Prefer properties. It's what they're there for.
The reason is that all attributes are public in Python. Starting names with an underscore or two is just a warning that the given attribute is an implementation detail that may not stay the same in future versions of the code. It doesn't prevent you from actually getting or setting that attribute. Therefore, standard attribute access is the normal, Pythonic way of, well, accessing attributes.
The advantage of properties is that they are syntactically identical to attribute access, so you can change from one to another without any changes to client code. You could even have one version of a class that uses properties (say, for code-by-contract or debugging) and one that doesn't for production, without changing the code that uses it. At the same time, you don't have to write getters and setters for everything just in case you might need to better control access later.
Answer from kindall on Stack OverflowVideos
Prefer properties. It's what they're there for.
The reason is that all attributes are public in Python. Starting names with an underscore or two is just a warning that the given attribute is an implementation detail that may not stay the same in future versions of the code. It doesn't prevent you from actually getting or setting that attribute. Therefore, standard attribute access is the normal, Pythonic way of, well, accessing attributes.
The advantage of properties is that they are syntactically identical to attribute access, so you can change from one to another without any changes to client code. You could even have one version of a class that uses properties (say, for code-by-contract or debugging) and one that doesn't for production, without changing the code that uses it. At the same time, you don't have to write getters and setters for everything just in case you might need to better control access later.
In Python you don't use getters or setters or properties just for the fun of it. You first just use attributes and then later, only if needed, eventually migrate to a property without having to change the code using your classes.
There is indeed a lot of code with extension .py that uses getters and setters and inheritance and pointless classes everywhere where e.g. a simple tuple would do, but it's code from people writing in C++ or Java using Python.
That's not Python code.
Hi everyone I do not understand getters and setters in python please help
Try this: Python Property
The sample code is:
class C(object):
def __init__(self):
self._x = None
@property
def x(self):
"""I'm the 'x' property."""
print("getter of x called")
return self._x
@x.setter
def x(self, value):
print("setter of x called")
self._x = value
@x.deleter
def x(self):
print("deleter of x called")
del self._x
c = C()
c.x = 'foo' # setter called
foo = c.x # getter called
del c.x # deleter called
What's the pythonic way to use getters and setters?
The "Pythonic" way is not to use "getters" and "setters", but to use plain attributes, like the question demonstrates, and del for deleting (but the names are changed to protect the innocent... builtins):
value = 'something'
obj.attribute = value
value = obj.attribute
del obj.attribute
If later, you want to modify the setting and getting, you can do so without having to alter user code, by using the property decorator:
class Obj:
"""property demo"""
#
@property # first decorate the getter method
def attribute(self): # This getter method name is *the* name
return self._attribute
#
@attribute.setter # the property decorates with `.setter` now
def attribute(self, value): # name, e.g. "attribute", is the same
self._attribute = value # the "value" name isn't special
#
@attribute.deleter # decorate with `.deleter`
def attribute(self): # again, the method name is the same
del self._attribute
(Each decorator usage copies and updates the prior property object, so note that you should use the same name for each set, get, and delete function/method.)
After defining the above, the original setting, getting, and deleting code is the same:
obj = Obj()
obj.attribute = value
the_value = obj.attribute
del obj.attribute
You should avoid this:
def set_property(property,value): def get_property(property):
Firstly, the above doesn't work, because you don't provide an argument for the instance that the property would be set to (usually self), which would be:
class Obj:
def set_property(self, property, value): # don't do this
...
def get_property(self, property): # don't do this either
...
Secondly, this duplicates the purpose of two special methods, __setattr__ and __getattr__.
Thirdly, we also have the setattr and getattr builtin functions.
setattr(object, 'property_name', value)
getattr(object, 'property_name', default_value) # default is optional
The @property decorator is for creating getters and setters.
For example, we could modify the setting behavior to place restrictions the value being set:
class Protective(object):
@property
def protected_value(self):
return self._protected_value
@protected_value.setter
def protected_value(self, value):
if acceptable(value): # e.g. type or range check
self._protected_value = value
In general, we want to avoid using property and just use direct attributes.
This is what is expected by users of Python. Following the rule of least-surprise, you should try to give your users what they expect unless you have a very compelling reason to the contrary.
Demonstration
For example, say we needed our object's protected attribute to be an integer between 0 and 100 inclusive, and prevent its deletion, with appropriate messages to inform the user of its proper usage:
class Protective(object):
"""protected property demo"""
#
def __init__(self, start_protected_value=0):
self.protected_value = start_protected_value
#
@property
def protected_value(self):
return self._protected_value
#
@protected_value.setter
def protected_value(self, value):
if value != int(value):
raise TypeError("protected_value must be an integer")
if 0 <= value <= 100:
self._protected_value = int(value)
else:
raise ValueError("protected_value must be " +
"between 0 and 100 inclusive")
#
@protected_value.deleter
def protected_value(self):
raise AttributeError("do not delete, protected_value can be set to 0")
(Note that __init__ refers to self.protected_value but the property methods refer to self._protected_value. This is so that __init__ uses the property through the public API, ensuring it is "protected".)
And usage:
>>> p1 = Protective(3)
>>> p1.protected_value
3
>>> p1 = Protective(5.0)
>>> p1.protected_value
5
>>> p2 = Protective(-5)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 3, in __init__
File "<stdin>", line 15, in protected_value
ValueError: protectected_value must be between 0 and 100 inclusive
>>> p1.protected_value = 7.3
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 17, in protected_value
TypeError: protected_value must be an integer
>>> p1.protected_value = 101
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 15, in protected_value
ValueError: protectected_value must be between 0 and 100 inclusive
>>> del p1.protected_value
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 18, in protected_value
AttributeError: do not delete, protected_value can be set to 0
Do the names matter?
Yes they do. .setter and .deleter make copies of the original property. This allows subclasses to properly modify behavior without altering the behavior in the parent.
class Obj:
"""property demo"""
#
@property
def get_only(self):
return self._attribute
#
@get_only.setter
def get_or_set(self, value):
self._attribute = value
#
@get_or_set.deleter
def get_set_or_delete(self):
del self._attribute
Now for this to work, you have to use the respective names:
obj = Obj()
# obj.get_only = 'value' # would error
obj.get_or_set = 'value'
obj.get_set_or_delete = 'new value'
the_value = obj.get_only
del obj.get_set_or_delete
# del obj.get_or_set # would error
I'm not sure where this would be useful, but the use-case is if you want a get, set, and/or delete-only property. Probably best to stick to semantically same property having the same name.
Conclusion
Start with simple attributes.
If you later need functionality around the setting, getting, and deleting, you can add it with the property decorator.
Avoid functions named set_... and get_... - that's what properties are for.