Python’s logging module basics - IPCS Automation
Because the logging module is part of Python's standard library, you can use it right away without having to install anything. The basic config() method of the logging module is the quickest approach to set up your logger's desired behavior.However, the Python documentation suggests that you create a logger for each module in your application, and configuring a logger-per-module configuration with basic config() alone can be challenging. As a result, most applications (including web frameworks like Django) default to using a file- or dictionary-based logging setup. We recommend jumping through to that section if you want to get started with one of those approaches.
Three of the main parameters of basicConfig() are:
level:
the lowest level of priority for messages to be logged The accessible log levels are DEBUG, INFO, WARNING, ERROR, and CRITICAL, in order of increasing severity. The level is set to WARNING by default, which means that any DEBUG or INFO messages will be filtered out by Python's logging module.
2.handler:
decides how your logs will be routed. Unless you specify otherwise, the logging library will send log messages to sys. stderr via a StreamHandler (usually the console).
3.format:
Messages are logged in the following format by default in the logging library: LEVEL>:LOGGER NAME>:MESSAGE>. We'll teach you how to adjust this to include timestamps and other troubleshooting information in the following section.
Because the logging module by default only records WARNING and higher-level messages, you may be missing out on lower-priority logs that are useful for root cause analysis. Instead of adding logs to a file, the logging module feeds them to the console. You should use a FileHandler to log to one or more files on a disc rather than a StreamHandler or a SocketHandler to stream logs directly to the console or to an external service over the network.
One of the biggest advantages of logging into a file is that it eliminates the need for your program to account for the possibility of network-related failures when streaming logs to an external destination. Because the logs are saved locally on each server, you won't lose access to them if there are any issues with streaming logs across the network. Logging to a file also enables you to establish a more personalised logging system, in which you can route different sorts of data to different files, then tail and consolidate those files using a log monitoring service.
We'll show you how to tweak basic config() to log lower-priority messages and send them to a file on disk in the next section.IPCS Automation offers the best python course in mumbai.
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