When to Use the Logger Class? Debugging and Troubleshooting: Detailed and customizable logs simplify identifying and rectifying issues in complex applications.
Monitoring and Analysis: Logging is essential for monitoring behavior, identifying performance bottlenecks, and analyzing usage patterns in production environments.
Security and Compliance: Comprehensive logging is vital for auditing and security analysis in applications handling sensitive information or needing to adhere to specific compliance requirements. Debugging and Troubleshooting: Detailed and customizable logs simplify identifying and rectifying issues in complex applications. Debugging and Troubleshooting Monitoring and Analysis: Logging is essential for monitoring behavior, identifying performance bottlenecks, and analyzing usage patterns in production environments. Monitoring and Analysis Security and Compliance: Comprehensive logging is vital for auditing and security analysis in applications handling sensitive information or needing to adhere to specific compliance requirements. Security and Compliance How to Use the Logger Class? Save the following code in a file named Logger.py, and then open another Python file main.py in the same root directory and use from Logger import Logger to import the package. Logger.py Python main.py from Logger import Logger Logger.py import logging
from logging import handlers

class Logger(object):
    level_relations = {
        'debug': logging.DEBUG,
        'info': logging.INFO,
        'warning': logging.WARNING,
        'error': logging.ERROR,
        'crit': logging.CRITICAL
    }  # relationship mapping

    def __init__(self, filename, level='info', when='D', backCount=3,
                 fmt='%(asctime)s - %(pathname)s[line:%(lineno)d] - %(levelname)s: %(message)s'):
        self.logger = logging.getLogger(filename)
        format_str = logging.Formatter(fmt)  # Setting the log format
        self.logger.setLevel(self.level_relations.get(level))  # Setting the log level
        console_handler = logging.StreamHandler()  # on-screen output
        console_handler .setFormatter(format_str)  # Setting the format
        th = handlers.TimedRotatingFileHandler(filename=filename, when=when, backupCount=backCount,encoding='utf-8')  # automatically generates the file at specified intervals
        th.setFormatter(format_str)  # Setting the format
        self.logger.addHandler(sh)  # Add the object to the logger
        self.logger.addHandler(th) import logging
from logging import handlers

class Logger(object):
    level_relations = {
        'debug': logging.DEBUG,
        'info': logging.INFO,
        'warning': logging.WARNING,
        'error': logging.ERROR,
        'crit': logging.CRITICAL
    }  # relationship mapping

    def __init__(self, filename, level='info', when='D', backCount=3,
                 fmt='%(asctime)s - %(pathname)s[line:%(lineno)d] - %(levelname)s: %(message)s'):
        self.logger = logging.getLogger(filename)
        format_str = logging.Formatter(fmt)  # Setting the log format
        self.logger.setLevel(self.level_relations.get(level))  # Setting the log level
        console_handler = logging.StreamHandler()  # on-screen output
        console_handler .setFormatter(format_str)  # Setting the format
        th = handlers.TimedRotatingFileHandler(filename=filename, when=when, backupCount=backCount,encoding='utf-8')  # automatically generates the file at specified intervals
        th.setFormatter(format_str)  # Setting the format
        self.logger.addHandler(sh)  # Add the object to the logger
        self.logger.addHandler(th) This code defines a custom Logger class that can be used to create and configure loggers in Python. The Logger class is initialized with several parameters:

filename: The name of the log file where the logs will be saved.
level: The logging level, which determines the severity of the messages to be logged (e.g., 'debug', 'info', 'warning', 'error', 'crit').
when: The interval at which the log files should be rotated (e.g., 'S' for seconds, 'M' for minutes, 'H' for hours, 'D' for days, 'W' for weeks).
backCount: The number of backup log files to retain.
fmt: The format of the log messages, which includes the time, file path, line number, log level, and the log message itself.


Inside the __init__ method, the logger is configured as follows:

The logging level is set based on the provided level.
A format string is created for formatting the log messages.
A console handler is created for logging messages to the console.
A rotating file handler is created for logging messages to the specified log file.


Finally, the logger is set up to use both the console handler and the rotating file handler for logging messages. The Logger class is initialized with several parameters:

filename: The name of the log file where the logs will be saved.
level: The logging level, which determines the severity of the messages to be logged (e.g., 'debug', 'info', 'warning', 'error', 'crit').
when: The interval at which the log files should be rotated (e.g., 'S' for seconds, 'M' for minutes, 'H' for hours, 'D' for days, 'W' for weeks).
backCount: The number of backup log files to retain.
fmt: The format of the log messages, which includes the time, file path, line number, log level, and the log message itself. Logger filename: The name of the log file where the logs will be saved.
level: The logging level, which determines the severity of the messages to be logged (e.g., 'debug', 'info', 'warning', 'error', 'crit').
when: The interval at which the log files should be rotated (e.g., 'S' for seconds, 'M' for minutes, 'H' for hours, 'D' for days, 'W' for weeks).
backCount: The number of backup log files to retain.
fmt: The format of the log messages, which includes the time, file path, line number, log level, and the log message itself. filename: The name of the log file where the logs will be saved. filename level: The logging level, which determines the severity of the messages to be logged (e.g., 'debug', 'info', 'warning', 'error', 'crit'). level when: The interval at which the log files should be rotated (e.g., 'S' for seconds, 'M' for minutes, 'H' for hours, 'D' for days, 'W' for weeks). when backCount: The number of backup log files to retain. backCount fmt: The format of the log messages, which includes the time, file path, line number, log level, and the log message itself. fmt Inside the __init__ method, the logger is configured as follows:

