实现了简单版本的logging.config,支持一般的通过config文件进行配置。
感觉还有更好的方法,是直接利用logging.config.fileConfig(log_config_file)方式读进来之后,通过修改handler方式来进行修改。
代码如下:
"""
project trace system
"""
import sys
import ConfigParser
import logging
import logging.config
import warnings
if __name__ == "__main__":
log_config_file = "log.conf"
log_data_file = "logs/run.log"
LEVEL_dic = {
"DEBUG": logging.DEBUG,
"INFO": logging.INFO,
"WARNING": logging.WARNING,
"ERROR": logging.ERROR,
"CRITICAL": logging.CRITICAL
}
class LogConfig(object):
def __init__(self, log_config_file, log_data_file=None):
self.log_config_file = log_config_file
self.log_data_file = log_data_file # for self app
self.log_config = ConfigParser.RawConfigParser()
self.log_config.read(self.log_config_file)
self.logger_prefix = "logger_"
self.handler_prefix = "handler_"
self.formatter_prefix = "formatter_"
self._check_section()
self._parse_option()
def _check_section(self):
# check logger
self.__check_logger()
# check handler
self.__check_handler()
# check formatter
self.__check_formatter()
def _parse_option(self):
# parse formatter option
for formatter, formatter_info in self.formatters.items():
section_name = formatter_info["section_name"]
f = self.log_config.get(section_name, "format")
datefmt = self.log_config.get(section_name, "datefmt")
self.formatters[formatter]["value"] = logging.Formatter(f, datefmt)
# parse handlers
for handler, handler_info in self.handlers.items():
section_name = handler_info["section_name"]
handler_class = self.log_config.get(section_name, "class")
handler_str = self.log_config.get(section_name, "args")
handler_args = eval(self.log_config.get(section_name, "args"))
level = self.log_config.get(section_name, "level")
formatter = self.log_config.get(section_name, "formatter")
_handler = eval("logging."+handler_class)
# only FileHandler has file path paramter.
if isinstance(_handler, logging.FileHandler):
if self.log_data_file:
handler_args[0] = self.log_data_file
else:
warnings.warn("fileHandler found, but log data file is not specified")
self.handlers[handler]["value"] = _handler(*handler_args)
self.handlers[handler]["value"].setLevel(
LEVEL_dic.get(level.upper(), LEVEL_dic["INFO"]))
self.handlers[handler]["value"].setFormatter(
self.formatters[formatter]["value"])
# parse logger
for logger, logger_info in self.loggers.items():
section_name = logger_info["section_name"]
self.__parse_logger(logger, section_name)
def __parse_logger(self, logger_name, section_name):
"""
"""
tuple_items = self.log_config.items(section_name)
logger = logging.getLogger(logger_name)
for k, v in tuple_items:
if k == "handlers":
handlers = filter(None, [h.strip() for h in v.split(",")])
for h in handlers:
logger.addHandler(self.handlers[h]["value"])
if k == "level":
logger.setLevel(LEVEL_dic.get(v, LEVEL_dic["INFO"]))
if k == "propagate" and v:
logger.propagate = int(v)
# here other attributes could be added. TODO
self.loggers[logger_name]['value'] = logger
def __check_logger(self):
_loggers = self.log_config.get("loggers", "keys").split(",")
self.loggers = {}
for logger in _loggers:
logger = logger.strip()
if logger:
logger_section_name = self.logger_prefix + logger
if not self.log_config.has_section(logger_section_name):
raise Exception(
"ERROR: no logger section name: {0}".format(logger_section_name))
self.loggers.setdefault(logger, {})
self.loggers[logger]["section_name"] = logger_section_name
if not self.loggers:
raise Exception(
"ERROR: No logger keys in {0}".format(self.log_config_file))
def __check_handler(self):
_handlers = self.log_config.get("handlers", "keys").split(",")
self.handlers = {}
for handler in _handlers:
handler = handler.strip()
if handler:
handler_section_name = self.handler_prefix + handler
if not self.log_config.has_section(handler_section_name):
raise Exception("ERROR: no handler section name: {0}".format(handler_section_name))
self.handlers.setdefault(handler , {})
self.handlers[handler]["section_name"] = handler_section_name
if not self.handlers:
raise Exception("ERROR: No handler keys in {0}".format(self.log_config_file))
def __check_formatter(self):
_formatters = self.log_config.get("formatters", "keys").split(",")
self.formatters = {}
for formatter in _formatters:
formatter = formatter.strip()
if formatter:
formatter_section_name = self.formatter_prefix + formatter
if not self.log_config.has_section(formatter_section_name):
raise Exception("ERROR: no formatter section name: {0}".format(formatter_section_name))
self.formatters.setdefault(formatter, {})
self.formatters[formatter]["section_name"] = formatter_section_name
if not self.formatters:
raise Exception("ERROR: No formatter keys in {0}".format(self.log_config_file))
def getLogger(self, logger_name="root"):
return self.loggers[logger_name]['value']
class Trace(object):
def __init__(self, log_config_file, log_key="root", log_data_file=None):
self.log_config_file = log_config_file
self.log_data_file = log_data_file
self.log_key = log_key
Log = LogConfig(self.log_config_file, self.log_data_file)
self.logger = Log.getLogger(self.log_key)
def info(self, key, info):
self.logger.info("[{0}]: {1}".format(key, info))
def error(self, key, err_info):
self.logger.error("[{0}]: {1}".format(key, err_info))
def warn(self, key, warn_info):
self.logger.warn("[{0}]: {1}".format(key, warn_info))
def test():
log_key = "root"
t = Trace(log_config_file, log_key, log_data_file)
t.info("TEST TRACE", "OK")
if __name__ == "__main__":
test()
log.conf
代码如下:
[loggers]
keys = root, debug
[handlers]
keys=consoleHandler, timedRotatingFileHandler
[formatters]
keys=simpleFormatter
[logger_root]
level=DEBUG
handlers=consoleHandler, timedRotatingFileHandler
[logger_debug]
level=DEBUG
handlers=consoleHandler
propagate=0
[handler_consoleHandler]
class=StreamHandler
level=DEBUG
formatter=simpleFormatter
args=(sys.stdout,)
[handler_timedRotatingFileHandler]
class=handlers.TimedRotatingFileHandler
level=DEBUG
formatter=simpleFormatter
args=("./run.log", 'midnight', 1, 10)
[formatter_simpleFormatter]
format=[%(asctime)s][%(levelname)s][%(process)d:%(thread)d][%(filename)s:%(lineno)d]:%(message)s
datefmt=%Y-%m-%d %H:%M:%S

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

ZendStudio 13.5.1 Mac
Powerful PHP integrated development environment

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.