标签归档：logging

使用登录多个模块

2021年7月31日 Python实用宝典

问题：使用登录多个模块

我有一个具有以下结构的小型python项目-

Project 
 -- pkg01
   -- test01.py
 -- pkg02
   -- test02.py
 -- logging.conf

我计划使用默认的日志记录模块将消息打印到stdout和日志文件。要使用日志记录模块，需要进行一些初始化-

import logging.config

logging.config.fileConfig('logging.conf')
logger = logging.getLogger('pyApp')

logger.info('testing')

目前，在开始记录消息之前，我会在每个模块中执行此初始化。是否可以只在一个地方执行一次初始化，以便通过记录整个项目来重复使用相同的设置？

I have a small python project that has the following structure –

Project 
 -- pkg01
   -- test01.py
 -- pkg02
   -- test02.py
 -- logging.conf

I plan to use the default logging module to print messages to stdout and a log file. To use the logging module, some initialization is required –

import logging.config

logging.config.fileConfig('logging.conf')
logger = logging.getLogger('pyApp')

logger.info('testing')

At present, I perform this initialization in every module before I start logging messages. Is it possible to perform this initialization only once in one place such that the same settings are reused by logging all over the project?

回答 0

最佳实践是在每个模块中都定义一个记录器，如下所示：

import logging
logger = logging.getLogger(__name__)

在模块顶部附近，然后在模块中的其他代码中执行例如

logger.debug('My message with %s', 'variable data')

如果您需要在模块内细分日志记录活动，请使用例如

loggerA = logging.getLogger(__name__ + '.A')
loggerB = logging.getLogger(__name__ + '.B')

并登录loggerA并loggerB视情况而定。

在您的一个或多个主程序中，执行例如：

def main():
    "your program code"

if __name__ == '__main__':
    import logging.config
    logging.config.fileConfig('/path/to/logging.conf')
    main()

要么

def main():
    import logging.config
    logging.config.fileConfig('/path/to/logging.conf')
    # your program code

if __name__ == '__main__':
    main()

见这里用于从多个模块记录，并在这里用于代码日志配置将被用作其它的代码库模块。

更新：调用时fileConfig()，您可能想指定disable_existing_loggers=False是否使用Python 2.6或更高版本（有关更多信息，请参阅文档）。缺省值是True为了向后兼容，fileConfig()除非所有现有记录器或其祖先在配置中被明确命名，否则它将被禁用。将该值设置为False，将保留现有记录器。如果使用的是Python 2.7 / Python 3.2或更高版本，则不妨考虑该dictConfig()API更好，fileConfig()因为它可以更好地控制配置。

Best practice is, in each module, to have a logger defined like this:

import logging
logger = logging.getLogger(__name__)

near the top of the module, and then in other code in the module do e.g.

logger.debug('My message with %s', 'variable data')

If you need to subdivide logging activity inside a module, use e.g.

loggerA = logging.getLogger(__name__ + '.A')
loggerB = logging.getLogger(__name__ + '.B')

and log to loggerA and loggerB as appropriate.

In your main program or programs, do e.g.:

def main():
    "your program code"

if __name__ == '__main__':
    import logging.config
    logging.config.fileConfig('/path/to/logging.conf')
    main()

def main():
    import logging.config
    logging.config.fileConfig('/path/to/logging.conf')
    # your program code

if __name__ == '__main__':
    main()

See here for logging from multiple modules, and here for logging configuration for code which will be used as a library module by other code.

Update: When calling fileConfig(), you may want to specify disable_existing_loggers=False if you’re using Python 2.6 or later (see the docs for more information). The default value is True for backward compatibility, which causes all existing loggers to be disabled by fileConfig() unless they or their ancestor are explicitly named in the configuration. With the value set to False, existing loggers are left alone. If using Python 2.7/Python 3.2 or later, you may wish to consider the dictConfig() API which is better than fileConfig() as it gives more control over the configuration.

回答 1

实际上，每个记录器都是父级程序包记录器的子级（即package.subpackage.module从继承配置package.subpackage)，因此您只需要做的就是配置根记录器。这可以通过logging.config.fileConfig（您自己的记录器配置）或logging.basicConfig（设置根记录器）来实现。在您的输入模块中登录安装程序（__main__.py或者您想要运行的任何程序，例如main_script.py。__init__.py也可以）

使用basicConfig：

# package/__main__.py
import logging
import sys

logging.basicConfig(stream=sys.stdout, level=logging.INFO)

使用fileConfig：

# package/__main__.py
import logging
import logging.config

logging.config.fileConfig('logging.conf')

然后使用以下命令创建每个记录器：

# package/submodule.py
# or
# package/subpackage/submodule.py
import logging
log = logging.getLogger(__name__)

log.info("Hello logging!")

有关更多信息，请参见高级日志记录教程。

Actually every logger is a child of the parent’s package logger (i.e. package.subpackage.module inherits configuration from package.subpackage), so all you need to do is just to configure the root logger. This can be achieved by logging.config.fileConfig (your own config for loggers) or logging.basicConfig (sets the root logger). Setup logging in your entry module (__main__.py or whatever you want to run, for example main_script.py. __init__.py works as well)

using basicConfig:

# package/__main__.py
import logging
import sys

logging.basicConfig(stream=sys.stdout, level=logging.INFO)

using fileConfig:

# package/__main__.py
import logging
import logging.config

logging.config.fileConfig('logging.conf')

and then create every logger using:

# package/submodule.py
# or
# package/subpackage/submodule.py
import logging
log = logging.getLogger(__name__)

log.info("Hello logging!")

For more information see Advanced Logging Tutorial.

回答 2

我总是这样做如下。

使用一个python文件将我的日志配置为名为“ log_conf.py”的单例模式

#-*-coding:utf-8-*-

import logging.config

def singleton(cls):
    instances = {}
    def get_instance():
        if cls not in instances:
            instances[cls] = cls()
        return instances[cls]
    return get_instance()

@singleton
class Logger():
    def __init__(self):
        logging.config.fileConfig('logging.conf')
        self.logr = logging.getLogger('root')

在另一个模块中，只需导入配置。

from log_conf import Logger

Logger.logr.info("Hello World")

这是一种简单有效的日志记录模式。

I always do it as below.

Use a single python file to config my log as singleton pattern which named ‘log_conf.py‘

#-*-coding:utf-8-*-

import logging.config

def singleton(cls):
    instances = {}
    def get_instance():
        if cls not in instances:
            instances[cls] = cls()
        return instances[cls]
    return get_instance()

@singleton
class Logger():
    def __init__(self):
        logging.config.fileConfig('logging.conf')
        self.logr = logging.getLogger('root')

In another module, just import the config.

from log_conf import Logger

Logger.logr.info("Hello World")

This is a singleton pattern to log, simply and efficiently.

回答 3

这些答案中有几个建议您在模块的顶部进行操作

import logging
logger = logging.getLogger(__name__)

据我了解，这被认为是非常糟糕的做法。原因是默认情况下，文件配置将禁用所有现有记录器。例如

#my_module
import logging

logger = logging.getLogger(__name__)

def foo():
    logger.info('Hi, foo')

class Bar(object):
    def bar(self):
        logger.info('Hi, bar')

在您的主模块中：

#main
import logging

# load my module - this now configures the logger
import my_module

# This will now disable the logger in my module by default, [see the docs][1] 
logging.config.fileConfig('logging.ini')

my_module.foo()
bar = my_module.Bar()
bar.bar()

现在，在logging.ini中指定的日志将为空，因为现有的记录器已被fileconfig调用禁用。

虽然当然可以解决此问题（disable_existing_Loggers = False），但实际上，您的库中的许多客户端将不了解此行为，并且不会收到您的日志。始终通过在本地调用logging.getLogger来使您的客户容易。帽子小贴士：我从这里了解了这种行为 Victor Lin的网站上。

因此，好的做法是始终在本地调用logging.getLogger。例如

#my_module
import logging

logger = logging.getLogger(__name__)

def foo():
    logging.getLogger(__name__).info('Hi, foo')

class Bar(object):
    def bar(self):
        logging.getLogger(__name__).info('Hi, bar')

另外，如果在主目录中使用fileconfig，请设置disable_existing_loggers = False，以防万一您的库设计人员使用模块级记录器实例。

Several of these answers suggest that at the top of a module you you do

import logging
logger = logging.getLogger(__name__)

It is my understanding that this is considered very bad practice. The reason is that the file config will disable all existing loggers by default. E.g.

#my_module
import logging

logger = logging.getLogger(__name__)

def foo():
    logger.info('Hi, foo')

class Bar(object):
    def bar(self):
        logger.info('Hi, bar')

And in your main module :

#main
import logging

# load my module - this now configures the logger
import my_module

# This will now disable the logger in my module by default, [see the docs][1] 
logging.config.fileConfig('logging.ini')

my_module.foo()
bar = my_module.Bar()
bar.bar()

Now the log specified in logging.ini will be empty, as the existing logger was disabled by fileconfig call.

While is is certainly possible to get around this (disable_existing_Loggers=False), realistically many clients of your library will not know about this behavior, and will not receive your logs. Make it easy for your clients by always calling logging.getLogger locally. Hat Tip : I learned about this behavior from Victor Lin’s Website.

So good practice is instead to always call logging.getLogger locally. E.g.

#my_module
import logging

logger = logging.getLogger(__name__)

def foo():
    logging.getLogger(__name__).info('Hi, foo')

class Bar(object):
    def bar(self):
        logging.getLogger(__name__).info('Hi, bar')

Also, if you use fileconfig in your main, set disable_existing_loggers=False, just in case your library designers use module level logger instances.

回答 4

对我来说，在多个模块中使用日志记录库实例的一种简单方法是解决方案：

base_logger.py

import logging

logger = logging
logger.basicConfig(format='%(asctime)s - %(message)s', level=logging.INFO)

其他的文件

from base_logger import logger

if __name__ == '__main__':
    logger.info("This is an info message")

A simple way of using one instance of logging library in multiple modules for me was following solution:

base_logger.py

import logging

logger = logging
logger.basicConfig(format='%(asctime)s - %(message)s', level=logging.INFO)

Other files

from base_logger import logger

if __name__ == '__main__':
    logger.info("This is an info message")

回答 5

抛出另一种解决方案。

在我模块的init .py中，我有类似以下内容：

# mymodule/__init__.py
import logging

def get_module_logger(mod_name):
  logger = logging.getLogger(mod_name)
  handler = logging.StreamHandler()
  formatter = logging.Formatter(
        '%(asctime)s %(name)-12s %(levelname)-8s %(message)s')
  handler.setFormatter(formatter)
  logger.addHandler(handler)
  logger.setLevel(logging.DEBUG)
  return logger

然后在每个模块中我需要一个记录器，我这样做：

# mymodule/foo.py
from [modname] import get_module_logger
logger = get_module_logger(__name__)

如果缺少日志，则可以通过其来源来区分其来源。

Throwing in another solution.

In my module’s init.py I have something like:

# mymodule/__init__.py
import logging

def get_module_logger(mod_name):
  logger = logging.getLogger(mod_name)
  handler = logging.StreamHandler()
  formatter = logging.Formatter(
        '%(asctime)s %(name)-12s %(levelname)-8s %(message)s')
  handler.setFormatter(formatter)
  logger.addHandler(handler)
  logger.setLevel(logging.DEBUG)
  return logger

Then in each module I need a logger, I do:

# mymodule/foo.py
from [modname] import get_module_logger
logger = get_module_logger(__name__)

When the logs are missed, you can differentiate their source by the module they came from.

回答 6

您也可以提出这样的建议！

def get_logger(name=None):
    default = "__app__"
    formatter = logging.Formatter('%(levelname)s: %(asctime)s %(funcName)s(%(lineno)d) -- %(message)s',
                              datefmt='%Y-%m-%d %H:%M:%S')
    log_map = {"__app__": "app.log", "__basic_log__": "file1.log", "__advance_log__": "file2.log"}
    if name:
        logger = logging.getLogger(name)
    else:
        logger = logging.getLogger(default)
    fh = logging.FileHandler(log_map[name])
    fh.setFormatter(formatter)
    logger.addHandler(fh)
    logger.setLevel(logging.DEBUG)
    return logger

现在，如果以上内容在单独的模块中定义并且在需要记录的其他模块中导入，则可以在同一模块和整个项目中使用多个记录器。

a=get_logger("__app___")
b=get_logger("__basic_log__")
a.info("Starting logging!")
b.debug("Debug Mode")

You could also come up with something like this!

def get_logger(name=None):
    default = "__app__"
    formatter = logging.Formatter('%(levelname)s: %(asctime)s %(funcName)s(%(lineno)d) -- %(message)s',
                              datefmt='%Y-%m-%d %H:%M:%S')
    log_map = {"__app__": "app.log", "__basic_log__": "file1.log", "__advance_log__": "file2.log"}
    if name:
        logger = logging.getLogger(name)
    else:
        logger = logging.getLogger(default)
    fh = logging.FileHandler(log_map[name])
    fh.setFormatter(formatter)
    logger.addHandler(fh)
    logger.setLevel(logging.DEBUG)
    return logger

Now you could use multiple loggers in same module and across whole project if the above is defined in a separate module and imported in other modules were logging is required.

a=get_logger("__app___")
b=get_logger("__basic_log__")
a.info("Starting logging!")
b.debug("Debug Mode")

回答 7

@Yarkee的解决方案似乎更好。我想补充一点-

class Singleton(type):
    _instances = {}

    def __call__(cls, *args, **kwargs):
        if cls not in cls._instances.keys():
            cls._instances[cls] = super(Singleton, cls).__call__(*args, **kwargs)
        return cls._instances[cls]


class LoggerManager(object):
    __metaclass__ = Singleton

    _loggers = {}

    def __init__(self, *args, **kwargs):
        pass

    @staticmethod
    def getLogger(name=None):
        if not name:
            logging.basicConfig()
            return logging.getLogger()
        elif name not in LoggerManager._loggers.keys():
            logging.basicConfig()
            LoggerManager._loggers[name] = logging.getLogger(str(name))
        return LoggerManager._loggers[name]    


log=LoggerManager().getLogger("Hello")
log.setLevel(level=logging.DEBUG)

因此LoggerManager可以插入整个应用程序。希望它有意义和有价值。

@Yarkee’s solution seemed better. I would like to add somemore to it –

class Singleton(type):
    _instances = {}

    def __call__(cls, *args, **kwargs):
        if cls not in cls._instances.keys():
            cls._instances[cls] = super(Singleton, cls).__call__(*args, **kwargs)
        return cls._instances[cls]


class LoggerManager(object):
    __metaclass__ = Singleton

    _loggers = {}

    def __init__(self, *args, **kwargs):
        pass

    @staticmethod
    def getLogger(name=None):
        if not name:
            logging.basicConfig()
            return logging.getLogger()
        elif name not in LoggerManager._loggers.keys():
            logging.basicConfig()
            LoggerManager._loggers[name] = logging.getLogger(str(name))
        return LoggerManager._loggers[name]    


log=LoggerManager().getLogger("Hello")
log.setLevel(level=logging.DEBUG)

So LoggerManager can be a pluggable to the entire application. Hope it makes sense and value.

回答 8

有几个答案。我最终得到了一个对我有意义的类似但又不同的解决方案，也许对您也很有意义。我的主要目标是能够按其级别将日志传递给处理程序（将调试级别的日志传递到控制台，将警告及以上信息传递给文件）：

from flask import Flask
import logging
from logging.handlers import RotatingFileHandler

app = Flask(__name__)

# make default logger output everything to the console
logging.basicConfig(level=logging.DEBUG)

rotating_file_handler = RotatingFileHandler(filename="logs.log")
rotating_file_handler.setLevel(logging.INFO)

app.logger.addHandler(rotating_file_handler)

创建了一个名为logger.py的实用程序文件：

import logging

def get_logger(name):
    return logging.getLogger("flask.app." + name)

flask.app是flask中的硬编码值。应用程序记录器始终以flask.app作为模块名称。

现在，在每个模块中，我都可以在以下模式下使用它：

from logger import get_logger
logger = get_logger(__name__)

logger.info("new log")

这将以最小的努力为“ app.flask.MODULE_NAME”创建一个新日志。

There are several answers. i ended up with a similar yet different solution that makes sense to me, maybe it will make sense to you as well. My main objective was to be able to pass logs to handlers by their level (debug level logs to the console, warnings and above to files):

from flask import Flask
import logging
from logging.handlers import RotatingFileHandler

app = Flask(__name__)

# make default logger output everything to the console
logging.basicConfig(level=logging.DEBUG)

rotating_file_handler = RotatingFileHandler(filename="logs.log")
rotating_file_handler.setLevel(logging.INFO)

app.logger.addHandler(rotating_file_handler)

created a nice util file named logger.py:

import logging

def get_logger(name):
    return logging.getLogger("flask.app." + name)

the flask.app is a hardcoded value in flask. the application logger is always starting with flask.app as its the module’s name.

now, in each module, i’m able to use it in the following mode:

from logger import get_logger
logger = get_logger(__name__)

logger.info("new log")

This will create a new log for “app.flask.MODULE_NAME” with minimum effort.

回答 9

最佳实践是分别创建一个模块，该模块只有一个方法，我们的任务是将记录程序处理程序提供给调用方法。将此文件另存为m_logger.py

import logger, logging

def getlogger():
    # logger
    logger = logging.getLogger(__name__)
    logger.setLevel(logging.DEBUG)
    # create console handler and set level to debug
    #ch = logging.StreamHandler()
    ch = logging.FileHandler(r'log.txt')
    ch.setLevel(logging.DEBUG)
    # create formatter
    formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')
    # add formatter to ch
    ch.setFormatter(formatter)
    # add ch to logger
    logger.addHandler(ch)
    return logger

现在，在需要记录器处理程序时调用getlogger（）方法。

from m_logger import getlogger
logger = getlogger()
logger.info('My mssg')

The best practice would be to create a module separately which has only one method whose task we be to give a logger handler to the the calling method. Save this file as m_logger.py

import logger, logging

def getlogger():
    # logger
    logger = logging.getLogger(__name__)
    logger.setLevel(logging.DEBUG)
    # create console handler and set level to debug
    #ch = logging.StreamHandler()
    ch = logging.FileHandler(r'log.txt')
    ch.setLevel(logging.DEBUG)
    # create formatter
    formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')
    # add formatter to ch
    ch.setFormatter(formatter)
    # add ch to logger
    logger.addHandler(ch)
    return logger

Now call the getlogger() method whenever logger handler is needed.

from m_logger import getlogger
logger = getlogger()
logger.info('My mssg')

回答 10

python的新手，所以我不知道这是否可取，但是它对不重写样板非常有用。

您的项目必须具有init .py，以便可以将其作为模块加载

# Put this in your module's __init__.py
import logging.config
import sys

# I used this dictionary test, you would put:
# logging.config.fileConfig('logging.conf')
# The "" entry in loggers is the root logger, tutorials always 
# use "root" but I can't get that to work
logging.config.dictConfig({
    "version": 1,
    "formatters": {
        "default": {
            "format": "%(asctime)s %(levelname)s %(name)s %(message)s"
        },
    },
    "handlers": {
        "console": {
            "level": 'DEBUG',
            "class": "logging.StreamHandler",
            "stream": "ext://sys.stdout"
        }
    },
    "loggers": {
        "": {
            "level": "DEBUG",
            "handlers": ["console"]
        }
    }
})

def logger():
    # Get the name from the caller of this function
    return logging.getLogger(sys._getframe(1).f_globals['__name__'])

sys._getframe(1)建议来自这里

然后在其他任何文件中使用记录器：

from [your module name here] import logger

logger().debug("FOOOOOOOOO!!!")

注意事项：

您必须将文件作为模块运行，否则import [your module]将无法工作：
- python -m [your module name].[your filename without .py]
程序入口点的记录程序的名称为__main__，但是使用的任何解决方案__name__都会出现该问题。

New to python so I don’t know if this is advisable, but it works great for not re-writing boilerplate.

Your project must have an init.py so it can be loaded as a module

# Put this in your module's __init__.py
import logging.config
import sys

# I used this dictionary test, you would put:
# logging.config.fileConfig('logging.conf')
# The "" entry in loggers is the root logger, tutorials always 
# use "root" but I can't get that to work
logging.config.dictConfig({
    "version": 1,
    "formatters": {
        "default": {
            "format": "%(asctime)s %(levelname)s %(name)s %(message)s"
        },
    },
    "handlers": {
        "console": {
            "level": 'DEBUG',
            "class": "logging.StreamHandler",
            "stream": "ext://sys.stdout"
        }
    },
    "loggers": {
        "": {
            "level": "DEBUG",
            "handlers": ["console"]
        }
    }
})

def logger():
    # Get the name from the caller of this function
    return logging.getLogger(sys._getframe(1).f_globals['__name__'])

sys._getframe(1) suggestion comes from here

Then to use your logger in any other file:

from [your module name here] import logger

logger().debug("FOOOOOOOOO!!!")

Caveats:

You must run your files as modules, otherwise import [your module] won’t work:
- python -m [your module name].[your filename without .py]
The name of the logger for the entry point of your program will be __main__, but any solution using __name__ will have that issue.

知识问答

如何禁用请求库中的日志消息？

2021年7月27日 Python实用宝典

问题：如何禁用请求库中的日志消息？

默认情况下，Requests python库按照以下方式将日志消息写入控制台：

Starting new HTTP connection (1): example.com
http://example.com:80 "GET / HTTP/1.1" 200 606

我通常对这些消息不感兴趣，因此想禁用它们。使这些消息静音或降低请求的详细程度的最佳方法是什么？

By default, the Requests python library writes log messages to the console, along the lines of:

Starting new HTTP connection (1): example.com
http://example.com:80 "GET / HTTP/1.1" 200 606

I’m usually not interested in these messages, and would like to disable them. What would be the best way to silence those messages or decrease Requests’ verbosity?

回答 0

我发现了如何配置请求的日志记录级别，这是通过标准的日志记录模块完成的。我决定将其配置为不记录消息，除非它们至少是警告：

import logging

logging.getLogger("requests").setLevel(logging.WARNING)

如果您也希望将此设置应用于urllib3库（通常由请求使用），请添加以下内容：

logging.getLogger("urllib3").setLevel(logging.WARNING)

I found out how to configure requests‘s logging level, it’s done via the standard logging module. I decided to configure it to not log messages unless they are at least warnings:

import logging

logging.getLogger("requests").setLevel(logging.WARNING)

If you wish to apply this setting for the urllib3 library (typically used by requests) too, add the following:

logging.getLogger("urllib3").setLevel(logging.WARNING)

回答 1

如果您是来这里寻找修改任何（可能是深度嵌套的）模块的日志记录的方法，请使用它logging.Logger.manager.loggerDict来获取所有记录器对象的字典。然后，返回的名称可用作以下参数logging.getLogger：

import requests
import logging
for key in logging.Logger.manager.loggerDict:
    print(key)
# requests.packages.urllib3.connectionpool
# requests.packages.urllib3.util
# requests.packages
# requests.packages.urllib3
# requests.packages.urllib3.util.retry
# PYREADLINE
# requests
# requests.packages.urllib3.poolmanager

logging.getLogger('requests').setLevel(logging.CRITICAL)
# Could also use the dictionary directly:
# logging.Logger.manager.loggerDict['requests'].setLevel(logging.CRITICAL)

请注意每个用户136036中的注释，此方法仅显示运行上述代码片段时存在的记录器。例如，如果某个模块在实例化一个类时创建了一个新的记录器，则必须在创建该类之后放置此代码段以打印其名称。

In case you came here looking for a way to modify logging of any (possibly deeply nested) module, use logging.Logger.manager.loggerDict to get a dictionary of all of the logger objects. The returned names can then be used as the argument to logging.getLogger:

import requests
import logging
for key in logging.Logger.manager.loggerDict:
    print(key)
# requests.packages.urllib3.connectionpool
# requests.packages.urllib3.util
# requests.packages
# requests.packages.urllib3
# requests.packages.urllib3.util.retry
# PYREADLINE
# requests
# requests.packages.urllib3.poolmanager

logging.getLogger('requests').setLevel(logging.CRITICAL)
# Could also use the dictionary directly:
# logging.Logger.manager.loggerDict['requests'].setLevel(logging.CRITICAL)

Per user136036 in a comment, be aware that this method only shows you the loggers that exist at the time you run the above snippet. If, for example, a module creates a new logger when you instantiate a class, then you must put this snippet after creating the class in order to print its name.

回答 2

import logging
urllib3_logger = logging.getLogger('urllib3')
urllib3_logger.setLevel(logging.CRITICAL)

这样，来自urllib3的所有level = INFO消息都不会出现在日志文件中。

因此，您可以继续将level = INFO用作日志消息…只需为您正在使用的库修改它即可。

import logging
urllib3_logger = logging.getLogger('urllib3')
urllib3_logger.setLevel(logging.CRITICAL)

In this way all the messages of level=INFO from urllib3 won’t be present in the logfile.

So you can continue to use the level=INFO for your log messages…just modify this for the library you are using.

回答 3

在遇到类似于您的问题之后，让我复制/粘贴一周或两周前写的文档部分：

import requests
import logging

# these two lines enable debugging at httplib level (requests->urllib3->httplib)
# you will see the REQUEST, including HEADERS and DATA, and RESPONSE with HEADERS but without DATA.
# the only thing missing will be the response.body which is not logged.
import httplib
httplib.HTTPConnection.debuglevel = 1

logging.basicConfig() # you need to initialize logging, otherwise you will not see anything from requests
logging.getLogger().setLevel(logging.DEBUG)
requests_log = logging.getLogger("requests.packages.urllib3")
requests_log.setLevel(logging.DEBUG)
requests_log.propagate = True

requests.get('http://httpbin.org/headers')

Let me copy/paste the documentation section which it I wrote about week or two ago, after having a problem similar to yours:

import requests
import logging

# these two lines enable debugging at httplib level (requests->urllib3->httplib)
# you will see the REQUEST, including HEADERS and DATA, and RESPONSE with HEADERS but without DATA.
# the only thing missing will be the response.body which is not logged.
import httplib
httplib.HTTPConnection.debuglevel = 1

logging.basicConfig() # you need to initialize logging, otherwise you will not see anything from requests
logging.getLogger().setLevel(logging.DEBUG)
requests_log = logging.getLogger("requests.packages.urllib3")
requests_log.setLevel(logging.DEBUG)
requests_log.propagate = True

requests.get('http://httpbin.org/headers')

回答 4

对于使用的任何人，logging.config.dictConfig您都可以像这样更改字典中的请求库日志级别：

'loggers': {
    '': {
        'handlers': ['file'],
        'level': level,
        'propagate': False
    },
    'requests.packages.urllib3': {
        'handlers': ['file'],
        'level': logging.WARNING
    }
}

For anybody using logging.config.dictConfig you can alter the requests library log level in the dictionary like this:

'loggers': {
    '': {
        'handlers': ['file'],
        'level': level,
        'propagate': False
    },
    'requests.packages.urllib3': {
        'handlers': ['file'],
        'level': logging.WARNING
    }
}

回答 5

将记录器名称设置为requests或requests.urllib3对我不起作用。我必须指定确切的记录器名称才能更改记录级别。

首先查看您已定义的记录器，以查看要删除的记录器

print(logging.Logger.manager.loggerDict)

您将看到类似以下内容：

{...'urllib3.poolmanager': <logging.Logger object at 0x1070a6e10>, 'django.request': <logging.Logger object at 0x106d61290>, 'django.template': <logging.Logger object at 0x10630dcd0>, 'django.server': <logging.Logger object at 0x106dd6a50>, 'urllib3.connection': <logging.Logger object at 0x10710a350>,'urllib3.connectionpool': <logging.Logger object at 0x106e09690> ...}

然后为确切的记录器配置级别：

   'loggers': {
    '': {
        'handlers': ['default'],
        'level': 'DEBUG',
        'propagate': True
    },
    'urllib3.connectionpool': {
        'handlers': ['default'],
        'level': 'WARNING',
        'propagate' : False
    },

Setting the logger name as requests or requests.urllib3 did not work for me. I had to specify the exact logger name to change the logging level.

