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Move logging code out of your business logic with decorators

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Move logging code out of your business logic with python decorators.

Logging is a nice tool in your toolbox for tracing bugs and getting a better sense how your application is working in production. But if you are like me, you often omit logging code, so it will not hide business logic or feature your code with complexity.

Fortunately pythons decorator now came to our rescue and provides us with a nice library to add logging to our code without stealing readability and understandability.

If you want to know more about the intentions behind logdecorator check out my blog post.

Update: logdecorator==2.0

Thanks to all dependants :) I just released a new version of logdecorator (2.0). You can read the changes at my blog or in the changelog.

Installation

Installation is as easy as it can get:

$ pip install logdecorator

How to use it

tl;dr

import logging
import requests
from logdecorator import log_on_start, log_on_end, log_on_error, log_exception


@log_on_start(logging.DEBUG, "Start downloading {url:s}...")
@log_on_error(logging.ERROR, "Error on downloading {url:s}: {e!r}",
              on_exceptions=IOError,
              reraise=True)
@log_on_end(logging.DEBUG, "Downloading {url:s} finished successfully within {result.elapsed!s}")
def download(url):
    # some code
    response = requests.get(url)
    # some more code
    return response


logging.basicConfig(level=logging.DEBUG)

download("https://www.sighalt.de")
# DEBUG:__main__:Start downloading https://www.sighalt.de...
# DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): www.sighalt.de
# DEBUG:urllib3.connectionpool:https://www.sighalt.de:443 "GET / HTTP/1.1" 200 None
# DEBUG:__main__:Downloading https://www.sighalt.de finished successfully within 0:00:00.130960

download("https://www.sighalt.der")
# DEBUG:__main__:Start downloading https://www.sighalt.der...
# DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): www.sighalt.der
# ERROR:__main__:Error on downloading https://www.sighalt.der: ConnectionError(MaxRetryError("
# HTTPSConnectionPool(host='www.sighalt.der', port=443): Max retries exceeded with url: /
# (Caused by NewConnectionError('<urllib3.connection.VerifiedHTTPSConnection object at 0x7fe3fc4b5320>:
# Failed to establish a new connection: [Errno -2] Name or service not known',))",),)

Long story

Imagine a function download with no arguments and some download code in it.

def download():
    # some download code
    pass

if __name__ == "__main__":
    download()

Say you are going to launch your new tool but want to add some logging before releasing the kraken. Your code will probably look something like the following:

import logging
from .exceptions import MyException1, MyException2

logger = logging.getLogger(__name__)


def download():
    logger.debug("Start downloading")
    # some download code
    logger.debug("Downloading finished successfully")


if __name__ == "__main__":
    try:
        download()
    except (MyException1, MyException2):
        logger.error("Error on downloading")
        raise

You just added at least a couple lines of code which are eventually stumbling in your way when you are trying to understand your business logic to find a bug. But what’s even worse is, that you added an additional indentation (try:… except: …) just for the sake of logging.

With logdecorator you can leave your code nearly as it was and reach the same goals.

import logging
from logdecorator import log_on_start, log_on_end, log_on_error
from .exceptions import MyException1, MyException2


@log_on_start(logging.DEBUG, "Start downloading")
@log_on_error(logging.ERROR, "Error on downloading",
              on_exceptions=(MyException1, MyException2),
              reraise=True)
@log_on_end(logging.DEBUG, "Downloading finished successfully")
def download():
    # some download code


if __name__ == "__main__":
    download()

Maybe the improvement to the previous snippet does not seem great for you but if you actually fill in business logic into # some download code it should become obvious :)

What logdecorator can do for you

Decorators

logdecorator provides four different built-in decorators:

  • log_on_start
  • log_on_end
  • log_on_error
  • log_exception

whose behaviour corresponds to their names.

Additionally logdecorator supports decorating async callables with the decorators:

  • async_log_on_start
  • async_log_on_end
  • async_log_on_error
  • async_log_exception

These decorators are found at logdecorator.asyncio

Use variables in messages

The message, given to the decorator, is treated as a python format string which takes the functions arguments as format arguments.

Sticking to the previous example one could write:

import logging
from logdecorator import log_on_start
from .exceptions import MyException1, MyException2


@log_on_start(logging.DEBUG, "Start downloading '{url:s}'")
def download(url):
    # some download code


if __name__ == "__main__":
    download("http://my.file.com/file.bin")

Which results in the message Start downloading 'http://my.file.com/file.bin' gets logged.

Documentation

log_on_start / async_log_on_start

Argument required? Description
log_level yes The log level at which the message should be send
message yes The message to log
logger no An alternative logger object. If no logger is given logdecorator creates a logger object with the name of the module the decorated function is in (decorated_function.__module__) Default: Creates a new logger with the name decorated_function.__module__

log_on_end / async_log_on_end

Argument required? Description
log_level yes The log level at which the message should be send
message yes The message to log
logger no An alternative logger object. If no logger is given logdecorator creates a logger object with the name of the module the decorated function is in (decorated_function.__module__) Default: Creates a new logger with the name decorated_function.__module__
result_format_variable no The variable name one can use in the message to reference the result of the > decorated function e.g. @log_on_end(DEBUG, “Result was: {result!r}”) Default: “result”

log_on_error / async_log_on_error

Argument required? Description
log_level yes The log level at which the message should be send
message yes The message to log
logger no An alternative logger object. If no logger is given logdecorator creates a logger object with the name of the module the decorated function is in (decorated_function.__module__) Default: Creates a new logger with the name decorated_function.__module__
on_exceptions no A tuple containing exception classes or a single exception, which should get caught and trigger the logging of the log_on_error decorator. Default: tuple() (No exceptions will get caught)
reraise no Controls if caught exceptions should get reraised after logging. Default: True
exception_format_variable no The variable name one can use in the message to reference the caught exception raised in the decorated function > e.g. @log_on_error(ERROR, “Error was: {e!r}”, …) Default: “e”

log_exception / async_log_exception

Argument required? Description
log_level yes The log level at which the message should be send
message yes The message to log
logger no An alternative logger object. If no logger is given logdecorator creates a logger object with the name of the module the decorated function is in (decorated_function.__module__) Default: Creates a new logger with the name decorated_function.__module__
on_exceptions no A tuple containing exception classes or a single exception, which should get caught and trigger the logging of the log_on_error decorator. Default: tuple() (No exceptions will get caught)
reraise no Controls if caught exceptions should get reraised after logging. Default: False
exception_format_variable no The variable name one can use in the message to reference the caught exception raised in the decorated function e.g. @log_on_error(ERROR, “Error was: {e!r}”, …) Default: “e”

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