lifecyclelogging 0.2.1
A comprehensive logging utility for managing application lifecycle logs
License: MIT
Requires Python: >=3.9
Keywords: debug, lifecycle, logging

# LifecycleLogging

[![LifecycleLogging Logo](docs/_static/logo.png)](https://github.com/jbcom/lifecyclelogging)

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

[![Documentation](https://img.shields.io/badge/docs-github.io-blue.svg)](https://jbcom.github.io/lifecyclelogging/)
[![GitHub](https://img.shields.io/badge/github-repo-black.svg)](https://github.com/jbcom/lifecyclelogging)

## Installation

```bash
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

```python
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

```python
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

```python
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

```python
# 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:

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

## Development

```bash
# 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](https://github.com/jbcom/lifecyclelogging/blob/main/LICENSE) for details.

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**Happy Logging!**