First See which loggers you have defined, to see which ones you want to remove

print(logging.Logger.manager.loggerDict)

And you will see something like this:

Then configure the level for the exact logger:

   'loggers': {
    '': {
        'handlers': ['default'],
        'level': 'DEBUG',
        'propagate': True
    },
    'urllib3.connectionpool': {
        'handlers': ['default'],
        'level': 'WARNING',
        'propagate' : False
    },

回答 6

如果您有配置文件，则可以对其进行配置。

在loggers部分中添加urllib3：

[loggers]
keys = root, urllib3

添加logger_urllib3部分：

[logger_urllib3]
level = WARNING
handlers =
qualname = requests.packages.urllib3.connectionpool

If You have configuration file, You can configure it.

Add urllib3 in loggers section:

[loggers]
keys = root, urllib3

Add logger_urllib3 section:

[logger_urllib3]
level = WARNING
handlers =
qualname = requests.packages.urllib3.connectionpool

回答 7

答案在这里： Python：如何抑制来自第三方库的日志记录语句？

您可以保留basicConfig的默认日志记录级别，然后在获取模块的记录器时设置DEBUG级别。

logging.basicConfig(format='%(asctime)s %(module)s %(filename)s:%(lineno)s - %(message)s')
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)

logger.debug("my debug message")

This answer is here: Python: how to suppress logging statements from third party libraries?

You can leave the default logging level for basicConfig, and then you set the DEBUG level when you get the logger for your module.

logging.basicConfig(format='%(asctime)s %(module)s %(filename)s:%(lineno)s - %(message)s')
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)

logger.debug("my debug message")

回答 8

import logging

# Only show warnings
logging.getLogger("urllib3").setLevel(logging.WARNING)

# Disable all child loggers of urllib3, e.g. urllib3.connectionpool
logging.getLogger("urllib3").propagate = False

import logging

# Only show warnings
logging.getLogger("urllib3").setLevel(logging.WARNING)

# Disable all child loggers of urllib3, e.g. urllib3.connectionpool
logging.getLogger("urllib3").propagate = False

回答 9

Kbrose关于查找哪个记录器正在生成日志消息的指南非常有用。对于我的Django项目，我不得不对120种不同的记录器进行分类，直到发现是elasticsearchPython库对我造成了问题。根据大多数问题的指导，我通过将其添加到记录器中来禁用了它：

      ...
      'elasticsearch': {
          'handlers': ['console'],
          'level': logging.WARNING,
      },     
      ...

如果有人在运行Elasticsearch查询时看到其他无用的日志消息，请在此处发布。

Kbrose’s guidance on finding which logger was generating log messages was immensely useful. For my Django project, I had to sort through 120 different loggers until I found that it was the elasticsearch Python library that was causing issues for me. As per the guidance in most of the questions, I disabled it by adding this to my loggers:

      ...
      'elasticsearch': {
          'handlers': ['console'],
          'level': logging.WARNING,
      },     
      ...

Posting here in case someone else is seeing the unhelpful log messages come through whenever they run an Elasticsearch query.

回答 10

简单：只需在requests.packages.urllib3.disable_warnings()之后添加import requests

simple: just add requests.packages.urllib3.disable_warnings() after import requests

回答 11

我不确定以前的方法是否已停止工作，但是无论如何，这是消除警告的另一种方法：

PYTHONWARNINGS="ignore:Unverified HTTPS request" ./do-insecure-request.py

基本上，在脚本执行的上下文中添加环境变量。

从文档中：https : //urllib3.readthedocs.org/en/latest/security.html#disabling-warnings

I’m not sure if the previous approaches have stopped working, but in any case, here’s another way of removing the warnings:

PYTHONWARNINGS="ignore:Unverified HTTPS request" ./do-insecure-request.py

Basically, adding an environment variable in the context of the script execution.

From the documentation: https://urllib3.readthedocs.org/en/latest/security.html#disabling-warnings

知识问答

记录器配置以记录到文件并打印到stdout

2021年7月27日 Python实用宝典

问题：记录器配置以记录到文件并打印到stdout

我正在使用Python的日志记录模块将一些调试字符串记录到运行良好的文件中。现在，此外，我想使用此模块还将字符串输出到stdout。我该怎么做呢？为了将我的字符串记录到文件中，我使用以下代码：

import logging
import logging.handlers
logger = logging.getLogger("")
logger.setLevel(logging.DEBUG)
handler = logging.handlers.RotatingFileHandler(
    LOGFILE, maxBytes=(1048576*5), backupCount=7
)
formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
handler.setFormatter(formatter)
logger.addHandler(handler)

然后调用记录器功能，例如

logger.debug("I am written to the file")

谢谢您的帮助！

I’m using Python’s logging module to log some debug strings to a file which works pretty well. Now in addition, I’d like to use this module to also print the strings out to stdout. How do I do this? In order to log my strings to a file I use following code:

import logging
import logging.handlers
logger = logging.getLogger("")
logger.setLevel(logging.DEBUG)
handler = logging.handlers.RotatingFileHandler(
    LOGFILE, maxBytes=(1048576*5), backupCount=7
)
formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
handler.setFormatter(formatter)
logger.addHandler(handler)

and then call a logger function like

logger.debug("I am written to the file")

Thank you for some help here!

回答 0

只需获取根记录器的句柄并添加即可StreamHandler。在StreamHandler写至标准错误。不知道您是否真的需要stdout而不是stderr，但这是我在设置Python记录器时使用的方法，我也添加了FileHandler它。然后，我所有的日志都转到两个地方（这听起来像您想要的）。

import logging
logging.getLogger().addHandler(logging.StreamHandler())

如果要输出到stdout而不是stderr，则只需将其指定给StreamHandler构造函数。

import sys
# ...
logging.getLogger().addHandler(logging.StreamHandler(sys.stdout))

您也可以在其中添加一个Formatter，以便所有日志行都有一个公共标题。

即：

import logging
logFormatter = logging.Formatter("%(asctime)s [%(threadName)-12.12s] [%(levelname)-5.5s]  %(message)s")
rootLogger = logging.getLogger()

fileHandler = logging.FileHandler("{0}/{1}.log".format(logPath, fileName))
fileHandler.setFormatter(logFormatter)
rootLogger.addHandler(fileHandler)

consoleHandler = logging.StreamHandler()
consoleHandler.setFormatter(logFormatter)
rootLogger.addHandler(consoleHandler)

打印为以下格式：

2012-12-05 16:58:26,618 [MainThread  ] [INFO ]  my message

Just get a handle to the root logger and add the StreamHandler. The StreamHandler writes to stderr. Not sure if you really need stdout over stderr, but this is what I use when I setup the Python logger and I also add the FileHandler as well. Then all my logs go to both places (which is what it sounds like you want).

import logging
logging.getLogger().addHandler(logging.StreamHandler())

If you want to output to stdout instead of stderr, you just need to specify it to the StreamHandler constructor.

import sys
# ...
logging.getLogger().addHandler(logging.StreamHandler(sys.stdout))

You could also add a Formatter to it so all your log lines have a common header.

ie:

import logging
logFormatter = logging.Formatter("%(asctime)s [%(threadName)-12.12s] [%(levelname)-5.5s]  %(message)s")
rootLogger = logging.getLogger()

fileHandler = logging.FileHandler("{0}/{1}.log".format(logPath, fileName))
fileHandler.setFormatter(logFormatter)
rootLogger.addHandler(fileHandler)

consoleHandler = logging.StreamHandler()
consoleHandler.setFormatter(logFormatter)
rootLogger.addHandler(consoleHandler)

Prints to the format of:

2012-12-05 16:58:26,618 [MainThread  ] [INFO ]  my message

回答 1

logging.basicConfig()handlers从Python 3.3开始可以使用关键字参数，这大大简化了日志记录设置，尤其是在使用同一格式化程序设置多个处理程序时：

handlers–如果指定，则这应该是已经创建的处理程序的迭代，以添加到根记录器。任何尚未设置格式器的处理程序都将被分配此函数中创建的默认格式器。

因此，整个设置可以通过以下单个调用完成：

import logging

logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s [%(levelname)s] %(message)s",
    handlers=[
        logging.FileHandler("debug.log"),
        logging.StreamHandler()
    ]
)

（或按照原始问题的要求加上import sys+ StreamHandler(sys.stdout)– StreamHandler的默认值是写入stderr。查看LogRecord属性如果要自定义日志格式并添加诸如文件名/行，线程信息等内容，请。）

上面的设置只需要在脚本开始处执行一次即可。您可以稍后在代码库的所有其他位置使用日志记录，如下所示：

logging.info('Useful message')
logging.error('Something bad happened')
...

注意：如果它不起作用，则可能是其他人已经用不同的方式初始化了日志系统。建议logging.root.handlers = []在调用之前先做评论basicConfig()。

logging.basicConfig() can take a keyword argument handlers since Python 3.3, which simplifies logging setup a lot, especially when setting up multiple handlers with the same formatter:

handlers – If specified, this should be an iterable of already created handlers to add to the root logger. Any handlers which don’t already have a formatter set will be assigned the default formatter created in this function.

The whole setup can therefore be done with a single call like this:

import logging

logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s [%(levelname)s] %(message)s",
    handlers=[
        logging.FileHandler("debug.log"),
        logging.StreamHandler()
    ]
)

(Or with import sys + StreamHandler(sys.stdout) per original question’s requirements – the default for StreamHandler is to write to stderr. Look at LogRecord attributes if you want to customize the log format and add things like filename/line, thread info etc.)

The setup above needs to be done only once near the beginning of the script. You can use the logging from all other places in the codebase later like this:

logging.info('Useful message')
logging.error('Something bad happened')
...

Note: If it doesn’t work, someone else has probably already initialized the logging system differently. Comments suggest doing logging.root.handlers = [] before the call to basicConfig().

回答 2

添加不带参数的StreamHandler转到stderr而不是stdout。如果某些其他进程依赖于stdout转储（即，在编写NRPE插件时），则请确保明确指定stdout，否则您可能会遇到一些意想不到的麻烦。

这是一个快速示例，该示例重用了问题中的假定值和LOGFILE：

import logging
from logging.handlers import RotatingFileHandler
from logging import handlers
import sys

log = logging.getLogger('')
log.setLevel(logging.DEBUG)
format = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")

ch = logging.StreamHandler(sys.stdout)
ch.setFormatter(format)
log.addHandler(ch)

fh = handlers.RotatingFileHandler(LOGFILE, maxBytes=(1048576*5), backupCount=7)
fh.setFormatter(format)
log.addHandler(fh)

Adding a StreamHandler without arguments goes to stderr instead of stdout. If some other process has a dependency on the stdout dump (i.e. when writing an NRPE plugin), then make sure to specify stdout explicitly or you might run into some unexpected troubles.

Here’s a quick example reusing the assumed values and LOGFILE from the question:

import logging
from logging.handlers import RotatingFileHandler
from logging import handlers
import sys

log = logging.getLogger('')
log.setLevel(logging.DEBUG)
format = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")

ch = logging.StreamHandler(sys.stdout)
ch.setFormatter(format)
log.addHandler(ch)

fh = handlers.RotatingFileHandler(LOGFILE, maxBytes=(1048576*5), backupCount=7)
fh.setFormatter(format)
log.addHandler(fh)

回答 3

在设置任何其他处理程序或记录任何消息之前，可以basicConfig使用stream=sys.stdout作为参数运行，或者手动添加一个StreamHandler将消息推入stdout的根记录器（或与此相关的任何其他记录器）。

Either run basicConfig with stream=sys.stdout as the argument prior to setting up any other handlers or logging any messages, or manually add a StreamHandler that pushes messages to stdout to the root logger (or any other logger you want, for that matter).

回答 4

在多个Python包中反复使用Waterboy的代码后，我最终将其转换为一个很小的独立Python包，您可以在这里找到：

https://github.com/acschaefer/duallog

该代码有据可查且易于使用。只需下载.py文件并将其包含在您的项目中，或通过安装整个软件包pip install duallog。

After having used Waterboy’s code over and over in multiple Python packages, I finally cast it into a tiny standalone Python package, which you can find here:

https://github.com/acschaefer/duallog

The code is well documented and easy to use. Simply download the .py file and include it in your project, or install the whole package via pip install duallog.

回答 5

import logging
import logging.handlers
import sys

if __name__ == "__main__":

    # Change root logger level from WARNING (default) to NOTSET in order for all messages to be delegated.
    logging.getLogger().setLevel(logging.NOTSET)

    # Add stdout handler, with level INFO
    console = logging.StreamHandler(sys.stdout)
    console.setLevel(logging.INFO)
    formater = logging.Formatter('%(name)-13s: %(levelname)-8s %(message)s')
    console.setFormatter(formater)
    logging.getLogger().addHandler(console)

    # Add file rotating handler, with level DEBUG
    rotatingHandler = logging.handlers.RotatingFileHandler(filename='rotating.log', maxBytes=1000, backupCount=5)
    rotatingHandler.setLevel(logging.DEBUG)
    formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
    rotatingHandler.setFormatter(formatter)
    logging.getLogger().addHandler(rotatingHandler)

    log = logging.getLogger("app." + __name__)

    log.debug('Debug message, should only appear in the file.')
    log.info('Info message, should appear in file and stdout.')
    log.warning('Warning message, should appear in file and stdout.')
    log.error('Error message, should appear in file and stdout.')

Logging to stdout and rotating file with different levels and formats:

import logging
import logging.handlers
import sys

if __name__ == "__main__":

    # Change root logger level from WARNING (default) to NOTSET in order for all messages to be delegated.
    logging.getLogger().setLevel(logging.NOTSET)

    # Add stdout handler, with level INFO
    console = logging.StreamHandler(sys.stdout)
    console.setLevel(logging.INFO)
    formater = logging.Formatter('%(name)-13s: %(levelname)-8s %(message)s')
    console.setFormatter(formater)
    logging.getLogger().addHandler(console)

    # Add file rotating handler, with level DEBUG
    rotatingHandler = logging.handlers.RotatingFileHandler(filename='rotating.log', maxBytes=1000, backupCount=5)
    rotatingHandler.setLevel(logging.DEBUG)
    formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
    rotatingHandler.setFormatter(formatter)
    logging.getLogger().addHandler(rotatingHandler)

    log = logging.getLogger("app." + __name__)

    log.debug('Debug message, should only appear in the file.')
    log.info('Info message, should appear in file and stdout.')
    log.warning('Warning message, should appear in file and stdout.')
    log.error('Error message, should appear in file and stdout.')

回答 6

这是一个完整的包装好的解决方案，基于Waterboy的答案和其他各种来源。它支持同时记录到控制台和日志文件，允许进行不同的日志级别设置，提供彩色输出，并且易于配置（也可以作为Gist使用）：

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

# -------------------------------------------------------------------------------
#                                                                               -
#  Python dual-logging setup (console and log file),                            -
#  supporting different log levels and colorized output                         -
#                                                                               -
#  Created by Fonic <https://github.com/fonic>                                  -
#  Date: 04/05/20                                                               -
#                                                                               -
#  Based on:                                                                    -
#  https://stackoverflow.com/a/13733863/1976617                                 -
#  https://uran198.github.io/en/python/2016/07/12/colorful-python-logging.html  -
#  https://en.wikipedia.org/wiki/ANSI_escape_code#Colors                        -
#                                                                               -
# -------------------------------------------------------------------------------

# Imports
import os
import sys
import logging

# Logging formatter supporting colored output
class LogFormatter(logging.Formatter):

    COLOR_CODES = {
        logging.CRITICAL: "\033[1;35m", # bright/bold magenta
        logging.ERROR:    "\033[1;31m", # bright/bold red
        logging.WARNING:  "\033[1;33m", # bright/bold yellow
        logging.INFO:     "\033[0;37m", # white / light gray
        logging.DEBUG:    "\033[1;30m"  # bright/bold black / dark gray
    }

    RESET_CODE = "\033[0m"

    def __init__(self, color, *args, **kwargs):
        super(LogFormatter, self).__init__(*args, **kwargs)
        self.color = color

    def format(self, record, *args, **kwargs):
        if (self.color == True and record.levelno in self.COLOR_CODES):
            record.color_on  = self.COLOR_CODES[record.levelno]
            record.color_off = self.RESET_CODE
        else:
            record.color_on  = ""
            record.color_off = ""
        return super(LogFormatter, self).format(record, *args, **kwargs)

# Setup logging
def setup_logging(console_log_output, console_log_level, console_log_color, logfile_file, logfile_log_level, logfile_log_color, log_line_template):

    # Create logger
    # For simplicity, we use the root logger, i.e. call 'logging.getLogger()'
    # without name argument. This way we can simply use module methods for
    # for logging throughout the script. An alternative would be exporting
    # the logger, i.e. 'global logger; logger = logging.getLogger("<name>")'
    logger = logging.getLogger()

    # Set global log level to 'debug' (required for handler levels to work)
    logger.setLevel(logging.DEBUG)

    # Create console handler
    console_log_output = console_log_output.lower()
    if (console_log_output == "stdout"):
        console_log_output = sys.stdout
    elif (console_log_output == "stderr"):
        console_log_output = sys.stderr
    else:
        print("Failed to set console output: invalid output: '%s'" % console_log_output)
        return False
    console_handler = logging.StreamHandler(console_log_output)

    # Set console log level
    try:
        console_handler.setLevel(console_log_level.upper()) # only accepts uppercase level names
    except:
        print("Failed to set console log level: invalid level: '%s'" % console_log_level)
        return False

    # Create and set formatter, add console handler to logger
    console_formatter = LogFormatter(fmt=log_line_template, color=console_log_color)
    console_handler.setFormatter(console_formatter)
    logger.addHandler(console_handler)

    # Create log file handler
    try:
        logfile_handler = logging.FileHandler(logfile_file)
    except Exception as exception:
        print("Failed to set up log file: %s" % str(exception))
        return False

    # Set log file log level
    try:
        logfile_handler.setLevel(logfile_log_level.upper()) # only accepts uppercase level names
    except:
        print("Failed to set log file log level: invalid level: '%s'" % logfile_log_level)
        return False

    # Create and set formatter, add log file handler to logger
    logfile_formatter = LogFormatter(fmt=log_line_template, color=logfile_log_color)
    logfile_handler.setFormatter(logfile_formatter)
    logger.addHandler(logfile_handler)

    # Success
    return True

# Main function
def main():

    # Setup logging
    script_name = os.path.splitext(os.path.basename(sys.argv[0]))[0]
    if (not setup_logging(console_log_output="stdout", console_log_level="warning", console_log_color=True,
                        logfile_file=script_name + ".log", logfile_log_level="debug", logfile_log_color=False,
                        log_line_template="%(color_on)s[%(created)d] [%(threadName)s] [%(levelname)-8s] %(message)s%(color_off)s")):
        print("Failed to setup logging, aborting.")
        return 1

    # Log some messages
    logging.debug("Debug message")
    logging.info("Info message")
    logging.warning("Warning message")
    logging.error("Error message")
    logging.critical("Critical message")

# Call main function
if (__name__ == "__main__"):
    sys.exit(main())

Here is a complete, nicely wrapped solution based on Waterboy’s answer and various other sources. It supports logging to both console and log file, allows for different log level settings, provides colorized output and is easily configurable (also available as Gist):

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

# -------------------------------------------------------------------------------
#                                                                               -
#  Python dual-logging setup (console and log file),                            -
#  supporting different log levels and colorized output                         -
#                                                                               -
#  Created by Fonic <https://github.com/fonic>                                  -
#  Date: 04/05/20                                                               -
#                                                                               -
#  Based on:                                                                    -
#  https://stackoverflow.com/a/13733863/1976617                                 -
#  https://uran198.github.io/en/python/2016/07/12/colorful-python-logging.html  -
#  https://en.wikipedia.org/wiki/ANSI_escape_code#Colors                        -
#                                                                               -
# -------------------------------------------------------------------------------

# Imports
import os
import sys
import logging

# Logging formatter supporting colored output
class LogFormatter(logging.Formatter):

    COLOR_CODES = {
        logging.CRITICAL: "\033[1;35m", # bright/bold magenta
        logging.ERROR:    "\033[1;31m", # bright/bold red
        logging.WARNING:  "\033[1;33m", # bright/bold yellow
        logging.INFO:     "\033[0;37m", # white / light gray
        logging.DEBUG:    "\033[1;30m"  # bright/bold black / dark gray
    }

    RESET_CODE = "\033[0m"

    def __init__(self, color, *args, **kwargs):
        super(LogFormatter, self).__init__(*args, **kwargs)
        self.color = color

    def format(self, record, *args, **kwargs):
        if (self.color == True and record.levelno in self.COLOR_CODES):
            record.color_on  = self.COLOR_CODES[record.levelno]
            record.color_off = self.RESET_CODE
        else:
            record.color_on  = ""
            record.color_off = ""
        return super(LogFormatter, self).format(record, *args, **kwargs)

# Setup logging
def setup_logging(console_log_output, console_log_level, console_log_color, logfile_file, logfile_log_level, logfile_log_color, log_line_template):

    # Create logger
    # For simplicity, we use the root logger, i.e. call 'logging.getLogger()'
    # without name argument. This way we can simply use module methods for
    # for logging throughout the script. An alternative would be exporting
    # the logger, i.e. 'global logger; logger = logging.getLogger("<name>")'
    logger = logging.getLogger()

    # Set global log level to 'debug' (required for handler levels to work)
    logger.setLevel(logging.DEBUG)

    # Create console handler
    console_log_output = console_log_output.lower()
    if (console_log_output == "stdout"):
        console_log_output = sys.stdout
    elif (console_log_output == "stderr"):
        console_log_output = sys.stderr
    else:
        print("Failed to set console output: invalid output: '%s'" % console_log_output)
        return False
    console_handler = logging.StreamHandler(console_log_output)

    # Set console log level
    try:
        console_handler.setLevel(console_log_level.upper()) # only accepts uppercase level names
    except:
        print("Failed to set console log level: invalid level: '%s'" % console_log_level)
        return False

    # Create and set formatter, add console handler to logger
    console_formatter = LogFormatter(fmt=log_line_template, color=console_log_color)
    console_handler.setFormatter(console_formatter)
    logger.addHandler(console_handler)

    # Create log file handler
    try:
        logfile_handler = logging.FileHandler(logfile_file)
    except Exception as exception:
        print("Failed to set up log file: %s" % str(exception))
        return False

    # Set log file log level
    try:
        logfile_handler.setLevel(logfile_log_level.upper()) # only accepts uppercase level names
    except:
        print("Failed to set log file log level: invalid level: '%s'" % logfile_log_level)
        return False

    # Create and set formatter, add log file handler to logger
    logfile_formatter = LogFormatter(fmt=log_line_template, color=logfile_log_color)
    logfile_handler.setFormatter(logfile_formatter)
    logger.addHandler(logfile_handler)

    # Success
    return True

# Main function
def main():

    # Setup logging
    script_name = os.path.splitext(os.path.basename(sys.argv[0]))[0]
    if (not setup_logging(console_log_output="stdout", console_log_level="warning", console_log_color=True,
                        logfile_file=script_name + ".log", logfile_log_level="debug", logfile_log_color=False,
                        log_line_template="%(color_on)s[%(created)d] [%(threadName)s] [%(levelname)-8s] %(message)s%(color_off)s")):
        print("Failed to setup logging, aborting.")
        return 1

    # Log some messages
    logging.debug("Debug message")
    logging.info("Info message")
    logging.warning("Warning message")
    logging.error("Error message")
    logging.critical("Critical message")

# Call main function
if (__name__ == "__main__"):
    sys.exit(main())

回答 7

对于2.7，请尝试以下操作：

fh = logging.handlers.RotatingFileHandler(LOGFILE, maxBytes=(1048576*5), backupCount=7)

For 2.7, try the following:

fh = logging.handlers.RotatingFileHandler(LOGFILE, maxBytes=(1048576*5), backupCount=7)

知识问答

如何为Python日志输出着色？

2021年7月27日 Python实用宝典

问题：如何为Python日志输出着色？

前一段时间，我看到一个带有彩色输出的Mono应用程序，大概是因为它的日志系统（因为所有消息都是标准化的）。

现在，Python具有该logging模块，您可以使用该模块指定许多选项来定制输出。因此，我在想使用Python可以实现类似的效果，但是我找不到在任何地方执行此操作的方法。

有什么方法可以使Python logging模块以彩色输出吗？

我想要的（例如）红色错误，蓝色或黄色调试消息，等等。

当然，这可能需要兼容的终端（大多数现代终端都需要）。但是logging如果不支持颜色，我可能会退回到原始输出。

有什么想法可以使用日志记录模块获取彩色输出吗？

Some time ago, I saw a Mono application with colored output, presumably because of its log system (because all the messages were standardized).

Now, Python has the logging module, which lets you specify a lot of options to customize output. So, I’m imagining something similar would be possible with Python, but I can’t find out how to do this anywhere.

Is there any way to make the Python logging module output in color?

What I want (for instance) errors in red, debug messages in blue or yellow, and so on.

Of course this would probably require a compatible terminal (most modern terminals are); but I could fallback to the original logging output if color isn’t supported.

Any ideas how I can get colored output with the logging module?

回答 0

我已经知道颜色转义，我不久前在bash提示中使用了它们。不管怎么说，还是要谢谢你。
我想要的是将其与日志记录模块集成在一起，但经过几次尝试和错误，我最终还是将其集成了。
这是我最终得到的结果：

BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8)

#The background is set with 40 plus the number of the color, and the foreground with 30

#These are the sequences need to get colored ouput
RESET_SEQ = "\033[0m"
COLOR_SEQ = "\033[1;%dm"
BOLD_SEQ = "\033[1m"

def formatter_message(message, use_color = True):
    if use_color:
        message = message.replace("$RESET", RESET_SEQ).replace("$BOLD", BOLD_SEQ)
    else:
        message = message.replace("$RESET", "").replace("$BOLD", "")
    return message

COLORS = {
    'WARNING': YELLOW,
    'INFO': WHITE,
    'DEBUG': BLUE,
    'CRITICAL': YELLOW,
    'ERROR': RED
}

class ColoredFormatter(logging.Formatter):
    def __init__(self, msg, use_color = True):
        logging.Formatter.__init__(self, msg)
        self.use_color = use_color

    def format(self, record):
        levelname = record.levelname
        if self.use_color and levelname in COLORS:
            levelname_color = COLOR_SEQ % (30 + COLORS[levelname]) + levelname + RESET_SEQ
            record.levelname = levelname_color
        return logging.Formatter.format(self, record)

并使用它，创建自己的Logger：

# Custom logger class with multiple destinations
class ColoredLogger(logging.Logger):
    FORMAT = "[$BOLD%(name)-20s$RESET][%(levelname)-18s]  %(message)s ($BOLD%(filename)s$RESET:%(lineno)d)"
    COLOR_FORMAT = formatter_message(FORMAT, True)
    def __init__(self, name):
        logging.Logger.__init__(self, name, logging.DEBUG)                

        color_formatter = ColoredFormatter(self.COLOR_FORMAT)

        console = logging.StreamHandler()
        console.setFormatter(color_formatter)

        self.addHandler(console)
        return


logging.setLoggerClass(ColoredLogger)

以防万一其他人需要它。

如果您使用多个记录器或处理程序，请小心：ColoredFormatter正在更改记录对象，该记录对象将进一步传递给其他处理程序或传播到其他记录器。如果配置了文件记录器等，则可能不想在日志文件中使用颜色。为避免这种情况，最好是在操作levelname属性之前简单地创建一个recordwith 的副本copy.copy()，或者在返回格式化的字符串之前，将levelname重置为先前的值（在注释中归因于Michael）。

I already knew about the color escapes, I used them in my bash prompt a while ago. Thanks anyway.
What I wanted was to integrate it with the logging module, which I eventually did after a couple of tries and errors.
Here is what I end up with:

BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8)

#The background is set with 40 plus the number of the color, and the foreground with 30

#These are the sequences need to get colored ouput
RESET_SEQ = "\033[0m"
COLOR_SEQ = "\033[1;%dm"
BOLD_SEQ = "\033[1m"

def formatter_message(message, use_color = True):
    if use_color:
        message = message.replace("$RESET", RESET_SEQ).replace("$BOLD", BOLD_SEQ)
    else:
        message = message.replace("$RESET", "").replace("$BOLD", "")
    return message

COLORS = {
    'WARNING': YELLOW,
    'INFO': WHITE,
    'DEBUG': BLUE,
    'CRITICAL': YELLOW,
    'ERROR': RED
}

class ColoredFormatter(logging.Formatter):
    def __init__(self, msg, use_color = True):
        logging.Formatter.__init__(self, msg)
        self.use_color = use_color

    def format(self, record):
        levelname = record.levelname
        if self.use_color and levelname in COLORS:
            levelname_color = COLOR_SEQ % (30 + COLORS[levelname]) + levelname + RESET_SEQ
            record.levelname = levelname_color
        return logging.Formatter.format(self, record)

And to use it, create your own Logger:

# Custom logger class with multiple destinations
class ColoredLogger(logging.Logger):
    FORMAT = "[$BOLD%(name)-20s$RESET][%(levelname)-18s]  %(message)s ($BOLD%(filename)s$RESET:%(lineno)d)"
    COLOR_FORMAT = formatter_message(FORMAT, True)
    def __init__(self, name):
        logging.Logger.__init__(self, name, logging.DEBUG)                

        color_formatter = ColoredFormatter(self.COLOR_FORMAT)

        console = logging.StreamHandler()
        console.setFormatter(color_formatter)

        self.addHandler(console)
        return


logging.setLoggerClass(ColoredLogger)

Just in case anyone else needs it.

