A Python logging library designed for data professionals and developers who need reliable, secure logging with minimal setup.
Project description
📋 Table of Contents
📣 Overview
A Python logging library designed for data professionals and developers who need reliable, secure logging with minimal setup. It extends Python's standard logging module with production-ready features commonly needed in data engineering and application development. It includes features like sensitive data masking, log rotation, asynchronous logging, rate limiting, and dynamic configuration, all while remaining lightweight and easy to use.
💡 Features
- Sensitive Data Masking: Automatically masks predefined sensitive fields (e.g.,
password,token) in logs. - Log Filtering: Filter logs based on specific keywords.
- Dynamic Masking Control: Enable or disable masking on a per-log basis using the
maskparameter. - Performance Metrics: Track logs per second for insights into logging activity.
- Interactive Log Viewer: View logs in a structured, styled table using the
richlibrary. - Rate Limiting: Avoid repetitive logs of the same message within a specified interval.
- Log Rotation: Supports rotating log files based on file size, with configurable backup counts.
- Asynchronous Logging: Offload logging to a background thread for improved performance.
- JSON Log Formatting: Optional structured JSON logging for integration with log aggregation tools.
- Dynamic Log Level Adjustments: Update logger settings (e.g., log level) dynamically at runtime.
- Reusable Global Logger: Easily access a shared logger across multiple modules with
get_logger. - Color-Coded Logs: Enable
richintegration for visually enhanced terminal output. - CLI Log Viewer (Static/Live): Log viewer using CLI, also supports live viewer and detects for changes.
- Custom Log Level: Runtime custom log level injection (e.g.
SECURITY,AUDIT)
📌 Quick Start
Installation
Install:
pip install pylogshield
Upgrade:
pip install --upgrade pylogshield
Documentation
Full developer docs with API reference, usage, and model schema:
👪 Contributing
All contributions are welcome. If you have a suggestion that would make this better, please fork the repo and create a merge request. You can also simply open an issue with the label 'enhancement'.
Don't forget to give the project a star! Thanks again!
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