python logging module tutorial

logging is an essential part of software development, allowing developers to record important information about the execution of their programs. python provides a built-in logging module that makes it easy to incorporate logging into your applications. in this tutorial, we'll explore the python logging module and walk through various features and examples.
to use the logging module, you need to import it and configure it appropriately. here's a basic setup:
in the example above, we set the logging level to debug, which means all log messages will be captured. the basicconfig function is used to configure the logging system with a basic configuration.
the logging module supports different logging levels, including debug, info, warning, error, and critical. you can set the logging level to control which messages are captured.
in this example, only messages with info level and above will be captured.
you can log messages to a file by specifying the filename parameter in the basicconfig function.
you can customize the format of log messages using the format parameter. the format string can include placeholders for various log record attributes.
in this example, we added the %(name)s placeholder to include the logger name in the log messages.
when working with multiple modules, it's a good practice to create a logger for each module. this allows you to control the logging level and format for each module independently.
logging is an essential part of any software development process. it allows developers to record and monitor the activities of a program, aiding in debugging and troubleshooting. python comes with a built-in logging module that provides a flexible and customizable way to manage logs. in this tutorial, we'll explore the python logging module, its features, and how to use it effectively with code examples.
let's start with the basics. the logging module provides a simple way to log messages:
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