♥ Foreword
In software development, it is a good habit to record the running status of the program through logs, which is very helpful for error troubleshooting and system operation and maintenance.
The Python standard library comes with a powerful logging module, which is widely used in various python modules.
1. Easy to use
1. Introductory small case
import logging
logging.basicConfig(level=logging.DEBUG, #设置级别，根据等级显示
format='%(asctime)s-[%(filename)s-->line:%(lineno)d]-%(levelname)s:% (message)s') # 设置输出格式
logging.debug('This is a debug log')
logging.info('This is a info log')
logging.warning('This is a warning log')
logging.error('This is a error log')
logging.critical('This is a critical log')2. Log level
Five log levels are set according to different situations, and different levels of logs are output in different situations.
| log level （level） |
describe |
| DEBUG |
Debug information, usually useful when diagnosing problems |
| INFO |
General information, confirming that the program works as expected |
| WARNING |
A warning message that indicates that something unexpected happened, or that something might go wrong next time, but the program continues to run |
| ERROR |
Error message, there are some problems in the running of the program, some functions of the program cannot be executed |
| CRITICAL |
Danger message, a critical error that prevents the program from continuing |
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logging.basicConfig(level=logging.WARNING, #设置级别，根据等级显示
format='%(asctime)s-[%(filename)s-->line:%(lineno)d]-%(levelname)s:% (message)s') # 设置输出格式
logging.debug('This is a debug log')
logging.info('This is a info log')
logging.warning('This is a warning log')
logging.error('This is a error log')
logging.critical('This is a critical log')2020-09-11 17:39:26,667-WARNING-This is a warning log
2020-09-11 17:39:26,669-ERROR-This is a error log
2020-09-11 17:39:26,669-CRITICAL-This is a critical log
3. Configuration
The basicConfig method supports the following keyword parameters for configuration.
| parameter |
describe |
| filename |
Create a FileHandler with the specified filename instead of a StreamHandler. |
| filemode |
If filename is specified, the file is opened with this mode. The default mode is 'a'. |
| format |
Specifies the format string used by the processor. |
| datefmt |
Use the specified date/time format, as accepted by time.strftime(). |
| style |
If format is specified, this style will be used for the format string. '%', '{' or '$' correspond to printf style, str.format() or string.Template respectively. The default is'%'. |
| level |
Sets the root logger level to the specified level. |
| stream |
Initializes a StreamHandler with the specified stream. Note that this parameter is incompatible with filename - a ValueError is raised if both are present. |
| handlers |
If specified, this should be an iterable containing the created handlers to join the root logger. Any handlers that do not already have a format descriptor set will be set to the default format descriptor created in this function. Note that this parameter is not compatible with filename or stream -- a ValueError is raised if both are present. |
| force |
If this keyword argument is specified as true, any existing handlers attached to the root logger will be removed and closed before executing the configuration specified by the other arguments. |
Default type: %(asctime)s-[%(filename)s-->line:%(lineno)d]-%(levelname)s:%(message)s
import logging
logging.basicConfig(level=logging.DEBUG, #设置级别，根据等级显示
format='%(asctime)s-[%(filename)s-->line:%(lineno)d]-%(levelname)s:% (message)s') # 设置输出格式
logging.debug('This is a debug log')[DEBUG]-2020-09-11 17:36:50,125--4:This is a debug log
5. Log written to file
Just configure the filename parameter
import logging
logging.basicConfig(
level=logging.WARNING, #设置级别，根据等级显示
filename='example.log'
format='%(asctime)s-[%(filename)s-->line:%(lineno)d]-%(levelname)s:% (message)s') # 设置输出格式
logging.debug('This is a debug log')
logging.info('This is a info log')
logging.warning('This is a warning log')
logging.error('This is a error log')
logging.critical('This is a critical log')Note that after fielname is configured, the log will not be output on the console.
2. Advanced usage
Simple code can be used directly through logging. If you want to use it in depth, you need to use logging in an object-oriented manner.
1. Log component
The logging module contains the following components.
| components |
illustrate |
| Loggers |
The interface that the provider uses directly |
| Handlers (log processor) |
Send recorded logs to the specified location |
| Filters (log filter) |
Used to filter specific log records |
| Formatters (log formatter) |
Used to control the output format of log information |
2. Steps
2.1 Create a logger
import logging
# 第一步创建一个logger，用来产生日志
logger = logging.getLogger('%s_log' % __name__)
logger.setLevel(logging.DEBUG) # 设置日志等级
A logger can be created through the getLogger method, pay attention to the name or return to the root logger.
Set the logger level by setLevel.
2.2 Create a log processor
# 创建一个文本处理器用来将日志写入到文件
file_handler = logging.FileHandler(filename='py34.log',encoding='utf-8')file_handler.setLevel('WARNING') # 设置处理器的日志等级# 创建一个控制台处理器用来将日志输出到控制台
console_handler = logging.StreamHandler()
console_handler.setLevel('INFO') # 设置控制台处理器的日志等级The log processor is to send the log to the specified location.
