#Starter logs code

You can learn more about all available tools and settings in the Logging Cookbook. Python logging library provides many tools and settings for handling different logging tasks. Or you can use filters to ask the logger to react differently to different events. As an example, you can send your logging results to a central URL address over HTTP by using the HTTP logging handler ( logging.HTTPHandler()). There are many advanced tools and settings that you can use in your logger. Now, you can imagine how hard it would be to replicate the same functionality with the print() statement. Finally, I started logging, and the logger managed both handlers properly. I repeated a similar process for the file handler. I added my console handler to the logger object. Then, I started creating my console handler and setting its level and format.

#Starter logs code

15:04:25,350 | CRITICAL | 25: OMG!!! A critical error happend and the code cannot run!ДЄs you see in the code, I simply created a logger object.

15:04:25,349 | ERROR | 24: Something unexpected and important happened. Relax! 15:04:25,349 | WARNING | 23: Something unexpected but not important happend. 15:04:25,350 | CRITICAL: OMG!!! A critical error happend and the code cannot run!Д«ut in your log file ( sample.log), you will see more detailed information. 15:04:25,349 | ERROR: Something unexpected and important happened. If you run this code, you will see the following output in the console.

There are twenty useful attributes that you can use based on your needs. Finally, we have the message attribute, which is simply the message we want to show. The levelname attribute outputs the logging level (DEBUG, INFO, etc.). The first attribute, asctime, shows the logging date and time. For example, in my formatting string, the attributes are asctime ( %(asctime)s), levelname ( %(levelname)s), and message ( %(message)s). The formatting string can include a mix of characters and attributes. 23:02:34,092 | CRITICAL: OMG!!! A critical error happend and the code cannot run!ДЄs you see, to format my logging messages, I need to pass a string to logging.basicConfig(). 23:02:34,092 | ERROR: Something unexpected and important happened. Relax! 23:02:34,090 | WARNING: Something unexpected but not important happend. 23:02:34,089 | DEBUG: Here you have some information for debugging. Note, I set the logging level to the lowest ( logging.NOTSET) to displays all messages.ДЄnd here is the output. Here is an example code to display different levels of logging messages. Again, remember that you can set your logging level using logging.basicConfig(). 30) which means, the logging module only displays/logs events with warning, error, or critical severity. The levels of logging from the lowest to the highest are NOTSET=0, DEBUG=10, INFO=20, WARNING=30, ERROR=40, and CRITICAL=50. 50 or constant logging.CRITICAL) and sets the logging level. logging.basicConfig(level=logging.CRITICAL)ДЄs you see the level argument in logging.basicConfig() takes an integer number (i.e. To set your logging level to CRITICAL, you can use logging.basicConfig(). If you set your logging level to CRITICAL, only logging messages of the CRITICAL level will be shown.

Critical ( logging.critical()): The code cannot run.Д«efore using these tools, letвЂ™s understand different levels of logging in Python.

Error ( logging.error()): The code was unable to run some parts.

Warning ( logging.warning()): Although the code is still working as expected, something unexpected happened.

Info ( ()): Tracking the normal operation of a program.

Debug ( bug()): Providing information to diagnosing problems.

The logging library provides you five tools to accomplish the logging tasks. Recording logging data inside a file or sending it over the internet needs additional works.ДЄ better way to track your code events and do debugging is using the вЂњLoggingвЂќ library (a Python standard library).

The print() statement only displays messages on the console.

Including additional logging information is not easy.

To define basic logging needs, several lines of code are needed.

The print() statement fails if your code does not have access to the console.

Why using print() for logging and debugging is not a good practice? Many of us (Python programmers and data scientists) have this bad habit of using print() to debug and track events in our codes. Logging is a popular solution for tracking events in a code or debugging.