The logging level is set based on the provided level.
A format string is created for formatting the log messages.
A console handler is created for logging messages to the console.
A rotating file handler is created for logging messages to the specified log file. __init__ The logging level is set based on the provided level.
A format string is created for formatting the log messages.
A console handler is created for logging messages to the console.
A rotating file handler is created for logging messages to the specified log file. The logging level is set based on the provided level. level A format string is created for formatting the log messages. A console handler is created for logging messages to the console. A rotating file handler is created for logging messages to the specified log file. Finally, the logger is set up to use both the console handler and the rotating file handler for logging messages. main.py from Logger import Logger

log = Logger('log\\all.log', level='debug')
log_error = Logger('log\\all.log', level='debug')

log.logger.info("This is an info message)")
log_error.info("This is an error message") from Logger import Logger

log = Logger('log\\all.log', level='debug')
log_error = Logger('log\\all.log', level='debug')

log.logger.info("This is an info message)")
log_error.info("This is an error message") This Python code shows how to use the Logger package to write log information to a file. It first initializes two Logger objects, one for general logging and one for error logging. It then uses these objects to write log messages at different levels, such as info and error. The log messages are written to the specified log file, allowing for easy monitoring and troubleshooting of the application. Customizing Parameters The Logger class provides several parameters that can be customized based on the specific logging needs. These parameters include: filename: The name of the log file where the logs will be written.
level: The log level, which determines the severity of the logs (e.g., debug, info, warning, error, crit).
when: The frequency at which the log files should be rotated (e.g., 'D' for daily, 'H' for hourly).
backCount: The number of backup log files to retain after rotation.
fmt: The format of the log messages, allowing customization of the timestamp, log level, file name, line number, and message content. filename: The name of the log file where the logs will be written. filename level: The log level, which determines the severity of the logs (e.g., debug, info, warning, error, crit). level when: The frequency at which the log files should be rotated (e.g., 'D' for daily, 'H' for hourly). when backCount: The number of backup log files to retain after rotation. backCount fmt: The format of the log messages, allowing customization of the timestamp, log level, file name, line number, and message content. fmt By adjusting these parameters, the Logger class can be tailored to meet the specific logging requirements of different projects and applications. Example 1: Customizing Log Level and Format log = Logger('custom.log', level='warning', fmt='%(asctime)s - %(levelname)s - %(message)s')
log.logger.debug("This is a debug message - won't be logged")
log.logger.warning("This is a warning message - will be logged") log = Logger('custom.log', level='warning', fmt='%(asctime)s - %(levelname)s - %(message)s')
log.logger.debug("This is a debug message - won't be logged")
log.logger.warning("This is a warning message - will be logged") Example 2: Specifying Log Rotation Parameters log = Logger('rotation.log', when='midnight', backCount=7)
log.logger.info("Logging with rotation based on time") log = Logger('rotation.log', when='midnight', backCount=7)
log.logger.info("Logging with rotation based on time") Conclusion Logging is crucial in software development for monitoring, troubleshooting, analyzing, and securing applications. Python's logging class offers a convenient and customizable way to implement logging with various configuration options. This class enables developers to tailor logging setups to meet project needs, ensuring comprehensive and efficient logging for debugging, monitoring, and compliance purposes. The Logger class empowers developers to harness the power of logging for robust application development and maintenance. Happy logging!

Walkthroughs, tutorials, guides, and tips. This story will teach you how to do something new or how to do something better.

Python Logging: Debugging, Monitoring, and Security with the Logger Class

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

A Quick Guide to Listing All Measures in Power BI via DAX Studio

10 Top Industries To Be Transformed By Artificial Intelligence, Soon

10 Essential Mobile App UI Design Principles for Building Outstanding Apps

11 AI & ML App Ideas For Startups and SME’s In 2019

11 Best Low-Code And No-Code Platforms in 2021

11 Tips to Save Time on App Development & Launch Processes

A Quick Guide to Listing All Measures in Power BI via DAX Studio

10 Top Industries To Be Transformed By Artificial Intelligence, Soon

10 Essential Mobile App UI Design Principles for Building Outstanding Apps

11 AI & ML App Ideas For Startups and SME’s In 2019

11 Best Low-Code And No-Code Platforms in 2021

11 Tips to Save Time on App Development & Launch Processes

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps