An Intro to Logging with Python and Loguru

Python’s logging module isn’t the only way to create logs. There are several third-party packages you can use, too. One of the most popular is Loguru. Loguru intends to remove all the boilerplate you get with the Python logging API.

You will find that Loguru greatly simplifies creating logs in Python.

This chapter has the following sections:

• Installation
• Logging made simple
• Handlers and formatting
• Catching exceptions
• Terminal logging with color
• Easy log rotation

Let’s find out how much easier Loguru makes logging in Python!

Before you can start with Loguru, you will need to install it. After all, the Loguru package doesn’t come with Python.

Fortunately, installing Loguru is easy with pip. Open up your terminal and run the following command:

python -m pip install loguru

Pip will install Loguru and any dependencies it might have for you. You will have a working package installed if you see no errors.

Now let’s start logging!

Logging with Loguru can be done in two lines of code. Loguru is really that simple!

Don’t believe it? Then open up your Python IDE or REPL and add the following code:

# hello.py

from loguru import logger

logger.debug("Hello from loguru!")
logger.info("Informed from loguru!")

One import is all you need. Then, you can immediately start logging! By default, the log will go to stdout.

Here’s what the output looks like in the terminal:

2024-05-07 14:34:28.663 | DEBUG    | __main__:<module>:5 - Hello from loguru!
2024-05-07 14:34:28.664 | INFO     | __main__:<module>:6 - Informed from loguru!

Pretty neat! Now, let’s find out how to change the handler and add formatting to your output.

Loguru doesn’t think of handlers the way the Python logging module does. Instead, you use the concept of sinks. The sink tells Loguru how to handle an incoming log message and write it somewhere.

Sinks can take lots of different forms:

• A file-like object, such as sys.stderr or a file handle
• A file path as a string or pathlib.Path
• A callable, such as a simple function
• An asynchronous coroutine function that you define using async def
• A built-in logging.Handler. If you use these, the Loguru records convert to logging records automatically

To see how this works, create a new file called file_formatting.py in your Python IDE. Then add the following code:

# file_formatting.py

from loguru import logger

fmt = "{time} - {name} - {level} - {message}"

logger.add("formatted.log", format=fmt, level="INFO")
logger.debug("This is a debug message")
logger.info("This is an informational message")

If you want to change where the logs go, use the add() method. Note that this adds a new sink, which, in this case, is a file. The logger will still log to stdout, too, as that is the default, and you are adding to the handler list. If you want to remove the default sink, add logger.remove() before you call add().

When you call add(), you can pass in several different arguments:

• sink – Where to send the log messages
• level – The logging level
• format – How to format the log messages
• filter – A logging filter

There are several more, but those are the ones you would use the most. If you want to know more about add(), you should check out the documentation.

You might have noticed that the formatting of the log records is a little different than what you saw in Python’s own logging module.

Here is a listing of the formatting directives you can use for Loguru:

• elapsed – The time elapsed since the app started
• exception – The formatted exception, if there was one
• extra – The dict of attributes that the user bound
• file – The name of the file where the logging call came from
• function – The function where the logging call came from
• level – The logging level
• line – The line number in the source code
• message – The unformatted logged message
• module – The module that the logging call was made from
• name – The __name__ where the logging call came from
• process – The process in which the logging call was made
• thread – The thread in which the logging call was made
• time – The aware local time when the logging call was made

You can also change the time formatting in the logs. In this case, you would use a subset of the formatting from the Pendulum package. For example, if you wanted to make the time exclude the date, you would use this: {time:HH:mm:ss} rather than simply {time}, which you see in the code example above.

See the documentation for details on formating time and messages.

When you run the code example, you will see something similar to the following in your log file:

2024-05-07T14:35:06.553342-0500 - __main__ - INFO - This is an informational message

You will also see log messages sent to your terminal in the same format as you saw in the first code example.

Now, you’re ready to move on and learn about catching exceptions with Loguru.

Catching exceptions with Loguru is done by using a decorator. You may remember that when you use Python’s own logging module, you use logger.exception in the except portion of a try/except statement to record the exception’s traceback to your log file.

When you use Loguru, you use the @logger.catch decorator on the function that contains code that may raise an exception.

Open up your Python IDE and create a new file named catching_exceptions.py. Then enter the following code:

# catching_exceptions.py

from loguru import logger

@logger.catch
def silly_function(x, y, z):
    return 1 / (x + y + z)

def main():
    fmt = "{time:HH:mm:ss} - {name} - {level} - {message}"
    logger.add("exception.log", format=fmt, level="INFO")
    logger.info("Application starting")
    silly_function(0, 0, 0)
    logger.info("Finished!")

if __name__ == "__main__":
    main()

According to Loguru’s documentation, the’ @logger.catch` decorator will catch regular exceptions and also work with applications with multiple threads. Add another file handler on top of the stream handler and start logging for this example.

Then you call silly_function() with a bunch of zeroes, which causes a ZeroDivisionError exception.

