adv-logging 0.0.4

An advanced Python logging library with context, cloud support, and more

AdvancedLogger

The AdvancedLogger library provides a robust, flexible, and secure logging solution suitable for modern applications, especially those deployed in distributed or cloud environments. It helps developers and system administrators easily manage logs, ensure data privacy, comply with regulations, and integrate with popular log analysis tools.

The enhanced AdvancedLogger library is packed with a wide range of features to make logging comprehensive, efficient, and secure for modern applications. Here is the detailed list of features:

1. Core Logging Features Multi-level Logging: Supports various log levels such as DEBUG, INFO, WARNING, ERROR, and CRITICAL. Asynchronous Logging: Uses ThreadPoolExecutor for non-blocking, asynchronous log writing, ensuring that logging does not slow down your application.
2. Log Handlers and Destinations Console Logging: Outputs logs to the console, with optional color-coding for better readability. File Logging with Compression: Rotating File Handler: Supports log rotation to manage log file sizes and avoid excessive disk usage. Compressed File Archiving: Automatically compresses old log files to save disk space using gzip.
3. Integration with Cloud Log Management Systems: AWS CloudWatch Handler: Sends logs directly to AWS CloudWatch for centralized log management. Splunk Handler: Sends logs to a Splunk HTTP Event Collector endpoint for real-time log monitoring.
4. Log Formatting Options Custom Timestamp Formatting: Users can specify a custom timestamp format (e.g., "Date: --/--/-- Time: --.--.--") or use the standard logging time format. Colorized Logging: Optionally apply colors to log messages based on the severity level, making them easier to distinguish in the console. JSON Log Formatting: Supports structured logging in JSON format, making logs easier to parse and analyze using log management tools.
5. Contextual and Traceable Logging Contextual Information: Attach additional context to each log message, such as request IDs, user information, or application state details. Unique Trace IDs: Optionally generate and include unique trace IDs for tracking and correlating log events across distributed systems.
6. Security and Compliance Sensitive Data Masking: Automatically masks sensitive information (like credit card numbers, SSNs, and email addresses) to ensure privacy and compliance with data protection regulations. Audit Trails: Logs specific security-related events (such as initialization and critical changes) to a separate audit trail file for compliance and monitoring purposes.
7. Advanced Filtering Content-Based Filtering: Users can define filters to include or exclude specific log messages based on criteria like message content, log level, or additional context fields.
8. Configuration Options Environment-Based Configuration: Allows easy configuration through environment variables or configuration files, simplifying setup in different environments (e.g., development, testing, production).
9. Error Handling and Resilience Graceful Error Handling: The logger can handle errors such as file write failures or losing connection to a remote logging service gracefully, without crashing the application. Fallback Mechanisms: Uses fallback strategies to ensure logging continuity when an error occurs in one of the handlers.
10. Additional Utilities Audit Logging: Maintains a separate audit log file for critical events, useful for security and compliance tracking. Masking Patterns: Customizable patterns for masking sensitive data in log messages. Dynamic Context Updates: Ability to dynamically add or update context information for logs as the application runs.