Be careful if you’re using more than one logger or handler: ColoredFormatter is changing the record object, which is passed further to other handlers or propagated to other loggers. If you have configured file loggers etc. you probably don’t want to have the colors in the log files. To avoid that, it’s probably best to simply create a copy of record with copy.copy() before manipulating the levelname attribute, or to reset the levelname to the previous value, before returning the formatted string (credit to Michael in the comments).

回答 1

多年前，我写了一个彩色的流处理程序供自己使用。然后我浏览了此页面，发现了人们正在复制/粘贴的代码片段集合：-(。我的流处理程序当前仅在UNIX（Linux，Mac OS X）上可用，但优点是可以在PyPI（和GitHub）上使用），而且使用起来非常简单，还具有Vim语法模式:-)。将来我可能会将其扩展到Windows上。

要安装软件包：

$ pip install coloredlogs

确认其有效：

$ coloredlogs --demo

要开始使用自己的代码：

$ python
> import coloredlogs, logging
> coloredlogs.install()
> logging.info("It works!")
2014-07-30 21:21:26 peter-macbook root[7471] INFO It works!

上例中显示的默认日志格式包含日期，时间，主机名，记录器的名称，PID，日志级别和日志消息。实际上是这样的：

注意：使用带有MinTTY的Git Bash时

Windows上的Git Bash有一些已记录的怪癖： Winpty和Git Bash

对于ANSI转义码以及ncurses样式字符重写和动画，您需要在命令前面加上winpty。

$ winpty coloredlogs --demo
$ winpty python your_colored_logs_script.py

Years ago I wrote a colored stream handler for my own use. Then I came across this page and found a collection of code snippets that people are copy/pasting :-(. My stream handler currently only works on UNIX (Linux, Mac OS X) but the advantage is that it’s available on PyPI (and GitHub) and it’s dead simple to use. It also has a Vim syntax mode :-). In the future I might extend it to work on Windows.

To install the package:

$ pip install coloredlogs

To confirm that it works:

$ coloredlogs --demo

To get started with your own code:

$ python
> import coloredlogs, logging
> coloredlogs.install()
> logging.info("It works!")
2014-07-30 21:21:26 peter-macbook root[7471] INFO It works!

The default log format shown in the above example contains the date, time, hostname, the name of the logger, the PID, the log level and the log message. This is what it looks like in practice:

NOTE: When using Git Bash w/ MinTTY

Git Bash on windows has some documented quirks: Winpty and Git Bash

Which for ANSI escape codes and for ncurses style character rewriting and animations, you need to prefix commands with winpty.

$ winpty coloredlogs --demo
$ winpty python your_colored_logs_script.py

回答 2

这是一个可以在任何平台上运行的解决方案。如果不只是告诉我，我会进行更新。

工作原理：在支持ANSI转义的平台上正在使用它们（非Windows），而在Windows上，它确实使用API调用来更改控制台颜色。

该脚本确实从标准库中破解了logging.StreamHandler.emit方法，并为其添加了一个包装器。

TestColorer.py

# Usage: add Colorer.py near you script and import it.
import logging
import Colorer

logging.warn("a warning")
logging.error("some error")
logging.info("some info")

着色器

#!/usr/bin/env python
# encoding: utf-8
import logging
# now we patch Python code to add color support to logging.StreamHandler
def add_coloring_to_emit_windows(fn):
        # add methods we need to the class
    def _out_handle(self):
        import ctypes
        return ctypes.windll.kernel32.GetStdHandle(self.STD_OUTPUT_HANDLE)
    out_handle = property(_out_handle)

    def _set_color(self, code):
        import ctypes
        # Constants from the Windows API
        self.STD_OUTPUT_HANDLE = -11
        hdl = ctypes.windll.kernel32.GetStdHandle(self.STD_OUTPUT_HANDLE)
        ctypes.windll.kernel32.SetConsoleTextAttribute(hdl, code)

    setattr(logging.StreamHandler, '_set_color', _set_color)

    def new(*args):
        FOREGROUND_BLUE      = 0x0001 # text color contains blue.
        FOREGROUND_GREEN     = 0x0002 # text color contains green.
        FOREGROUND_RED       = 0x0004 # text color contains red.
        FOREGROUND_INTENSITY = 0x0008 # text color is intensified.
        FOREGROUND_WHITE     = FOREGROUND_BLUE|FOREGROUND_GREEN |FOREGROUND_RED
       # winbase.h
        STD_INPUT_HANDLE = -10
        STD_OUTPUT_HANDLE = -11
        STD_ERROR_HANDLE = -12

        # wincon.h
        FOREGROUND_BLACK     = 0x0000
        FOREGROUND_BLUE      = 0x0001
        FOREGROUND_GREEN     = 0x0002
        FOREGROUND_CYAN      = 0x0003
        FOREGROUND_RED       = 0x0004
        FOREGROUND_MAGENTA   = 0x0005
        FOREGROUND_YELLOW    = 0x0006
        FOREGROUND_GREY      = 0x0007
        FOREGROUND_INTENSITY = 0x0008 # foreground color is intensified.

        BACKGROUND_BLACK     = 0x0000
        BACKGROUND_BLUE      = 0x0010
        BACKGROUND_GREEN     = 0x0020
        BACKGROUND_CYAN      = 0x0030
        BACKGROUND_RED       = 0x0040
        BACKGROUND_MAGENTA   = 0x0050
        BACKGROUND_YELLOW    = 0x0060
        BACKGROUND_GREY      = 0x0070
        BACKGROUND_INTENSITY = 0x0080 # background color is intensified.     

        levelno = args[1].levelno
        if(levelno>=50):
            color = BACKGROUND_YELLOW | FOREGROUND_RED | FOREGROUND_INTENSITY | BACKGROUND_INTENSITY 
        elif(levelno>=40):
            color = FOREGROUND_RED | FOREGROUND_INTENSITY
        elif(levelno>=30):
            color = FOREGROUND_YELLOW | FOREGROUND_INTENSITY
        elif(levelno>=20):
            color = FOREGROUND_GREEN
        elif(levelno>=10):
            color = FOREGROUND_MAGENTA
        else:
            color =  FOREGROUND_WHITE
        args[0]._set_color(color)

        ret = fn(*args)
        args[0]._set_color( FOREGROUND_WHITE )
        #print "after"
        return ret
    return new

def add_coloring_to_emit_ansi(fn):
    # add methods we need to the class
    def new(*args):
        levelno = args[1].levelno
        if(levelno>=50):
            color = '\x1b[31m' # red
        elif(levelno>=40):
            color = '\x1b[31m' # red
        elif(levelno>=30):
            color = '\x1b[33m' # yellow
        elif(levelno>=20):
            color = '\x1b[32m' # green 
        elif(levelno>=10):
            color = '\x1b[35m' # pink
        else:
            color = '\x1b[0m' # normal
        args[1].msg = color + args[1].msg +  '\x1b[0m'  # normal
        #print "after"
        return fn(*args)
    return new

import platform
if platform.system()=='Windows':
    # Windows does not support ANSI escapes and we are using API calls to set the console color
    logging.StreamHandler.emit = add_coloring_to_emit_windows(logging.StreamHandler.emit)
else:
    # all non-Windows platforms are supporting ANSI escapes so we use them
    logging.StreamHandler.emit = add_coloring_to_emit_ansi(logging.StreamHandler.emit)
    #log = logging.getLogger()
    #log.addFilter(log_filter())
    #//hdlr = logging.StreamHandler()
    #//hdlr.setFormatter(formatter())

Here is a solution that should work on any platform. If it doesn’t just tell me and I will update it.

How it works: on platform supporting ANSI escapes is using them (non-Windows) and on Windows it does use API calls to change the console colors.

The script does hack the logging.StreamHandler.emit method from standard library adding a wrapper to it.

TestColorer.py

# Usage: add Colorer.py near you script and import it.
import logging
import Colorer

logging.warn("a warning")
logging.error("some error")
logging.info("some info")

Colorer.py

#!/usr/bin/env python
# encoding: utf-8
import logging
# now we patch Python code to add color support to logging.StreamHandler
def add_coloring_to_emit_windows(fn):
        # add methods we need to the class
    def _out_handle(self):
        import ctypes
        return ctypes.windll.kernel32.GetStdHandle(self.STD_OUTPUT_HANDLE)
    out_handle = property(_out_handle)

    def _set_color(self, code):
        import ctypes
        # Constants from the Windows API
        self.STD_OUTPUT_HANDLE = -11
        hdl = ctypes.windll.kernel32.GetStdHandle(self.STD_OUTPUT_HANDLE)
        ctypes.windll.kernel32.SetConsoleTextAttribute(hdl, code)

    setattr(logging.StreamHandler, '_set_color', _set_color)

    def new(*args):
        FOREGROUND_BLUE      = 0x0001 # text color contains blue.
        FOREGROUND_GREEN     = 0x0002 # text color contains green.
        FOREGROUND_RED       = 0x0004 # text color contains red.
        FOREGROUND_INTENSITY = 0x0008 # text color is intensified.
        FOREGROUND_WHITE     = FOREGROUND_BLUE|FOREGROUND_GREEN |FOREGROUND_RED
       # winbase.h
        STD_INPUT_HANDLE = -10
        STD_OUTPUT_HANDLE = -11
        STD_ERROR_HANDLE = -12

        # wincon.h
        FOREGROUND_BLACK     = 0x0000
        FOREGROUND_BLUE      = 0x0001
        FOREGROUND_GREEN     = 0x0002
        FOREGROUND_CYAN      = 0x0003
        FOREGROUND_RED       = 0x0004
        FOREGROUND_MAGENTA   = 0x0005
        FOREGROUND_YELLOW    = 0x0006
        FOREGROUND_GREY      = 0x0007
        FOREGROUND_INTENSITY = 0x0008 # foreground color is intensified.

        BACKGROUND_BLACK     = 0x0000
        BACKGROUND_BLUE      = 0x0010
        BACKGROUND_GREEN     = 0x0020
        BACKGROUND_CYAN      = 0x0030
        BACKGROUND_RED       = 0x0040
        BACKGROUND_MAGENTA   = 0x0050
        BACKGROUND_YELLOW    = 0x0060
        BACKGROUND_GREY      = 0x0070
        BACKGROUND_INTENSITY = 0x0080 # background color is intensified.     

        levelno = args[1].levelno
        if(levelno>=50):
            color = BACKGROUND_YELLOW | FOREGROUND_RED | FOREGROUND_INTENSITY | BACKGROUND_INTENSITY 
        elif(levelno>=40):
            color = FOREGROUND_RED | FOREGROUND_INTENSITY
        elif(levelno>=30):
            color = FOREGROUND_YELLOW | FOREGROUND_INTENSITY
        elif(levelno>=20):
            color = FOREGROUND_GREEN
        elif(levelno>=10):
            color = FOREGROUND_MAGENTA
        else:
            color =  FOREGROUND_WHITE
        args[0]._set_color(color)

        ret = fn(*args)
        args[0]._set_color( FOREGROUND_WHITE )
        #print "after"
        return ret
    return new

def add_coloring_to_emit_ansi(fn):
    # add methods we need to the class
    def new(*args):
        levelno = args[1].levelno
        if(levelno>=50):
            color = '\x1b[31m' # red
        elif(levelno>=40):
            color = '\x1b[31m' # red
        elif(levelno>=30):
            color = '\x1b[33m' # yellow
        elif(levelno>=20):
            color = '\x1b[32m' # green 
        elif(levelno>=10):
            color = '\x1b[35m' # pink
        else:
            color = '\x1b[0m' # normal
        args[1].msg = color + args[1].msg +  '\x1b[0m'  # normal
        #print "after"
        return fn(*args)
    return new

import platform
if platform.system()=='Windows':
    # Windows does not support ANSI escapes and we are using API calls to set the console color
    logging.StreamHandler.emit = add_coloring_to_emit_windows(logging.StreamHandler.emit)
else:
    # all non-Windows platforms are supporting ANSI escapes so we use them
    logging.StreamHandler.emit = add_coloring_to_emit_ansi(logging.StreamHandler.emit)
    #log = logging.getLogger()
    #log.addFilter(log_filter())
    #//hdlr = logging.StreamHandler()
    #//hdlr.setFormatter(formatter())

回答 3

更新：因为这是我很久以来一直想抓痒的痒，所以我继续为像我这样的懒人编写了一个库，这些人只想简单地做事： zenlog

Colorlog对此非常有用。它可以在PyPI上使用（因此可以通过安装pip install colorlog），并可以进行积极维护。

这是一个快速复制粘贴的代码段，用于设置日志记录并打印看起来不错的日志消息：

import logging
LOG_LEVEL = logging.DEBUG
LOGFORMAT = "  %(log_color)s%(levelname)-8s%(reset)s | %(log_color)s%(message)s%(reset)s"
from colorlog import ColoredFormatter
logging.root.setLevel(LOG_LEVEL)
formatter = ColoredFormatter(LOGFORMAT)
stream = logging.StreamHandler()
stream.setLevel(LOG_LEVEL)
stream.setFormatter(formatter)
log = logging.getLogger('pythonConfig')
log.setLevel(LOG_LEVEL)
log.addHandler(stream)

log.debug("A quirky message only developers care about")
log.info("Curious users might want to know this")
log.warn("Something is wrong and any user should be informed")
log.error("Serious stuff, this is red for a reason")
log.critical("OH NO everything is on fire")

输出：

Update: Because this is an itch that I’ve been meaning to scratch for so long, I went ahead and wrote a library for lazy people like me who just want simple ways to do things: zenlog

Colorlog is excellent for this. It’s available on PyPI (and thus installable through pip install colorlog) and is actively maintained.

Here’s a quick copy-and-pasteable snippet to set up logging and print decent-looking log messages:

import logging
LOG_LEVEL = logging.DEBUG
LOGFORMAT = "  %(log_color)s%(levelname)-8s%(reset)s | %(log_color)s%(message)s%(reset)s"
from colorlog import ColoredFormatter
logging.root.setLevel(LOG_LEVEL)
formatter = ColoredFormatter(LOGFORMAT)
stream = logging.StreamHandler()
stream.setLevel(LOG_LEVEL)
stream.setFormatter(formatter)
log = logging.getLogger('pythonConfig')
log.setLevel(LOG_LEVEL)
log.addHandler(stream)

log.debug("A quirky message only developers care about")
log.info("Curious users might want to know this")
log.warn("Something is wrong and any user should be informed")
log.error("Serious stuff, this is red for a reason")
log.critical("OH NO everything is on fire")

Output:

回答 4

快速而肮脏的解决方案，用于预定义的日志级别，而无需定义新类。

logging.addLevelName( logging.WARNING, "\033[1;31m%s\033[1;0m" % logging.getLevelName(logging.WARNING))
logging.addLevelName( logging.ERROR, "\033[1;41m%s\033[1;0m" % logging.getLevelName(logging.ERROR))

Quick and dirty solution for predefined log levels and without defining a new class.

logging.addLevelName( logging.WARNING, "\033[1;31m%s\033[1;0m" % logging.getLevelName(logging.WARNING))
logging.addLevelName( logging.ERROR, "\033[1;41m%s\033[1;0m" % logging.getLevelName(logging.ERROR))

回答 5

2020代码，无需其他软件包，Python 3

定义一个Class

import logging

class CustomFormatter(logging.Formatter):
    """Logging Formatter to add colors and count warning / errors"""

    grey = "\x1b[38;21m"
    yellow = "\x1b[33;21m"
    red = "\x1b[31;21m"
    bold_red = "\x1b[31;1m"
    reset = "\x1b[0m"
    format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s (%(filename)s:%(lineno)d)"

    FORMATS = {
        logging.DEBUG: grey + format + reset,
        logging.INFO: grey + format + reset,
        logging.WARNING: yellow + format + reset,
        logging.ERROR: red + format + reset,
        logging.CRITICAL: bold_red + format + reset
    }

    def format(self, record):
        log_fmt = self.FORMATS.get(record.levelno)
        formatter = logging.Formatter(log_fmt)
        return formatter.format(record)

实例化记录器

# create logger with 'spam_application'
logger = logging.getLogger("My_app")
logger.setLevel(logging.DEBUG)

# create console handler with a higher log level
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)

ch.setFormatter(CustomFormatter())

logger.addHandler(ch)

并使用！

logger.debug("debug message")
logger.info("info message")
logger.warning("warning message")
logger.error("error message")
logger.critical("critical message")

结果

全彩方案

对于窗户

此解决方案可在Mac OS，IDE终端上使用。看起来window的命令提示符在默认情况下根本没有颜色。以下是如何启用它们的说明，我没有尝试过这些说明https://www.howtogeek.com/322432/how-to-customize-your-command-prompts-color-scheme-with-microsofts-colortool/

2020 code, no additional packages required, Python 3

Define a class

import logging

class CustomFormatter(logging.Formatter):
    """Logging Formatter to add colors and count warning / errors"""

    grey = "\x1b[38;21m"
    yellow = "\x1b[33;21m"
    red = "\x1b[31;21m"
    bold_red = "\x1b[31;1m"
    reset = "\x1b[0m"
    format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s (%(filename)s:%(lineno)d)"

    FORMATS = {
        logging.DEBUG: grey + format + reset,
        logging.INFO: grey + format + reset,
        logging.WARNING: yellow + format + reset,
        logging.ERROR: red + format + reset,
        logging.CRITICAL: bold_red + format + reset
    }

    def format(self, record):
        log_fmt = self.FORMATS.get(record.levelno)
        formatter = logging.Formatter(log_fmt)
        return formatter.format(record)

Instantiate logger

# create logger with 'spam_application'
logger = logging.getLogger("My_app")
logger.setLevel(logging.DEBUG)

# create console handler with a higher log level
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)

ch.setFormatter(CustomFormatter())

logger.addHandler(ch)

And use!

logger.debug("debug message")
logger.info("info message")
logger.warning("warning message")
logger.error("error message")
logger.critical("critical message")

Result

The full color scheme

For windows

This solution works on Mac OS, IDE terminals. Looks like window’s command prompt doesn’t have colors at all by default. Here are instructions how to enable them, which I haven’t try https://www.howtogeek.com/322432/how-to-customize-your-command-prompts-color-scheme-with-microsofts-colortool/

回答 6

好吧，我想我也应该添加我的彩色记录器版本。

这没什么花哨的，但是它使用起来非常简单并且不会更改记录对象，从而避免了在使用文件处理程序的情况下将ANSI转义序列记录到日志文件中。它不会影响日志消息的格式。

如果您已经在使用日志记录模块的Formatter，则要获取彩色级别名称，只需将您的顾问处理程序Formatter替换为ColoredFormatter即可。如果要记录整个应用程序，则只需要对顶级记录器执行此操作。

Colored_log.py

#!/usr/bin/env python

from copy import copy
from logging import Formatter

MAPPING = {
    'DEBUG'   : 37, # white
    'INFO'    : 36, # cyan
    'WARNING' : 33, # yellow
    'ERROR'   : 31, # red
    'CRITICAL': 41, # white on red bg
}

PREFIX = '\033['
SUFFIX = '\033[0m'

class ColoredFormatter(Formatter):

    def __init__(self, patern):
        Formatter.__init__(self, patern)

    def format(self, record):
        colored_record = copy(record)
        levelname = colored_record.levelname
        seq = MAPPING.get(levelname, 37) # default white
        colored_levelname = ('{0}{1}m{2}{3}') \
            .format(PREFIX, seq, levelname, SUFFIX)
        colored_record.levelname = colored_levelname
        return Formatter.format(self, colored_record)

用法示例

app.py

#!/usr/bin/env python

import logging
from colored_log import ColoredFormatter

# Create top level logger
log = logging.getLogger("main")

# Add console handler using our custom ColoredFormatter
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
cf = ColoredFormatter("[%(name)s][%(levelname)s]  %(message)s (%(filename)s:%(lineno)d)")
ch.setFormatter(cf)
log.addHandler(ch)

# Add file handler
fh = logging.FileHandler('app.log')
fh.setLevel(logging.DEBUG)
ff = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
fh.setFormatter(ff)
log.addHandler(fh)

# Set log level
log.setLevel(logging.DEBUG)

# Log some stuff
log.debug("app has started")
log.info("Logging to 'app.log' in the script dir")
log.warning("This is my last warning, take heed")
log.error("This is an error")
log.critical("He's dead, Jim")

# Import a sub-module 
import sub_module

sub_module.py

#!/usr/bin/env python

import logging
log = logging.getLogger('main.sub_module')

log.debug("Hello from the sub module")

结果

终端输出

app.log内容

2017-09-29 00:32:23,434 - main - DEBUG - app has started
2017-09-29 00:32:23,434 - main - INFO - Logging to 'app.log' in the script dir
2017-09-29 00:32:23,435 - main - WARNING - This is my last warning, take heed
2017-09-29 00:32:23,435 - main - ERROR - This is an error
2017-09-29 00:32:23,435 - main - CRITICAL - He's dead, Jim
2017-09-29 00:32:23,435 - main.sub_module - DEBUG - Hello from the sub module

当然，通过格式化终端和日志文件输出，您可以得到所需的效果。仅日志级别将被着色。

我希望有人觉得这有用，并且不仅仅是太多了。:)

可以从GitHub Gist下载Python示例文件：https : //gist.github.com/KurtJacobson/48e750701acec40c7161b5a2f79e6bfd

Well, I guess I might as well add my variation of the colored logger.

This is nothing fancy, but it is very simple to use and does not change the record object, thereby avoids logging the ANSI escape sequences to a log file if a file handler is used. It does not effect the log message formatting.

If you are already using the logging module’s Formatter, all you have to do to get colored level names is to replace your counsel handlers Formatter with the ColoredFormatter. If you are logging an entire app you only need to do this for the top level logger.

colored_log.py

#!/usr/bin/env python

from copy import copy
from logging import Formatter

MAPPING = {
    'DEBUG'   : 37, # white
    'INFO'    : 36, # cyan
    'WARNING' : 33, # yellow
    'ERROR'   : 31, # red
    'CRITICAL': 41, # white on red bg
}

PREFIX = '\033['
SUFFIX = '\033[0m'

class ColoredFormatter(Formatter):

    def __init__(self, patern):
        Formatter.__init__(self, patern)

    def format(self, record):
        colored_record = copy(record)
        levelname = colored_record.levelname
        seq = MAPPING.get(levelname, 37) # default white
        colored_levelname = ('{0}{1}m{2}{3}') \
            .format(PREFIX, seq, levelname, SUFFIX)
        colored_record.levelname = colored_levelname
        return Formatter.format(self, colored_record)

Example usage

app.py

#!/usr/bin/env python

import logging
from colored_log import ColoredFormatter

# Create top level logger
log = logging.getLogger("main")

# Add console handler using our custom ColoredFormatter
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
cf = ColoredFormatter("[%(name)s][%(levelname)s]  %(message)s (%(filename)s:%(lineno)d)")
ch.setFormatter(cf)
log.addHandler(ch)

# Add file handler
fh = logging.FileHandler('app.log')
fh.setLevel(logging.DEBUG)
ff = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
fh.setFormatter(ff)
log.addHandler(fh)

# Set log level
log.setLevel(logging.DEBUG)

# Log some stuff
log.debug("app has started")
log.info("Logging to 'app.log' in the script dir")
log.warning("This is my last warning, take heed")
log.error("This is an error")
log.critical("He's dead, Jim")

# Import a sub-module 
import sub_module

sub_module.py

#!/usr/bin/env python

import logging
log = logging.getLogger('main.sub_module')

log.debug("Hello from the sub module")

Results

Terminal output

app.log content

2017-09-29 00:32:23,434 - main - DEBUG - app has started
2017-09-29 00:32:23,434 - main - INFO - Logging to 'app.log' in the script dir
2017-09-29 00:32:23,435 - main - WARNING - This is my last warning, take heed
2017-09-29 00:32:23,435 - main - ERROR - This is an error
2017-09-29 00:32:23,435 - main - CRITICAL - He's dead, Jim
2017-09-29 00:32:23,435 - main.sub_module - DEBUG - Hello from the sub module

Of course you can get as fancy as you want with formatting the terminal and log file outputs. Only the log level will be colorized.

