lifecyclelogging 2.1.1

A comprehensive logging utility for managing application lifecycle logs

LifecycleLogging

Lifecycle-aware logging with rich output and message storage.

LifecycleLogging is a comprehensive logging utility that combines Python's logging with rich output formatting. It provides configurable console and file outputs, message storage with context markers, verbosity controls, and seamless Gunicorn integration.

Key Features

• Rich Formatting - Enhanced readability with configurable console and file outputs
• Message Storage - Store and retrieve messages by context and storage markers
• Verbosity Control - Fine-grained verbosity thresholds with bypass markers
• Level Filtering - Case-insensitive allowed/denied storage rules
• JSON Attachment - Attach structured data to log entries
• Gunicorn Integration - Automatic logger inheritance when running under Gunicorn
• Type-Safe - Full type annotations throughout

---

Installation

pip install lifecyclelogging

Quick Start

from lifecyclelogging import Logging

# Initialize logger
logger = Logging(
    enable_console=True,
    enable_file=True,
    logger_name="my_app"
)

# Basic logging
logger.logged_statement("Basic message", log_level="info")

# With context marker
logger.logged_statement(
    "Application started",
    context_marker="STARTUP",
    log_level="info"
)

# With JSON data
logger.logged_statement(
    "Request received",
    json_data={"method": "GET", "path": "/api/users"},
    log_level="debug"
)

Advanced Features

Verbosity Control

logger = Logging(
    enable_verbose_output=True,
    verbosity_threshold=2
)

# Only logged if verbosity threshold allows
logger.logged_statement(
    "Detailed debug info",
    verbose=True,
    verbosity=2,
    log_level="debug"
)

Verbosity Bypass

logger.register_verbosity_bypass_marker("IMPORTANT")

# Logged regardless of verbosity settings
logger.logged_statement(
    "Critical info",
    context_marker="IMPORTANT",
    verbose=True,
    verbosity=5,
    log_level="debug"
)

Message Storage

# Store message under a marker
logger.logged_statement(
    "Important event",
    storage_marker="EVENTS",
    log_level="info"
)

# Access stored messages
events = logger.stored_messages["EVENTS"]

---

Contributing

Contributions are welcome! Please see the Contributing Guidelines for more information.

Project Links

• PyPI
• GitHub
• Documentation
• Changelog