How to Use Log4j With the Help of Logging Library in Python

1. Overview of Log4j and Its Importance to Use
2. Use Log4j With the Help of logging Library in Python

This article explains what is log4j and, how it works and why we should use it. We’ll also see how to use log4j inside the Python programming language with the help of the logging library.

Overview of Log4j and Its Importance to Use

The log4j is a piece of software leveraged by programmers to help them when they are logging data in their application. And, logging data means keeping a diary of the activities or actions performed in the application.

We can use log4j for security reasons, like looking at the various authentications. But, it could also be for keeping a record of things that have happened in the application for debugging purposes.

Or to generally know what the application has been doing. For example, the log4j is a framework in the Java programming language that is a semi-build application.

Similarly, in Python, we used a logging module instead of log4j. logging is a process of recording application actions and states to a secondary interface. In other words, write your program actions to a file, but how do you start logging?

Well, you need to get acquainted with logging levels. Every logging library allows you to lock information on a certain level. There are five primary logging levels that you must know.

Use Log4j With the Help of logging Library in Python

Now we are just going to run a simple basic code, and there is no such logic, but we want to show you some understanding, like how you can write all the logs inside a file.

Let’s jump into the code and first configure the logging system, call the basicConfig() method, and pass in a file name using the filename parameter. Python will write all the log messages to this file; if it does not exist, Python will create it.

The following parameter is filemode, which means file mode means whether it is an append mode to write mode or whatever you put there, and by default, the file will be created in append mode. The next one is the format that represents a lot of information such as asctime, levelname, and message.

asctime basically shows what kind of time it is printing inside this particular text file concerning the logs. The second parameter value is something called levelname; this parameter shows us what kind of error occurred during the execution.

The message is all the messages we are trying to print inside that log message. We are using datefmt; this parameter will get printed the time in a specific order.

The basicConfig() function has a different attribute, we can read about all attributes from here.

import logging

logging.basicConfig(
    filename="demo.txt",
    filemode="a",
    format="%(asctime)s %(levelname)s-%(message)s",
    datefmt="%Y-%m-%d %H:%M:%S",
)

Now we have written a simple logic where we compare the percentile with some numbers and append some logs inside the text file.

for i in range(0, 15):
    if i % 2 == 0:
        logging.error("Log error message")
    elif i % 3 == 0:
        logging.warning("Log warning message")
    elif i % 5 == 0:
        logging.debug("Log debug message")
    elif i % 7 == 0:
        logging.critical("Log critical message")
    else:
        logging.info("Log info message")

Output:

2022-09-01 23:21:28 ERROR-Log error message
2022-09-01 23:21:28 ERROR-Log error message
2022-09-01 23:21:28 WARNING-Log warning message
2022-09-01 23:21:28 ERROR-Log error message
2022-09-01 23:21:28 ERROR-Log error message
2022-09-01 23:21:28 CRITICAL-Log critical message
2022-09-01 23:21:28 ERROR-Log error message
2022-09-01 23:21:28 WARNING-Log warning message
2022-09-01 23:21:28 ERROR-Log error message
2022-09-01 23:21:28 ERROR-Log error message
2022-09-01 23:21:28 ERROR-Log error message

After running the program, we can notice the info and debug log are not added inside the text file because, by default, levelname calls error and error levels do not show info and debug.

However, we can use other levels by using the level parameter while passing logging.DEBUG.

level = logging.DEBUG

Now, if we run and open the demo.txt file, we will see all log messages, but if we update the log level to logging.ERROR, we see the error and critical messages.

2022-09-01 23:23:57 ERROR-Log error message
2022-09-01 23:23:57 INFO-Log info message
2022-09-01 23:23:57 ERROR-Log error message
2022-09-01 23:23:57 WARNING-Log warning message
2022-09-01 23:23:57 ERROR-Log error message
2022-09-01 23:23:57 DEBUG-Log debug message
2022-09-01 23:23:57 ERROR-Log error message
2022-09-01 23:23:57 CRITICAL-Log critical message
2022-09-01 23:23:57 ERROR-Log error message
2022-09-01 23:23:57 WARNING-Log warning message
2022-09-01 23:23:57 ERROR-Log error message
2022-09-01 23:23:57 INFO-Log info message
2022-09-01 23:23:57 ERROR-Log error message
2022-09-01 23:23:57 INFO-Log info message
2022-09-01 23:23:57 ERROR-Log error message

Let’s take a common problem where we are going to divide any number by zero. To determine this operation, we will use the try block.

If the operation gets failed, we will go inside the except block and display the log error.

try:
    1 / 0
except:
    logging.error("Log zero division error occurs")

Output:

2022-09-02 00:29:48 ERROR-Log zero division error occurs

It is an essential part of a project because you probably have to write this kind of logging mechanism whenever you are working on a project.

Complete Python Code:

import logging

logging.basicConfig(
    filename="demo.txt",
    filemode="w",
    format="%(asctime)s %(levelname)s-%(message)s",
    datefmt="%Y-%m-%d %H:%M:%S",
    level=logging.DEBUG,
)

# for i in range(0,15):
#     if i%2==0:
#         logging.error('Log error message')
#     elif i%3==0:
#         logging.warning('Log warning message')
#     elif i%5==0:
#         logging.debug('Log debug message')
#     elif i%7==0:
#         logging.critical('Log critical message')
#     else:
#         logging.info('Log info message')

try:
    1 / 0
except:
    logging.error("Log zero division error occurs")