Here’s the output from the terminal:

If you open up the exception.log, you will see that the contents are a little different because you formatted the timestamp and also because logging those funny lines that show what arguments were passed to the silly_function() don’t translate that well:

14:38:30 - __main__ - INFO - Application starting
14:38:30 - __main__ - ERROR - An error has been caught in function 'main', process 'MainProcess' (8920), thread 'MainThread' (22316):
Traceback (most recent call last):

  File "C:\books\11_loguru\catching_exceptions.py", line 17, in <module>
    main()
    â”” <function main at 0x00000253B01AB7E0>

> File "C:\books\11_loguru\catching_exceptions.py", line 13, in main
    silly_function(0, 0, 0)
    â”” <function silly_function at 0x00000253ADE6D440>

  File "C:\books\11_loguru\catching_exceptions.py", line 7, in silly_function
    return 1 / (x + y + z)
                │   │   └ 0
                │   └ 0
                â”” 0

ZeroDivisionError: division by zero
14:38:30 - __main__ - INFO - Finished!

On the whole, using the @logger.catch is a nice way to catch exceptions.

Now, you’re ready to move on and learn about changing the color of your logs in the terminal.

Loguru will print out logs in color in the terminal by default if the terminal supports color. Colorful logs can make reading through the logs easier as you can highlight warnings and exceptions with unique colors.

You can use markup tags to add specific colors to any formatter string. You can also apply bold and underline to the tags.

Open up your Python IDE and create a new file called terminal_formatting.py. After saving the file, enter the following code into it:

# terminal_formatting.py
import sys
from loguru import logger

fmt = ("<red>{time}</red> - "
       "<yellow>{name}</yellow> - "
       "{level} - {message}")

logger.add(sys.stdout, format=fmt, level="DEBUG")
logger.debug("This is a debug message")
logger.info("This is an informational message")

You create a special format that sets the “time” portion to red and the “name” to yellow. Then, you add() that format to the logger. You will now have two sinks: the default root handler, which logs to stderr, and the new sink, which logs to stdout. You do formatting to compare the default colors to your custom ones.

Go ahead and run the code. You should see something like this:

Neat! It would be best if you now spent a few moments studying the documentation and trying out some of the other colors. For example, you can use hex and RGB colors and a handful of named colors.

The last section you will look at is how to do log rotation with Loguru!

Loguru makes log rotation easy. You don’t need to import any special handlers. Instead, you only need to specify the rotation argument when you call add().

Here are a few examples:

• logger.add("file.log", rotation="100 MB")
• logger.add("file.log", rotation="12:00")
• logger.add("file.log", rotation="1 week")

These demonstrate that you can set the rotation at 100 megabytes at noon daily or even rotate weekly.

Open up your Python IDE so you can create a full-fledged example. Name the file log_rotation.py and add the following code:

# log_rotation.py

from loguru import logger

fmt = "{time} - {name} - {level} - {message}"

logger.add("rotated.log",
           format=fmt,
           level="DEBUG",
           rotation="50 B")
logger.debug("This is a debug message")
logger.info("This is an informational message")

Here, you set up a log format, set the level to DEBUG, and set the rotation to every 50 bytes. When you run this code, you will get a couple of log files. Loguru will add a timestamp to the file’s name when it rotates the log.

What if you want to add compression? You don’t need to override the rotator like you did with Python’s logging module. Instead, you can turn on compression using the compression argument.

Create a new Python script called log_rotation_compression.py and add this code for a fully working example:

# log_rotation_compression.py

from loguru import logger

fmt = "{time} - {name} - {level} - {message}"

logger.add("compressed.log",
           format=fmt,
           level="DEBUG",
           rotation="50 B",
           compression="zip")
logger.debug("This is a debug message")
logger.info("This is an informational message")
for i in range(10):
    logger.info(f"Log message {i}")

The new file is automatically compressed in the zip format when the log rotates. There is also a retention argument that you can use with add() to tell Loguru to clean the logs after so many days:

logger.add("file.log",
             rotation="100 MB",
             retention="5 days")

If you were to add this code, the logs that were more than five days old would get cleaned up automatically by Loguru!

The Loguru package makes logging much easier than Python’s logging library. It removes the boilerplate needed to create and format logs.

In this chapter, you learned about the following:

• Installation
• Logging made simple
• Handlers and formatting
• Catching exceptions
• Terminal logging with color
• Easy log rotation

Loguru can do much more than what is covered here, though. You can serialize your logs to JSON or contextualize your logger messages. Loguru also allows you to add lazy evaluation to your logs to prevent them from affecting performance in production. Loguru also makes adding custom log levels very easy. For full details about all the things Loguru can do, you should consult Loguru’s website.

The post An Intro to Logging with Python and Loguru appeared first on Mouse Vs Python.

Find A Teacher Form:
https://docs.google.com/forms/d/1vREBnX5n262umf4wU5U2pyTwvk9O-JrAgblA-wH9GFQ/viewform?edit_requested=true#responses

Email:
public1989two@gmail.com






www.itsec.hk
www.itsec.vip
www.itseceu.uk