Python logging formats: How to collect and centralize Python logs

Python's built-in logging module is designed to give critical visibility into applications with minimal setup. The main parameters of `basicConfig()` are level, handler, and format, which can be customized to suit specific needs. Logging to a file allows for more customization and routing options, making it easier to troubleshoot issues. Customizing log levels, handlers, and formats can help capture lower-priority logs and exceptions, providing deeper insights into application performance and errors. The logging module also supports JSON formatting, which is easily parseable by external log management services. By centralizing logs with a service like Datadog, developers can explore them alongside distributed request traces and infrastructure metrics to get a full picture of their applications' performance and behavior.