I hope somebody finds this useful and it is not just too much more of the same. :)

The Python example files can be downloaded from this GitHub Gist: https://gist.github.com/KurtJacobson/48e750701acec40c7161b5a2f79e6bfd

回答 7

我从airmind支持前景和背景标签更新了该示例。只需在日志格式化程序字符串中使用颜色变量$ BLACK-$ WHITE。要设置背景，只需使用$ BG-BLACK-$ BG-WHITE。

import logging

BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8)

COLORS = {
    'WARNING'  : YELLOW,
    'INFO'     : WHITE,
    'DEBUG'    : BLUE,
    'CRITICAL' : YELLOW,
    'ERROR'    : RED,
    'RED'      : RED,
    'GREEN'    : GREEN,
    'YELLOW'   : YELLOW,
    'BLUE'     : BLUE,
    'MAGENTA'  : MAGENTA,
    'CYAN'     : CYAN,
    'WHITE'    : WHITE,
}

RESET_SEQ = "\033[0m"
COLOR_SEQ = "\033[1;%dm"
BOLD_SEQ  = "\033[1m"

class ColorFormatter(logging.Formatter):

    def __init__(self, *args, **kwargs):
        # can't do super(...) here because Formatter is an old school class
        logging.Formatter.__init__(self, *args, **kwargs)

    def format(self, record):
        levelname = record.levelname
        color     = COLOR_SEQ % (30 + COLORS[levelname])
        message   = logging.Formatter.format(self, record)
        message   = message.replace("$RESET", RESET_SEQ)\
                           .replace("$BOLD",  BOLD_SEQ)\
                           .replace("$COLOR", color)
        for k,v in COLORS.items():
            message = message.replace("$" + k,    COLOR_SEQ % (v+30))\
                             .replace("$BG" + k,  COLOR_SEQ % (v+40))\
                             .replace("$BG-" + k, COLOR_SEQ % (v+40))
        return message + RESET_SEQ

logging.ColorFormatter = ColorFormatter

因此，现在您可以在配置文件中简单地执行以下操作：

[formatter_colorFormatter]
class=logging.ColorFormatter
format= $COLOR%(levelname)s $RESET %(asctime)s $BOLD$COLOR%(name)s$RESET %(message)s

I updated the example from airmind supporting tags for foreground and background. Just use the color variables $BLACK – $WHITE in your log formatter string. To set the background just use $BG-BLACK – $BG-WHITE.

import logging

BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8)

COLORS = {
    'WARNING'  : YELLOW,
    'INFO'     : WHITE,
    'DEBUG'    : BLUE,
    'CRITICAL' : YELLOW,
    'ERROR'    : RED,
    'RED'      : RED,
    'GREEN'    : GREEN,
    'YELLOW'   : YELLOW,
    'BLUE'     : BLUE,
    'MAGENTA'  : MAGENTA,
    'CYAN'     : CYAN,
    'WHITE'    : WHITE,
}

RESET_SEQ = "\033[0m"
COLOR_SEQ = "\033[1;%dm"
BOLD_SEQ  = "\033[1m"

class ColorFormatter(logging.Formatter):

    def __init__(self, *args, **kwargs):
        # can't do super(...) here because Formatter is an old school class
        logging.Formatter.__init__(self, *args, **kwargs)

    def format(self, record):
        levelname = record.levelname
        color     = COLOR_SEQ % (30 + COLORS[levelname])
        message   = logging.Formatter.format(self, record)
        message   = message.replace("$RESET", RESET_SEQ)\
                           .replace("$BOLD",  BOLD_SEQ)\
                           .replace("$COLOR", color)
        for k,v in COLORS.items():
            message = message.replace("$" + k,    COLOR_SEQ % (v+30))\
                             .replace("$BG" + k,  COLOR_SEQ % (v+40))\
                             .replace("$BG-" + k, COLOR_SEQ % (v+40))
        return message + RESET_SEQ

logging.ColorFormatter = ColorFormatter

So now you can simple do the following in your config file:

[formatter_colorFormatter]
class=logging.ColorFormatter
format= $COLOR%(levelname)s $RESET %(asctime)s $BOLD$COLOR%(name)s$RESET %(message)s

回答 8

您可以导入colorlog模块并使用其ColoredFormatter用于为日志消息着色。

例

主模块样板：

import logging
import os
import sys
try:
    import colorlog
except ImportError:
    pass

def setup_logging():
    root = logging.getLogger()
    root.setLevel(logging.DEBUG)
    format      = '%(asctime)s - %(levelname)-8s - %(message)s'
    date_format = '%Y-%m-%d %H:%M:%S'
    if 'colorlog' in sys.modules and os.isatty(2):
        cformat = '%(log_color)s' + format
        f = colorlog.ColoredFormatter(cformat, date_format,
              log_colors = { 'DEBUG'   : 'reset',       'INFO' : 'reset',
                             'WARNING' : 'bold_yellow', 'ERROR': 'bold_red',
                             'CRITICAL': 'bold_red' })
    else:
        f = logging.Formatter(format, date_format)
    ch = logging.StreamHandler()
    ch.setFormatter(f)
    root.addHandler(ch)

setup_logging()
log = logging.getLogger(__name__)

该代码仅在安装了colorlog模块并且输出实际到达终端时才在日志消息中启用颜色。这样可以避免在重定向日志输出时将转义序列写入文件。

另外，设置了自定义配色方案，该方案更适合于深色背景的终端。

一些记录调用示例：

log.debug   ('Hello Debug')
log.info    ('Hello Info')
log.warn    ('Hello Warn')
log.error   ('Hello Error')
log.critical('Hello Critical')

输出：

You can import the colorlog module and use its ColoredFormatter for colorizing log messages.

Example

Boilerplate for main module:

import logging
import os
import sys
try:
    import colorlog
except ImportError:
    pass

def setup_logging():
    root = logging.getLogger()
    root.setLevel(logging.DEBUG)
    format      = '%(asctime)s - %(levelname)-8s - %(message)s'
    date_format = '%Y-%m-%d %H:%M:%S'
    if 'colorlog' in sys.modules and os.isatty(2):
        cformat = '%(log_color)s' + format
        f = colorlog.ColoredFormatter(cformat, date_format,
              log_colors = { 'DEBUG'   : 'reset',       'INFO' : 'reset',
                             'WARNING' : 'bold_yellow', 'ERROR': 'bold_red',
                             'CRITICAL': 'bold_red' })
    else:
        f = logging.Formatter(format, date_format)
    ch = logging.StreamHandler()
    ch.setFormatter(f)
    root.addHandler(ch)

setup_logging()
log = logging.getLogger(__name__)

The code only enables colors in log messages, if the colorlog module is installed and if the output actually goes to a terminal. This avoids escape sequences being written to a file when the log output is redirected.

Also, a custom color scheme is setup that is better suited for terminals with dark background.

Some example logging calls:

log.debug   ('Hello Debug')
log.info    ('Hello Info')
log.warn    ('Hello Warn')
log.error   ('Hello Error')
log.critical('Hello Critical')

Output:

回答 9

查看以下解决方案。流处理程序应该是进行着色的东西，然后您可以选择对单词进行着色，而不仅仅是对整个行（使用Formatter）进行着色。

http://plumberjack.blogspot.com/2010/12/colorizing-logging-output-in-terminals.html

Look at the following solution. The stream handler should be the thing doing the colouring, then you have the option of colouring words rather than just the whole line (with the Formatter).

http://plumberjack.blogspot.com/2010/12/colorizing-logging-output-in-terminals.html

回答 10

我修改了Sorin提供的原始示例，并将StreamHandler子类化为ColorizedConsoleHandler。

他们解决方案的缺点是它修改了消息，并且因为这是在修改实际的日志消息，所以其他任何处理程序也将获得修改后的消息。

在我们的例子中，这导致在日志文件中带有颜色代码，因为我们使用了多个记录器。

下面的类仅在支持ansi的平台上起作用，但是向其添加Windows颜色代码应该是微不足道的。

import copy
import logging


class ColoredConsoleHandler(logging.StreamHandler):
    def emit(self, record):
        # Need to make a actual copy of the record
        # to prevent altering the message for other loggers
        myrecord = copy.copy(record)
        levelno = myrecord.levelno
        if(levelno >= 50):  # CRITICAL / FATAL
            color = '\x1b[31m'  # red
        elif(levelno >= 40):  # ERROR
            color = '\x1b[31m'  # red
        elif(levelno >= 30):  # WARNING
            color = '\x1b[33m'  # yellow
        elif(levelno >= 20):  # INFO
            color = '\x1b[32m'  # green
        elif(levelno >= 10):  # DEBUG
            color = '\x1b[35m'  # pink
        else:  # NOTSET and anything else
            color = '\x1b[0m'  # normal
        myrecord.msg = color + str(myrecord.msg) + '\x1b[0m'  # normal
        logging.StreamHandler.emit(self, myrecord)

I modified the original example provided by Sorin and subclassed StreamHandler to a ColorizedConsoleHandler.

The downside of their solution is that it modifies the message, and because that is modifying the actual logmessage any other handlers will get the modified message as well.

This resulted in logfiles with colorcodes in them in our case because we use multiple loggers.

The class below only works on platforms that support ansi, but it should be trivial to add the windows colorcodes to it.

import copy
import logging


class ColoredConsoleHandler(logging.StreamHandler):
    def emit(self, record):
        # Need to make a actual copy of the record
        # to prevent altering the message for other loggers
        myrecord = copy.copy(record)
        levelno = myrecord.levelno
        if(levelno >= 50):  # CRITICAL / FATAL
            color = '\x1b[31m'  # red
        elif(levelno >= 40):  # ERROR
            color = '\x1b[31m'  # red
        elif(levelno >= 30):  # WARNING
            color = '\x1b[33m'  # yellow
        elif(levelno >= 20):  # INFO
            color = '\x1b[32m'  # green
        elif(levelno >= 10):  # DEBUG
            color = '\x1b[35m'  # pink
        else:  # NOTSET and anything else
            color = '\x1b[0m'  # normal
        myrecord.msg = color + str(myrecord.msg) + '\x1b[0m'  # normal
        logging.StreamHandler.emit(self, myrecord)

回答 11

现在有一个已发布的PyPi模块，用于自定义彩色日志输出：

https://pypi.python.org/pypi/rainbow_logging_handler/

和

https://github.com/laysakura/rainbow_logging_handler

支持Windows
支持Django
可自定义的颜色

由于它是作为Python鸡蛋分发的，因此对于任何Python应用程序都非常容易安装。

Now there is a released PyPi module for customizable colored logging output:

https://pypi.python.org/pypi/rainbow_logging_handler/

and

https://github.com/laysakura/rainbow_logging_handler

Supports Windows
Supports Django
Customizable colors

As this is distributed as a Python egg, it is very easy to install for any Python application.

回答 12

有很多回应。但是没有人在谈论装饰器。所以这是我的。

因为它要简单得多。

无需导入任何内容，也无需编写任何子类：

#!/usr/bin/env python
# -*- coding: utf-8 -*-


import logging


NO_COLOR = "\33[m"
RED, GREEN, ORANGE, BLUE, PURPLE, LBLUE, GREY = \
    map("\33[%dm".__mod__, range(31, 38))

logging.basicConfig(format="%(message)s", level=logging.DEBUG)
logger = logging.getLogger(__name__)

# the decorator to apply on the logger methods info, warn, ...
def add_color(logger_method, color):
  def wrapper(message, *args, **kwargs):
    return logger_method(
      # the coloring is applied here.
      color+message+NO_COLOR,
      *args, **kwargs
    )
  return wrapper

for level, color in zip((
  "info", "warn", "error", "debug"), (
  GREEN, ORANGE, RED, BLUE
)):
  setattr(logger, level, add_color(getattr(logger, level), color))

# this is displayed in red.
logger.error("Launching %s." % __file__)

这会将错误设置为红色，将调试消息设置为蓝色，依此类推。喜欢问的问题。

我们甚至可以使包装纸适应 color参数来动态设置消息的颜色：logger.debug("message", color=GREY)

编辑：因此，这是在运行时设置颜色的适应性装饰器：

def add_color(logger_method, _color):
  def wrapper(message, *args, **kwargs):
    color = kwargs.pop("color", _color)
    if isinstance(color, int):
      color = "\33[%dm" % color
    return logger_method(
      # the coloring is applied here.
      color+message+NO_COLOR,
      *args, **kwargs
    )
  return wrapper

# blah blah, apply the decorator...

# this is displayed in red.
logger.error("Launching %s." % __file__)
# this is displayed in blue
logger.error("Launching %s." % __file__, color=34)
# and this, in grey
logger.error("Launching %s." % __file__, color=GREY)

There are tons of responses. But none is talking about decorators. So here’s mine.

Because it is a lot more simple.

There’s no need to import anything, nor to write any subclass:

#!/usr/bin/env python
# -*- coding: utf-8 -*-


import logging


NO_COLOR = "\33[m"
RED, GREEN, ORANGE, BLUE, PURPLE, LBLUE, GREY = \
    map("\33[%dm".__mod__, range(31, 38))

logging.basicConfig(format="%(message)s", level=logging.DEBUG)
logger = logging.getLogger(__name__)

# the decorator to apply on the logger methods info, warn, ...
def add_color(logger_method, color):
  def wrapper(message, *args, **kwargs):
    return logger_method(
      # the coloring is applied here.
      color+message+NO_COLOR,
      *args, **kwargs
    )
  return wrapper

for level, color in zip((
  "info", "warn", "error", "debug"), (
  GREEN, ORANGE, RED, BLUE
)):
  setattr(logger, level, add_color(getattr(logger, level), color))

# this is displayed in red.
logger.error("Launching %s." % __file__)

This set the errors in red, debug messages in blue, and so on. Like asked in the question.

We could even adapt the wrapper to take a color argument to dynamicaly set the message’s color using logger.debug("message", color=GREY)

EDIT: So here’s the adapted decorator to set colors at runtime:

def add_color(logger_method, _color):
  def wrapper(message, *args, **kwargs):
    color = kwargs.pop("color", _color)
    if isinstance(color, int):
      color = "\33[%dm" % color
    return logger_method(
      # the coloring is applied here.
      color+message+NO_COLOR,
      *args, **kwargs
    )
  return wrapper

# blah blah, apply the decorator...

# this is displayed in red.
logger.error("Launching %s." % __file__)
# this is displayed in blue
logger.error("Launching %s." % __file__, color=34)
# and this, in grey
logger.error("Launching %s." % __file__, color=GREY)

回答 13

Airmind方法的另一种小混搭，使所有内容都保持同一类：

class ColorFormatter(logging.Formatter):
  FORMAT = ("[$BOLD%(name)-20s$RESET][%(levelname)-18s]  "
            "%(message)s "
            "($BOLD%(filename)s$RESET:%(lineno)d)")

  BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8)

  RESET_SEQ = "\033[0m"
  COLOR_SEQ = "\033[1;%dm"
  BOLD_SEQ = "\033[1m"

  COLORS = {
    'WARNING': YELLOW,
    'INFO': WHITE,
    'DEBUG': BLUE,
    'CRITICAL': YELLOW,
    'ERROR': RED
  }

  def formatter_msg(self, msg, use_color = True):
    if use_color:
      msg = msg.replace("$RESET", self.RESET_SEQ).replace("$BOLD", self.BOLD_SEQ)
    else:
      msg = msg.replace("$RESET", "").replace("$BOLD", "")
    return msg

  def __init__(self, use_color=True):
    msg = self.formatter_msg(self.FORMAT, use_color)
    logging.Formatter.__init__(self, msg)
    self.use_color = use_color

  def format(self, record):
    levelname = record.levelname
    if self.use_color and levelname in self.COLORS:
      fore_color = 30 + self.COLORS[levelname]
      levelname_color = self.COLOR_SEQ % fore_color + levelname + self.RESET_SEQ
      record.levelname = levelname_color
    return logging.Formatter.format(self, record)

要将格式化程序附加到处理程序，例如：

handler.setFormatter(ColorFormatter())
logger.addHandler(handler)

Another minor remix of airmind’s approach that keeps everything in one class:

class ColorFormatter(logging.Formatter):
  FORMAT = ("[$BOLD%(name)-20s$RESET][%(levelname)-18s]  "
            "%(message)s "
            "($BOLD%(filename)s$RESET:%(lineno)d)")

  BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8)

  RESET_SEQ = "\033[0m"
  COLOR_SEQ = "\033[1;%dm"
  BOLD_SEQ = "\033[1m"

  COLORS = {
    'WARNING': YELLOW,
    'INFO': WHITE,
    'DEBUG': BLUE,
    'CRITICAL': YELLOW,
    'ERROR': RED
  }

  def formatter_msg(self, msg, use_color = True):
    if use_color:
      msg = msg.replace("$RESET", self.RESET_SEQ).replace("$BOLD", self.BOLD_SEQ)
    else:
      msg = msg.replace("$RESET", "").replace("$BOLD", "")
    return msg

  def __init__(self, use_color=True):
    msg = self.formatter_msg(self.FORMAT, use_color)
    logging.Formatter.__init__(self, msg)
    self.use_color = use_color

  def format(self, record):
    levelname = record.levelname
    if self.use_color and levelname in self.COLORS:
      fore_color = 30 + self.COLORS[levelname]
      levelname_color = self.COLOR_SEQ % fore_color + levelname + self.RESET_SEQ
      record.levelname = levelname_color
    return logging.Formatter.format(self, record)

To use attach the formatter to a handler, something like:

handler.setFormatter(ColorFormatter())
logger.addHandler(handler)

回答 14

一个简单但非常灵活的工具，可以为任何终端文本加上颜色是’ colout ‘。

pip install colout
myprocess | colout REGEX_WITH_GROUPS color1,color2...

如果“ myprocess”的输出中与正则表达式的第1组匹配的任何文本将使用color1进行着色，将第2组使用color2进行着色，等等。

例如：

tail -f /var/log/mylogfile | colout '^(\w+ \d+ [\d:]+)|(\w+\.py:\d+ .+\(\)): (.+)$' white,black,cyan bold,bold,normal

也就是说，第一个正则表达式组（parens）与日志文件中的初始日期匹配，第二个正则表达式组与python文件名，行号和函数名称匹配，而第三组则匹配之后的日志消息。我还使用了并行的“粗体/法线”序列以及颜色序列。看起来像：

请注意，与我的任何正则表达式都不匹配的行或行的部分仍会回显，因此这与’grep –color’并不一样-输出不会过滤掉任何内容。

显然，这足够灵活，您可以将其用于任何进程，而不仅仅是尾随日志文件。我通常想在任何时候给某物上色的过程中，都会立即制作一个新的正则表达式。因此，我喜欢使用colout而不是任何自定义日志文件着色工具，因为无论我要着色什么，我都只需要学习一种工具：日志记录，测试输出，终端中语法高亮的代码片段等。

它还避免实际在日志文件本身中转储ANSI代码，这是个不好的主意，因为除非您始终记得在grep regex中匹配ANSI代码，否则它会破坏对日志文件中的模式进行grepping之类的操作。

A simple but very flexible tool for coloring ANY terminal text is ‘colout‘.

pip install colout
myprocess | colout REGEX_WITH_GROUPS color1,color2...

Where any text in the output of ‘myprocess’ which matches group 1 of the regex will be colored with color1, group 2 with color2, etc.

For example:

tail -f /var/log/mylogfile | colout '^(\w+ \d+ [\d:]+)|(\w+\.py:\d+ .+\(\)): (.+)$' white,black,cyan bold,bold,normal

i.e. the first regex group (parens) matches the initial date in the logfile, the second group matches a python filename, line number and function name, and the third group matches the log message that comes after that. I also use a parallel sequence of ‘bold/normals’ as well as the sequence of colors. This looks like:

Note that lines or parts of lines which don’t match any of my regex are still echoed, so this isn’t like ‘grep –color’ – nothing is filtered out of the output.

Obviously this is flexible enough that you can use it with any process, not just tailing logfiles. I usually just whip up a new regex on the fly any time I want to colorize something. For this reason, I prefer colout to any custom logfile-coloring tool, because I only need to learn one tool, regardless of what I’m coloring: logging, test output, syntax highlighting snippets of code in the terminal, etc.

It also avoids actually dumping ANSI codes in the logfile itself, which IMHO is a bad idea, because it will break things like grepping for patterns in the logfile unless you always remember to match the ANSI codes in your grep regex.

回答 15

import logging
import sys

colors = {'pink': '\033[95m', 'blue': '\033[94m', 'green': '\033[92m', 'yellow': '\033[93m', 'red': '\033[91m',
      'ENDC': '\033[0m', 'bold': '\033[1m', 'underline': '\033[4m'}

logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)


def str_color(color, data):
    return colors[color] + str(data) + colors['ENDC']

params = {'param1': id1, 'param2': id2}

logging.info('\nParams:' + str_color("blue", str(params)))`

import logging
import sys

colors = {'pink': '\033[95m', 'blue': '\033[94m', 'green': '\033[92m', 'yellow': '\033[93m', 'red': '\033[91m',
      'ENDC': '\033[0m', 'bold': '\033[1m', 'underline': '\033[4m'}

logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)


def str_color(color, data):
    return colors[color] + str(data) + colors['ENDC']

params = {'param1': id1, 'param2': id2}

logging.info('\nParams:' + str_color("blue", str(params)))`

回答 16

这是我的解决方案：

class ColouredFormatter(logging.Formatter):
    RESET = '\x1B[0m'
    RED = '\x1B[31m'
    YELLOW = '\x1B[33m'
    BRGREEN = '\x1B[01;32m'  # grey in solarized for terminals

    def format(self, record, colour=False):
        message = super().format(record)

        if not colour:
            return message

        level_no = record.levelno
        if level_no >= logging.CRITICAL:
            colour = self.RED
        elif level_no >= logging.ERROR:
            colour = self.RED
        elif level_no >= logging.WARNING:
            colour = self.YELLOW
        elif level_no >= logging.INFO:
            colour = self.RESET
        elif level_no >= logging.DEBUG:
            colour = self.BRGREEN
        else:
            colour = self.RESET

        message = colour + message + self.RESET

        return message


class ColouredHandler(logging.StreamHandler):
    def __init__(self, stream=sys.stdout):
        super().__init__(stream)

    def format(self, record, colour=False):
        if not isinstance(self.formatter, ColouredFormatter):
            self.formatter = ColouredFormatter()

        return self.formatter.format(record, colour)

    def emit(self, record):
        stream = self.stream
        try:
            msg = self.format(record, stream.isatty())
            stream.write(msg)
            stream.write(self.terminator)
            self.flush()
        except Exception:
            self.handleError(record)


h = ColouredHandler()
h.formatter = ColouredFormatter('{asctime} {levelname:8} {message}', '%Y-%m-%d %H:%M:%S', '{')
logging.basicConfig(level=logging.DEBUG, handlers=[h])

Here’s my solution:

class ColouredFormatter(logging.Formatter):
    RESET = '\x1B[0m'
    RED = '\x1B[31m'
    YELLOW = '\x1B[33m'
    BRGREEN = '\x1B[01;32m'  # grey in solarized for terminals

    def format(self, record, colour=False):
        message = super().format(record)

        if not colour:
            return message

        level_no = record.levelno
        if level_no >= logging.CRITICAL:
            colour = self.RED
        elif level_no >= logging.ERROR:
            colour = self.RED
        elif level_no >= logging.WARNING:
            colour = self.YELLOW
        elif level_no >= logging.INFO:
            colour = self.RESET
        elif level_no >= logging.DEBUG:
            colour = self.BRGREEN
        else:
            colour = self.RESET

        message = colour + message + self.RESET

        return message


class ColouredHandler(logging.StreamHandler):
    def __init__(self, stream=sys.stdout):
        super().__init__(stream)

    def format(self, record, colour=False):
        if not isinstance(self.formatter, ColouredFormatter):
            self.formatter = ColouredFormatter()

        return self.formatter.format(record, colour)

    def emit(self, record):
        stream = self.stream
        try:
            msg = self.format(record, stream.isatty())
            stream.write(msg)
            stream.write(self.terminator)
            self.flush()
        except Exception:
            self.handleError(record)


h = ColouredHandler()
h.formatter = ColouredFormatter('{asctime} {levelname:8} {message}', '%Y-%m-%d %H:%M:%S', '{')
logging.basicConfig(level=logging.DEBUG, handlers=[h])

回答 17

我遇到的麻烦是正确设置了格式化程序：

class ColouredFormatter(logging.Formatter):    
    def __init__(self, msg):
        logging.Formatter.__init__(self, msg)
        self._init_colour = _get_colour()

    def close(self):
        # restore the colour information to what it was
        _set_colour(self._init_colour)

    def format(self, record):        
        # Add your own colourer based on the other examples
        _set_colour( LOG_LEVEL_COLOUR[record.levelno] )
        return logging.Formatter.format(self, record)         

def init():
    # Set up the formatter. Needs to be first thing done.
    rootLogger = logging.getLogger()
    hdlr = logging.StreamHandler()
    fmt = ColouredFormatter('%(message)s')
    hdlr.setFormatter(fmt)
    rootLogger.addHandler(hdlr)

然后使用：

import coloured_log
import logging

coloured_log.init()
logging.info("info")    
logging.debug("debug")    

coloured_log.close()    # restore colours

The bit I had trouble with was setting up the formatter properly:

class ColouredFormatter(logging.Formatter):    
    def __init__(self, msg):
        logging.Formatter.__init__(self, msg)
        self._init_colour = _get_colour()

    def close(self):
        # restore the colour information to what it was
        _set_colour(self._init_colour)

    def format(self, record):        
        # Add your own colourer based on the other examples
        _set_colour( LOG_LEVEL_COLOUR[record.levelno] )
        return logging.Formatter.format(self, record)         

def init():
    # Set up the formatter. Needs to be first thing done.
    rootLogger = logging.getLogger()
    hdlr = logging.StreamHandler()
    fmt = ColouredFormatter('%(message)s')
    hdlr.setFormatter(fmt)
    rootLogger.addHandler(hdlr)

And then to use:

import coloured_log
import logging

coloured_log.init()
logging.info("info")    
logging.debug("debug")    

coloured_log.close()    # restore colours

回答 18

尽管其他解决方案看起来不错，但它们仍有一些问题。有些会为整个行上色，有些时候是不需要的，有些则忽略了您可能一起拥有的任何配置。下面的解决方案只影响消息本身，什么都不会影响。

码

class ColoredFormatter(logging.Formatter):
    def format(self, record):
        if record.levelno == logging.WARNING:
            record.msg = '\033[93m%s\033[0m' % record.msg
        elif record.levelno == logging.ERROR:
            record.msg = '\033[91m%s\033[0m' % record.msg
        return logging.Formatter.format(self, record)

例

logger = logging.getLogger('mylogger')
handler = logging.StreamHandler()

log_format = '[%(asctime)s]:%(levelname)-7s:%(message)s'
time_format = '%H:%M:%S'
formatter = ColoredFormatter(log_format, datefmt=time_format)
handler.setFormatter(formatter)
logger.addHandler(handler)

logger.warn('this should be yellow')
logger.error('this should be red')

输出量

[17:01:36]:WARNING:this should be yellow
[17:01:37]:ERROR  :this should be red

如您所见，其他所有内容仍会输出，并保持其初始颜色。如果您想更改消息以外的任何内容，则只需log_format在示例中将颜色代码传递给即可。

While the other solutions seem fine they have some issues. Some do colour the whole lines which some times is not wanted and some omit any configuration you might have all together. The solution below doesn’t affect anything but the message itself.

Code

class ColoredFormatter(logging.Formatter):
    def format(self, record):
        if record.levelno == logging.WARNING:
            record.msg = '\033[93m%s\033[0m' % record.msg
        elif record.levelno == logging.ERROR:
            record.msg = '\033[91m%s\033[0m' % record.msg
        return logging.Formatter.format(self, record)

Example

logger = logging.getLogger('mylogger')
handler = logging.StreamHandler()

log_format = '[%(asctime)s]:%(levelname)-7s:%(message)s'
time_format = '%H:%M:%S'
formatter = ColoredFormatter(log_format, datefmt=time_format)
handler.setFormatter(formatter)
logger.addHandler(handler)

logger.warn('this should be yellow')
logger.error('this should be red')

Output

[17:01:36]:WARNING:this should be yellow
[17:01:37]:ERROR  :this should be red

As you see, everything else still gets outputted and remain in their initial color. If you want to change anything else than the message you can simply pass the color codes to log_format in the example.

回答 19

我要添加两个提交，其中一个仅使消息着色（ColoredFormatter），而另一个使整个行着色（ColorizingStreamHandler）。与以前的解决方案相比，它们还包含更多的ANSI颜色代码。

一些内容来自（经过修改）：上面的帖子，以及http://plumberjack.blogspot.com/2010/12/colorizing-logging-output-in-terminals.html。

仅使消息着色：

class ColoredFormatter(logging.Formatter):
    """Special custom formatter for colorizing log messages!"""

