是否有一种方法可以方便地在Python中定义类c结构?我厌倦了写这样的东西:
class MyStruct():
def __init__(self, field1, field2, field3):
self.field1 = field1
self.field2 = field2
self.field3 = field3
是否有一种方法可以方便地在Python中定义类c结构?我厌倦了写这样的东西:
class MyStruct():
def __init__(self, field1, field2, field3):
self.field1 = field1
self.field2 = field2
self.field3 = field3
当前回答
就我个人而言,我也喜欢这种变体。它扩展了@dF的答案。
class struct:
def __init__(self, *sequential, **named):
fields = dict(zip(sequential, [None]*len(sequential)), **named)
self.__dict__.update(fields)
def __repr__(self):
return str(self.__dict__)
它支持两种初始化模式(可以混合使用):
# Struct with field1, field2, field3 that are initialized to None.
mystruct1 = struct("field1", "field2", "field3")
# Struct with field1, field2, field3 that are initialized according to arguments.
mystruct2 = struct(field1=1, field2=2, field3=3)
而且,它打印得更好:
print(mystruct2)
# Prints: {'field3': 3, 'field1': 1, 'field2': 2}
其他回答
更新:数据类
随着Python 3.7中数据类的引入,我们已经非常接近了。
下面的示例与下面的NamedTuple示例类似,但是生成的对象是可变的,并且允许使用默认值。
from dataclasses import dataclass
@dataclass
class Point:
x: float
y: float
z: float = 0.0
p = Point(1.5, 2.5)
print(p) # Point(x=1.5, y=2.5, z=0.0)
如果您想使用更特定的类型注释,这可以很好地配合新的类型模块。
我一直在绝望地等待这一刻!要我说,Data Classes和新的NamedTuple声明,再加上typing模块,简直就是天赐之物!
改进的NamedTuple声明
自从Python 3.6以来,它变得非常简单和美丽(恕我直言),只要你能忍受不变性。
引入了一种声明NamedTuples的新方法,它也允许类型注释:
from typing import NamedTuple
class User(NamedTuple):
name: str
class MyStruct(NamedTuple):
foo: str
bar: int
baz: list
qux: User
my_item = MyStruct('foo', 0, ['baz'], User('peter'))
print(my_item) # MyStruct(foo='foo', bar=0, baz=['baz'], qux=User(name='peter'))
我写了一个装饰器,你可以在任何方法上使用它,这样所有传入的参数,或任何默认值,都被分配给实例。
def argumentsToAttributes(method):
argumentNames = method.func_code.co_varnames[1:]
# Generate a dictionary of default values:
defaultsDict = {}
defaults = method.func_defaults if method.func_defaults else ()
for i, default in enumerate(defaults, start = len(argumentNames) - len(defaults)):
defaultsDict[argumentNames[i]] = default
def newMethod(self, *args, **kwargs):
# Use the positional arguments.
for name, value in zip(argumentNames, args):
setattr(self, name, value)
# Add the key word arguments. If anything is missing, use the default.
for name in argumentNames[len(args):]:
setattr(self, name, kwargs.get(name, defaultsDict[name]))
# Run whatever else the method needs to do.
method(self, *args, **kwargs)
return newMethod
快速演示一下。注意,我使用一个位置参数a,使用默认值b,和一个命名参数c。然后我打印所有3个引用self,以显示它们在方法输入之前已正确分配。
class A(object):
@argumentsToAttributes
def __init__(self, a, b = 'Invisible', c = 'Hello'):
print(self.a)
print(self.b)
print(self.c)
A('Why', c = 'Nothing')
注意,我的装饰器应该适用于任何方法,而不仅仅是__init__。
https://stackoverflow.com/a/32448434/159695在Python3中不起作用。
https://stackoverflow.com/a/35993/159695在Python3中工作。
然后我扩展它来添加默认值。
class myStruct:
def __init__(self, **kwds):
self.x=0
self.__dict__.update(kwds) # Must be last to accept assigned member variable.
def __repr__(self):
args = ['%s=%s' % (k, repr(v)) for (k,v) in vars(self).items()]
return '%s(%s)' % ( self.__class__.__qualname__, ', '.join(args) )
a=myStruct()
b=myStruct(x=3,y='test')
c=myStruct(x='str')
>>> a
myStruct(x=0)
>>> b
myStruct(x=3, y='test')
>>> c
myStruct(x='str')
NamedTuple很舒服。但是没有人共享性能和存储。
from typing import NamedTuple
import guppy # pip install guppy
import timeit
class User:
def __init__(self, name: str, uid: int):
self.name = name
self.uid = uid
class UserSlot:
__slots__ = ('name', 'uid')
def __init__(self, name: str, uid: int):
self.name = name
self.uid = uid
class UserTuple(NamedTuple):
# __slots__ = () # AttributeError: Cannot overwrite NamedTuple attribute __slots__
name: str
uid: int
def get_fn(obj, attr_name: str):
def get():
getattr(obj, attr_name)
return get
if 'memory test':
obj = [User('Carson', 1) for _ in range(1000000)] # Cumulative: 189138883
obj_slot = [UserSlot('Carson', 1) for _ in range(1000000)] # 77718299 <-- winner
obj_namedtuple = [UserTuple('Carson', 1) for _ in range(1000000)] # 85718297
print(guppy.hpy().heap()) # Run this function individually.
"""
Index Count % Size % Cumulative % Kind (class / dict of class)
0 1000000 24 112000000 34 112000000 34 dict of __main__.User
1 1000000 24 64000000 19 176000000 53 __main__.UserTuple
2 1000000 24 56000000 17 232000000 70 __main__.User
3 1000000 24 56000000 17 288000000 87 __main__.UserSlot
...
"""
if 'performance test':
obj = User('Carson', 1)
obj_slot = UserSlot('Carson', 1)
obj_tuple = UserTuple('Carson', 1)
time_normal = min(timeit.repeat(get_fn(obj, 'name'), repeat=20))
print(time_normal) # 0.12550550000000005
time_slot = min(timeit.repeat(get_fn(obj_slot, 'name'), repeat=20))
print(time_slot) # 0.1368690000000008
time_tuple = min(timeit.repeat(get_fn(obj_tuple, 'name'), repeat=20))
print(time_tuple) # 0.16006120000000124
print(time_tuple/time_slot) # 1.1694481584580898 # The slot is almost 17% faster than NamedTuple on Windows. (Python 3.7.7)
如果你的__dict__没有被使用,请在__slots__(更高的性能和存储)和NamedTuple(清晰的阅读和使用)之间选择。
您可以查看此链接(插槽的使用 )来获取更多的__slots__信息。
我在这里没有看到这个答案,所以我想我将添加它,因为我现在正在学习Python,并且刚刚发现它。Python教程(在本例中是Python 2)给出了以下简单而有效的示例:
class Employee:
pass
john = Employee() # Create an empty employee record
# Fill the fields of the record
john.name = 'John Doe'
john.dept = 'computer lab'
john.salary = 1000
也就是说,创建一个空类对象,然后实例化,动态添加字段。
这样做的好处是非常简单。缺点是它不是特别自记录的(在类“定义”中没有列出预期的成员),并且未设置字段在访问时可能会导致问题。这两个问题可以通过以下方法解决:
class Employee:
def __init__ (self):
self.name = None # or whatever
self.dept = None
self.salary = None
现在,您至少可以一目了然地看到程序将期望哪些字段。
两者都很容易打错别字,约翰。Slarly = 1000将成功。不过,它还是有效的。