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#!/user/bin/env python
"""null.py
Original:
This is a sample implementation of the 'Null Object' design pattern.
Roughly, the goal with Null objects is to provide an 'intelligent'
replacement for the often used primitive data type None in Python or
Null (or Null pointers) in other languages. These are used for many
purposes including the important case where one member of some group
of otherwise similar elements is special for whatever reason. Most
often this results in conditional statements to distinguish between
ordinary elements and the primitive Null value.
Among the advantages of using Null objects are the following:
- Superfluous conditional statements can be avoided
by providing a first class object alternative for
the primitive value None.
- Code readability is improved.
- Null objects can act as a placeholder for objects
with behaviour that is not yet implemented.
- Null objects can be replaced for any other class.
- Null objects are very predictable at what they do.
To cope with the disadvantage of creating large numbers of passive
objects that do nothing but occupy memory space Null objects are
often combined with the Singleton pattern.
For more information use any internet search engine and look for
combinations of these words: Null, object, design and pattern.
Dinu C. Gherman,
August 2001
Revision 0.2:
- Add __nonzero__
Another, perhaps useful addition... This allows you to test if you have a real "live" reference. Or not. For example, you may have a reference to a Customer object, but you want to do something if you have a real customer and skip that processing if you have a Null. Additionally, testing the reference, through a 'not' or an 'if' throws a TypeError if you DON'T have the __nonzero__.
Revision 0.3:
Fix __str__ to return nothing
str(Null()). IMHO the '__str__' method should rather return an empty string. At least that's what I'd expect of 'do nothing'.
0xnz <yunxinyi@gmail.com>
Sep 2013
"""
class Null:
"""A class for implementing Null objects.
This class ignores all parameters passed when constructing or
calling instances and traps all attribute and method requests.
Instances of it always (and reliably) do 'nothing'.
The code might benefit from implementing some further special
Python methods depending on the context in which its instances
are used. Especially when comparing and coercing Null objects
the respective methods' implementation will depend very much
on the environment and, hence, these special methods are not
provided here.
"""
# object constructing
def __init__(self, *args, **kwargs):
"Ignore parameters."
return None
# object calling
def __call__(self, *args, **kwargs):
"Ignore method calls."
return self
# attribute handling
def __getattr__(self, mname):
"Ignore attribute requests."
return self
def __setattr__(self, name, value):
"Ignore attribute setting."
return self
def __delattr__(self, name):
"Ignore deleting attributes."
return self
def __nonzero__(self):
return False
# misc.
def __repr__(self):
"Return a string representation."
#return "<Null>"
return ""
def __str__(self):
"Convert to a string and return it."
#return "Null"
return ""
def test():
"Perform some decent tests, or rather: demos."
# constructing and calling
n = Null()
n = Null('value')
n = Null('value', param='value')
n()
n('value')
n('value', param='value')
# attribute handling
n.attr1
n.attr1.attr2
n.method1()
n.method1().method2()
n.method('value')
n.method(param='value')
n.method('value', param='value')
n.attr1.method1()
n.method1().attr1
n.attr1 = 'value'
n.attr1.attr2 = 'value'
del n.attr1
del n.attr1.attr2.attr3
# representation and conversion to a string
#assert repr(n) == '<Null>'
assert repr(n) == ""
#assert str(n) == 'Null'
assert str(n) == ""
if __name__ == '__main__':
test()