chameleon-log 1.5.0

Colourful handlers for Logbook, based on Rich and Journald.

🦎 ChameleonLog

Colourful logging handlers for Logbook.

ChameleonLog provides colorful, structured logging for Python applications using the Logbook.

• RichHandler: Beautiful console output with syntax highlighting and tracebacks using the Rich library (recommended for development).

• JournaldHandler: Structured logging to systemd journald with automatic level-based coloring and filtering (recommended for production/Live systems on Linux).

📦 Installation

Install ChameleonLog using pip:

pip install chameleon_log

Or using uv:

uv add chameleon_log

🔧 Optional Dependencies

To use the JournaldHandler for sending logs to systemd journald:

pip install chameleon_log[journald]

Or using uv:

uv add chameleon_log --extra journald

This will also install the systemd-python package, requiring systemd-based Linux distros.

🚀 Usage

✨ RichHandler

For development and debugging in terminal environments, use RichHandler for colorful, formatted console output:

import logbook

from chameleon_log import RichHandler

# Create a RichHandler with default settings
handler = RichHandler()

with handler:
    logger = logbook.Logger(__name__)
    logger.info('Application started successfully')
    logger.warning('This is a warning message')
    logger.error('An error occurred')

The rich_rendering parameter controls Rich formatting:

• True: Always use Rich colorful rendering

• False: Disable Rich formatting, render plain output

• None (default): Auto-detect based on isatty()

🖼️ Example output

🐧 JournaldHandler

For applications deployed on Linux servers or in production environments, use JournaldHandler to write logs directly to journald, using its native protocol. This provides more efficient troubleshooting capabilities compared to file-based logging or stdout / stderr capture.

Note

This is not the same as writing logs to stdout / stderr and letting journald collect them. The latter method makes you lose important metadata (timestamps, severity levels, extra fields) needed for effective log filtering and analysis.

Basic usage:

import logbook
from chameleon_log.journald import JournaldHandler

handler = JournaldHandler(syslog_identifier='my-app')

with handler:
    logger = logbook.Logger(__name__)
    logger.info('Application started successfully')
    logger.warning('This is a warning message')
    logger.error('An error occurred')

📝 Simple logging output:

🏗️ With extra fields for structured filtering:

Logbook provides two ways to attach extra fields:

Option 1: Use the extra= parameter (simple and direct)

import logbook
from chameleon_log.journald import JournaldHandler

handler = JournaldHandler(syslog_identifier='my-app')

with handler:
    logger = logbook.Logger(__name__)
    logger.info('User logged in', extra={'user_id': 123, 'action': 'login'})

Option 2: Use a Processor (for reusable context)

import logbook
from logbook import Logger, Processor
from chameleon_log.journald import JournaldHandler

handler = JournaldHandler()
    # or
handler = JournaldHandler(syslog_identifier='my-app')

# Use a Processor to inject context into multiple log records
def inject_request_context(record):
    record.extra['user_id'] = 123
    record.extra['request_id'] = 'abc-456'

with handler:
    logger = logbook.Logger(__name__)

    with Processor(inject_request_context):
        logger.info('User logged in')  # Fields injected automatically
        logger.info('Data processed')

View logs with journalctl:

journalctl -fu my-service
journalctl -t my-app F_USER_ID=123
journalctl -eu my-service -o json

Normally, you view your app logs with -u (unit), the syslog_identifier is helpful if your app scatters across many systemd units, you then can use journalctl -t to view all.

📖 Documentation

Full documentation is available at: https://chameleon-log.readthedocs.io

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

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