pyhunt is a lightweight logging tool designed to enhance Python code quality through visual call tracing and structured logging. Ideal for both standard and AI-generated codebases, it simplifies debugging by allowing developers to add a simple decorator to their functions, automatically generating organized, color-coded logs in the terminal.

Features

• Automatic Function/Method Call Tracing: Record the flow of synchronous and asynchronous functions and classes effortlessly with the @trace decorator.
• Rich Colors and Tree-Structured Logs: Improve readability and understanding of logs with visually distinct coloring and indentation based on call depth.
• Multiple Log Levels Supported: Easily manage log severity levels including DEBUG, INFO, WARNING, ERROR, and CRITICAL.
• Set Log Level via CLI: Conveniently configure and store the HUNT_LEVEL within a .env file for better environment management.
• Optimized for AI Workflows: Facilitate tracing for code generated by AI systems, enhancing debugging capabilities.
• Detailed Exception Information: Capture and display essential details such as call arguments, error location, and stack trace on exceptions, aiding in rapid debugging.

Quick Start

1. Set Up Environment Variable File

Set the logging level with:

hunt

This command initializes the HUNT_LEVEL to DEBUG in your .env file.

2. Apply the @trace Decorator

To utilize the tracing functionality, simply decorate your functions or classes:

Basic Example

from pyhunt import trace

@trace
def test(value):
    return value

Asynchronous Function

@trace
async def test(value):
    return value

Class Methods

@trace
class MyClass:
    def first_method(self, value):
        return value

    def second_method(self, value):
        return value

Logger Usage

Although the logger interface is available, the recommended approach is to rely on the @trace decorator for most logging needs to maintain clarity and readability. For situations requiring more granular control, use the logger as follows:

from pyhunt import logger

logger.debug("This is a debug log.")
logger.info("This is an info log.")
logger.warning("This is a warning log.")
logger.error("This is an error log.")
logger.critical("This is a critical log.")

CLI Usage

Execute commands with logging options using:

hunt [options]

Supported Options

• --debug: Activate DEBUG level logging for detailed insights
• --info: Use INFO level for standard logging
• --warning: Switch to WARNING level for potential issues
• --error: Log ERROR level messages for serious problems
• --critical: Log CRITICAL level events for immediate attention

If no specific option is chosen, the default log level is set to INFO.