Introduction to EventLogger

EventLogger is a powerful logging library that allows developers to efficiently track events, errors, and other crucial metrics within their applications. This comprehensive guide will introduce you to the core functionalities of EventLogger and provide useful API explanations with illustrative code snippets.

Basic Usage

The following example demonstrates the basic usage of EventLogger for logging a simple message.

  
    import eventlogger

    logger = eventlogger.get_logger("my_app")
    logger.info("This is an informational message")
  

Configuring EventLogger

To configure EventLogger, you can set various parameters such as log level, output format, and destination.

  
    import eventlogger

    config = {
      "log_level": "DEBUG",
      "format": "%(asctime)s - %(name)s - %(levelname)s - %(message)s",
      "destination": "file",
      "file_name": "app.log"
    }
    eventlogger.configure(config)
  

Logging Different Severity Levels

EventLogger allows logging messages at different severity levels such as DEBUG, INFO, WARNING, ERROR, and CRITICAL.

  
    import eventlogger

    logger = eventlogger.get_logger("my_app")

    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")
  

Adding Custom Fields

You can add custom fields to your log messages for additional context.

  
    import eventlogger

    logger = eventlogger.get_logger("my_app")

    logger.info("User login", user="john_doe", action="login")
  

Exception Logging

EventLogger provides a convenient way to log exceptions along with stack trace information.

  
    import eventlogger

    logger = eventlogger.get_logger("my_app")

    try:
      1 / 0
    except ZeroDivisionError as e:
      logger.exception("An exception occurred: %s", e)
  

Performance Metrics Logging

EventLogger can be used to log performance metrics, which is crucial for profiling and optimizing your application.

  
    import eventlogger
    import time

    logger = eventlogger.get_logger("performance")

    start_time = time.time()
    # Perform some operations
    end_time = time.time()

    elapsed_time = end_time - start_time
    logger.info("Operation completed", duration=elapsed_time)
  

Building an Application with EventLogger

Below is a simple application that utilizes various EventLogger APIs. This example showcases how different logging functionalities can be integrated into a real-world application.

  
    import eventlogger
    import time

    def configure_logging():
      config = {
        "log_level": "INFO",
        "format": "%(asctime)s - %(name)s - %(levelname)s - %(message)s",
        "destination": "file",
        "file_name": "app.log"
      }
      eventlogger.configure(config)

    def perform_complex_operation():
      logger = eventlogger.get_logger("operation")
      try:
        logger.info("Starting complex operation")
        start_time = time.time()

        # Simulate operation
        time.sleep(2)
        result = 1 / 0  # This will cause an exception

        end_time = time.time()
        logger.info("Completed complex operation", duration=end_time - start_time)
        return result
      except Exception as e:
        logger.exception("An error occurred during complex operation: %s", e)
        raise

    if __name__ == "__main__":
      configure_logging()
      logger = eventlogger.get_logger("main")
      logger.info("Application started")

      try:
        perform_complex_operation()
      except Exception:
        logger.error("Complex operation failed")

      logger.info("Application finished")
  

By leveraging the EventLogger library, developers can significantly enhance the maintainability and robustness of their applications, making it easier to diagnose issues and track important events.

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