-
FileHandler to send logs to a file
-
StreaHandler It can send logging output to a data stream such as sys.stdout, sys.stderr or any file-like object. Default sys.stdout is the console.
-
RotatingFileHandler supports rotation based on log file size
-
TimedRotatingFileHandler supports rotating log files based on time
See official docs for more details
（https://docs.python.org/zh-cn/3/library/logging.handlers.html?utm_source=testingpai.com#module-logging.handlers）
2.3 Create a formatter
formatter = logging.Formatter(fmt='%(levelname)s %(asctime)s [%(filename)s-->line:%(lineno)d]:%(message)s')
The formatter needs to be set on the handler
file_handler.setFormatter(formatter)
console_handler.setFormatter(formatter)2.4 Create filter
Filters are used to filter specified logs. The specific use is omitted, generally not used.
See the official documentation for details
（https://docs.python.org/zh-cn/3/howto/logging-cookbook.html?utm_source=testingpai.com#filters-contextual）
2.5 Add the processor to the logger
logger.addHandler(file_handler)
logger.addHandler(console_handler)2.6 Logging
logger.info('This is a info')2020-09-11 22:22:44,095-[-->line:1]-INFO:This is a info
logger.warning('This is a warning')
2020-09-11 22:23:20,337-[-->line:1]-WARNING:This is a warning
3. Log module encapsulation
1. Functional analysis
-
Ability to customize the logger name
-
Ability to customize log file name and path
-
Ability to customize log file encoding
-
Ability to customize log format
-
Use a time-round handler, and be able to configure
2. Encapsulated into a function
Create the module log_handler.py in the common directory and create the following functions in it.
import logging
from logging.handlers import TimedRotatingFileHandler
def get_logger(name, filename, encoding='utf-8', fmt=None, when='d', interval=1, backup_count=7, debug=False):
"""
:param name: 日志器的名字
:param filename: 日志文件名(包含路径)
:param encoding: 字符编码
:param fmt: 日志格式
:param when: 日志轮转时间单位
:param interval: 间隔
:param backup_count: 日志文件个数
:param debug: 调试模式
:return:
"""
logger = logging.getLogger(name)
logger.setLevel(logging.DEBUG)
# 文件处理器的等级一般情况一定比控制台要高
if debug:
file_level = logging.DEBUG
console_level = logging.DEBUG
else:
file_level = logging.WARNING
console_level = logging.INFO
if fmt is None:
fmt = '%(levelname)s %(asctime)s [%(filename)s-->line:%(lineno)d]:%(message)s'
file_handler = TimedRotatingFileHandler(
filename=filename, when=when, interval=interval, backupCount=backup_count, encoding=encoding)
file_handler.setLevel(file_level)
console_handler = logging.StreamHandler()
console_handler.setLevel(console_level)
formatter = logging.Formatter(fmt=fmt)
file_handler.setFormatter(formatter)
console_handler.setFormatter(formatter)
logger.addHandler(file_handler)
logger.addHandler(console_handler)
return logger
if __name__ == '__main__':
log = get_logger(name='py41', filename='py41.log', debug=True, when='s')
log.info('我是普通信息')
import time
time.sleep(3)
log.warning('我是警告信息')
4. Apply to the project
1. Import
The import of the log generator function cannot be imported once in each use case module like the Excel data reading function. Because it returns a logger object, when the logger generation function is called multiple times with the same logger name, multiple log processors will be added to the same logger, resulting in the problem of duplicating loggers.
In order to solve the above problem, create a file named __init__.py under the common folder. When the common module is imported, the code in this file will be executed automatically, and it will only be executed once.
Write the following code in the __init__.py file:
from .log_handler import get_logger
logger = get_logger('py41', 'py38.log')
Then in other modules in the project, you can import it through the following code
from common import loggerThis ensures that the get_logger method will only be executed once during project execution.
2. Logging
The role of the log is to record the running status of the program and provide a basis for locating and analyzing errors when the program has problems.
When and what kind of logs need to be recorded depends on everyone's understanding of the program and experience.
In our project, the process of executing use cases is the core, so our logs also revolve around the execution of use cases.
Use logs to record the test data and test results of each use case. The code is as follows:
...
@list_data(*cases)
def test_login(self, case):
"""
登陆测试
"""
logger.info('测试用例【{}】开始测试'.format(case['title']))
# 1. 测试数据
# 传入进来的case参数
logger.info('测试用例【{}】的测试数据是:{}'.format(case['title'], case))
# 2. 测试步骤
res = login_check(case['username'], case['password'])
logger.info('测试用例【{}】的测试结果是:{}'.format(case['title'], res))
# 3. 断言
try:
self.assertEqual(res, case['expect'])
except AssertionError as e:
logger.error('测试用例【{}】断言失败'.format(case['title']))
raise e
else:
logger.info('测试用例【{}】断言成功'.format(case['title']))
finally:
logger.info('测试用例【{}】测试结束')