Comprehensive Guide to Log Writer APIs for Efficient Development

Introduction to Log Writer

The log-writer library is a powerful tool for logging system in various applications. Efficient logging is crucial for debugging, monitoring, and performance tracking in software development. In this guide, we introduce several essential APIs provided by log-writer along with code snippets to illustrate their usage.

Setting Up Log Writer

To get started with log-writer, you need to install the library:

pip install log-writer

Basic Usage

Here’s a simple example of initializing the logger and writing a basic log message:

 from log_writer import Logger
# Initialize logger logger = Logger('app.log')
# Write a log message logger.info('This is an informational message.') 

Advanced API Usage

Logging at Different Levels

The log-writer library supports various logging levels:

 logger.debug('This is a debug message.') logger.info('This is an informational message.') logger.warning('This is a warning message.') logger.error('This is an error message.') logger.critical('This is a critical message.') 

Configuring Log Format

Customize the format of your log entries:

 logger.set_format('%(asctime)s - %(levelname)s - %(message)s') 

Rotating Logs

Manage log file sizes by rotating logs:

 logger.enable_rotation(max_bytes=1024, backup_count=3) 

Adding Context to Logs

Include additional context in your logs:

 with logger.context(user='john_doe'):
    logger.info('User logged in.')

Application Example

Integrating the log-writer APIs in a simple application:

 import time from log_writer import Logger
# Setup logger logger = Logger('app.log') logger.set_format('%(asctime)s - %(levelname)s - %(message)s') logger.enable_rotation(max_bytes=1024, backup_count=3)
def simulate_work():
    logger.info('Starting work simulation.')
    for i in range(5):
        logger.debug(f'Iteration {i+1}')
        time.sleep(1)
    logger.info('Work simulation completed.')

if __name__ == "__main__":
    with logger.context(user='admin'):
        logger.info('Application started.')
        simulate_work()
        logger.info('Application finished.')

With these APIs, you can now effectively handle logging in your applications, ensuring better performance tracking and easier debugging.

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