I'm new to classes, this is a small piece of code I've written, but I'm still really shaky on this concept, and am wondering exactly how the method node_name comes into play here and if it's even needed?
from rdflib import BNode
class HigherNode(object):
def node_name(name):
return name
def __init__(self, **kwargs):
self.node_type = kwargs.get('node_type', 'cog_con')
self.position = kwargs.get('position', 0)
self.node_id = self.node_name
self.node = kwargs.get(self.node_name(), BNode())
for key, value in kwargs.items():
setattr(self, key, value)
def __str__(self):
return 'This is the node of {} in the graph'.format(self.node_id)
I behavior that I'm seeking is something equivalent to this:
elephant = BNode()
when used as:
some_node = HigherNode(node_id = 'elephant')
So, first off, methods have to be called by an instance of the class. So, your behavior would look something like this:
# create an instance
node = HigherNode()
# get the name
print node.node_name()
However, you never declared name inside the class. So, you'll have to do something like this:
def node_name(self):
return self.name
(All instances pass a reference to themselves to thier functions when called, so you'll always have to have at least one variable in the function call. You don't have to call it self.)
Really, it looks like what you want is actually a name setter/getter.
Try this:
Declare/set the variable in __init__.
def __init__(self, **kwargs):
self.node_name= kwargs.get('node_name', None)
Then you can use the variable like this:
# create an instance
node = HigherNode()
# get the name
print node.node_name
# set the name
node.node_name = "bluh"
Since your class extends object, use getter/setter properties.
#property
def node_name(self):
return self.node_name
#node_name.setter
def node_name(self, x):
self.node_name = str(x)
These are called exactly the same as above in option 1:
# create an instance
node = HigherNode()
# get the name
print node.node_name
# set the name
node.node_name = "bluh"
I prefer this method, since it allows you much more control over how things are set, or even whether or not you can set or get them! (Just make a getter property without a corresponding setter property, for instance.)
However, this second method is more work to set up and may not be suitable for simple variables.
Related
I think a code sample will better speak for itself:
class SomeClass:
example = create_get_method()
Yes, that's all – ideally.
In that case, create_get_method would add a get_example() to SomeClass in a way that it can be accessed via an instance of SomeClass:
obj = SomeClass()
obj.get_example() <- returns the value of self.example
(Of course, the idea is to implement a complex version of get_contact, that's why I want to do that in a non-repetitive way, and this is a simplified version that represents well the issue.)
I don't know if that's possible, because it require to have access to the property name (example) and the class (SomeClass) since these can not be guessed in advance (that function will be used on many and various classes).
I know it's something possible, because that's kind of what SQLAlchemy does with their relationship() function on a class:
class Model(BaseModel):
id = ...
contact_id = db.Integer(db.ForeignKey..)
contact = relationship('contact') <-- This !
How can this be done?
Objects bound to class-level variables can have a __set_name__ method that will be called immediately after the class object has been created. It will be called with two arguments, the class object, and the name of the variable the object is saved as in the class.
You could use this to create your extra getter method, though I'm not sure why exactly you want to (you could make the object a descriptor instead, which would probably be better than adding a separate getter function to the parent class).
class create_get_method:
def __set_name__(self, owner, name):
def getter(self):
return getattr(self, name)
getter_name = f"get_{name}"
getter.__name__ = getter_name
setattr(owner, getter_name, getter)
# you might also want a __get__ method here to give a default value (like None)
Here's how that would work:
>>> class Test:
... example = create_get_method()
...
>>> t = Test()
>>> print(t.get_example())
<__main__.create_get_method at 0x000001E0B4D41400>
>>> t.example = "foo"
>>> print(t.get_example())
foo
You could change the value returned by default (in the first print call), so that the create_get_method object isn't as exposed. Just add a __get__ method to the create_get_method class.
