lifecyclelogging 202511.3.0

A comprehensive logging utility for managing application lifecycle logs

LifecycleLogging

A comprehensive logging utility for managing application lifecycle logs, combining the power of Python's logging with rich output formatting.

Installation

pip install lifecyclelogging

Features

• Configurable console and file logging outputs
• Rich formatting for enhanced readability
• Message storage with context and storage markers
• Verbosity controls with bypass markers
• Case-insensitive level filtering for allowed/denied storage rules
• JSON data attachment support
• Type-safe implementation
• Seamless integration with existing logging systems
• Automatic Gunicorn logger integration

Project Goals

• Provide a batteries-included logging helper that stays compatible with modern Python releases
• Keep configuration ergonomic while remaining type-safe and explicit
• Offer sensible defaults that work locally and in containerized runtimes
• Deliver reliable automation through testing, linting, and release workflows

Basic Usage

from lifecyclelogging import Logging

# Initialize logger
logger = Logging(
    enable_console=True,  # Enable console output
    enable_file=True,     # Enable file output
    logger_name="my_app"
)

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

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

# With JSON data
logger.logged_statement(
    "Message with data",
    json_data={"key": "value"},
    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 Helpers

logger.register_verbosity_bypass_marker("IMPORTANT")

# Will be 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"]

Gunicorn Integration

When running under Gunicorn, LifecycleLogging automatically detects and inherits Gunicorn's logger configuration:

# The logger will automatically use Gunicorn's handlers if available
logger = Logging(
    enable_console=True,
    enable_file=True
)

Development

# Install development dependencies
pip install -e ".[dev,test,docs]"

# Run tests
make test

# Run linting and type checks
make check

# Build documentation
make docs

License

MIT License - See LICENSE for details.

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Happy Logging!