Table of Contents
- List Attributes
- Get Instance Type
- Declare a Class
- Has / Get / Set Attributes
- Check Inheritance
- Get Class Name
- New and Init
- The Diamond Problem
- Representation of a Class
- Callable Object
- Context Manager
- Using contextlib
- Property
- Computed Attributes
- Descriptor
- Singleton Decorator
- Static and Class Methond
- Abstract Method
- Using slot to Save Memory
- Common Magic
>>> dir(list) # check all attr of list
['__add__', '__class__', ...]
>>> ex = 10
>>> isinstance(ex, int)
True
>>> def fib(self, n):
... if n <= 2:
... return 1
... return fib(self, n-1) + fib(self, n-2)
...
>>> Fib = type('Fib', (object,), {'val': 10,
... 'fib': fib})
>>> f = Fib()
>>> f.val
10
>>> f.fib(f.val)
55
Equals to
>>> class Fib(object):
... val = 10
... def fib(self, n):
... if n <=2:
... return 1
... return self.fib(n-1)+self.fib(n-2)
...
>>> f = Fib()
>>> f.val
10
>>> f.fib(f.val)
55
>>> class Example(object):
... def __init__(self):
... self.name = "ex"
... def printex(self):
... print("This is an example")
...
>>> ex = Example()
>>> hasattr(ex,"name")
True
>>> hasattr(ex,"printex")
True
>>> hasattr(ex,"print")
False
>>> getattr(ex,'name')
'ex'
>>> setattr(ex,'name','example')
>>> ex.name
'example'
>>> class Example(object):
... def __init__(self):
... self.name = "ex"
... def printex(self):
... print("This is an Example")
...
>>> issubclass(Example, object)
True
>>> class ExampleClass(object):
... pass
...
>>> ex = ExampleClass()
>>> ex.__class__.__name__
'ExampleClass'
__init__
will be invoked
>>> class ClassA(object):
... def __new__(cls, arg):
... print('__new__ ' + arg)
... return object.__new__(cls, arg)
... def __init__(self, arg):
... print('__init__ ' + arg)
...
>>> o = ClassA("Hello")
__new__ Hello
__init__ Hello
__init__
won't be invoked
>>> class ClassB(object):
... def __new__(cls, arg):
... print('__new__ ' + arg)
... return object
... def __init__(self, arg):
... print('__init__ ' + arg)
...
>>> o = ClassB("Hello")
__new__ Hello
The problem of multiple inheritance in searching a method
>>> def foo_a(self):
... print("This is ClsA")
...
>>> def foo_b(self):
... print("This is ClsB")
...
>>> def foo_c(self):
... print("This is ClsC")
...
>>> class Type(type):
... def __repr__(cls):
... return cls.__name__
...
>>> ClsA = Type("ClsA", (object,), {'foo': foo_a})
>>> ClsB = Type("ClsB", (ClsA,), {'foo': foo_b})
>>> ClsC = Type("ClsC", (ClsA,), {'foo': foo_c})
>>> ClsD = Type("ClsD", (ClsB, ClsC), {})
>>> ClsD.mro()
[ClsD, ClsB, ClsC, ClsA, <type 'object'>]
>>> ClsD().foo()
This is ClsB
>>> class Example(object):
... def __str__(self):
... return "Example __str__"
... def __repr__(self):
... return "Example __repr__"
...
>>> print(str(Example()))
Example __str__
>>> Example()
Example __repr__
>>> class CallableObject(object):
... def example(self, *args, **kwargs):
... print("I am callable!")
... def __call__(self, *args, **kwargs):
... self.example(*args, **kwargs)
...
>>> ex = CallableObject()
>>> ex()
I am callable!
# replace try: ... finally: ...
# see: PEP343
# common use in open and close
import socket
class Socket(object):
def __init__(self, host, port):
self.host = host
self.port = port
def __enter__(self):
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.bind((self.host,self.port))
sock.listen(5)
self.sock = sock
return self.sock
def __exit__(self,*exc_info):
if exc_info[0] is not None:
import traceback
traceback.print_exception(*exc_info)
self.sock.close()
if __name__=="__main__":
host = 'localhost'
port = 5566
with Socket(host, port) as s:
while True:
conn, addr = s.accept()
msg = conn.recv(1024)
print(msg)
conn.send(msg)
conn.close()
from contextlib import contextmanager
@contextmanager
def opening(filename, mode='r'):
f = open(filename, mode)
try:
yield f
finally:
f.close()
with opening('example.txt') as fd:
fd.read()
>>> class Example(object):
... def __init__(self, value):
... self._val = value
... @property
... def val(self):
... return self._val
... @val.setter
... def val(self, value):
... if not isinstance(value, int):
... raise TypeError("Expected int")
... self._val = value
... @val.deleter
... def val(self):
... del self._val
...
>>> ex = Example(123)
>>> ex.val = "str"
Traceback (most recent call last):
File "", line 1, in
File "test.py", line 12, in val
raise TypeError("Expected int")
TypeError: Expected int
Equals to
>>> class Example(object):
... def __init__(self, value):
... self._val = value
...
... def _val_getter(self):
... return self._val
...
... def _val_setter(self, value):
... if not isinstance(value, int):
... raise TypeError("Expected int")
... self._val = value
...
... def _val_deleter(self):
... del self._val
...
