OneLogger 🚀

A Simple and Efficient Logging Library

OneLogger is a lightweight logging library built to help you dynamically configure and manage log settings with ease using oneenv. It leverages Python's built-in logging module and (for Python versions up to 3.12) enhances performance with picologging. Perfect for development, testing, and production environments!

Features ✨

• Dynamic Configuration: Easily manage logging settings using environment variables via oneenv.
• High Performance Logging:
  • For Python versions ≤ 3.12, OneLogger uses picologging to deliver blazing-fast logging 🚀.
  • For Python 3.13 and later, it seamlessly falls back to the standard logging module.
• Flexible Output Options: Configure logs to output to the console, files (with rotation), or both.
• Custom Formatting: Supports both plain text and JSON log formats.
• Asynchronous Logging: Optionally enable asynchronous logging for better performance under high load.
• Easy Integration: A simple API with a singleton pattern for effortless logger retrieval.

Supported Environments 🖥️

• Python ≥ 3.11
  • Python < 3.13: Utilizes picologging for enhanced performance.
  • Python ≥ 3.13: Uses the standard logging module for full compatibility.

Installation 🛠️

For Users 👥

pip install onelogger

For Developers 🛠️

1. Clone the Repository

   git clone <repository-url>
   cd onelogger
   

2. Create and Activate a Virtual Environment

   python -m venv .venv
   # Windows (PowerShell)
   .\.venv\Scripts\Activate.ps1
   # macOS/Linux
   source .venv/bin/activate
   

3. Install Development Dependencies

   pip install -e ".[dev]"
   

Usage 🚀

OneLogger integrates effortlessly into your projects. For example:

from onelogger import Logger

# Retrieve a configured logger instance
logger = Logger.get_logger("example_logger")

# Log messages at various levels
logger.info("This is an informational message.")
logger.error("This is an error message.")

try:
    result = 1 / 0
except Exception as e:
    logger.exception("An exception occurred during division!")

You can try out the example provided in the examples folder:

python examples/example_logger.py

Configuration 📦

OneLogger uses oneenv to manage environment variables with ease. The library automatically generates a .env.example template file with detailed descriptions for all available settings. This makes it simple to:

• View all available configuration options with descriptions
• Understand the purpose and valid values for each setting
• Create your own .env file by copying and modifying the template

Here's an example of the auto-generated template:

# Auto-generated by OneEnv

# Specifies the logging level used by OneLogger.
# Valid options are DEBUG, INFO, WARNING, ERROR, and CRITICAL.
# Required
LOG_LEVEL=DEBUG

# Specifies the destination for log output.
# Options: 'console' for standard output, 'file' for file logging, or 'both'.
# Required
LOG_OUTPUT=both

# Specifies the log file path when LOG_OUTPUT is set to 'file' or 'both'.
LOG_FILE_PATH=example.log

# ... (other settings with descriptions)

To configure OneLogger, simply:

1. Copy .env.example to .env
2. Modify the values in .env according to your needs
3. OneLogger will automatically load these settings when initialized

Contributing 🤝

Contributions are welcome! Please follow best practices and add tests as necessary.

License 📄

This project is licensed under the MIT License.

Color Support 🎨

OneLogger supports ANSI color codes in log messages:

• Console output shows colored messages (when supported)
• File output can strip color codes (configurable via LOG_STRIP_COLORS)

Windows Users

Color support is automatically enabled on Windows 10 and later. For earlier versions, you might need to use Windows Terminal or another terminal that supports ANSI colors.

Environment Variables

• LOG_STRIP_COLORS: Set to "true" to remove color codes from file output (default: "false")
• NO_COLOR: Set to any value to disable colors completely

Enjoy fast and configurable logging with OneLogger! 🎉