github.com/AmritRai1234/plumbrC.git
cd plumbrC/python

# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest tests/ -v

Running Tests

# Install test dependencies
pip install pytest pytest-cov

# Run tests
pytest tests/

# With coverage
pytest tests/ --cov=plumbrc --cov-report=html

License

Source Available License — Free for non-commercial use. See LICENSE for details.

Links

• Homepage: https://plumbr.ca
• GitHub: https://github.com/AmritRai1234/plumbrC
• PyPI: https://pypi.org/project/plumbrc/
• Documentation: https://plumbr.ca

Support

• Issues: GitHub Issues
• Commercial Licensing: See LICENSE file

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PlumbrC — Protect your logs. Protect your secrets.