You can do this with a custom non-data descriptor, like a property, except that you don't need a __set__ method:
class ComplicatedDescriptor:
def __init__(self, name):
self.name = name
def __get__(self, owner, type):
# Here, `owner` is the instance of `SomeClass` that contains this descriptor
# Use `owner` to do some complicated stuff, like DB lookup or whatever
name = f'_{self.name}'
# These two lines for demo only
value = owner.__dict__.get(name, 0)
value += 1
setattr(owner, name, value)
return value
Now you can have any number of classes that use this descriptor:
class SomeClass:
example = ComplicatedDescriptor('example')
Now you can do something like:
>>> inst0 = SomeClass()
>>> inst1 = SomeClass()
>>> inst0.example
1
>>> inst1.example
1
>>> inst1.example
2
>>> inst0.example
2
The line name = f'_{self.name} is necessary because the descriptor here is a non-data descriptor: it has no __set__ method, so if you create inst0.__dict__['example'], the lookup will no longer happen: inst0.example will return inst0.__dict__['example'] instead of calling SomeClass.example.__get__(inst0, type(inst0)). One workaround is to store the value under the attribute name _example. The other is to make your descriptor into a data descriptor:
class ComplicatedDescriptor_v2:
def __init__(self, name):
self.name = name
def __get__(self, owner, type):
# Here, `owner` is the instance of `SomeClass` that contains this descriptor
# Use `owner` to do some complicated stuff, like DB lookup or whatever
# These two lines for demo only
value = owner.__dict__.get(self.name, 0)
value += 1
owner.__dict__[self.name] = value
return value
def __set__(self, *args):
raise AttributeError(f'{self.name} is a read-only attribute')
The usage is generally identical:
class SomeClass:
example = ComplicatedDescriptor_v2('example')
Except that now you can't accidentally override your attribute:
>>> inst = SomeClass()
>>> inst.example
1
>>> inst.example
2
>>> inst.example = 0
AttributeError: example is a read-only attribute
Descriptors are a fairly idiomatic way to get and set values in python. They are preferred to getters and setters in almost all cases. The simplest cases are handled by the built-in property. That being said, if you wanted to explicitly have a getter method, I would recommend doing something very similar, but just returning a method instead of calling __get__ directly.
For example:
def __get__(self, owner, type):
def enclosed():
# Use `owner` to do some complicated stuff, like DB lookup or whatever
name = f'_{self.name}'
# These two lines for demo only
value = owner.__dict__.get(name, 0)
value += 1
setattr(owner, name, value)
return value
return enclosed
There is really no point to doing something like this unless you plan on really just want to be able to call inst.example().
I'm writing a script in Maya and trying to assign a variable inside another method instead of inside __init__ like we normally do. I put my window commands inside the __init__ so when a new instance is initialized, if we assign variables inside __init__ it will run all the way through without assigning the variables the value I want.
For example:
def __init__(self, windowID = 'selectsomething', title = 'select something'):
self.windowID = windowID
self.title = title
if cmds.window(self.windowID, exists = True):
cmds.deleteUI(self.windowID)
myWindow = cmds.window(self.windowID, title = self.title)
cmds.rowColumnLayout(numberOfColumns = 2, columnWidth = [(1, 300), (2, 100)],
columnAttach = [1, 'left', 10], columnSpacing = [1, 10],
rowSpacing = [1, 5])
cmds.button(label = "Apply", command = self.applyButton) #it should print out selected object
cmds.button(label = "Cancel", command = self.cancelButton)
cmds.showWindow(myWindow)
#now for example if I have a sel variable to store selected objects, it would actually return nothing cuz the code ran all the way through and didnt wait for me to select what I needed
sel = cmds.ls(selection = True) #this will return nothing
My solution is to assign variables inside the applyButton method, which will store what I selected. I found it's a bit weird to call a method which uses a variable from another method from that method itself.
For example:
class Abc:
def func(*arg):
print(self.var)
def var(self):
self.var = 1
self.func()
abc = Abc()
abc.var()
For now the code runs, but doesn't it sound a bit weird to call the func method which uses the variable from var method from var method itself?
I haven't seen anyone do it. I mean without class, a variable assigned inside a function stays inside that function and we can only use it with return. But it looks like in class we can make any inside-method-variable global by adding self. before it?
My friend also said we can use #property in this case but I don't think I figured it out yet.
You need to be aware that data attributes are implicitly a member of the class and can therefore be used by any method in the same class after they have been assigned somewhere.
From the Python documentation:
Data attributes need not be declared; like local variables, they
spring into existence when they are first assigned to.
While your example will work (if you call Abc.var() before Abc.func()), it would IMHO be better style to initialize the variable at class level like this (note that I call it val to avoid confusion with the method name):
class Abc:
val = 0
def func(self, *arg):
print(self.val)
def var(self):
self.val = 1
self.func()
The purpose of the self keyword is nicely explained here and here.