... val = property(fget=_val_getter, fset=_val_setter, fdel=_val_deleter, doc=None)
...
@property
computes a value of a attribute only when we need. Not store in
memory previously.
>>> class Example(object):
... @property
... def square3(self):
... return 2**3
...
>>> ex = Example()
>>> ex.square3
8
>>> class Integer(object):
... def __init__(self, name):
... self._name = name
... def __get__(self, inst, cls):
... if inst is None:
... return self
... else:
... return inst.__dict__[self._name]
... def __set__(self, inst, value):
... if not isinstance(value, int):
... raise TypeError("Expected int")
... inst.__dict__[self._name] = value
... def __delete__(self,inst):
... del inst.__dict__[self._name]
...
>>> class Example(object):
... x = Integer('x')
... def __init__(self, val):
... self.x = val
...
>>> ex1 = Example(1)
>>> ex1.x
1
>>> ex2 = Example("str")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 4, in __init__
File "<stdin>", line 11, in __set__
TypeError: Expected an int
>>> ex3 = Example(3)
>>> hasattr(ex3, 'x')
True
>>> del ex3.x
>>> hasattr(ex3, 'x')
False
Singleton is a design pattern that restricts the creation of instances of a class so that it only creates one instance of the class that implements it.
#!/usr/bin/env python3
"""Singleton decorator class."""
class Singleton(object):
def __init__(self, cls):
self.__cls = cls
self.__obj = None
def __call__(self, *args, **kwargs):
if not self.__obj:
self.__obj = self.__cls(*args, **kwargs)
return self.__obj
if __name__ == "__main__":
# Testing ...
@Singleton
class Test(object):
def __init__(self, text):
self.text = text
a = Test("Hello")
b = Test("World")
print("id(a):", id(a), "id(b):", id(b), "Diff:", id(a)-id(b))
@classmethod
is bound to a class. @staticmethod
is similar to a python
function but define in a class.
>>> class example(object):
... @classmethod
... def clsmethod(cls):
... print("I am classmethod")
... @staticmethod
... def stmethod():
... print("I am staticmethod")
... def instmethod(self):
... print("I am instancemethod")
...
>>> ex = example()
>>> ex.clsmethod()
I am classmethod
>>> ex.stmethod()
I am staticmethod
>>> ex.instmethod()
I am instancemethod
>>> example.clsmethod()
I am classmethod
>>> example.stmethod()
I am staticmethod
>>> example.instmethod()
Traceback (most recent call last):
File "", line 1, in
TypeError: unbound method instmethod() ...
abc
is used to define methods but not implement
>>> from abc import ABCMeta, abstractmethod
>>> class base(object):
... __metaclass__ = ABCMeta
... @abstractmethod
... def absmethod(self):
... """ Abstract method """
...
>>> class example(base):
... def absmethod(self):
... print("abstract")
...
>>> ex = example()
>>> ex.absmethod()
abstract
Another common way is to raise NotImplementedError
>>> class base(object):
... def absmethod(self):
... raise NotImplementedError
...
>>> class example(base):
... def absmethod(self):
... print("abstract")
...
>>> ex = example()
>>> ex.absmethod()
abstract
#!/usr/bin/env python3
import resource
import platform
import functools
def profile_mem(func):
@functools.wraps(func)
def wrapper(*a, **k):
s = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
ret = func(*a, **k)
e = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
uname = platform.system()
if uname == "Linux":
print(f"mem usage: {e - s} kByte")
elif uname == "Darwin":
print(f"mem usage: {e - s} Byte")
else:
raise Exception("not support")
return ret
return wrapper
class S(object):
__slots__ = ['attr1', 'attr2', 'attr3']
def __init__(self):
self.attr1 = "Foo"
self.attr2 = "Bar"
self.attr3 = "Baz"
class D(object):
def __init__(self):
self.attr1 = "Foo"
self.attr2 = "Bar"
self.attr3 = "Baz"
@profile_mem
def alloc(cls):
_ = [cls() for _ in range(1000000)]
alloc(S)
alloc(D)
output:
$ python3.6 s.py
mem usage: 70922240 Byte
mem usage: 100659200 Byte
# see python document: data model
# For command class
__main__
__name__
__file__
__module__
__all__
__dict__
__class__
__doc__
__init__(self, [...)
__str__(self)
__repr__(self)
__del__(self)
# For Descriptor
__get__(self, instance, owner)
__set__(self, instance, value)
__delete__(self, instance)
# For Context Manager
__enter__(self)
__exit__(self, exc_ty, exc_val, tb)
# Emulating container types
__len__(self)
__getitem__(self, key)
__setitem__(self, key, value)
__delitem__(self, key)
__iter__(self)
__contains__(self, value)
# Controlling Attribute Access
__getattr__(self, name)
__setattr__(self, name, value)
__delattr__(self, name)
__getattribute__(self, name)
# Callable object
__call__(self, [args...])
# Compare related
__cmp__(self, other)
__eq__(self, other)
__ne__(self, other)
__lt__(self, other)
__gt__(self, other)
__le__(self, other)
__ge__(self, other)
# arithmetical operation related
__add__(self, other)
__sub__(self, other)
__mul__(self, other)
__div__(self, other)
__mod__(self, other)
__and__(self, other)
__or__(self, other)
__xor__(self, other)