    BLACK = '\033[0;30m'
    RED = '\033[0;31m'
    GREEN = '\033[0;32m'
    BROWN = '\033[0;33m'
    BLUE = '\033[0;34m'
    PURPLE = '\033[0;35m'
    CYAN = '\033[0;36m'
    GREY = '\033[0;37m'

    DARK_GREY = '\033[1;30m'
    LIGHT_RED = '\033[1;31m'
    LIGHT_GREEN = '\033[1;32m'
    YELLOW = '\033[1;33m'
    LIGHT_BLUE = '\033[1;34m'
    LIGHT_PURPLE = '\033[1;35m'
    LIGHT_CYAN = '\033[1;36m'
    WHITE = '\033[1;37m'

    RESET = "\033[0m"

    def __init__(self, *args, **kwargs):
        self._colors = {logging.DEBUG: self.DARK_GREY,
                        logging.INFO: self.RESET,
                        logging.WARNING: self.BROWN,
                        logging.ERROR: self.RED,
                        logging.CRITICAL: self.LIGHT_RED}
        super(ColoredFormatter, self).__init__(*args, **kwargs)

    def format(self, record):
        """Applies the color formats"""
        record.msg = self._colors[record.levelno] + record.msg + self.RESET
        return logging.Formatter.format(self, record)

    def setLevelColor(self, logging_level, escaped_ansi_code):
        self._colors[logging_level] = escaped_ansi_code

使整个行着色：

class ColorizingStreamHandler(logging.StreamHandler):

    BLACK = '\033[0;30m'
    RED = '\033[0;31m'
    GREEN = '\033[0;32m'
    BROWN = '\033[0;33m'
    BLUE = '\033[0;34m'
    PURPLE = '\033[0;35m'
    CYAN = '\033[0;36m'
    GREY = '\033[0;37m'

    DARK_GREY = '\033[1;30m'
    LIGHT_RED = '\033[1;31m'
    LIGHT_GREEN = '\033[1;32m'
    YELLOW = '\033[1;33m'
    LIGHT_BLUE = '\033[1;34m'
    LIGHT_PURPLE = '\033[1;35m'
    LIGHT_CYAN = '\033[1;36m'
    WHITE = '\033[1;37m'

    RESET = "\033[0m"

    def __init__(self, *args, **kwargs):
        self._colors = {logging.DEBUG: self.DARK_GREY,
                        logging.INFO: self.RESET,
                        logging.WARNING: self.BROWN,
                        logging.ERROR: self.RED,
                        logging.CRITICAL: self.LIGHT_RED}
        super(ColorizingStreamHandler, self).__init__(*args, **kwargs)

    @property
    def is_tty(self):
        isatty = getattr(self.stream, 'isatty', None)
        return isatty and isatty()

    def emit(self, record):
        try:
            message = self.format(record)
            stream = self.stream
            if not self.is_tty:
                stream.write(message)
            else:
                message = self._colors[record.levelno] + message + self.RESET
                stream.write(message)
            stream.write(getattr(self, 'terminator', '\n'))
            self.flush()
        except (KeyboardInterrupt, SystemExit):
            raise
        except:
            self.handleError(record)

    def setLevelColor(self, logging_level, escaped_ansi_code):
        self._colors[logging_level] = escaped_ansi_code

I have two submissions to add, one of which colorizes just the message (ColoredFormatter), and one of which colorizes the entire line (ColorizingStreamHandler). These also include more ANSI color codes than previous solutions.

Some content has been sourced (with modification) from: The post above, and http://plumberjack.blogspot.com/2010/12/colorizing-logging-output-in-terminals.html.

Colorizes the message only:

class ColoredFormatter(logging.Formatter):
    """Special custom formatter for colorizing log messages!"""

    BLACK = '\033[0;30m'
    RED = '\033[0;31m'
    GREEN = '\033[0;32m'
    BROWN = '\033[0;33m'
    BLUE = '\033[0;34m'
    PURPLE = '\033[0;35m'
    CYAN = '\033[0;36m'
    GREY = '\033[0;37m'

    DARK_GREY = '\033[1;30m'
    LIGHT_RED = '\033[1;31m'
    LIGHT_GREEN = '\033[1;32m'
    YELLOW = '\033[1;33m'
    LIGHT_BLUE = '\033[1;34m'
    LIGHT_PURPLE = '\033[1;35m'
    LIGHT_CYAN = '\033[1;36m'
    WHITE = '\033[1;37m'

    RESET = "\033[0m"

    def __init__(self, *args, **kwargs):
        self._colors = {logging.DEBUG: self.DARK_GREY,
                        logging.INFO: self.RESET,
                        logging.WARNING: self.BROWN,
                        logging.ERROR: self.RED,
                        logging.CRITICAL: self.LIGHT_RED}
        super(ColoredFormatter, self).__init__(*args, **kwargs)

    def format(self, record):
        """Applies the color formats"""
        record.msg = self._colors[record.levelno] + record.msg + self.RESET
        return logging.Formatter.format(self, record)

    def setLevelColor(self, logging_level, escaped_ansi_code):
        self._colors[logging_level] = escaped_ansi_code

Colorizes the whole line:

class ColorizingStreamHandler(logging.StreamHandler):

    BLACK = '\033[0;30m'
    RED = '\033[0;31m'
    GREEN = '\033[0;32m'
    BROWN = '\033[0;33m'
    BLUE = '\033[0;34m'
    PURPLE = '\033[0;35m'
    CYAN = '\033[0;36m'
    GREY = '\033[0;37m'

    DARK_GREY = '\033[1;30m'
    LIGHT_RED = '\033[1;31m'
    LIGHT_GREEN = '\033[1;32m'
    YELLOW = '\033[1;33m'
    LIGHT_BLUE = '\033[1;34m'
    LIGHT_PURPLE = '\033[1;35m'
    LIGHT_CYAN = '\033[1;36m'
    WHITE = '\033[1;37m'

    RESET = "\033[0m"

    def __init__(self, *args, **kwargs):
        self._colors = {logging.DEBUG: self.DARK_GREY,
                        logging.INFO: self.RESET,
                        logging.WARNING: self.BROWN,
                        logging.ERROR: self.RED,
                        logging.CRITICAL: self.LIGHT_RED}
        super(ColorizingStreamHandler, self).__init__(*args, **kwargs)

    @property
    def is_tty(self):
        isatty = getattr(self.stream, 'isatty', None)
        return isatty and isatty()

    def emit(self, record):
        try:
            message = self.format(record)
            stream = self.stream
            if not self.is_tty:
                stream.write(message)
            else:
                message = self._colors[record.levelno] + message + self.RESET
                stream.write(message)
            stream.write(getattr(self, 'terminator', '\n'))
            self.flush()
        except (KeyboardInterrupt, SystemExit):
            raise
        except:
            self.handleError(record)

    def setLevelColor(self, logging_level, escaped_ansi_code):
        self._colors[logging_level] = escaped_ansi_code

回答 20

刚刚回答了同样的类似的问题：Python的| 更改外壳中的文本颜色

这个想法是使用clint库。它支持MAC，Linux和Windows Shell（CLI）。

Just answered the same on similar question: Python | change text color in shell

The idea is to use the clint library. Which has support for MAC, Linux and Windows shells (CLI).

回答 21

这是一个包含颜色代码的枚举：

class TerminalColour:
    """
    Terminal colour formatting codes
    """
    # /programming/287871/print-in-terminal-with-colors
    MAGENTA = '\033[95m'
    BLUE = '\033[94m'
    GREEN = '\033[92m'
    YELLOW = '\033[93m'
    RED = '\033[91m'
    GREY = '\033[0m'  # normal
    WHITE = '\033[1m'  # bright white
    UNDERLINE = '\033[4m'

这可以应用于每个日志级别的名称。请注意，这是一个可怕的骇客。

logging.addLevelName(logging.INFO, "{}{}{}".format(TerminalColour.WHITE, logging.getLevelName(logging.INFO), TerminalColour.GREY))
logging.addLevelName(logging.WARNING, "{}{}{}".format(TerminalColour.YELLOW, logging.getLevelName(logging.WARNING), TerminalColour.GREY))
logging.addLevelName(logging.ERROR, "{}{}{}".format(TerminalColour.RED, logging.getLevelName(logging.ERROR), TerminalColour.GREY))
logging.addLevelName(logging.CRITICAL, "{}{}{}".format(TerminalColour.MAGENTA, logging.getLevelName(logging.CRITICAL), .GREY))

请注意，您的日志格式化程序必须包含日志级别的名称

%(levelname)

例如：

    LOGGING = {
...
        'verbose': {
            'format': '%(asctime)s %(levelname)s %(name)s:%(lineno)s %(module)s %(process)d %(thread)d %(message)s'
        },
        'simple': {
            'format': '[%(asctime)s] %(levelname)s %(name)s %(message)s'
        },

This is an Enum containing the colour codes:

class TerminalColour:
    """
    Terminal colour formatting codes
    """
    # https://stackoverflow.com/questions/287871/print-in-terminal-with-colors
    MAGENTA = '\033[95m'
    BLUE = '\033[94m'
    GREEN = '\033[92m'
    YELLOW = '\033[93m'
    RED = '\033[91m'
    GREY = '\033[0m'  # normal
    WHITE = '\033[1m'  # bright white
    UNDERLINE = '\033[4m'

This may be applied to the names of each log level. Be aware that this is a monstrous hack.

logging.addLevelName(logging.INFO, "{}{}{}".format(TerminalColour.WHITE, logging.getLevelName(logging.INFO), TerminalColour.GREY))
logging.addLevelName(logging.WARNING, "{}{}{}".format(TerminalColour.YELLOW, logging.getLevelName(logging.WARNING), TerminalColour.GREY))
logging.addLevelName(logging.ERROR, "{}{}{}".format(TerminalColour.RED, logging.getLevelName(logging.ERROR), TerminalColour.GREY))
logging.addLevelName(logging.CRITICAL, "{}{}{}".format(TerminalColour.MAGENTA, logging.getLevelName(logging.CRITICAL), .GREY))

Note that your log formatter must include the name of the log level

%(levelname)

for example:

    LOGGING = {
...
        'verbose': {
            'format': '%(asctime)s %(levelname)s %(name)s:%(lineno)s %(module)s %(process)d %(thread)d %(message)s'
        },
        'simple': {
            'format': '[%(asctime)s] %(levelname)s %(name)s %(message)s'
        },

回答 22

FriendlyLog是另一种选择。它可以在Linux，Windows和MacOS下与Python 2和3一起使用。

FriendlyLog is another alternative. It works with Python 2 & 3 under Linux, Windows and MacOS.

回答 23

除了按级别着色外，高亮显示日志消息参数时还应使用交替的颜色吗？我最近为此编写了简单的代码。另一个优点是，日志调用是使用Python 3大括号样式的格式进行的。（"{}"）。

在这里查看最新的代码和示例：https : //github.com/davidohana/colargulog

样本记录代码：

root_logger = logging.getLogger()
console_handler = logging.StreamHandler(stream=sys.stdout)
console_format = "%(asctime)s - %(levelname)-8s - %(name)-25s - %(message)s"
colored_formatter = ColorizedArgsFormatter(console_format)
console_handler.setFormatter(colored_formatter)
root_logger.addHandler(console_handler)

logger = logging.getLogger(__name__)
logger.info("Hello World")
logger.info("Request from {} handled in {:.3f} ms", socket.gethostname(), 11)
logger.info("Request from {} handled in {:.3f} ms", "127.0.0.1", 33.1)
logger.info("My favorite drinks are {}, {}, {}, {}", "milk", "wine", "tea", "beer")
logger.debug("this is a {} message", logging.getLevelName(logging.DEBUG))
logger.info("this is a {} message", logging.getLevelName(logging.INFO))
logger.warning("this is a {} message", logging.getLevelName(logging.WARNING))
logger.error("this is a {} message", logging.getLevelName(logging.ERROR))
logger.critical("this is a {} message", logging.getLevelName(logging.CRITICAL))
logger.info("Does old-style formatting also work? %s it is, but no colors (yet)", True)

输出：

实现方式：

"""
colargulog - Python3 Logging with Colored Arguments and new string formatting style

Written by david.ohana@ibm.com
License: Apache-2.0
"""

import logging
import logging.handlers
import re


class ColorCodes:
    grey = "\x1b[38;21m"
    green = "\x1b[1;32m"
    yellow = "\x1b[33;21m"
    red = "\x1b[31;21m"
    bold_red = "\x1b[31;1m"
    blue = "\x1b[1;34m"
    light_blue = "\x1b[1;36m"
    purple = "\x1b[1;35m"
    reset = "\x1b[0m"


class ColorizedArgsFormatter(logging.Formatter):
    arg_colors = [ColorCodes.purple, ColorCodes.light_blue]
    level_fields = ["levelname", "levelno"]
    level_to_color = {
        logging.DEBUG: ColorCodes.grey,
        logging.INFO: ColorCodes.green,
        logging.WARNING: ColorCodes.yellow,
        logging.ERROR: ColorCodes.red,
        logging.CRITICAL: ColorCodes.bold_red,
    }

    def __init__(self, fmt: str):
        super().__init__()
        self.level_to_formatter = {}

        def add_color_format(level: int):
            color = ColorizedArgsFormatter.level_to_color[level]
            _format = fmt
            for fld in ColorizedArgsFormatter.level_fields:
                search = "(%\(" + fld + "\).*?s)"
                _format = re.sub(search, f"{color}\\1{ColorCodes.reset}", _format)
            formatter = logging.Formatter(_format)
            self.level_to_formatter[level] = formatter

        add_color_format(logging.DEBUG)
        add_color_format(logging.INFO)
        add_color_format(logging.WARNING)
        add_color_format(logging.ERROR)
        add_color_format(logging.CRITICAL)

    @staticmethod
    def rewrite_record(record: logging.LogRecord):
        if not BraceFormatStyleFormatter.is_brace_format_style(record):
            return

        msg = record.msg
        msg = msg.replace("{", "_{{")
        msg = msg.replace("}", "_}}")
        placeholder_count = 0
        # add ANSI escape code for next alternating color before each formatting parameter
        # and reset color after it.
        while True:
            if "_{{" not in msg:
                break
            color_index = placeholder_count % len(ColorizedArgsFormatter.arg_colors)
            color = ColorizedArgsFormatter.arg_colors[color_index]
            msg = msg.replace("_{{", color + "{", 1)
            msg = msg.replace("_}}", "}" + ColorCodes.reset, 1)
            placeholder_count += 1

        record.msg = msg.format(*record.args)
        record.args = []

    def format(self, record):
        orig_msg = record.msg
        orig_args = record.args
        formatter = self.level_to_formatter.get(record.levelno)
        self.rewrite_record(record)
        formatted = formatter.format(record)

        # restore log record to original state for other handlers
        record.msg = orig_msg
        record.args = orig_args
        return formatted


class BraceFormatStyleFormatter(logging.Formatter):
    def __init__(self, fmt: str):
        super().__init__()
        self.formatter = logging.Formatter(fmt)

    @staticmethod
    def is_brace_format_style(record: logging.LogRecord):
        if len(record.args) == 0:
            return False

        msg = record.msg
        if '%' in msg:
            return False

        count_of_start_param = msg.count("{")
        count_of_end_param = msg.count("}")

        if count_of_start_param != count_of_end_param:
            return False

        if count_of_start_param != len(record.args):
            return False

        return True

    @staticmethod
    def rewrite_record(record: logging.LogRecord):
        if not BraceFormatStyleFormatter.is_brace_format_style(record):
            return

        record.msg = record.msg.format(*record.args)
        record.args = []

    def format(self, record):
        orig_msg = record.msg
        orig_args = record.args
        self.rewrite_record(record)
        formatted = self.formatter.format(record)

        # restore log record to original state for other handlers
        record.msg = orig_msg
        record.args = orig_args
        return formatted

What about highlighting also log message arguments with alternating colors, in addition to coloring by level? I recently wrote simple code for that. Another advantage is that log call is made with Python 3 brace-style formatting. ("{}").

See latest code and examples here: https://github.com/davidohana/colargulog

Sample Logging code:

root_logger = logging.getLogger()
console_handler = logging.StreamHandler(stream=sys.stdout)
console_format = "%(asctime)s - %(levelname)-8s - %(name)-25s - %(message)s"
colored_formatter = ColorizedArgsFormatter(console_format)
console_handler.setFormatter(colored_formatter)
root_logger.addHandler(console_handler)

logger = logging.getLogger(__name__)
logger.info("Hello World")
logger.info("Request from {} handled in {:.3f} ms", socket.gethostname(), 11)
logger.info("Request from {} handled in {:.3f} ms", "127.0.0.1", 33.1)
logger.info("My favorite drinks are {}, {}, {}, {}", "milk", "wine", "tea", "beer")
logger.debug("this is a {} message", logging.getLevelName(logging.DEBUG))
logger.info("this is a {} message", logging.getLevelName(logging.INFO))
logger.warning("this is a {} message", logging.getLevelName(logging.WARNING))
logger.error("this is a {} message", logging.getLevelName(logging.ERROR))
logger.critical("this is a {} message", logging.getLevelName(logging.CRITICAL))
logger.info("Does old-style formatting also work? %s it is, but no colors (yet)", True)

Output:

Implementation:

"""
colargulog - Python3 Logging with Colored Arguments and new string formatting style

Written by david.ohana@ibm.com
License: Apache-2.0
"""

import logging
import logging.handlers
import re


class ColorCodes:
    grey = "\x1b[38;21m"
    green = "\x1b[1;32m"
    yellow = "\x1b[33;21m"
    red = "\x1b[31;21m"
    bold_red = "\x1b[31;1m"
    blue = "\x1b[1;34m"
    light_blue = "\x1b[1;36m"
    purple = "\x1b[1;35m"
    reset = "\x1b[0m"


class ColorizedArgsFormatter(logging.Formatter):
    arg_colors = [ColorCodes.purple, ColorCodes.light_blue]
    level_fields = ["levelname", "levelno"]
    level_to_color = {
        logging.DEBUG: ColorCodes.grey,
        logging.INFO: ColorCodes.green,
        logging.WARNING: ColorCodes.yellow,
        logging.ERROR: ColorCodes.red,
        logging.CRITICAL: ColorCodes.bold_red,
    }

    def __init__(self, fmt: str):
        super().__init__()
        self.level_to_formatter = {}

        def add_color_format(level: int):
            color = ColorizedArgsFormatter.level_to_color[level]
            _format = fmt
            for fld in ColorizedArgsFormatter.level_fields:
                search = "(%\(" + fld + "\).*?s)"
                _format = re.sub(search, f"{color}\\1{ColorCodes.reset}", _format)
            formatter = logging.Formatter(_format)
            self.level_to_formatter[level] = formatter

        add_color_format(logging.DEBUG)
        add_color_format(logging.INFO)
        add_color_format(logging.WARNING)
        add_color_format(logging.ERROR)
        add_color_format(logging.CRITICAL)

    @staticmethod
    def rewrite_record(record: logging.LogRecord):
        if not BraceFormatStyleFormatter.is_brace_format_style(record):
            return

        msg = record.msg
        msg = msg.replace("{", "_{{")
        msg = msg.replace("}", "_}}")
        placeholder_count = 0
        # add ANSI escape code for next alternating color before each formatting parameter
        # and reset color after it.
        while True:
            if "_{{" not in msg:
                break
            color_index = placeholder_count % len(ColorizedArgsFormatter.arg_colors)
            color = ColorizedArgsFormatter.arg_colors[color_index]
            msg = msg.replace("_{{", color + "{", 1)
            msg = msg.replace("_}}", "}" + ColorCodes.reset, 1)
            placeholder_count += 1

        record.msg = msg.format(*record.args)
        record.args = []

    def format(self, record):
        orig_msg = record.msg
        orig_args = record.args
        formatter = self.level_to_formatter.get(record.levelno)
        self.rewrite_record(record)
        formatted = formatter.format(record)

        # restore log record to original state for other handlers
        record.msg = orig_msg
        record.args = orig_args
        return formatted


class BraceFormatStyleFormatter(logging.Formatter):
    def __init__(self, fmt: str):
        super().__init__()
        self.formatter = logging.Formatter(fmt)

    @staticmethod
    def is_brace_format_style(record: logging.LogRecord):
        if len(record.args) == 0:
            return False

        msg = record.msg
        if '%' in msg:
            return False

        count_of_start_param = msg.count("{")
        count_of_end_param = msg.count("}")

        if count_of_start_param != count_of_end_param:
            return False

        if count_of_start_param != len(record.args):
            return False

        return True

    @staticmethod
    def rewrite_record(record: logging.LogRecord):
        if not BraceFormatStyleFormatter.is_brace_format_style(record):
            return

        record.msg = record.msg.format(*record.args)
        record.args = []

    def format(self, record):
        orig_msg = record.msg
        orig_args = record.args
        self.rewrite_record(record)
        formatted = self.formatter.format(record)

        # restore log record to original state for other handlers
        record.msg = orig_msg
        record.args = orig_args
        return formatted

回答 24

使用pyfancy。

例：

print(pyfancy.RED + "Hello Red!" + pyfancy.END)

Use pyfancy.

Example:

print(pyfancy.RED + "Hello Red!" + pyfancy.END)

回答 25

另一个解决方案，使用ZetaSyanthis的颜色：

def config_log(log_level):

    def set_color(level, code):
        level_fmt = "\033[1;" + str(code) + "m%s\033[1;0m" 
        logging.addLevelName( level, level_fmt % logging.getLevelName(level) )

    std_stream = sys.stdout
    isatty = getattr(std_stream, 'isatty', None)
    if isatty and isatty():
        levels = [logging.DEBUG, logging.CRITICAL, logging.WARNING, logging.ERROR]
        for idx, level in enumerate(levels):
            set_color(level, 30 + idx )
        set_color(logging.DEBUG, 0)
    logging.basicConfig(stream=std_stream, level=log_level)

从您的__main__函数调用一次。我在那里有这样的东西：

options, arguments = p.parse_args()
log_level = logging.DEBUG if options.verbose else logging.WARNING
config_log(log_level)

它还会验证输出是否为控制台，否则不使用任何颜色。

Just another solution, with the colors of ZetaSyanthis:

def config_log(log_level):

    def set_color(level, code):
        level_fmt = "\033[1;" + str(code) + "m%s\033[1;0m" 
        logging.addLevelName( level, level_fmt % logging.getLevelName(level) )

    std_stream = sys.stdout
    isatty = getattr(std_stream, 'isatty', None)
    if isatty and isatty():
        levels = [logging.DEBUG, logging.CRITICAL, logging.WARNING, logging.ERROR]
        for idx, level in enumerate(levels):
            set_color(level, 30 + idx )
        set_color(logging.DEBUG, 0)
    logging.basicConfig(stream=std_stream, level=log_level)

call it once from your __main__ function. I have something like this there:

options, arguments = p.parse_args()
log_level = logging.DEBUG if options.verbose else logging.WARNING
config_log(log_level)

it also verifies that the output is a console, otherwise no colors are used.

回答 26

import logging

logging.basicConfig(filename="f.log" filemode='w', level=logging.INFO,
                    format = "%(logger_name)s %(color)s  %(message)s %(endColor)s")


class Logger(object):
    __GREEN = "\033[92m"
    __RED = '\033[91m'
    __ENDC = '\033[0m'

    def __init__(self, name):
        self.logger = logging.getLogger(name)
        self.extra={'logger_name': name, 'endColor': self.__ENDC, 'color': self.__GREEN}


    def info(self, msg):
        self.extra['color'] = self.__GREEN
        self.logger.info(msg, extra=self.extra)

    def error(self, msg):
        self.extra['color'] = self.__RED
        self.logger.error(msg, extra=self.extra)

用法

Logger("File Name").info("This shows green text")

import logging

logging.basicConfig(filename="f.log" filemode='w', level=logging.INFO,
                    format = "%(logger_name)s %(color)s  %(message)s %(endColor)s")


class Logger(object):
    __GREEN = "\033[92m"
    __RED = '\033[91m'
    __ENDC = '\033[0m'

    def __init__(self, name):
        self.logger = logging.getLogger(name)
        self.extra={'logger_name': name, 'endColor': self.__ENDC, 'color': self.__GREEN}


    def info(self, msg):
        self.extra['color'] = self.__GREEN
        self.logger.info(msg, extra=self.extra)

    def error(self, msg):
        self.extra['color'] = self.__RED
        self.logger.error(msg, extra=self.extra)

Usage

Logger("File Name").info("This shows green text")

回答 27

以下解决方案仅适用于python 3，但对我而言，它看起来最为清晰。

想法是使用日志记录工厂向日志记录对象添加“彩色”属性，然后以日志格式使用这些“彩色”属性。

import logging
logger = logging.getLogger(__name__)

def configure_logging(level):

    # add 'levelname_c' attribute to log resords
    orig_record_factory = logging.getLogRecordFactory()
    log_colors = {
        logging.DEBUG:     "\033[1;34m",  # blue
        logging.INFO:      "\033[1;32m",  # green
        logging.WARNING:   "\033[1;35m",  # magenta
        logging.ERROR:     "\033[1;31m",  # red
        logging.CRITICAL:  "\033[1;41m",  # red reverted
    }
    def record_factory(*args, **kwargs):
        record = orig_record_factory(*args, **kwargs)
        record.levelname_c = "{}{}{}".format(
            log_colors[record.levelno], record.levelname, "\033[0m")
        return record

    logging.setLogRecordFactory(record_factory)

    # now each log record object would contain 'levelname_c' attribute
    # and you can use this attribute when configuring logging using your favorite
    # method.
    # for demo purposes I configure stderr log right here

    formatter_c = logging.Formatter("[%(asctime)s] %(levelname_c)s:%(name)s:%(message)s")

    stderr_handler = logging.StreamHandler()
    stderr_handler.setLevel(level)
    stderr_handler.setFormatter(formatter_c)

    root_logger = logging.getLogger('')
    root_logger.setLevel(logging.DEBUG)
    root_logger.addHandler(stderr_handler)


def main():
    configure_logging(logging.DEBUG)

    logger.debug("debug message")
    logger.info("info message")
    logger.critical("something unusual happened")


if __name__ == '__main__':
    main()

您可以轻松地修改此示例以创建其他彩色属性（fe message_c），然后使用这些属性在需要的位置获取彩色文本（仅）。

（我最近发现的一个有用的技巧：我有一个带有彩色调试日志的文件，每当我想临时增加应用程序的日志级别时，我只是tail -f在不同终端中的日志文件，并在屏幕上看到调试日志，而无需更改任何配置并重新启动应用程序）

The following solution works with python 3 only, but for me it looks most clear.

The idea is to use log record factory to add ‘colored’ attributes to log record objects and than use these ‘colored’ attributes in log format.

import logging
logger = logging.getLogger(__name__)

def configure_logging(level):

    # add 'levelname_c' attribute to log resords
    orig_record_factory = logging.getLogRecordFactory()
    log_colors = {
        logging.DEBUG:     "\033[1;34m",  # blue
        logging.INFO:      "\033[1;32m",  # green
        logging.WARNING:   "\033[1;35m",  # magenta
        logging.ERROR:     "\033[1;31m",  # red
        logging.CRITICAL:  "\033[1;41m",  # red reverted
    }
    def record_factory(*args, **kwargs):
        record = orig_record_factory(*args, **kwargs)
        record.levelname_c = "{}{}{}".format(
            log_colors[record.levelno], record.levelname, "\033[0m")
        return record

    logging.setLogRecordFactory(record_factory)

    # now each log record object would contain 'levelname_c' attribute
    # and you can use this attribute when configuring logging using your favorite
    # method.
    # for demo purposes I configure stderr log right here

    formatter_c = logging.Formatter("[%(asctime)s] %(levelname_c)s:%(name)s:%(message)s")

    stderr_handler = logging.StreamHandler()
    stderr_handler.setLevel(level)
    stderr_handler.setFormatter(formatter_c)

    root_logger = logging.getLogger('')
    root_logger.setLevel(logging.DEBUG)
    root_logger.addHandler(stderr_handler)


def main():
    configure_logging(logging.DEBUG)

    logger.debug("debug message")
    logger.info("info message")
    logger.critical("something unusual happened")


if __name__ == '__main__':
    main()

You can easily modify this example to create other colored attributes (f.e. message_c) and then use these attributes to get colored text (only) where you want.