Also note that initializing an attribute inside the __init__ method will bind this attribute to a class instance, whereas initializing it outside of the __init__ method will bind it to the class itself, which is a different thing (see this discussion).
If I'm creating a class that needs to store properties, when is it appropriate to use an #property decorator and when should I simply define them in __init__?
The reasons I can think of:
Say I have a class like
class Apple:
def __init__(self):
self.foodType = "fruit"
self.edible = True
self.color = "red"
This works fine. In this case, it's pretty clear to me that I shouldn't write the class as:
class Apple:
#property
def foodType(self):
return "fruit"
#property
def edible(self):
return True
#property
def color(self):
return "red"
But say I have a more complicated class, which has slower methods (say, fetching data over the internet).
I could implement this assigning attributes in __init__:
class Apple:
def __init__(self):
self.wikipedia_url = "https://en.wikipedia.org/wiki/Apple"
self.wikipedia_article_content = requests.get(self.wikipedia_url).text
or I could implement this with #property:
class Apple:
def __init__(self):
self.wikipedia_url = "https://en.wikipedia.org/wiki/Apple"
#property
def wikipedia_article_content(self):
return requests.get(self.wikipedia_url).text
In this case, the latter is about 50,000 times faster to instantiate. However, I could argue that if I were fetching wikipedia_article_content multiple times, the former is faster:
a = Apple()
a.wikipedia_article_content
a.wikipedia_article_content
a.wikipedia_article_content
In which case, the former is ~3 times faster because it has one third the number of requests.
My question
Is the only difference between assigning properties in these two ways the ones I've thought of? What else does #property allow me to do other than save time (in some cases)? For properties that take some time to assign, is there a "right way" to assign them?
Using a property allows for more complex behavior. Such as fetching the article content only when it has changed and only after a certain time period has passed.
Yes, I would suggest using property for those arguments. If you want to make it lazy or cached you can subclass property.
This is just an implementation of a lazy property. It does some operations inside the property and returns the result. This result is saved in the class with another name and each subsequent call on the property just returns the saved result.
class LazyProperty(property):
def __init__(self, *args, **kwargs):
# Let property set everything up
super(LazyProperty, self).__init__(*args, **kwargs)
# We need a name to save the cached result. If the property is called
# "test" save the result as "_test".
self._key = '_{0}'.format(self.fget.__name__)
def __get__(self, obj, owner=None):
# Called on the class not the instance
if obj is None:
return self
# Value is already fetched so just return the stored value
elif self._key in obj.__dict__:
return obj.__dict__[self._key]
# Value is not fetched, so fetch, save and return it
else:
val = self.fget(obj)
obj.__dict__[self._key] = val
return val
This allows you to calculate the value once and then always return it:
class Test:
def __init__(self):
pass
#LazyProperty
def test(self):
print('Doing some very slow stuff.')
return 100
This is how it would work (obviously you need to adapt it for your case):
>>> a = Test()
>>> a._test # The property hasn't been called so there is no result saved yet.
AttributeError: 'Test' object has no attribute '_test'
>>> a.test # First property access will evaluate the code you have in your property
Doing some very slow stuff.
100
>>> a.test # Accessing the property again will give you the saved result
100
>>> a._test # Or access the saved result directly
100
I have code that someone else wrote like this:
class MyClass(object):
def __init__(self, data):
self.data = data
#property
def attribute1(self):
return self.data.another_name1
#property
def attribute2(self):
return self.data.another_name2
and I want to automatically create the corresponding property setters at run time so I don't have to modify the other person's code. The property setters should look like this:
#attribute1.setter
def attribue1(self, val):
self.data.another_name1= val
#attribute2.setter
def attribue2(self, val):
self.data.another_name2= val
How do I dynamically add these setter methods to the class?
You can write a custom Descriptor like this:
from operator import attrgetter
class CustomProperty(object):
def __init__(self, attr):
self.attr = attr
def __get__(self, ins, type):
print 'inside __get__'
if ins is None:
return self
else:
return attrgetter(self.attr)(ins)
def __set__(self, ins, value):
print 'inside __set__'
head, tail = self.attr.rsplit('.', 1)
obj = attrgetter(head)(ins)
setattr(obj, tail, value)
class MyClass(object):
def __init__(self, data):
self.data = data
attribute1 = CustomProperty('data.another_name1')
attribute2 = CustomProperty('data.another_name2')
Demo:
>>> class Foo():
... pass
...
