PythonMaker 2020-04-10
装饰器的应用场景
不同应用场景下装饰器实现
函数注册表
简单注册表
funcs = [] def register(func): funcs.append(func) return func @register def a(): return 3 @register def b(): return 5 # 访问结果 result = [func() for func in funcs]
注册表隔离(使用类的不同实例)
class Registry(object): def __init__(self): self._funcs = [] def register(self, func): self._funcs.append(func) def run_all(self): return [func() for func in self._funcs] r1 = Registry() r2 = Registry() @r1.register def a(): return 3 @r2.register def b(): return 5 @r1.register @r2.register
执行时封装代码
类型检查
from functools import wraps def require_ints(func): @wraps(func) # 将func的信息复制给inner def inner(*args, **kwargs): for arg list(args) + list(kwargs.values()): if not isinstance(arg, int: raise TypeError("{} 只接受int类型参数".format(func.__name__) return func(*args, **kwargs) return inner
用户验证
from functools import wraps class User(object): def __init__(self, username, email): self.username = username self.email = email class AnonymousUser(object): def __init__(self): self.username = self.email = None def __nonzero__(self): # 将对象转换为bool类型时调用 return False def requires_user(func): @wraps(func) def inner(user, *args, **kwargs): # 由于第一个参数无法支持self, 该装饰器不支持装饰类 if user and isinstance(user, User): return func(use, *args, **kwargs) else: raise ValueError("非合法用户") return inner
输出格式化
import json from functools import wraps def json_output(func): # 将原本func返回的字典格式转为返回json字符串格式 @wrap(func) def inner(*args, **kwargs): return json.dumps(func(*args, **kwargs)) return inner
异常捕获
import json from functools import wraps class Error1(Exception): def __init__(self, msg): self.msg = msg def __str__(self): return self.msg def json_output(func): @wrap(func) def inner(*args, **kwargs): try: result = func(*args, **kwargs) except Error1 as ex: result = {"status": "error", "msg": str(ex)} return json.dumps(result) return inner # 使用方法 @json_ouput def error(): raise Error1("该条异常会被捕获并按JSON格式输出")
日志管理
import time import logging from functools import wraps def logged(func): @wraps(func) def inner(*args, **kwargs): # *args可以装饰函数也可以装饰类 start = time.time() result = func(*args, **kwargs) exec_time = time.time() - start logger = logging.getLoger("func.logged") logger.warning("{} 调用时间:{:.2} 执行时间:{:.2}s 结果:{}".format(func.__name__, start, exec_time, result)
带参数的装饰器
带参数的装饰器相当于一个返回装饰器的函数,@deco(a=1)在调用@之前会首先执行deco(a=1)得到一个实际的装饰器, 带参数的装饰器deco(a=1)模块导入时立即执行
装饰类
为类增加可排序功能(而不通过继承子类扩充父类方法,比如多个类需要增加此功能时)
import time from functools import wraps def sortable_by_created(cls): original_init = cls.__init__ @wrap(original_init) def new_init(self, *args, **kwargs): original_init(*args, **kwargs) self._created = time.time() cls.__init__ = new_init cls.__lt__ = lambda self, other: self._created < other._created cls.__gt__ = lambda self, other: self._created > other._created return cls
也可定义一个SortableByCreated()类, 子类使用多重继承其父类和SortableByCreated
类型转换
函数被装饰后有可能变为一个类的实例,此时为了兼容函数调用,应为所返回的类提供__call__方法
class Task(object): def __call__(self, *args, **kwargs): return self.run(*args, **kwargs) def run(self, *args, **kwargs): raise NotImplementedError("子类未实现该接口") def task(func): class SubTask(Task): def run(self, *args, **kwargs): func(*args, **kwargs) return SubTask()
第二章 上下文管理器
定义
包装任意代码
确保执行的一致性
语法
with语句
__enter__和__exit__方法
class ContextManager(object): def __init__(self): self.entered = False def __enter__(self): self.entered = True return self def __exit__(self, exc_type, exc_instance, traceback): self.entered = False
应用场景
资源清理
import pymysql class DBConnection(object): def __init__(self, *args, **kwargs): self.args,self.kwargs = args, kwargs def __enter__(self): self.conn = pymysql.connect(*args, **kwargs) return self.conn.cursor() def __exit__(self, exc_type, exc_instance, trackback): self.conn.close()
异常处理(避免重复)
传播异常(__exit__中return False)
终止异常(__exit__中return True)
class BubleExceptions(object): def __enter__(self): return self def __exit__(self, exc_type, exc_instance, trackback): if exc_instance: print("出现异常: {}".format(exc_instance) return False # return True终止异常
处理特定的异常
class HandleValueError(object): def __enter__(self): return self def __exit__(self, exc_type, exc_instance, trackback): if not exc_type: return True if issubclass(exc_type, ValueError): print("处理ValueError: {}".format(exc_instance) return False
if issubclass...语句改为if exec_type == ValueError则不处理ValueType的子类异常
也可以根据异常的属性来判断是否传播或终止
更简单的语法
import contextlib @contextlib.contextmanager def acceptable_error_codes(*codes): try: yield except ShellException as exc_instance: if exc_instance.code not in codes: raise pass
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