(handy trick I discovered recently: I have a file with colored debug logs and whenever I want temporary increase the log level of my application I just tail -f the log file in different terminal and see debug logs on screen w/o changing any configuration and restarting application)

回答 28

这是airmind示例的另一个Python3变体。我想要一些其他示例中没有的特定功能

为终端使用颜色，但不要在文件处理程序中写入不可打印的字符（为此我定义了2个格式化程序）
能够覆盖特定日志消息的颜色
从文件（在这种情况下为Yaml）配置记录器

注意：我使用了colorama，但是您可以对其进行修改，因此不是必需的。同样，在我的测试中，我只是运行python文件，所以我的类在模块中。__main__您必须更改(): __main__.ColoredFormatter为任何模块。

pip install colorama pyyaml

logging.yaml

---
version: 1
disable_existing_loggers: False
formatters:
  simple:
    format: "%(threadName)s - %(name)s - %(levelname)s - %(message)s"
  color:
    format: "%(threadName)s - %(name)s - %(levelname)s - %(message)s"
    (): __main__.ColoredFormatter
    use_color: true

handlers:
  console:
    class: logging.StreamHandler
    level: DEBUG
    formatter: color
    stream: ext://sys.stdout

  info_file_handler:
    class: logging.handlers.RotatingFileHandler
    level: INFO
    formatter: simple
    filename: app.log
    maxBytes: 20971520 
    backupCount: 20
    encoding: utf8

  error_file_handler:
    class: logging.handlers.RotatingFileHandler
    level: ERROR
    formatter: simple
    filename: errors.log
    maxBytes: 10485760 
    backupCount: 20
    encoding: utf8

root:
  level: DEBUG
  handlers: [console, info_file_handler, error_file_handler]

main.py

import logging
import logging.config
import os
from logging import Logger

import colorama
import yaml
from colorama import Back, Fore, Style

COLORS = {
    "WARNING": Fore.YELLOW,
    "INFO": Fore.CYAN,
    "DEBUG": Fore.BLUE,
    "CRITICAL": Fore.YELLOW,
    "ERROR": Fore.RED,
}


class ColoredFormatter(logging.Formatter):
    def __init__(self, *, format, use_color):
        logging.Formatter.__init__(self, fmt=format)
        self.use_color = use_color

    def format(self, record):
        msg = super().format(record)
        if self.use_color:
            levelname = record.levelname
            if hasattr(record, "color"):
                return f"{record.color}{msg}{Style.RESET_ALL}"
            if levelname in COLORS:
                return f"{COLORS[levelname]}{msg}{Style.RESET_ALL}"
        return msg


with open("logging.yaml", "rt") as f:
    config = yaml.safe_load(f.read())
    logging.config.dictConfig(config)

logger: Logger = logging.getLogger(__name__)
logger.info("Test INFO", extra={"color": Back.RED})
logger.info("Test INFO", extra={"color": f"{Style.BRIGHT}{Back.RED}"})
logger.info("Test INFO")
logger.debug("Test DEBUG")
logger.warning("Test WARN")

输出：

This is another Python3 variant of airmind’s example. I wanted some specific features I didn’t see in the other examples

use colors for the terminal but do not write non-printable characters in the file handlers (I defined 2 formatters for this)
ability to override the color for a specific log message
configure the logger from a file (yaml in this case)

Notes: I used colorama but you could modify this so it is not required. Also for my testing I was just running python file so my class is in module __main__ You would have to change (): __main__.ColoredFormatter to whatever your module is.

pip install colorama pyyaml

logging.yaml

---
version: 1
disable_existing_loggers: False
formatters:
  simple:
    format: "%(threadName)s - %(name)s - %(levelname)s - %(message)s"
  color:
    format: "%(threadName)s - %(name)s - %(levelname)s - %(message)s"
    (): __main__.ColoredFormatter
    use_color: true

handlers:
  console:
    class: logging.StreamHandler
    level: DEBUG
    formatter: color
    stream: ext://sys.stdout

  info_file_handler:
    class: logging.handlers.RotatingFileHandler
    level: INFO
    formatter: simple
    filename: app.log
    maxBytes: 20971520 
    backupCount: 20
    encoding: utf8

  error_file_handler:
    class: logging.handlers.RotatingFileHandler
    level: ERROR
    formatter: simple
    filename: errors.log
    maxBytes: 10485760 
    backupCount: 20
    encoding: utf8

root:
  level: DEBUG
  handlers: [console, info_file_handler, error_file_handler]

main.py

import logging
import logging.config
import os
from logging import Logger

import colorama
import yaml
from colorama import Back, Fore, Style

COLORS = {
    "WARNING": Fore.YELLOW,
    "INFO": Fore.CYAN,
    "DEBUG": Fore.BLUE,
    "CRITICAL": Fore.YELLOW,
    "ERROR": Fore.RED,
}


class ColoredFormatter(logging.Formatter):
    def __init__(self, *, format, use_color):
        logging.Formatter.__init__(self, fmt=format)
        self.use_color = use_color

    def format(self, record):
        msg = super().format(record)
        if self.use_color:
            levelname = record.levelname
            if hasattr(record, "color"):
                return f"{record.color}{msg}{Style.RESET_ALL}"
            if levelname in COLORS:
                return f"{COLORS[levelname]}{msg}{Style.RESET_ALL}"
        return msg


with open("logging.yaml", "rt") as f:
    config = yaml.safe_load(f.read())
    logging.config.dictConfig(config)

logger: Logger = logging.getLogger(__name__)
logger.info("Test INFO", extra={"color": Back.RED})
logger.info("Test INFO", extra={"color": f"{Style.BRIGHT}{Back.RED}"})
logger.info("Test INFO")
logger.debug("Test DEBUG")
logger.warning("Test WARN")

output:

知识问答

python异常消息捕获

2021年7月25日 Python实用宝典

问题：python异常消息捕获

import ftplib
import urllib2
import os
import logging
logger = logging.getLogger('ftpuploader')
hdlr = logging.FileHandler('ftplog.log')
formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')
hdlr.setFormatter(formatter)
logger.addHandler(hdlr)
logger.setLevel(logging.INFO)
FTPADDR = "some ftp address"

def upload_to_ftp(con, filepath):
    try:
        f = open(filepath,'rb')                # file to send
        con.storbinary('STOR '+ filepath, f)         # Send the file
        f.close()                                # Close file and FTP
        logger.info('File successfully uploaded to '+ FTPADDR)
    except, e:
        logger.error('Failed to upload to ftp: '+ str(e))

这似乎不起作用，出现语法错误，将所有类型的异常记录到文件中的正确方法是什么

import ftplib
import urllib2
import os
import logging
logger = logging.getLogger('ftpuploader')
hdlr = logging.FileHandler('ftplog.log')
formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')
hdlr.setFormatter(formatter)
logger.addHandler(hdlr)
logger.setLevel(logging.INFO)
FTPADDR = "some ftp address"

def upload_to_ftp(con, filepath):
    try:
        f = open(filepath,'rb')                # file to send
        con.storbinary('STOR '+ filepath, f)         # Send the file
        f.close()                                # Close file and FTP
        logger.info('File successfully uploaded to '+ FTPADDR)
    except, e:
        logger.error('Failed to upload to ftp: '+ str(e))

This doesn’t seem to work, I get syntax error, what is the proper way of doing this for logging all kind of exceptions to a file

回答 0

您必须定义要捕获的异常类型。所以写except Exception, e:的，而不是except, e:一个普通的异常（即无论如何都会被记录）。

其他可能性是通过这种方式编写您的整个try / except代码：

try:
    with open(filepath,'rb') as f:
        con.storbinary('STOR '+ filepath, f)
    logger.info('File successfully uploaded to '+ FTPADDR)
except Exception, e: # work on python 2.x
    logger.error('Failed to upload to ftp: '+ str(e))

在Python 3.x和现代版本的Python 2.x中，使用except Exception as e代替except Exception, e：

try:
    with open(filepath,'rb') as f:
        con.storbinary('STOR '+ filepath, f)
    logger.info('File successfully uploaded to '+ FTPADDR)
except Exception as e: # work on python 3.x
    logger.error('Failed to upload to ftp: '+ str(e))

You have to define which type of exception you want to catch. So write except Exception, e: instead of except, e: for a general exception (that will be logged anyway).

Other possibility is to write your whole try/except code this way:

try:
    with open(filepath,'rb') as f:
        con.storbinary('STOR '+ filepath, f)
    logger.info('File successfully uploaded to '+ FTPADDR)
except Exception, e: # work on python 2.x
    logger.error('Failed to upload to ftp: '+ str(e))

in Python 3.x and modern versions of Python 2.x use except Exception as e instead of except Exception, e:

try:
    with open(filepath,'rb') as f:
        con.storbinary('STOR '+ filepath, f)
    logger.info('File successfully uploaded to '+ FTPADDR)
except Exception as e: # work on python 3.x
    logger.error('Failed to upload to ftp: '+ str(e))

回答 1

python 3不再支持该语法。请改用以下内容。

try:
    do_something()
except BaseException as e:
    logger.error('Failed to do something: ' + str(e))

The syntax is no longer supported in python 3. Use the following instead.

try:
    do_something()
except BaseException as e:
    logger.error('Failed to do something: ' + str(e))

回答 2

将其更新为更简单的记录器（适用于python 2和3）。您不需要回溯模块。

import logging

logger = logging.Logger('catch_all')

def catchEverythingInLog():
    try:
        ... do something ...
    except Exception as e:
        logger.error(e, exc_info=True)
        ... exception handling ...

现在这是旧方法（尽管仍然有效）：

import sys, traceback

def catchEverything():
    try:
        ... some operation(s) ...
    except:
        exc_type, exc_value, exc_traceback = sys.exc_info()
        ... exception handling ...

exc_value是错误消息。

Updating this to something simpler for logger (works for both python 2 and 3). You do not need traceback module.

import logging

logger = logging.Logger('catch_all')

def catchEverythingInLog():
    try:
        ... do something ...
    except Exception as e:
        logger.error(e, exc_info=True)
        ... exception handling ...

This is now the old way (though still works):

import sys, traceback

def catchEverything():
    try:
        ... some operation(s) ...
    except:
        exc_type, exc_value, exc_traceback = sys.exc_info()
        ... exception handling ...

exc_value is the error message.

回答 3

在某些情况下，您可以使用e.message或e.messages ..但是，并非在所有情况下都有效。无论如何，使用str（e）更安全

try:
  ...
except Exception as e:
  print(e.message)

There are some cases where you can use the e.message or e.messages.. But it does not work in all cases. Anyway the more safe is to use the str(e)

try:
  ...
except Exception as e:
  print(e.message)

回答 4

如果您需要错误类，错误消息和堆栈跟踪（或其中一些），请使用sys.exec_info()。

带有某些格式的最少工作代码：

import sys
import traceback

try:
    ans = 1/0
except BaseException as ex:
    # Get current system exception
    ex_type, ex_value, ex_traceback = sys.exc_info()

    # Extract unformatter stack traces as tuples
    trace_back = traceback.extract_tb(ex_traceback)

    # Format stacktrace
    stack_trace = list()

    for trace in trace_back:
        stack_trace.append("File : %s , Line : %d, Func.Name : %s, Message : %s" % (trace[0], trace[1], trace[2], trace[3]))

    print("Exception type : %s " % ex_type.__name__)
    print("Exception message : %s" %ex_value)
    print("Stack trace : %s" %stack_trace)

给出以下输出：

Exception type : ZeroDivisionError
Exception message : division by zero
Stack trace : ['File : .\\test.py , Line : 5, Func.Name : <module>, Message : ans = 1/0']

函数sys.exc_info（）为您提供有关最新异常的详细信息。返回的元组(type, value, traceback)。

traceback是回溯对象的实例。您可以使用提供的方法来格式化跟踪。在追溯文档中可以找到更多内容。

If you want the error class, error message and stack trace (or some of those), use sys.exec_info().

Minimal working code with some formatting:

import sys
import traceback

try:
    ans = 1/0
except BaseException as ex:
    # Get current system exception
    ex_type, ex_value, ex_traceback = sys.exc_info()

    # Extract unformatter stack traces as tuples
    trace_back = traceback.extract_tb(ex_traceback)

    # Format stacktrace
    stack_trace = list()

    for trace in trace_back:
        stack_trace.append("File : %s , Line : %d, Func.Name : %s, Message : %s" % (trace[0], trace[1], trace[2], trace[3]))

    print("Exception type : %s " % ex_type.__name__)
    print("Exception message : %s" %ex_value)
    print("Stack trace : %s" %stack_trace)

Which gives the following output:

Exception type : ZeroDivisionError
Exception message : division by zero
Stack trace : ['File : .\\test.py , Line : 5, Func.Name : <module>, Message : ans = 1/0']

The function sys.exc_info() gives you details about the most recent exception. It returns a tuple of (type, value, traceback).

traceback is an instance of traceback object. You can format the trace with the methods provided. More can be found in the traceback documentation .

回答 5

您可以使用logger.exception("msg")traceback记录异常：

try:
    #your code
except Exception as e:
    logger.exception('Failed: ' + str(e))

You can use logger.exception("msg") for logging exception with traceback:

try:
    #your code
except Exception as e:
    logger.exception('Failed: ' + str(e))

回答 6

在python 3.6之后，您可以使用格式化的字符串文字。干净利落！（https://docs.python.org/3/whatsnew/3.6.html#whatsnew36-pep498）

try
 ...
except Exception as e:
    logger.error(f"Failed to upload to ftp: {e}")

After python 3.6, you can use formatted string literal. It’s neat! (https://docs.python.org/3/whatsnew/3.6.html#whatsnew36-pep498)

try
 ...
except Exception as e:
    logger.error(f"Failed to upload to ftp: {e}")

回答 7

您可以尝试明确指定BaseException类型。但是，这只会捕获BaseException的派生类。尽管这包括所有实现提供的异常，但也可能会引发任意旧式类。

try:
  do_something()
except BaseException, e:
  logger.error('Failed to do something: ' + str(e))

You can try specifying the BaseException type explicitly. However, this will only catch derivatives of BaseException. While this includes all implementation-provided exceptions, it is also possibly to raise arbitrary old-style classes.

try:
  do_something()
except BaseException, e:
  logger.error('Failed to do something: ' + str(e))

回答 8

使用str（ex）打印执行

try:
   #your code
except ex:
   print(str(ex))

Use str(ex) to print execption

try:
   #your code
except ex:
   print(str(ex))

回答 9

对于未来的奋斗者，在python 3.8.2（可能还有之前的几个版本）中，语法为

except Attribute as e:
    print(e)

for the future strugglers, in python 3.8.2(and maybe a few versions before that), the syntax is

except Attribute as e:
    print(e)

回答 10

使用str(e)或repr(e)表示异常，您将无法获得实际的堆栈跟踪，因此查找异常在哪里没有帮助。

阅读其他答案和日志记录包doc之后，以下两种方法可以很好地打印实际的堆栈跟踪信息，以便于调试：

`logger.debug()`与参数一起使用`exc_info`

try:
    # my code
exception SomeError as e:
    logger.debug(e, exc_info=True)

采用 `logger.exception()`

或者我们可以直接使用它logger.exception()来打印异常。

try:
    # my code
exception SomeError as e:
    logger.exception(e)

Using str(e) or repr(e) to represent the exception, you won’t get the actual stack trace, so it is not helpful to find where the exception is.

After reading other answers and the logging package doc, the following two ways works great to print the actual stack trace for easier debugging:

use `logger.debug()` with parameter `exc_info`

try:
    # my code
exception SomeError as e:
    logger.debug(e, exc_info=True)

use `logger.exception()`

or we can directly use logger.exception() to print the exception.

try:
    # my code
exception SomeError as e:
    logger.exception(e)

知识问答

如何记录带有调试信息的Python错误？

2021年7月25日 Python实用宝典

问题：如何记录带有调试信息的Python错误？

我正在使用以下命令将Python异常消息打印到日志文件中logging.error：

import logging
try:
    1/0
except ZeroDivisionError as e:
    logging.error(e)  # ERROR:root:division by zero

除了异常字符串以外，是否可以打印有关异常及其生成代码的更多详细信息？行号或堆栈跟踪之类的东西会很棒。

I am printing Python exception messages to a log file with logging.error:

import logging
try:
    1/0
except ZeroDivisionError as e:
    logging.error(e)  # ERROR:root:division by zero

Is it possible to print more detailed information about the exception and the code that generated it than just the exception string? Things like line numbers or stack traces would be great.

回答 0

logger.exception 将在错误消息旁边输出堆栈跟踪。

例如：

import logging
try:
    1/0
except ZeroDivisionError as e:
    logging.exception("message")

输出：

ERROR:root:message
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
ZeroDivisionError: integer division or modulo by zero

@Paulo Check指出：“请注意，在Python 3中，您必须logging.exception在except零件内部调用该方法。如果在任意位置调用此方法，则可能会遇到奇怪的异常。文档对此有所提示。”

logger.exception will output a stack trace alongside the error message.

For example:

import logging
try:
    1/0
except ZeroDivisionError as e:
    logging.exception("message")

Output:

ERROR:root:message
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
ZeroDivisionError: integer division or modulo by zero

@Paulo Cheque notes, “be aware that in Python 3 you must call the logging.exception method just inside the except part. If you call this method in an arbitrary place you may get a bizarre exception. The docs alert about that.”

回答 1

约一个好处logging.exception是SiggyF的回答并没有显示的是，你可以在任意的消息传递和记录仍然会显示完整的回溯与所有异常的详细信息：

import logging
try:
    1/0
except ZeroDivisionError:
    logging.exception("Deliberate divide by zero traceback")

在默认情况下（在最新版本中），仅将错误打印到的日志记录行为sys.stderr如下所示：

>>> import logging
>>> try:
...     1/0
... except ZeroDivisionError:
...     logging.exception("Deliberate divide by zero traceback")
... 
ERROR:root:Deliberate divide by zero traceback
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
ZeroDivisionError: integer division or modulo by zero

One nice thing about logging.exception that SiggyF’s answer doesn’t show is that you can pass in an arbitrary message, and logging will still show the full traceback with all the exception details:

import logging
try:
    1/0
except ZeroDivisionError:
    logging.exception("Deliberate divide by zero traceback")

With the default (in recent versions) logging behaviour of just printing errors to sys.stderr, it looks like this:

>>> import logging
>>> try:
...     1/0
... except ZeroDivisionError:
...     logging.exception("Deliberate divide by zero traceback")
... 
ERROR:root:Deliberate divide by zero traceback
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
ZeroDivisionError: integer division or modulo by zero

回答 2

使用exc_info选项可能更好，允许您选择错误级别（如果使用exception，它将始终处于错误error级别）：

try:
    # do something here
except Exception as e:
    logging.critical(e, exc_info=True)  # log exception info at CRITICAL log level

Using exc_info options may be better, to allow you to choose the error level (if you use exception, it will always be at the error level):

try:
    # do something here
except Exception as e:
    logging.critical(e, exc_info=True)  # log exception info at CRITICAL log level

回答 3

报价单

如果您的应用程序以其他方式记录日志而不使用logging模块怎么办？

现在，traceback可以在这里使用。

import traceback

def log_traceback(ex, ex_traceback=None):
    if ex_traceback is None:
        ex_traceback = ex.__traceback__
    tb_lines = [ line.rstrip('\n') for line in
                 traceback.format_exception(ex.__class__, ex, ex_traceback)]
    exception_logger.log(tb_lines)

在Python 2中使用它：

try:
    # your function call is here
except Exception as ex:
    _, _, ex_traceback = sys.exc_info()
    log_traceback(ex, ex_traceback)

在Python 3中使用它：

try:
    x = get_number()
except Exception as ex:
    log_traceback(ex)

Quoting

What if your application does logging some other way – not using the logging module?

Now, traceback could be used here.

import traceback

def log_traceback(ex, ex_traceback=None):
    if ex_traceback is None:
        ex_traceback = ex.__traceback__
    tb_lines = [ line.rstrip('\n') for line in
                 traceback.format_exception(ex.__class__, ex, ex_traceback)]
    exception_logger.log(tb_lines)

Use it in Python 2:

try:
    # your function call is here
except Exception as ex:
    _, _, ex_traceback = sys.exc_info()
    log_traceback(ex, ex_traceback)

Use it in Python 3:

try:
    x = get_number()
except Exception as ex:
    log_traceback(ex)

回答 4

如果您使用纯日志-您的所有日志记录都应符合以下规则：one record = one line。遵循此规则，您可以使用grep和其他工具来处理日志文件。

但是回溯信息是多行的。因此，我的答案是zangw在此线程中提出的解决方案的扩展版本。问题是回溯线可能在\n内部，因此我们需要做一些额外的工作来消除该行的结尾：

import logging


logger = logging.getLogger('your_logger_here')

def log_app_error(e: BaseException, level=logging.ERROR) -> None:
    e_traceback = traceback.format_exception(e.__class__, e, e.__traceback__)
    traceback_lines = []
    for line in [line.rstrip('\n') for line in e_traceback]:
        traceback_lines.extend(line.splitlines())
    logger.log(level, traceback_lines.__str__())

之后（当您要分析日志时），您可以从日志文件中复制/粘贴所需的回溯行，然后执行以下操作：

ex_traceback = ['line 1', 'line 2', ...]
for line in ex_traceback:
    print(line)

利润！

If you use plain logs – all your log records should correspond this rule: one record = one line. Following this rule you can use grep and other tools to process your log files.

But traceback information is multi-line. So my answer is an extended version of solution proposed by zangw above in this thread. The problem is that traceback lines could have \n inside, so we need to do an extra work to get rid of this line endings:

import logging


logger = logging.getLogger('your_logger_here')

def log_app_error(e: BaseException, level=logging.ERROR) -> None:
    e_traceback = traceback.format_exception(e.__class__, e, e.__traceback__)
    traceback_lines = []
    for line in [line.rstrip('\n') for line in e_traceback]:
        traceback_lines.extend(line.splitlines())
    logger.log(level, traceback_lines.__str__())

After that (when you’ll be analyzing your logs) you could copy / paste required traceback lines from your log file and do this:

ex_traceback = ['line 1', 'line 2', ...]
for line in ex_traceback:
    print(line)

Profit!

回答 5

这个答案是建立在上述优秀答案之上的。

在大多数应用程序中，您不会直接调用logging.exception（e）。您很可能已经定义了特定于您的应用程序或模块的自定义记录器，如下所示：

# Set the name of the app or module
my_logger = logging.getLogger('NEM Sequencer')
# Set the log level
my_logger.setLevel(logging.INFO)

# Let's say we want to be fancy and log to a graylog2 log server
graylog_handler = graypy.GELFHandler('some_server_ip', 12201)
graylog_handler.setLevel(logging.INFO)
my_logger.addHandler(graylog_handler)

在这种情况下，只需使用记录器调用异常（e），如下所示：

try:
    1/0
except ZeroDivisionError, e:
    my_logger.exception(e)

This answer builds up from the above excellent ones.

In most applications, you won’t be calling logging.exception(e) directly. Most likely you have defined a custom logger specific for your application or module like this:

# Set the name of the app or module
my_logger = logging.getLogger('NEM Sequencer')
# Set the log level
my_logger.setLevel(logging.INFO)

# Let's say we want to be fancy and log to a graylog2 log server
graylog_handler = graypy.GELFHandler('some_server_ip', 12201)
graylog_handler.setLevel(logging.INFO)
my_logger.addHandler(graylog_handler)

In this case, just use the logger to call the exception(e) like this:

try:
    1/0
except ZeroDivisionError, e:
    my_logger.exception(e)

回答 6

您可以毫无exceptions地记录堆栈跟踪。

https://docs.python.org/3/library/logging.html#logging.Logger.debug

第二个可选的关键字参数是stack_info，默认为False。如果为true，则将堆栈信息添加到日志消息中，包括实际的日志调用。请注意，这与通过指定exc_info显示的堆栈信息不同：前者是从堆栈底部到当前线程中的日志记录调用的堆栈帧，而后者是有关已取消缠绕的堆栈帧的信息，在搜索异常处理程序时跟踪异常。

例：

>>> import logging
>>> logging.basicConfig(level=logging.DEBUG)
>>> logging.getLogger().info('This prints the stack', stack_info=True)
INFO:root:This prints the stack
Stack (most recent call last):
  File "<stdin>", line 1, in <module>
>>>

You can log the stack trace without an exception.

https://docs.python.org/3/library/logging.html#logging.Logger.debug

The second optional keyword argument is stack_info, which defaults to False. If true, stack information is added to the logging message, including the actual logging call. Note that this is not the same stack information as that displayed through specifying exc_info: The former is stack frames from the bottom of the stack up to the logging call in the current thread, whereas the latter is information about stack frames which have been unwound, following an exception, while searching for exception handlers.

Example:

>>> import logging
>>> logging.basicConfig(level=logging.DEBUG)
>>> logging.getLogger().info('This prints the stack', stack_info=True)
INFO:root:This prints the stack
Stack (most recent call last):
  File "<stdin>", line 1, in <module>
>>>

回答 7

一点点装饰器处理（受Maybe monad和举重的启发很松散）。您可以安全地删除Python 3.6类型注释，并使用较旧的消息格式样式。

fallable.py

from functools import wraps
from typing import Callable, TypeVar, Optional
import logging


A = TypeVar('A')


def fallible(*exceptions, logger=None) \
        -> Callable[[Callable[..., A]], Callable[..., Optional[A]]]:
    """
    :param exceptions: a list of exceptions to catch
    :param logger: pass a custom logger; None means the default logger, 
                   False disables logging altogether.
    """
    def fwrap(f: Callable[..., A]) -> Callable[..., Optional[A]]:

        @wraps(f)
        def wrapped(*args, **kwargs):
            try:
                return f(*args, **kwargs)
            except exceptions:
                message = f'called {f} with *args={args} and **kwargs={kwargs}'
                if logger:
                    logger.exception(message)
                if logger is None:
                    logging.exception(message)
                return None

        return wrapped

    return fwrap

演示：

In [1] from fallible import fallible

In [2]: @fallible(ArithmeticError)
    ...: def div(a, b):
    ...:     return a / b
    ...: 
    ...: 

In [3]: div(1, 2)
Out[3]: 0.5

In [4]: res = div(1, 0)
ERROR:root:called <function div at 0x10d3c6ae8> with *args=(1, 0) and **kwargs={}
Traceback (most recent call last):
  File "/Users/user/fallible.py", line 17, in wrapped
    return f(*args, **kwargs)
  File "<ipython-input-17-e056bd886b5c>", line 3, in div
    return a / b

In [5]: repr(res)
'None'

您还可以修改此解决方案来回报比的东西更有意义一点None从except部分（甚至使溶液一般，通过指定该返回值fallible的论点）。

A little bit of decorator treatment (very loosely inspired by the Maybe monad and lifting). You can safely remove Python 3.6 type annotations and use an older message formatting style.

fallible.py

from functools import wraps
from typing import Callable, TypeVar, Optional
import logging


A = TypeVar('A')


def fallible(*exceptions, logger=None) \
        -> Callable[[Callable[..., A]], Callable[..., Optional[A]]]:
    """
    :param exceptions: a list of exceptions to catch
    :param logger: pass a custom logger; None means the default logger, 
                   False disables logging altogether.
    """
    def fwrap(f: Callable[..., A]) -> Callable[..., Optional[A]]:

        @wraps(f)
        def wrapped(*args, **kwargs):
            try:
                return f(*args, **kwargs)
            except exceptions:
                message = f'called {f} with *args={args} and **kwargs={kwargs}'
                if logger:
                    logger.exception(message)
                if logger is None:
                    logging.exception(message)
                return None

        return wrapped

    return fwrap

Demo:

In [1] from fallible import fallible

In [2]: @fallible(ArithmeticError)
    ...: def div(a, b):
    ...:     return a / b
    ...: 
    ...: 

In [3]: div(1, 2)
Out[3]: 0.5

In [4]: res = div(1, 0)
ERROR:root:called <function div at 0x10d3c6ae8> with *args=(1, 0) and **kwargs={}
Traceback (most recent call last):
  File "/Users/user/fallible.py", line 17, in wrapped
    return f(*args, **kwargs)
  File "<ipython-input-17-e056bd886b5c>", line 3, in div
    return a / b

In [5]: repr(res)
'None'

You can also modify this solution to return something a bit more meaningful than None from the except part (or even make the solution generic, by specifying this return value in fallible‘s arguments).

