标准库函数
- logging.Handler, logging.Formatter
logging
getLogger FileHandler StreamHandler
logging 是个用来定义输出的模块, print 函数只能指定一个输出, 有时候我们既想在终端输出, 也想保存在文件中, 一种方法是同时使用 print 和文件操作的 write 函数来进行, 而 logging 则可以很优雅的定制双输出方式. 代码如下
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import os
import logging
from time import time, strftime, localtime
from datetime import datetime
levels = [logging.NOTSET,
logging.DEBUG,
logging.INFO,
logging.WARNING,
logging.ERROR,
logging.CRITICAL]
def create_logger(log_file=None, file_=True, console=True,
withtime=False, file_level=2, console_level=2):
if file_:
prefix = strftime('%Y%m%d%H%M%S', localtime(time()))
if log_file is None:
log_file = os.path.join(os.path.dirname(__file__), prefix)
elif withtime:
log_file = os.path.join(os.path.dirname(log_file), prefix + "_" + os.path.basename(log_file))
if os.path.exists(log_file):
os.remove(log_file)
logger = logging.getLogger()
logger.setLevel(levels[0])
formatter = logging.Formatter("%(message)s")
if file_:
# Create file handler
file_handler = logging.FileHandler(log_file)
file_handler.setLevel(levels[file_level])
file_handler.setFormatter(formatter)
# Register handler
logger.addHandler(file_handler)
if console:
# Create console handler
console_handler = logging.StreamHandler()
console_handler.setLevel(levels[console_level])
console_handler.setFormatter(formatter)
logger.addHandler(console_handler)
return logger
# Using
logger = create_logger()
logger.info('Some messages')
logger.debug('Debug infomation')
logger.error('Some errors')
输出
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# Console
Some messages
Some errors
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# File 20171119020228.log
Some messages
Some errors
注意以下几点:
- 不指定文件名时使用当前日期和时间自动生成文件名比如
20171119020228.log setlevel()函数用来设置记录信息的级别, 在logging模块中总共有六级信息, 分别是- CRITICAL
- ERROR
- WARNING
- INFO
- DEBUG
- NOTSET
等级从高到低, 设置为某一等级的意思是低于该等级的信息将不会显示, 比如我们上面设置了等级为
INFO, 那么logger.debug('message')的信息将不会被记录下来.- 使用
logging.FileHandler()创建文件句柄, 使用logging.StreamHandler()创建控制台句柄. - 使用
logging.Formatter()创建信息格式化方式, 其中%(message)s是python中的格式化字符串, 一般来说%s表示字符串, 可以使用'%s - %s' % (name1, name2)这样的形式(元组)来为格式化字符串传值. 而%(message)s的方式可以为该格式化字符串指定名称message, 这样可以通过字典来传值, 比如'%(message)s - %(name)s' % {'message': msg, 'name': name}.
Formatter
有时候我们希望 logger 的输出有一定的格式, 那么就可以使用 logging.Formatter 类来指定. 自动识别的格式有如下几种, 其他的请参考 .
| 属性名 | 格式 | 描述 |
|---|---|---|
asctime |
%(asctime)s |
字符串形式的当前时间。默认格式是 “2003-07-08 16:49:45,896”。逗号后面的是毫秒 |
levelname |
%(levelname)s |
日志级别, 英文单词 |
levelno |
%(levelno)s |
日志级别, 数字 |
message |
%(message)s |
输出的消息 |
msecs |
%(msecs)d |
时间的毫秒数 |
name |
%(name)s |
Logger 的名字 |
举个例子, 假如格式化字符串为
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formatter = logging.Formatter("%(asctime)s %(levelname)s %(message)s")
那么 logger.info('Some message') 会输出 2017-11-19 15:54:12,345 INFO Some message 这样的信息.
下面给出一个实例, 用来得到和 tensorflow 类似下面这样的输出消息格式
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2017-11-19 02:02:37.110996: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2017-11-19 02:02:37.111027: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-11-19 02:02:37.111033: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-11-19 02:02:37.111055: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-11-19 02:02:37.111060: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
2017-11-19 02:02:37.823554: I tensorflow/core/common_runtime/gpu/gpu_device.cc:955] Found device 0 with properties:
name: GeForce GTX 1080 Ti
major: 6 minor: 1 memoryClockRate (GHz) 1.582
pciBusID 0000:86:00.0
Total memory: 10.91GiB
Free memory: 10.76GiB
2017-11-19 02:02:37.823608: I tensorflow/core/common_runtime/gpu/gpu_device.cc:976] DMA: 0
2017-11-19 02:02:37.823624: I tensorflow/core/common_runtime/gpu/gpu_device.cc:986] 0: Y
2017-11-19 02:02:37.823642: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1045] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:86:00.0)
我们看到这里的时间是以小数点加三位毫秒和三位微秒数字结尾的, 并且级别信息为单个字母. 可以通过重载 logging.Formatter() 类来实现
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import logging
class MyFormatter(logging.Formatter):
converter = datetime.fromtimestamp
# Here the `record` is a LogRecord obejct
def formatTime(self, record, datefmt=None):
ct = self.converter(record.created)
if datefmt:
s = ct.strftime(datefmt)
else:
t = ct.strftime("%Y-%m-%d %H:%M:%S")
s = "%s.%03d" % (t, record.msecs)
return s
def create_logger(...):
...
...
formatter = MyFormatter("%(asctime)s: %(levelname).1s %(message)s")
...
...
return logger
其中 %(levelname).1s 表示只输出字符串的第一个字符.
Stream
有时候我们不用 print() 来打印信息, 而需要 pprint.pprint() 这样的函数来打印格式化的信息, 一般来说 pprint 函数也是直接打印到控制台的, 如果要控制打印位置, 则需要添加参数. 此时我们可以按照如下的方式使用我们的 logger :
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from pprint import pprint
some_message = "123456"
# print 函数
for handler in logger.handlers:
print(some_message, file=handler.stream)
# pprint 函数
for handler in logger.handlers:
pprint(some_message, stream=handler.stream)