内容简介:Python provides more than one way to format strings:
Python provides more than one way to format strings: %-formatting , str.format() , string.Template and f-strings . What format developers use is the matter of personal aesthetic reasons rather than anything else. Still there are use cases where good old printf-style %-formatting may have advantages over other formats. Python’s logging module is one of these cases. Let’s see what are the main reasons to use %-formatting for logging in Python.
Python logging optimization: format string until it cannot be avoided
Python logging methods like debug get in message argument along with optional args and kwargs . Arguments used for message formatting. Formatting of these arguments is deferred until it cannot be avoided. That means the final message is not evaluated if its log level is below the logger’s log level. On the other hand, f-string is really an expression that evaluated at runtime and it lacks logging’s optimizations. Let’s see an example:
In [1]: import logging ...: logging.basicConfig(level=logging.INFO) ...: logger = logging.getLogger('TestLogger') In [2]: class A: ...: def __str__(self): ...: print('Unnecessary slow computations are done here!') ...: return self.__class__.__name__ ...: ...: obj = A() In [3]: logger.debug("log level below INFO with args: %s", obj) In [4]: logger.debug(f"log level below INFO with f-string: {obj}") Unnecessary slow computations are done here! In [5]: logger.info("log level INFO with args: %s", obj) Unnecessary slow computations are done here! INFO:TestLogger:log level INFO with args: A
As you can see in step 3 message is not logged as root logger’s level is higher than debug . That’s why that message is not formatted. In step 4 f-string is evaluated even though it’s not getting logged either.
Logging module has other nice optimizations that worth learning.
Sentry integration with logging
Sentry is a popular error tracking solution. Sentry integrates with the Python logging module. Error aggregation is another great feature of Sentry. Sentry looks at the event’s stacktrace, exception, or message and group it with existing ones if they are the same. If you get a hundred of exceptions that are all the same they get grouped into one with nice statistics.
When integrating Sentry with Python logging, it’s important to use %-formatting , so that Sentry can group your messages. As an example, let’s log failed attempts to retrieve an URL :
logger.error("Failed to retrieve URL %s", url)
With printf-style formatting your messages will be grouped together no matter what value url variable holds. But in this case:
logger.error(f"Failed to retrieve URL {url}")
you get a separate event in Sentry for every single unique URL . If you get 1000 unique URL , your Sentry dashboard might get messy.
Conclusions
Although Python is not Perl, there’s still more than one way to do it. Which string formatting style to use is an open question. Your project may not use Sentry, or you may prefer f-strings for readability reasons. You may see deferred formatting in logging for printf-style strings as a futile micro-optimization that won’t improve your app performance. But still, there may be cases where using an oldie but goldie %-formatting is beneficial, even at price of string formatting inconsistency.
以上就是本文的全部内容,希望本文的内容对大家的学习或者工作能带来一定的帮助,也希望大家多多支持 码农网
猜你喜欢:本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们。
复杂:信息时代的连接、机会与布局
罗家德 / 中信出版集团股份有限公司 / 2017-8-1 / 49.00 元
信息科技一方面创造了人们互联的需要,另一方面让人们在互联中抱团以寻找归属感,因此创造了大大小小各类群体的认同和圈子力量的兴起,即互联的同时又产生了聚群,甚至聚群间的相斥。要如何分析这张网?如何预测它的未来变化?如何在网中寻找机会,实现突围?本书提出了4个关键概念──关系、圈子、自组织与复杂系统: • 关系 关系是人与人的连接,又可以被分为强关系和弱关系。强关系就是和你拥有亲密关系的人,......一起来看看 《复杂:信息时代的连接、机会与布局》 这本书的介绍吧!