回答 8

在您的日志记录模块（如果是自定义模块）中，只需启用stack_info即可。

api_logger.exceptionLog("*Input your Custom error message*",stack_info=True)

In your logging module(if custom module) just enable stack_info.

api_logger.exceptionLog("*Input your Custom error message*",stack_info=True)

回答 9

如果您可以处理额外的依赖关系，则可以使用twisted.log，您不必显式记录错误，而且它会将整个回溯和时间返回到文件或流。

If you can cope with the extra dependency then use twisted.log, you don’t have to explicitly log errors and also it returns the entire traceback and time to the file or stream.

回答 10

一种干净的方法是使用format_exc()，然后解析输出以获取相关部分：

from traceback import format_exc

try:
    1/0
except Exception:
    print 'the relevant part is: '+format_exc().split('\n')[-2]

问候

A clean way to do it is using format_exc() and then parse the output to get the relevant part:

from traceback import format_exc

try:
    1/0
except Exception:
    print 'the relevant part is: '+format_exc().split('\n')[-2]

Regards

知识问答

使Python记录器将除日志文件外的所有消息输出到stdout

2021年7月25日 Python实用宝典

问题：使Python记录器将除日志文件外的所有消息输出到stdout

除了应该将日志文件放到哪里，是否有一种方法可以使用该logging模块使Python日志自动输出到stdout ？例如，我想所有呼叫，，去他们预期的地方，但除了总是被复制到。这是为了避免重复消息，例如：logger.warninglogger.criticallogger.errorstdout

mylogger.critical("something failed")
print "something failed"

Is there a way to make Python logging using the logging module automatically output things to stdout in addition to the log file where they are supposed to go? For example, I’d like all calls to logger.warning, logger.critical, logger.error to go to their intended places but in addition always be copied to stdout. This is to avoid duplicating messages like:

mylogger.critical("something failed")
print "something failed"

回答 0

所有日志记录输出均由处理程序处理；只需添加一个logging.StreamHandler()在根记录器中即可。

这是配置流处理程序（使用stdout而不是默认值stderr）并将其添加到根记录器的示例：

import logging
import sys

root = logging.getLogger()
root.setLevel(logging.DEBUG)

handler = logging.StreamHandler(sys.stdout)
handler.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
root.addHandler(handler)

All logging output is handled by the handlers; just add a logging.StreamHandler() to the root logger.

Here’s an example configuring a stream handler (using stdout instead of the default stderr) and adding it to the root logger:

import logging
import sys

root = logging.getLogger()
root.setLevel(logging.DEBUG)

handler = logging.StreamHandler(sys.stdout)
handler.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
root.addHandler(handler)

回答 1

登录到stdout的最简单方法：

import logging
import sys
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)

The simplest way to log to stdout:

import logging
import sys
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)

回答 2

可以使用多个处理程序。

import logging
import auxiliary_module

# create logger with 'spam_application'
log = logging.getLogger('spam_application')
log.setLevel(logging.DEBUG)

# create formatter and add it to the handlers
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')

# create file handler which logs even debug messages
fh = logging.FileHandler('spam.log')
fh.setLevel(logging.DEBUG)
fh.setFormatter(formatter)
log.addHandler(fh)

# create console handler with a higher log level
ch = logging.StreamHandler()
ch.setLevel(logging.ERROR)
ch.setFormatter(formatter)
log.addHandler(ch)

log.info('creating an instance of auxiliary_module.Auxiliary')
a = auxiliary_module.Auxiliary()
log.info('created an instance of auxiliary_module.Auxiliary')

log.info('calling auxiliary_module.Auxiliary.do_something')
a.do_something()
log.info('finished auxiliary_module.Auxiliary.do_something')

log.info('calling auxiliary_module.some_function()')
auxiliary_module.some_function()
log.info('done with auxiliary_module.some_function()')

# remember to close the handlers
for handler in log.handlers:
    handler.close()
    log.removeFilter(handler)

请参阅：https : //docs.python.org/2/howto/logging-cookbook.html

It’s possible using multiple handlers.

import logging
import auxiliary_module

# create logger with 'spam_application'
log = logging.getLogger('spam_application')
log.setLevel(logging.DEBUG)

# create formatter and add it to the handlers
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')

# create file handler which logs even debug messages
fh = logging.FileHandler('spam.log')
fh.setLevel(logging.DEBUG)
fh.setFormatter(formatter)
log.addHandler(fh)

# create console handler with a higher log level
ch = logging.StreamHandler()
ch.setLevel(logging.ERROR)
ch.setFormatter(formatter)
log.addHandler(ch)

log.info('creating an instance of auxiliary_module.Auxiliary')
a = auxiliary_module.Auxiliary()
log.info('created an instance of auxiliary_module.Auxiliary')

log.info('calling auxiliary_module.Auxiliary.do_something')
a.do_something()
log.info('finished auxiliary_module.Auxiliary.do_something')

log.info('calling auxiliary_module.some_function()')
auxiliary_module.some_function()
log.info('done with auxiliary_module.some_function()')

# remember to close the handlers
for handler in log.handlers:
    handler.close()
    log.removeFilter(handler)

Please see: https://docs.python.org/2/howto/logging-cookbook.html

回答 3

您可以为file和stdout创建两个处理程序，然后创建一个handlers参数为的记录器basicConfig。如果两个处理程序具有相同的log_level和format输出，则可能会很有用：

import logging
import sys

file_handler = logging.FileHandler(filename='tmp.log')
stdout_handler = logging.StreamHandler(sys.stdout)
handlers = [file_handler, stdout_handler]

logging.basicConfig(
    level=logging.DEBUG, 
    format='[%(asctime)s] {%(filename)s:%(lineno)d} %(levelname)s - %(message)s',
    handlers=handlers
)

logger = logging.getLogger('LOGGER_NAME')

You could create two handlers for file and stdout and then create one logger with handlers argument to basicConfig. It could be useful if you have the same log_level and format output for both handlers:

import logging
import sys

file_handler = logging.FileHandler(filename='tmp.log')
stdout_handler = logging.StreamHandler(sys.stdout)
handlers = [file_handler, stdout_handler]

logging.basicConfig(
    level=logging.DEBUG, 
    format='[%(asctime)s] {%(filename)s:%(lineno)d} %(levelname)s - %(message)s',
    handlers=handlers
)

logger = logging.getLogger('LOGGER_NAME')

回答 4

登录文件和stderr的最简单方法：

import logging

logging.basicConfig(filename="logfile.txt")
stderrLogger=logging.StreamHandler()
stderrLogger.setFormatter(logging.Formatter(logging.BASIC_FORMAT))
logging.getLogger().addHandler(stderrLogger)

The simplest way to log to file and to stderr:

import logging

logging.basicConfig(filename="logfile.txt")
stderrLogger=logging.StreamHandler()
stderrLogger.setFormatter(logging.Formatter(logging.BASIC_FORMAT))
logging.getLogger().addHandler(stderrLogger)

回答 5

这是基于强大的，但记录不完整的解决方案logging.config.dictConfig的方法。而不是将所有日志消息发送到stdout，而是将日志级别ERROR和更高级别的消息发送stderr到stdout。如果系统的其他部分正在收听stderr或，则此功能很有用stdout。

import logging
import logging.config
import sys

class _ExcludeErrorsFilter(logging.Filter):
    def filter(self, record):
        """Filters out log messages with log level ERROR (numeric value: 40) or higher."""
        return record.levelno < 40


config = {
    'version': 1,
    'filters': {
        'exclude_errors': {
            '()': _ExcludeErrorsFilter
        }
    },
    'formatters': {
        # Modify log message format here or replace with your custom formatter class
        'my_formatter': {
            'format': '(%(process)d) %(asctime)s %(name)s (line %(lineno)s) | %(levelname)s %(message)s'
        }
    },
    'handlers': {
        'console_stderr': {
            # Sends log messages with log level ERROR or higher to stderr
            'class': 'logging.StreamHandler',
            'level': 'ERROR',
            'formatter': 'my_formatter',
            'stream': sys.stderr
        },
        'console_stdout': {
            # Sends log messages with log level lower than ERROR to stdout
            'class': 'logging.StreamHandler',
            'level': 'DEBUG',
            'formatter': 'my_formatter',
            'filters': ['exclude_errors'],
            'stream': sys.stdout
        },
        'file': {
            # Sends all log messages to a file
            'class': 'logging.FileHandler',
            'level': 'DEBUG',
            'formatter': 'my_formatter',
            'filename': 'my.log',
            'encoding': 'utf8'
        }
    },
    'root': {
        # In general, this should be kept at 'NOTSET'.
        # Otherwise it would interfere with the log levels set for each handler.
        'level': 'NOTSET',
        'handlers': ['console_stderr', 'console_stdout', 'file']
    },
}

logging.config.dictConfig(config)

Here is a solution based on the powerful but poorly documented logging.config.dictConfig method. Instead of sending every log message to stdout, it sends messages with log level ERROR and higher to stderr and everything else to stdout. This can be useful if other parts of the system are listening to stderr or stdout.

import logging
import logging.config
import sys

class _ExcludeErrorsFilter(logging.Filter):
    def filter(self, record):
        """Filters out log messages with log level ERROR (numeric value: 40) or higher."""
        return record.levelno < 40


config = {
    'version': 1,
    'filters': {
        'exclude_errors': {
            '()': _ExcludeErrorsFilter
        }
    },
    'formatters': {
        # Modify log message format here or replace with your custom formatter class
        'my_formatter': {
            'format': '(%(process)d) %(asctime)s %(name)s (line %(lineno)s) | %(levelname)s %(message)s'
        }
    },
    'handlers': {
        'console_stderr': {
            # Sends log messages with log level ERROR or higher to stderr
            'class': 'logging.StreamHandler',
            'level': 'ERROR',
            'formatter': 'my_formatter',
            'stream': sys.stderr
        },
        'console_stdout': {
            # Sends log messages with log level lower than ERROR to stdout
            'class': 'logging.StreamHandler',
            'level': 'DEBUG',
            'formatter': 'my_formatter',
            'filters': ['exclude_errors'],
            'stream': sys.stdout
        },
        'file': {
            # Sends all log messages to a file
            'class': 'logging.FileHandler',
            'level': 'DEBUG',
            'formatter': 'my_formatter',
            'filename': 'my.log',
            'encoding': 'utf8'
        }
    },
    'root': {
        # In general, this should be kept at 'NOTSET'.
        # Otherwise it would interfere with the log levels set for each handler.
        'level': 'NOTSET',
        'handlers': ['console_stderr', 'console_stdout', 'file']
    },
}

logging.config.dictConfig(config)

回答 6

由于没有人共享两个整齐的班轮，我将分享我自己的：

logging.basicConfig(filename='logs.log', level=logging.DEBUG, format="%(asctime)s:%(levelname)s: %(message)s")
logging.getLogger().addHandler(logging.StreamHandler())

Since no one has shared a neat two liner, I will share my own:

logging.basicConfig(filename='logs.log', level=logging.DEBUG, format="%(asctime)s:%(levelname)s: %(message)s")
logging.getLogger().addHandler(logging.StreamHandler())

回答 7

这是一个非常简单的示例：

import logging
l = logging.getLogger("test")

# Add a file logger
f = logging.FileHandler("test.log")
l.addHandler(f)

# Add a stream logger
s = logging.StreamHandler()
l.addHandler(s)

# Send a test message to both -- critical will always log
l.critical("test msg")

输出将在标准输出和文件中显示“ test msg”。

Here’s an extremely simple example:

import logging
l = logging.getLogger("test")

# Add a file logger
f = logging.FileHandler("test.log")
l.addHandler(f)

# Add a stream logger
s = logging.StreamHandler()
l.addHandler(s)

# Send a test message to both -- critical will always log
l.critical("test msg")

The output will show “test msg” on stdout and also in the file.

知识问答

如何查看pytest运行期间创建的正常打印输出？

2021年7月25日 Python实用宝典

问题：如何查看pytest运行期间创建的正常打印输出？

有时候，我只想在代码中插入一些打印语句，然后看看在执行该操作时打印出来的内容。我通常的“锻炼”方式是使用现有的pytest测试。但是，当我运行这些命令时，我似乎看不到任何标准输出（至少从我的IDE PyCharm内部）。

有没有一种简单的方法可以在pytest运行期间查看标准输出？

Sometimes I want to just insert some print statements in my code, and see what gets printed out when I exercise it. My usual way to “exercise” it is with existing pytest tests. But when I run these, I don’t seem able to see any standard output (at least from within PyCharm, my IDE).

Is there a simple way to see standard output during a pytest run?

回答 0

该-s开关禁用每次测试捕获。

The -s switch disables per-test capturing.

回答 1

在对已接受答案的评论中，乔问：

有什么方法可以打印到控制台并捕获输出，以便将其显示在junit报告中？

在UNIX中，这通常称为teeing。理想情况下，py.test默认是发球而不是捕获。尽管Python很少支持开箱即用，但py.test或任何现有的第三方py.test插件（无论如何我都知道）都不理想。

用Monkey修补py.test来做不受支持的事情并非易事。为什么？因为：

大多数py.test功能都锁定在不打算从外部导入的私有_pytest软件包后面。尝试这样做而不知道自己在做什么，通常会导致公共包在运行时引发模糊的异常。^{非常感谢py.test。}^{真正可靠的体系结构。}pytest
即使您确实想出了如何以_pytest安全的方式对专用API 进行Monkey补丁的操作，也必须在运行pytest由外部py.test命令运行的公共程序包之前这样做。您不能在插件中执行此操作（例如，conftest测试套件中的顶级模块）。到py.test懒惰地动态导入插件时，您想要进行Monkey补丁的任何py.test类都已被实例化很久了-并且您无权访问该实例。这意味着，如果您希望有意义地应用Monkey补丁，则无法再安全地运行外部py.test命令。相反，您必须使用自定义setuptools包装该命令的运行test 命令（按顺序）：
1. Monkey修补专用_pytestAPI。
2. 调用public pytest.main()函数运行py.test命令。

这个答案是Monkey修补py.test -s和--capture=no选项来捕获stderr而不是 stdout的。默认情况下，这些选项既不捕获stderr也不捕获stdout。当然，这还不够。但是，每一次伟大的旅程都是从一个繁琐的前传开始的，每个人在五年之内就忘记了。

为什么这样我现在告诉你。我的py.test驱动的测试套件包含缓慢的功能测试。显示这些测试的标准输出是有益的，让人放心，防止leycec到达了killall -9 py.test当又一个长期运行的功能测试失败做几星期什么。但是，显示这些测试的stderr可以防止py.test报告有关测试失败的异常回溯。这是完全没有帮助的。因此，我们强制py.test捕获stderr 而不捕获stdout。

在开始之前，此答案假定您已经有一个test调用py.test 的自定义setuptools 命令。如果不这样做，请参阅py.test编写良好的“良好做法”页面的“ 手动集成”小节。

不要不安装pytest亚军，第三方插件setuptools的提供自定义setuptools的test命令也调用py.test。如果已经安装pytest-runner，则可能需要卸载该pip3软件包，然后采用上面链接的手动方法。

假设您按照上面突出显示的“ 手动集成”中的说明进行操作，则您的代码库现在应包含一个PyTest.run_tests()方法。修改此方法，使其类似于：

class PyTest(TestCommand):
             .
             .
             .
    def run_tests(self):
        # Import the public "pytest" package *BEFORE* the private "_pytest"
        # package. While importation order is typically ignorable, imports can
        # technically have side effects. Tragicomically, that is the case here.
        # Importing the public "pytest" package establishes runtime
        # configuration required by submodules of the private "_pytest" package.
        # The former *MUST* always be imported before the latter. Failing to do
        # so raises obtuse exceptions at runtime... which is bad.
        import pytest
        from _pytest.capture import CaptureManager, FDCapture, MultiCapture

        # If the private method to be monkey-patched no longer exists, py.test
        # is either broken or unsupported. In either case, raise an exception.
        if not hasattr(CaptureManager, '_getcapture'):
            from distutils.errors import DistutilsClassError
            raise DistutilsClassError(
                'Class "pytest.capture.CaptureManager" method _getcapture() '
                'not found. The current version of py.test is either '
                'broken (unlikely) or unsupported (likely).'
            )

        # Old method to be monkey-patched.
        _getcapture_old = CaptureManager._getcapture

        # New method applying this monkey-patch. Note the use of:
        #
        # * "out=False", *NOT* capturing stdout.
        # * "err=True", capturing stderr.
        def _getcapture_new(self, method):
            if method == "no":
                return MultiCapture(
                    out=False, err=True, in_=False, Capture=FDCapture)
            else:
                return _getcapture_old(self, method)

        # Replace the old with the new method.
        CaptureManager._getcapture = _getcapture_new

        # Run py.test with all passed arguments.
        errno = pytest.main(self.pytest_args)
        sys.exit(errno)

要启用此Monkey补丁，请运行py.test，如下所示：

python setup.py test -a "-s"

现在将捕获Stderr而不是 stdout。好漂亮！

将上面的Monkey补丁扩展到tee stdout和stderr上，作为练习，留给读者一整桶的空闲时间。

In an upvoted comment to the accepted answer, Joe asks:

Is there any way to print to the console AND capture the output so that it shows in the junit report?

In UNIX, this is commonly referred to as teeing. Ideally, teeing rather than capturing would be the py.test default. Non-ideally, neither py.test nor any existing third-party py.test plugin (…that I know of, anyway) supports teeing – despite Python trivially supporting teeing out-of-the-box.

Monkey-patching py.test to do anything unsupported is non-trivial. Why? Because:

Most py.test functionality is locked behind a private _pytest package not intended to be externally imported. Attempting to do so without knowing what you’re doing typically results in the public pytest package raising obscure exceptions at runtime. ^{Thanks alot, py.test. Really robust architecture you got there.}
Even when you do figure out how to monkey-patch the private _pytest API in a safe manner, you have to do so before running the public pytest package run by the external py.test command. You cannot do this in a plugin (e.g., a top-level conftest module in your test suite). By the time py.test lazily gets around to dynamically importing your plugin, any py.test class you wanted to monkey-patch has long since been instantiated – and you do not have access to that instance. This implies that, if you want your monkey-patch to be meaningfully applied, you can no longer safely run the external py.test command. Instead, you have to wrap the running of that command with a custom setuptools test command that (in order):
1. Monkey-patches the private _pytest API.
2. Calls the public pytest.main() function to run the py.test command.

This answer monkey-patches py.test’s -s and --capture=no options to capture stderr but not stdout. By default, these options capture neither stderr nor stdout. This isn’t quite teeing, of course. But every great journey begins with a tedious prequel everyone forgets in five years.

Why do this? I shall now tell you. My py.test-driven test suite contains slow functional tests. Displaying the stdout of these tests is helpful and reassuring, preventing leycec from reaching for killall -9 py.test when yet another long-running functional test fails to do anything for weeks on end. Displaying the stderr of these tests, however, prevents py.test from reporting exception tracebacks on test failures. Which is completely unhelpful. Hence, we coerce py.test to capture stderr but not stdout.

Before we get to it, this answer assumes you already have a custom setuptools test command invoking py.test. If you don’t, see the Manual Integration subsection of py.test’s well-written Good Practices page.

Do not install pytest-runner, a third-party setuptools plugin providing a custom setuptools test command also invoking py.test. If pytest-runner is already installed, you’ll probably need to uninstall that pip3 package and then adopt the manual approach linked to above.

Assuming you followed the instructions in Manual Integration highlighted above, your codebase should now contain a PyTest.run_tests() method. Modify this method to resemble:

class PyTest(TestCommand):
             .
             .
             .
    def run_tests(self):
        # Import the public "pytest" package *BEFORE* the private "_pytest"
        # package. While importation order is typically ignorable, imports can
        # technically have side effects. Tragicomically, that is the case here.
        # Importing the public "pytest" package establishes runtime
        # configuration required by submodules of the private "_pytest" package.
        # The former *MUST* always be imported before the latter. Failing to do
        # so raises obtuse exceptions at runtime... which is bad.
        import pytest
        from _pytest.capture import CaptureManager, FDCapture, MultiCapture

        # If the private method to be monkey-patched no longer exists, py.test
        # is either broken or unsupported. In either case, raise an exception.
        if not hasattr(CaptureManager, '_getcapture'):
            from distutils.errors import DistutilsClassError
            raise DistutilsClassError(
                'Class "pytest.capture.CaptureManager" method _getcapture() '
                'not found. The current version of py.test is either '
                'broken (unlikely) or unsupported (likely).'
            )

        # Old method to be monkey-patched.
        _getcapture_old = CaptureManager._getcapture

        # New method applying this monkey-patch. Note the use of:
        #
        # * "out=False", *NOT* capturing stdout.
        # * "err=True", capturing stderr.
        def _getcapture_new(self, method):
            if method == "no":
                return MultiCapture(
                    out=False, err=True, in_=False, Capture=FDCapture)
            else:
                return _getcapture_old(self, method)

        # Replace the old with the new method.
        CaptureManager._getcapture = _getcapture_new

        # Run py.test with all passed arguments.
        errno = pytest.main(self.pytest_args)
        sys.exit(errno)

To enable this monkey-patch, run py.test as follows:

python setup.py test -a "-s"

Stderr but not stdout will now be captured. Nifty!

Extending the above monkey-patch to tee stdout and stderr is left as an exercise to the reader with a barrel-full of free time.

回答 2

运行测试时，请使用该-s选项。exampletest.py测试运行时，所有打印语句将在控制台上打印。

py.test exampletest.py -s

When running the test use the -s option. All print statements in exampletest.py would get printed on the console when test is run.

py.test exampletest.py -s

回答 3

根据pytest文档，pytest的版本3可以临时禁用测试中的捕获：

def test_disabling_capturing(capsys):
    print('this output is captured')
    with capsys.disabled():
        print('output not captured, going directly to sys.stdout')
    print('this output is also captured')

According to pytest documentation, version 3 of pytest can temporary disable capture in a test:

def test_disabling_capturing(capsys):
    print('this output is captured')
    with capsys.disabled():
        print('output not captured, going directly to sys.stdout')
    print('this output is also captured')

回答 4

pytest捕获单个测试的标准输出，并仅在特定条件下显示它们，并默认显示其打印的测试摘要。

额外的摘要信息可以使用’-r’选项显示：

pytest -rP

显示已通过测试的捕获输出。

pytest -rx

显示捕获的失败测试输出（默认行为）。

-r的输出格式比-s的输出格式更漂亮。

pytest captures the stdout from individual tests and displays them only on certain conditions, along with the summary of the tests it prints by default.

Extra summary info can be shown using the ‘-r’ option:

pytest -rP

shows the captured output of passed tests.

pytest -rx

shows the captured output of failed tests (default behaviour).

The formatting of the output is prettier with -r than with -s.

回答 5

尝试 pytest -s -v test_login.py在控制台中获取更多信息。

-v 很短 --verbose

-s 表示“禁用所有捕获”

Try pytest -s -v test_login.py for more info in console.

-v it’s a short --verbose

-s means ‘disable all capturing’

回答 6

如果您使用的是PyCharm IDE，则可以使用“运行”工具栏运行该单个测试或所有测试。“运行”工具窗口显示由应用程序生成的输出，您可以在其中看到所有打印语句，作为测试输出的一部分。

If you are using PyCharm IDE, then you can run that individual test or all tests using Run toolbar. The Run tool window displays output generated by your application and you can see all the print statements in there as part of test output.

回答 7

pytest --capture=tee-sys是最近添加的。您可以捕获并查看stdout / err上的输出。

pytest --capture=tee-sys was recently added. You can capture as well as see the output on stdout/err.

回答 8

其他答案不起作用。查看捕获的输出的唯一方法是使用以下标志：

pytest-显示全部

The other answers don’t work. The only way to see the captured output is using the following flag:

pytest –show-capture all

知识问答

字符串格式：％与.format

2021年7月24日 Python实用宝典

问题：字符串格式：％与.format

Python 2.6引入的str.format()方法与现有%运算符的语法略有不同。哪个更好，什么情况下适合？

以下使用每种方法并具有相同的结果，那么有什么区别？

#!/usr/bin/python
sub1 = "python string!"
sub2 = "an arg"

a = "i am a %s" % sub1
b = "i am a {0}".format(sub1)

c = "with %(kwarg)s!" % {'kwarg':sub2}
d = "with {kwarg}!".format(kwarg=sub2)

print a    # "i am a python string!"
print b    # "i am a python string!"
print c    # "with an arg!"
print d    # "with an arg!"

此外，何时在Python中进行字符串格式化？例如，如果我的日志记录级别设置为HIGH，那么执行以下%操作是否还会对我有所帮助？如果是这样，有办法避免这种情况吗？
```
log.debug("some debug info: %s" % some_info)
```

Python 2.6 introduced the str.format() method with a slightly different syntax from the existing % operator. Which is better and for what situations?

The following uses each method and has the same outcome, so what is the difference?

#!/usr/bin/python
sub1 = "python string!"
sub2 = "an arg"

a = "i am a %s" % sub1
b = "i am a {0}".format(sub1)

c = "with %(kwarg)s!" % {'kwarg':sub2}
d = "with {kwarg}!".format(kwarg=sub2)

print a    # "i am a python string!"
print b    # "i am a python string!"
print c    # "with an arg!"
print d    # "with an arg!"

Furthermore when does string formatting occur in Python? For example, if my logging level is set to HIGH will I still take a hit for performing the following % operation? And if so, is there a way to avoid this?
```
log.debug("some debug info: %s" % some_info)
```

回答 0

要回答您的第一个问题… .format在许多方面似乎都更加复杂。令人烦恼的%是它如何可以采用变量或元组。您会认为以下各项将始终有效：

"hi there %s" % name

但是，如果name碰巧(1, 2, 3)，它将抛出一个TypeError。为了确保它始终打印，您需要执行

"hi there %s" % (name,)   # supply the single argument as a single-item tuple

真丑。.format没有那些问题。同样在您给出的第二个示例中，该.format示例看起来更加简洁。

为什么不使用它？

不知道（我在阅读本文之前）
必须与Python 2.5兼容

为了回答您的第二个问题，字符串格式化与其他任何操作都同时发生-计算字符串格式化表达式时。而且，Python并不是一种惰性语言，它会在调用函数之前先对表达式求值，因此在您的log.debug示例中，表达式"some debug info: %s"%some_info将首先求值，例如"some debug info: roflcopters are active"，然后将该字符串传递给log.debug()。

To answer your first question… .format just seems more sophisticated in many ways. An annoying thing about % is also how it can either take a variable or a tuple. You’d think the following would always work:

"hi there %s" % name

yet, if name happens to be (1, 2, 3), it will throw a TypeError. To guarantee that it always prints, you’d need to do

"hi there %s" % (name,)   # supply the single argument as a single-item tuple

which is just ugly. .format doesn’t have those issues. Also in the second example you gave, the .format example is much cleaner looking.

Why would you not use it?

not knowing about it (me before reading this)
having to be compatible with Python 2.5

To answer your second question, string formatting happens at the same time as any other operation – when the string formatting expression is evaluated. And Python, not being a lazy language, evaluates expressions before calling functions, so in your log.debug example, the expression "some debug info: %s"%some_infowill first evaluate to, e.g. "some debug info: roflcopters are active", then that string will be passed to log.debug().