>>> bar = MyClass(Foo())
>>>
>>> bar.attribute1 = 10
inside __set__
>>> bar.attribute2 = 20
inside __set__
>>> bar.attribute1
inside __get__
10
>>> bar.attribute2
inside __get__
20
>>> bar.data.another_name1
10
>>> bar.data.another_name2
20
This is the author of the question. I found out a very jerry-rigged solution, but I don't know another way to do it. (I am using python 3.4 by the way.)
I'll start with the problems I ran into.
First, I thought about overwriting the property entirely, something like this:
Given this class
class A(object):
def __init__(self):
self._value = 42
#property
def value(self):
return self._value
and you can over write the property entirely by doing something like this:
a = A()
A.value = 31 # This just redirects A.value from the #property to the int 31
a.value # Returns 31
The problem is that this is done at the class level and not at the instance level, so if I make a new instance of A then this happens:
a2 = A()
a.value # Returns 31, because the class itself was modified in the previous code block.
I want that to return a2._value because a2 is a totally new instance of A() and therefore shouldn't be influenced by what I did to a.
The solution to this was to overwrite A.value with a new property rather than whatever I wanted to assign the instance _value to. I learned that you can create a new property that instantiates itself from the old property using the special getter, setter, and deleter methods (see here). So I can overwrite A's value property and make a setter for it by doing this:
def make_setter(name):
def value_setter(self, val):
setattr(self, name, val)
return value_setter
my_setter = make_setter('_value')
A.value = A.value.setter(my_setter) # This takes the property defined in the above class and overwrites the setter with my_setter
setattr(A, 'value', getattr(A, 'value').setter(my_setter)) # This does the same thing as the line above I think so you only need one of them
This is all well and good as long as the original class has something extremely simple in the original class's property definition (in this case it was just return self._value). However, as soon as you get more complicated, to something like return self.data._value like I have, things get nasty -- like #BrenBarn said in his comment on my post. I used the inspect.getsourcelines(A.value.fget) function to get the source code line that contains the return value and parsed that. If I failed to parse the string, I raised an exception. The result looks something like this:
def make_setter(name, attrname=None):
def setter(self, val):
try:
split_name = name.split('.')
child_attr = getattr(self, split_name[0])
for i in range(len(split_name)-2):
child_attr = getattr(child_attr, split_name[i+1])
setattr(child_attr, split_name[-1], val)
except:
raise Exception("Failed to set property attribute {0}".format(name))
It seems to work but there are probably bugs.
Now the question is, what to do if the thing failed? That's up to you and sort of off track from this question. Personally, I did a bit of nasty stuff that involves creating a new class that inherits from A (let's call this class B). Then if the setter worked for A, it will work for the instance of B because A is a base class. However, if it didn't work (because the return value defined in A was something nasty), I ran a settattr(B, name, val) on the class B. This would normally change all other instances that were created from B (like in the 2nd code block in this post) but I dynamically create B using type('B', (A,), {}) and only use it once ever, so changing the class itself has no affect on anything else.
There is a lot of black-magic type stuff going on here I think, but it's pretty cool and quite versatile in the day or so I've been using it. None of this is copy-pastable code, but if you understand it then you can write your modifications.
I really hope/wish there is a better way, but I do not know of one. Maybe metaclasses or descriptors created from classes can do some nice magic for you, but I do not know enough about them yet to be sure.
Comments appreciated!
Sorry, badly worded title. I hope a simple example will make it clear. Here's the easiest way to do what I want to do:
class Lemon(object):
headers = ['ripeness', 'colour', 'juiciness', 'seeds?']
def to_row(self):
return [self.ripeness, self.colour, self.juiciness, self.seeds > 0]
def save_lemons(lemonset):
f = open('lemons.csv', 'w')
out = csv.writer(f)
out.write(Lemon.headers)
for lemon in lemonset:
out.writerow(lemon.to_row())
This works alright for this small example, but I feel like I'm "repeating myself" in the Lemon class. And in the actual code I'm trying to write (where the number of variables I'm exporting is ~50 rather than 4, and where to_row calls a number of private methods that do a bunch of weird calculations), it becomes awkward.
