From New-style and classic classes:
Up to Python 2.1, old-style classes were the only flavour available to the user.
The concept of (old-style) class is unrelated to the concept of type:
if x
is an instance of an old-style class, then x.__class__
designates the class of x
, but type(x)
is always <type
'instance'>
.
This reflects the fact that all old-style instances, independently of
their class, are implemented with a single built-in type, called
instance.
New-style classes were introduced in Python 2.2 to unify the concepts of class and type.
A new-style class is simply a user-defined type, no more, no less.
If x is an instance of a new-style class, then type(x)
is typically
the same as x.__class__
(although this is not guaranteed – a
new-style class instance is permitted to override the value returned
for x.__class__
).
The major motivation for introducing new-style classes is to provide a unified object model with a full meta-model.
It also has a number of immediate benefits, like the ability to
subclass most built-in types, or the introduction of "descriptors",
which enable computed properties.
For compatibility reasons, classes are still old-style by default.
New-style classes are created by specifying another new-style class
(i.e. a type) as a parent class, or the "top-level type" object if no
other parent is needed.
The behaviour of new-style classes differs from that of old-style
classes in a number of important details in addition to what type
returns.
Some of these changes are fundamental to the new object model, like
the way special methods are invoked. Others are "fixes" that could not
be implemented before for compatibility concerns, like the method
resolution order in case of multiple inheritance.
Python 3 only has new-style classes.
No matter if you subclass from object
or not, classes are new-style
in Python 3.
Maybe a bit of example code will help: Notice the difference in the call signatures of foo
, class_foo
and static_foo
:
class A(object):
def foo(self, x):
print(f"executing foo({self}, {x})")
@classmethod
def class_foo(cls, x):
print(f"executing class_foo({cls}, {x})")
@staticmethod
def static_foo(x):
print(f"executing static_foo({x})")
a = A()
Below is the usual way an object instance calls a method. The object instance, a
, is implicitly passed as the first argument.
a.foo(1)
# executing foo(<__main__.A object at 0xb7dbef0c>, 1)
With classmethods, the class of the object instance is implicitly passed as the first argument instead of self
.
a.class_foo(1)
# executing class_foo(<class '__main__.A'>, 1)
You can also call class_foo
using the class. In fact, if you define something to be
a classmethod, it is probably because you intend to call it from the class rather than from a class instance. A.foo(1)
would have raised a TypeError, but A.class_foo(1)
works just fine:
A.class_foo(1)
# executing class_foo(<class '__main__.A'>, 1)
One use people have found for class methods is to create inheritable alternative constructors.
With staticmethods, neither self
(the object instance) nor cls
(the class) is implicitly passed as the first argument. They behave like plain functions except that you can call them from an instance or the class:
a.static_foo(1)
# executing static_foo(1)
A.static_foo('hi')
# executing static_foo(hi)
Staticmethods are used to group functions which have some logical connection with a class to the class.
foo
is just a function, but when you call a.foo
you don't just get the function,
you get a "partially applied" version of the function with the object instance a
bound as the first argument to the function. foo
expects 2 arguments, while a.foo
only expects 1 argument.
a
is bound to foo
. That is what is meant by the term "bound" below:
print(a.foo)
# <bound method A.foo of <__main__.A object at 0xb7d52f0c>>
With a.class_foo
, a
is not bound to class_foo
, rather the class A
is bound to class_foo
.
print(a.class_foo)
# <bound method type.class_foo of <class '__main__.A'>>
Here, with a staticmethod, even though it is a method, a.static_foo
just returns
a good 'ole function with no arguments bound. static_foo
expects 1 argument, and
a.static_foo
expects 1 argument too.
print(a.static_foo)
# <function static_foo at 0xb7d479cc>
And of course the same thing happens when you call static_foo
with the class A
instead.
print(A.static_foo)
# <function static_foo at 0xb7d479cc>
Best Answer
dateutil
is an extension package to the python standarddatetime
module. As you say, it provides extra functionality, such as timedeltas that are expressed in units larger than a day.This is useful if you have to ask questions such as how many months can I save before my girlfriend's birthday comes up, or what's the last Friday in the month? This hides complex calculations that are caused by the different lengths of the months, or extra days in leap years.
In your case, you are only interested in the number of days. So you'd best use
timedelta
as this avoids an extra dependency on thedateutil
package.