回答 1

afaik，模运算符（％）无法做到的事情：

tu = (12,45,22222,103,6)
print '{0} {2} {1} {2} {3} {2} {4} {2}'.format(*tu)

结果

12 22222 45 22222 103 22222 6 22222

很有用。

另一点：format()作为函数，可以用作其他函数的参数：

li = [12,45,78,784,2,69,1254,4785,984]
print map('the number is {}'.format,li)   

print

from datetime import datetime,timedelta

once_upon_a_time = datetime(2010, 7, 1, 12, 0, 0)
delta = timedelta(days=13, hours=8,  minutes=20)

gen =(once_upon_a_time +x*delta for x in xrange(20))

print '\n'.join(map('{:%Y-%m-%d %H:%M:%S}'.format, gen))

结果是：

['the number is 12', 'the number is 45', 'the number is 78', 'the number is 784', 'the number is 2', 'the number is 69', 'the number is 1254', 'the number is 4785', 'the number is 984']

2010-07-01 12:00:00
2010-07-14 20:20:00
2010-07-28 04:40:00
2010-08-10 13:00:00
2010-08-23 21:20:00
2010-09-06 05:40:00
2010-09-19 14:00:00
2010-10-02 22:20:00
2010-10-16 06:40:00
2010-10-29 15:00:00
2010-11-11 23:20:00
2010-11-25 07:40:00
2010-12-08 16:00:00
2010-12-22 00:20:00
2011-01-04 08:40:00
2011-01-17 17:00:00
2011-01-31 01:20:00
2011-02-13 09:40:00
2011-02-26 18:00:00
2011-03-12 02:20:00

Something that the modulo operator ( % ) can’t do, afaik:

tu = (12,45,22222,103,6)
print '{0} {2} {1} {2} {3} {2} {4} {2}'.format(*tu)

result

12 22222 45 22222 103 22222 6 22222

Very useful.

Another point: format(), being a function, can be used as an argument in other functions:

li = [12,45,78,784,2,69,1254,4785,984]
print map('the number is {}'.format,li)   

print

from datetime import datetime,timedelta

once_upon_a_time = datetime(2010, 7, 1, 12, 0, 0)
delta = timedelta(days=13, hours=8,  minutes=20)

gen =(once_upon_a_time +x*delta for x in xrange(20))

print '\n'.join(map('{:%Y-%m-%d %H:%M:%S}'.format, gen))

Results in:

['the number is 12', 'the number is 45', 'the number is 78', 'the number is 784', 'the number is 2', 'the number is 69', 'the number is 1254', 'the number is 4785', 'the number is 984']

2010-07-01 12:00:00
2010-07-14 20:20:00
2010-07-28 04:40:00
2010-08-10 13:00:00
2010-08-23 21:20:00
2010-09-06 05:40:00
2010-09-19 14:00:00
2010-10-02 22:20:00
2010-10-16 06:40:00
2010-10-29 15:00:00
2010-11-11 23:20:00
2010-11-25 07:40:00
2010-12-08 16:00:00
2010-12-22 00:20:00
2011-01-04 08:40:00
2011-01-17 17:00:00
2011-01-31 01:20:00
2011-02-13 09:40:00
2011-02-26 18:00:00
2011-03-12 02:20:00

回答 2

假设您正在使用Python的logging模块，则可以将字符串格式参数作为参数传递给.debug()方法，而不必自己进行格式设置：

log.debug("some debug info: %s", some_info)

除非记录器实际记录某些内容，否则可以避免进行格式化。

Assuming you’re using Python’s logging module, you can pass the string formatting arguments as arguments to the .debug() method rather than doing the formatting yourself:

log.debug("some debug info: %s", some_info)

which avoids doing the formatting unless the logger actually logs something.

回答 3

从Python 3.6（2016）开始，您可以使用f字符串替换变量：

>>> origin = "London"
>>> destination = "Paris"
>>> f"from {origin} to {destination}"
'from London to Paris'

注意f"前缀。如果您在Python 3.5或更早版本中尝试此操作，则会看到一个SyntaxError。

参见https://docs.python.org/3.6/reference/lexical_analysis.html#f-strings

As of Python 3.6 (2016) you can use f-strings to substitute variables:

>>> origin = "London"
>>> destination = "Paris"
>>> f"from {origin} to {destination}"
'from London to Paris'

Note the f" prefix. If you try this in Python 3.5 or earlier, you’ll get a SyntaxError.

See https://docs.python.org/3.6/reference/lexical_analysis.html#f-strings

回答 4

PEP 3101提议%用Python 3中新的高级字符串格式替换运算符，这将是默认格式。

PEP 3101 proposes the replacement of the % operator with the new, advanced string formatting in Python 3, where it would be the default.

回答 5

但是请小心，刚才我在尝试%用.format现有代码替换所有内容时发现了一个问题：'{}'.format(unicode_string)将尝试对unicode_string进行编码，并且可能会失败。

只需查看以下Python交互式会话日志即可：

Python 2.7.2 (default, Aug 27 2012, 19:52:55) 
[GCC 4.1.2 20080704 (Red Hat 4.1.2-48)] on linux2
; s='й'
; u=u'й'
; s
'\xd0\xb9'
; u
u'\u0439'

s只是一个字符串（在Python3中称为“字节数组”），并且u是Unicode字符串（在Python3中称为“字符串”）：

; '%s' % s
'\xd0\xb9'
; '%s' % u
u'\u0439'

当将Unicode对象作为%运算符的参数时，即使原始字符串不是Unicode，它也会产生一个Unicode字符串：

; '{}'.format(s)
'\xd0\xb9'
; '{}'.format(u)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
UnicodeEncodeError: 'latin-1' codec can't encode character u'\u0439' in position 0: ordinal not in range(256)

但该.format函数将引发“ UnicodeEncodeError”：

; u'{}'.format(s)
u'\xd0\xb9'
; u'{}'.format(u)
u'\u0439'

并且仅当原始字符串为Unicode时，它才可以与Unicode参数一起使用。

; '{}'.format(u'i')
'i'

或者参数字符串可以转换为字符串（所谓的“字节数组”）

But please be careful, just now I’ve discovered one issue when trying to replace all % with .format in existing code: '{}'.format(unicode_string) will try to encode unicode_string and will probably fail.

Just look at this Python interactive session log:

Python 2.7.2 (default, Aug 27 2012, 19:52:55) 
[GCC 4.1.2 20080704 (Red Hat 4.1.2-48)] on linux2
; s='й'
; u=u'й'
; s
'\xd0\xb9'
; u
u'\u0439'

s is just a string (called ‘byte array’ in Python3) and u is a Unicode string (called ‘string’ in Python3):

; '%s' % s
'\xd0\xb9'
; '%s' % u
u'\u0439'

When you give a Unicode object as a parameter to % operator it will produce a Unicode string even if the original string wasn’t Unicode:

; '{}'.format(s)
'\xd0\xb9'
; '{}'.format(u)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
UnicodeEncodeError: 'latin-1' codec can't encode character u'\u0439' in position 0: ordinal not in range(256)

but the .format function will raise “UnicodeEncodeError”:

; u'{}'.format(s)
u'\xd0\xb9'
; u'{}'.format(u)
u'\u0439'

and it will work with a Unicode argument fine only if the original string was Unicode.

; '{}'.format(u'i')
'i'

or if argument string can be converted to a string (so called ‘byte array’)

回答 6

的另一个优点.format（我没有在答案中看到）：它可以具有对象属性。

In [12]: class A(object):
   ....:     def __init__(self, x, y):
   ....:         self.x = x
   ....:         self.y = y
   ....:         

In [13]: a = A(2,3)

In [14]: 'x is {0.x}, y is {0.y}'.format(a)
Out[14]: 'x is 2, y is 3'

或者，作为关键字参数：

In [15]: 'x is {a.x}, y is {a.y}'.format(a=a)
Out[15]: 'x is 2, y is 3'

%据我所知，这是不可能的。

Yet another advantage of .format (which I don’t see in the answers): it can take object properties.

In [12]: class A(object):
   ....:     def __init__(self, x, y):
   ....:         self.x = x
   ....:         self.y = y
   ....:         

In [13]: a = A(2,3)

In [14]: 'x is {0.x}, y is {0.y}'.format(a)
Out[14]: 'x is 2, y is 3'

Or, as a keyword argument:

In [15]: 'x is {a.x}, y is {a.y}'.format(a=a)
Out[15]: 'x is 2, y is 3'

This is not possible with % as far as I can tell.

回答 7

%比format我的测试提供更好的性能。

测试代码：

Python 2.7.2：

import timeit
print 'format:', timeit.timeit("'{}{}{}'.format(1, 1.23, 'hello')")
print '%:', timeit.timeit("'%s%s%s' % (1, 1.23, 'hello')")

结果：

> format: 0.470329046249
> %: 0.357107877731

Python 3.5.2

import timeit
print('format:', timeit.timeit("'{}{}{}'.format(1, 1.23, 'hello')"))
print('%:', timeit.timeit("'%s%s%s' % (1, 1.23, 'hello')"))

结果

> format: 0.5864730989560485
> %: 0.013593495357781649

它在Python2中看起来很小，而在Python3中%则比快得多format。

感谢@Chris Cogdon提供示例代码。

编辑1：

2019年7月在Python 3.7.2中再次测试。

结果：

> format: 0.86600608
> %: 0.630180146

没有太大的区别。我想Python正在逐步完善。

编辑2：

在有人在评论中提到python 3的f字符串后，我在python 3.7.2下对以下代码进行了测试：

import timeit
print('format:', timeit.timeit("'{}{}{}'.format(1, 1.23, 'hello')"))
print('%:', timeit.timeit("'%s%s%s' % (1, 1.23, 'hello')"))
print('f-string:', timeit.timeit("f'{1}{1.23}{\"hello\"}'"))

结果：

format: 0.8331376779999999
%: 0.6314778750000001
f-string: 0.766649943

看来f-string仍然比慢，%但比慢format。

% gives better performance than format from my test.

Test code:

Python 2.7.2:

import timeit
print 'format:', timeit.timeit("'{}{}{}'.format(1, 1.23, 'hello')")
print '%:', timeit.timeit("'%s%s%s' % (1, 1.23, 'hello')")

Result:

> format: 0.470329046249
> %: 0.357107877731

Python 3.5.2

import timeit
print('format:', timeit.timeit("'{}{}{}'.format(1, 1.23, 'hello')"))
print('%:', timeit.timeit("'%s%s%s' % (1, 1.23, 'hello')"))

Result

> format: 0.5864730989560485
> %: 0.013593495357781649

It looks in Python2, the difference is small whereas in Python3, % is much faster than format.

Thanks @Chris Cogdon for the sample code.

Edit 1:

Tested again in Python 3.7.2 in July 2019.

Result:

> format: 0.86600608
> %: 0.630180146

There is not much difference. I guess Python is improving gradually.

Edit 2:

After someone mentioned python 3’s f-string in comment, I did a test for the following code under python 3.7.2 :

import timeit
print('format:', timeit.timeit("'{}{}{}'.format(1, 1.23, 'hello')"))
print('%:', timeit.timeit("'%s%s%s' % (1, 1.23, 'hello')"))
print('f-string:', timeit.timeit("f'{1}{1.23}{\"hello\"}'"))

Result:

format: 0.8331376779999999
%: 0.6314778750000001
f-string: 0.766649943

It seems f-string is still slower than % but better than format.

回答 8

正如我今天发现的那样，通过格式化字符串的旧方法%不支持Decimalpython的用于十进制定点和浮点算术的模块。

示例（使用Python 3.3.5）：

#!/usr/bin/env python3

from decimal import *

getcontext().prec = 50
d = Decimal('3.12375239e-24') # no magic number, I rather produced it by banging my head on my keyboard

print('%.50f' % d)
print('{0:.50f}'.format(d))

输出：

0.00000000000000000000000312375239000000009907464850 0.00000000000000000000000312312239239000000000000000000

当然可能有解决方法，但是您仍然可以考虑立即使用该format()方法。

As I discovered today, the old way of formatting strings via % doesn’t support Decimal, Python’s module for decimal fixed point and floating point arithmetic, out of the box.

Example (using Python 3.3.5):

#!/usr/bin/env python3

from decimal import *

getcontext().prec = 50
d = Decimal('3.12375239e-24') # no magic number, I rather produced it by banging my head on my keyboard

print('%.50f' % d)
print('{0:.50f}'.format(d))

Output:

0.00000000000000000000000312375239000000009907464850 0.00000000000000000000000312375239000000000000000000

There surely might be work-arounds but you still might consider using the format() method right away.

回答 9

如果您的python> = 3.6，则F字符串格式的文字是您的新朋友。

它更简单，更干净，性能更好。

In [1]: params=['Hello', 'adam', 42]

In [2]: %timeit "%s %s, the answer to everything is %d."%(params[0],params[1],params[2])
448 ns ± 1.48 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [3]: %timeit "{} {}, the answer to everything is {}.".format(*params)
449 ns ± 1.42 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [4]: %timeit f"{params[0]} {params[1]}, the answer to everything is {params[2]}."
12.7 ns ± 0.0129 ns per loop (mean ± std. dev. of 7 runs, 100000000 loops each)

If your python >= 3.6, F-string formatted literal is your new friend.

It’s more simple, clean, and better performance.

In [1]: params=['Hello', 'adam', 42]

In [2]: %timeit "%s %s, the answer to everything is %d."%(params[0],params[1],params[2])
448 ns ± 1.48 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [3]: %timeit "{} {}, the answer to everything is {}.".format(*params)
449 ns ± 1.42 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [4]: %timeit f"{params[0]} {params[1]}, the answer to everything is {params[2]}."
12.7 ns ± 0.0129 ns per loop (mean ± std. dev. of 7 runs, 100000000 loops each)

回答 10

附带说明，您不必为了提高性能而在日志记录中使用新样式格式。您可以将任何实现了magic方法的对象传递给logging.debug，logging.info等等__str__。当日志记录模块决定必须发出您的消息对象（无论它是什么）时，它将str(message_object)在发出消息之前先进行调用。因此，您可以执行以下操作：

import logging


class NewStyleLogMessage(object):
    def __init__(self, message, *args, **kwargs):
        self.message = message
        self.args = args
        self.kwargs = kwargs

    def __str__(self):
        args = (i() if callable(i) else i for i in self.args)
        kwargs = dict((k, v() if callable(v) else v) for k, v in self.kwargs.items())

        return self.message.format(*args, **kwargs)

N = NewStyleLogMessage

# Neither one of these messages are formatted (or calculated) until they're
# needed

# Emits "Lazily formatted log entry: 123 foo" in log
logging.debug(N('Lazily formatted log entry: {0} {keyword}', 123, keyword='foo'))


def expensive_func():
    # Do something that takes a long time...
    return 'foo'

# Emits "Expensive log entry: foo" in log
logging.debug(N('Expensive log entry: {keyword}', keyword=expensive_func))

所有这些都在Python 3文档（https://docs.python.org/3/howto/logging-cookbook.html#formatting-styles）中进行了描述。但是，它也可以在Python 2.6中使用（https://docs.python.org/2.6/library/logging.html#using-arbitrary-objects-as-messages）。

使用该技术的优点之一是它允许使用惰性值，例如expensive_func上面的函数，这是事实，除了格式风格不可知。这为Python文档中的建议提供了更优雅的替代方法：https : //docs.python.org/2.6/library/logging.html#optimization。

As a side note, you don’t have to take a performance hit to use new style formatting with logging. You can pass any object to logging.debug, logging.info, etc. that implements the __str__ magic method. When the logging module has decided that it must emit your message object (whatever it is), it calls str(message_object) before doing so. So you could do something like this:

import logging


class NewStyleLogMessage(object):
    def __init__(self, message, *args, **kwargs):
        self.message = message
        self.args = args
        self.kwargs = kwargs

    def __str__(self):
        args = (i() if callable(i) else i for i in self.args)
        kwargs = dict((k, v() if callable(v) else v) for k, v in self.kwargs.items())

        return self.message.format(*args, **kwargs)

N = NewStyleLogMessage

# Neither one of these messages are formatted (or calculated) until they're
# needed

# Emits "Lazily formatted log entry: 123 foo" in log
logging.debug(N('Lazily formatted log entry: {0} {keyword}', 123, keyword='foo'))


def expensive_func():
    # Do something that takes a long time...
    return 'foo'

# Emits "Expensive log entry: foo" in log
logging.debug(N('Expensive log entry: {keyword}', keyword=expensive_func))

This is all described in the Python 3 documentation (https://docs.python.org/3/howto/logging-cookbook.html#formatting-styles). However, it will work with Python 2.6 as well (https://docs.python.org/2.6/library/logging.html#using-arbitrary-objects-as-messages).

One of the advantages of using this technique, other than the fact that it’s formatting-style agnostic, is that it allows for lazy values e.g. the function expensive_func above. This provides a more elegant alternative to the advice being given in the Python docs here: https://docs.python.org/2.6/library/logging.html#optimization.

回答 11

一种%可能有用的情况是格式化正则表达式时。例如，

'{type_names} [a-z]{2}'.format(type_names='triangle|square')

加薪IndexError。在这种情况下，您可以使用：

'%(type_names)s [a-z]{2}' % {'type_names': 'triangle|square'}

这样可以避免将正则表达式写为'{type_names} [a-z]{{2}}'。当您有两个正则表达式时，这很有用，其中一个正则表达式单独使用而没有格式，但是两个正则表达式的连接都已格式化。

One situation where % may help is when you are formatting regex expressions. For example,

'{type_names} [a-z]{2}'.format(type_names='triangle|square')

raises IndexError. In this situation, you can use:

'%(type_names)s [a-z]{2}' % {'type_names': 'triangle|square'}

This avoids writing the regex as '{type_names} [a-z]{{2}}'. This can be useful when you have two regexes, where one is used alone without format, but the concatenation of both is formatted.

回答 12

我要补充一点，从3.6版开始，我们可以像下面这样使用fstrings

foo = "john"
bar = "smith"
print(f"My name is {foo} {bar}")

哪个给

我叫约翰·史密斯

一切都转换为字符串

mylist = ["foo", "bar"]
print(f"mylist = {mylist}")

结果：

mylist = [‘foo’，’bar’]

您可以像其他格式一样传递函数

print(f'Hello, here is the date : {time.strftime("%d/%m/%Y")}')

举个例子

您好，这是日期：16/04/2018

I would add that since version 3.6, we can use fstrings like the following

foo = "john"
bar = "smith"
print(f"My name is {foo} {bar}")

Which give

My name is john smith

Everything is converted to strings

mylist = ["foo", "bar"]
print(f"mylist = {mylist}")

Result:

mylist = [‘foo’, ‘bar’]

you can pass function, like in others formats method

print(f'Hello, here is the date : {time.strftime("%d/%m/%Y")}')

Giving for example

Hello, here is the date : 16/04/2018

回答 13

对于python版本> = 3.6（请参阅PEP 498）

s1='albha'
s2='beta'

f'{s1}{s2:>10}'

#output
'albha      beta'

For python version >= 3.6 (see PEP 498)

s1='albha'
s2='beta'

f'{s1}{s2:>10}'

#output
'albha      beta'

回答 14

Python 3.6.7比较：

#!/usr/bin/env python
import timeit

def time_it(fn):
    """
    Measure time of execution of a function
    """
    def wrapper(*args, **kwargs):
        t0 = timeit.default_timer()
        fn(*args, **kwargs)
        t1 = timeit.default_timer()
        print("{0:.10f} seconds".format(t1 - t0))
    return wrapper


@time_it
def new_new_format(s):
    print("new_new_format:", f"{s[0]} {s[1]} {s[2]} {s[3]} {s[4]}")


@time_it
def new_format(s):
    print("new_format:", "{0} {1} {2} {3} {4}".format(*s))


@time_it
def old_format(s):
    print("old_format:", "%s %s %s %s %s" % s)


def main():
    samples = (("uno", "dos", "tres", "cuatro", "cinco"), (1,2,3,4,5), (1.1, 2.1, 3.1, 4.1, 5.1), ("uno", 2, 3.14, "cuatro", 5.5),) 
    for s in samples:
        new_new_format(s)
        new_format(s)
        old_format(s)
        print("-----")


if __name__ == '__main__':
    main()

输出：

new_new_format: uno dos tres cuatro cinco
0.0000170280 seconds
new_format: uno dos tres cuatro cinco
0.0000046750 seconds
old_format: uno dos tres cuatro cinco
0.0000034820 seconds
-----
new_new_format: 1 2 3 4 5
0.0000043980 seconds
new_format: 1 2 3 4 5
0.0000062590 seconds
old_format: 1 2 3 4 5
0.0000041730 seconds
-----
new_new_format: 1.1 2.1 3.1 4.1 5.1
0.0000092650 seconds
new_format: 1.1 2.1 3.1 4.1 5.1
0.0000055340 seconds
old_format: 1.1 2.1 3.1 4.1 5.1
0.0000052130 seconds
-----
new_new_format: uno 2 3.14 cuatro 5.5
0.0000053380 seconds
new_format: uno 2 3.14 cuatro 5.5
0.0000047570 seconds
old_format: uno 2 3.14 cuatro 5.5
0.0000045320 seconds
-----

Python 3.6.7 comparative:

#!/usr/bin/env python
import timeit

def time_it(fn):
    """
    Measure time of execution of a function
    """
    def wrapper(*args, **kwargs):
        t0 = timeit.default_timer()
        fn(*args, **kwargs)
        t1 = timeit.default_timer()
        print("{0:.10f} seconds".format(t1 - t0))
    return wrapper


@time_it
def new_new_format(s):
    print("new_new_format:", f"{s[0]} {s[1]} {s[2]} {s[3]} {s[4]}")


@time_it
def new_format(s):
    print("new_format:", "{0} {1} {2} {3} {4}".format(*s))


@time_it
def old_format(s):
    print("old_format:", "%s %s %s %s %s" % s)


def main():
    samples = (("uno", "dos", "tres", "cuatro", "cinco"), (1,2,3,4,5), (1.1, 2.1, 3.1, 4.1, 5.1), ("uno", 2, 3.14, "cuatro", 5.5),) 
    for s in samples:
        new_new_format(s)
        new_format(s)
        old_format(s)
        print("-----")


if __name__ == '__main__':
    main()

Output:

new_new_format: uno dos tres cuatro cinco
0.0000170280 seconds
new_format: uno dos tres cuatro cinco
0.0000046750 seconds
old_format: uno dos tres cuatro cinco
0.0000034820 seconds
-----
new_new_format: 1 2 3 4 5
0.0000043980 seconds
new_format: 1 2 3 4 5
0.0000062590 seconds
old_format: 1 2 3 4 5
0.0000041730 seconds
-----
new_new_format: 1.1 2.1 3.1 4.1 5.1
0.0000092650 seconds
new_format: 1.1 2.1 3.1 4.1 5.1
0.0000055340 seconds
old_format: 1.1 2.1 3.1 4.1 5.1
0.0000052130 seconds
-----
new_new_format: uno 2 3.14 cuatro 5.5
0.0000053380 seconds
new_format: uno 2 3.14 cuatro 5.5
0.0000047570 seconds
old_format: uno 2 3.14 cuatro 5.5
0.0000045320 seconds
-----

回答 15

但是有一件事是，如果您嵌套了花括号，则不能使用格式但%可以使用。

例：

>>> '{{0}, {1}}'.format(1,2)
Traceback (most recent call last):
  File "<pyshell#3>", line 1, in <module>
    '{{0}, {1}}'.format(1,2)
ValueError: Single '}' encountered in format string
>>> '{%s, %s}'%(1,2)
'{1, 2}'
>>>

But one thing is that also if you have nested curly-braces, won’t work for format but % will work.

Example:

>>> '{{0}, {1}}'.format(1,2)
Traceback (most recent call last):
  File "<pyshell#3>", line 1, in <module>
    '{{0}, {1}}'.format(1,2)
ValueError: Single '}' encountered in format string
>>> '{%s, %s}'%(1,2)
'{1, 2}'
>>>

github

PySnooper-不再使用打印进行调试

2021年7月15日 Python实用宝典

PySnooper-绝不再使用打印进行调试

PySnooper是穷人的调试器。如果你用过Bash，它就像set -x对于Python来说，只是它更华丽

您的故事：您正在试图弄清楚为什么Python代码没有执行您认为它应该执行的操作。您可能希望使用具有断点和监视的功能齐全的调试器，但是您现在不需要费心设置一个调试器

您想知道哪些行正在运行，哪些没有运行，以及局部变量的值是什么

大多数人都会用print战略位置的线条，其中一些线条显示变量的值

PySnooper让您做同样的事情，只是不需要仔细设计正确的print行，您只需向您感兴趣的函数添加一个修饰符行。您将获得函数的逐个播放日志，包括运行哪些行、运行时间以及更改局部变量的确切时间

是什么让PySnooper从所有其他代码智能工具中脱颖而出？您可以在您糟糕的、杂乱无章的企业代码库中使用它，而不必进行任何设置。只需启动修饰符，如下所示，并通过将其路径指定为第一个参数将输出重定向到专用日志文件

示例

我们正在编写一个函数，通过返回位列表将数字转换为二进制。让我们通过添加@pysnooper.snoop()装饰师：

import pysnooper

@pysnooper.snoop()

def number_to_bits(number):
    if number:
        bits = []
        while number:
            number, remainder = divmod(number, 2)
            bits.insert(0, remainder)
        return bits
    else:
        return [0]

number_to_bits(6)

stderr的输出为：

Source path:... /my_code/foo.py
Starting var:.. number = 6
15:29:11.327032 call         4 def number_to_bits(number):
15:29:11.327032 line         5     if number:
15:29:11.327032 line         6         bits = []
New var:....... bits = []
15:29:11.327032 line         7         while number:
15:29:11.327032 line         8             number, remainder = divmod(number, 2)
New var:....... remainder = 0
Modified var:.. number = 3
15:29:11.327032 line         9             bits.insert(0, remainder)
Modified var:.. bits = [0]
15:29:11.327032 line         7         while number:
15:29:11.327032 line         8             number, remainder = divmod(number, 2)
Modified var:.. number = 1
Modified var:.. remainder = 1
15:29:11.327032 line         9             bits.insert(0, remainder)
Modified var:.. bits = [1, 0]
15:29:11.327032 line         7         while number:
15:29:11.327032 line         8             number, remainder = divmod(number, 2)
Modified var:.. number = 0
15:29:11.327032 line         9             bits.insert(0, remainder)
Modified var:.. bits = [1, 1, 0]
15:29:11.327032 line         7         while number:
15:29:11.327032 line        10         return bits
15:29:11.327032 return      10         return bits
Return value:.. [1, 1, 0]
Elapsed time: 00:00:00.000001

或者，如果您不想跟踪整个函数，可以将相关部分包装在with挡路：

import pysnooper
import random

def foo():
    lst = []
    for i in range(10):
        lst.append(random.randrange(1, 1000))

    with pysnooper.snoop():
        lower = min(lst)
        upper = max(lst)
        mid = (lower + upper) / 2
        print(lower, mid, upper)

foo()

它输出类似于以下内容的内容：

New var:....... i = 9
New var:....... lst = [681, 267, 74, 832, 284, 678, ...]
09:37:35.881721 line        10         lower = min(lst)
New var:....... lower = 74
09:37:35.882137 line        11         upper = max(lst)
New var:....... upper = 832
09:37:35.882304 line        12         mid = (lower + upper) / 2
74 453.0 832
New var:....... mid = 453.0
09:37:35.882486 line        13         print(lower, mid, upper)
Elapsed time: 00:00:00.000344

功能

如果您不容易访问stderr，您可以将输出重定向到文件：

@pysnooper.snoop('/my/log/file.log')

您也可以改为传递一个流或一个可调用的，它们将被使用

请查看一些不是局部变量的表达式的值：

@pysnooper.snoop(watch=('foo.bar', 'self.x["whatever"]'))

显示函数调用的函数的监听行：

@pysnooper.snoop(depth=2)

看见Advanced Usage了解更多选项<

使用管道安装

安装的最佳方式是PySnooper是和皮普在一起：

$ pip install pysnooper

其他安装选项

带Conda-Forge通道的Conda：

$ conda install -c conda-forge pysnooper

Arch Linux：

$ yay -S python-pysnooper

Feddora Linux：

$ dnf install python3-pysnooper

许可证

媒体报道

Hacker News thread和/r/Python Reddit thread(2019年4月22日)