As I write the code to generate a row, I need to constantly refer to the "headers" variable to make sure I'm building my list in the correct order. If I want to change the variables being outputted, I need to make sure to_row and headers are being changed in parallel (exactly the kind of thing that DRY is meant to prevent, right?).
Is there a better way I could design this code? I've been playing with function decorators, but nothing has stuck. Ideally I should still be able to get at the headers without having a particular lemon instance (i.e. it should be a class variable or class method), and I don't want to have a separate method for each variable.
In this case, getattr() is your friend: it allows you to get a variable based on a string name. For example:
def to_row(self):
return [getattr(self, head) for head in self.headers]
EDIT: to properly use the header seeds?, you would need to set the attribute seeds? for the objects. setattr(self, 'seeds?', self.seeds > 0) right above the return statement.
We could use some metaclass shenanegans to do this...
In python 2, attributes are passed to the metaclass in a dict, without
preserving order, we'll also want a base class to work with so we can
distinguish class attributes that should be mapped into the row. In python3, we could dispense with just about all of this base descriptor class.
import itertools
import functools
#functools.total_ordering
class DryDescriptor(object):
_order_gen = itertools.count()
def __init__(self, alias=None):
self.alias = alias
self.order = next(self._order_gen)
def __lt__(self, other):
return self.order < other.order
We will want a python descriptor for every attribute we wish to map into the
row. slots are a nice way to get data descriptors without much work. One
caveat, though, we'll have to manually remove the helper instance to make the
real slot descriptor visible.
class slot(DryDescriptor):
def annotate(self, attr, attrs):
del attrs[attr]
self.attr = attr
slots = attrs.setdefault('__slots__', []).append(attr)
def annotate_class(self, cls):
if self.alias is not None:
setattr(cls, self.alias, getattr(self.attr))
For computed fields, we can memoize results. Memoizing off of the annotated
instance is tricky without a memory leak, we need weakref. alternatively, we
could have arranged for another slot just to store the cached value. This also isn't quite thread safe, but pretty close.
import weakref
class memo(DryDescriptor):
_memo = None
def __call__(self, method):
self.getter = method
return self
def annotate(self, attr, attrs):
if self.alias is not None:
attrs[self.alias] = self
def annotate_class(self, cls): pass
def __get__(self, instance, owner):
if instance is None:
return self
if self._memo is None:
self._memo = weakref.WeakKeyDictionary()
try:
return self._memo[instance]
except KeyError:
return self._memo.setdefault(instance, self.getter(instance))
On the metaclass, all of the descriptors we created above are found, sorted by
creation order, and instructed to annotate the new, created class. This does
not correctly treat derived classes and could use some other conveniences like
an __init__ for all the slots.
class DryMeta(type):
def __new__(mcls, name, bases, attrs):
descriptors = sorted((value, key)
for key, value
in attrs.iteritems()
if isinstance(value, DryDescriptor))
for descriptor, attr in descriptors:
descriptor.annotate(attr, attrs)
cls = type.__new__(mcls, name, bases, attrs)
for descriptor, attr in descriptors:
descriptor.annotate_class(cls)
cls._header_descriptors = [getattr(cls, attr) for descriptor, attr in descriptors]
return cls
Finally, we want a base class to inherit from so that we can have a to_row
method. this just invokes all of the __get__s for all of the respective
descriptors, in order.
class DryBase(object):
__metaclass__ = DryMeta
def to_row(self):
cls = type(self)
return [desc.__get__(self, cls) for desc in cls._header_descriptors]
Assuming all of that is tucked away, out of sight, the definition of a class
that uses this feature is mostly free of repitition. The only short coming is
that to be practical, every field needs a python friendly name, thus we had the
alias key to associate 'seeds?' to has_seeds
class ADryRow(DryBase):
__slots__ = ['seeds']
ripeness = slot()
colour = slot()
juiciness = slot()
#memo(alias='seeds?')
def has_seeds(self):
print "Expensive!!!"
return self.seeds > 0
>>> my_row = ADryRow()
>>> my_row.ripeness = "tart"
>>> my_row.colour = "#8C2"
>>> my_row.juiciness = 0.3479
>>> my_row.seeds = 19
>>>
>>> print my_row.to_row()
Expensive!!!
['tart', '#8C2', 0.3479, True]
>>> print my_row.to_row()
['tart', '#8C2', 0.3479, True]