Python provides a logging system as a part of its standard library, so you can quickly add logging to your application. By logging useful data from the right places, you can not only debug errors easily but also use the data to analyze the performance of the application to plan for scaling or look at usage patterns to plan for marketing. Logs provide developers with an extra set of eyes that are constantly looking at the flow that an application is going through. They can store information, like which user or IP accessed the application. If an error occurs, then they can provide more insights than a stack trace by telling you what the state of the program was before it arrived at the line of code where the error occurred. In this session, we have explained basic logging, levels of logging, the use of creating custom loggers, and logging logs into the file.