I was wondering if there was some kind of python variable (which isn't a custom made class) which would support the following code :
a = some_creation_procedure
a.variable_a = 1
a.variable_b = 2
a.variable_c = 3
print ("{}, {}, {}".format(a.variable_a, a.variable_b, a.variable_c))
output -
[1, 2, 3]
I could probably create a custom class and support this with "get_attribute" function, but I was wondering if there was a built-in support for this.
Motivation:
I want to debug a certain function within a class (Which requires a lot of operations / variables for initliazing), so I want to create a sub-class instance which has variables corresponding to that specific function (and send it as self for that specific function).
for example :
class some_class():
def __init__(var1, var2, var3, var4 , ....):
do_a()
do_b()
and so on...
def minimal_func(self):
print (self.var1)
my_variable.var1 = "a"
some_class.minimal_func(my_variable)
The simplest way is a class without anything inside it:
class Namespace: pass
a = Namespace()
a.variable_a = 1
a.variable_b = 2
a.variable_c = 3
print ("{}, {}, {}".format(a.variable_a, a.variable_b, a.variable_c))
prints:
1, 2, 3
as #James said in the comments:
Instances of class objects can have attributes assigned to them on the fly. There are ways to restrict attribute assignment as well, but by default, you can just assign anything
As #Aran-Frey pointed out, you can also use the types.SimpleNamespace class instead of of the above empty class:
import types
a = types.SimpleNamespace()
This also allows you to add attributes in the constructor:
import types
a = types.SimpleNamespace(
variable_a=1,
variable_b=2,
variable_c=3)
Also it has a nice __repr__ function:
print(a)
prints:
namespace(variable_a=1, variable_b=2, variable_c=3)
Related
I found that some classes contain a __init__ function, and some don’t. I’m confused about something described below.
What is the difference between these two pieces of code:
class Test1(object):
i = 1
and
class Test2(object):
def __init__(self):
self.i = 1
I know that the result or any instance created by these two class and the way of getting their instance variable are pretty much the same. But is there any kind of “default” or “hidden” initialization mechanism of Python behind the scene when we don’t define the __init__ function for a class? And why I can’t write the first code in this way:
class Test1(object):
self.i = 1
That’s my questions. Thank you very much!
Thank you very much Antti Haapala! Your answer gives me further understanding of my questions. Now, I understand that they are different in a way that one is a "class variable", and the other is a "instance variable". But, as I tried it further, I got yet another confusing problem.
Here is what it is. I created 2 new classes for understanding what you said:
class Test3(object):
class_variable = [1]
def __init__(self):
self.instance_variable = [2]
class Test4(object):
class_variable = 1
def __init__(self):
self.instance_variable = 2
As you said in the answer to my first questions, I understand the class_variable is a "class variable" general to the class, and should be passed or changed by reference to the same location in the memory. And the instance_variable would be created distinctly for different instances.
But as I tried out, what you said is true for the Test3's instances, they all share the same memory. If I change it in one instance, its value changes wherever I call it.
But that's not true for instances of Test4. Shouldn't the int in the Test4 class also be changed by reference?
i1 = Test3()
i2 = Test3()
>>> i1.i.append(2)
>>> i2.i
[1, 2]
j1 = Test4()
j2 = Test4()
>>> j1.i = 3
>>> j2.i
1
Why is that? Does that "=" create an "instance variable" named "i" without changing the original "Test4.i" by default? Yet the "append" method just handles the "class variable"?
Again, thank you for your exhaustive explanation of the most boring basic concepts to a newbie of Python. I really appreciate that!
In python the instance attributes (such as self.i) are stored in the instance dictionary (i.__dict__). All the variable declarations in the class body are stored as attributes of the class.
Thus
class Test(object):
i = 1
is equivalent to
class Test(object):
pass
Test.i = 1
If no __init__ method is defined, the newly created instance usually starts with an empty instance dictionary, meaning that none of the properties are defined.
Now, when Python does the get attribute (as in print(instance.i) operation, it first looks for the attribute named i that is set on the instance). If that fails, the i attribute is looked up on type(i) instead (that is, the class attribute i).
So you can do things like:
class Test:
i = 1
t = Test()
print(t.i) # prints 1
t.i += 1
print(t.i) # prints 2
but what this actually does is:
>>> class Test(object):
... i = 1
...
>>> t = Test()
>>> t.__dict__
{}
>>> t.i += 1
>>> t.__dict__
{'i': 2}
There is no i attribute on the newly created t at all! Thus in t.i += 1 the .i was looked up in the Test class for reading, but the new value was set into the t.
If you use __init__:
>>> class Test2(object):
... def __init__(self):
... self.i = 1
...
>>> t2 = Test2()
>>> t2.__dict__
{'i': 1}
The newly created instance t2 will already have the attribute set.
Now in the case of immutable value such as int there is not that much difference. But suppose that you used a list:
class ClassHavingAList():
the_list = []
vs
class InstanceHavingAList()
def __init__(self):
self.the_list = []
Now, if you create 2 instances of both:
>>> c1 = ClassHavingAList()
>>> c2 = ClassHavingAList()
>>> i1 = InstanceHavingAList()
>>> i2 = InstanceHavingAList()
>>> c1.the_list is c2.the_list
True
>>> i1.the_list is i2.the_list
False
>>> c1.the_list.append(42)
>>> c2.the_list
[42]
c1.the_list and c2.the_list refer to the exactly same list object in memory, whereas i1.the_list and i2.the_list are distinct. Modifying the c1.the_list looks as if the c2.the_list also changes.
This is because the attribute itself is not set, it is just read. The c1.the_list.append(42) is identical in behaviour to
getattr(c1, 'the_list').append(42)
That is, it only tries read the value of attribute the_list on c1, and if not found there, then look it up in the superclass. The append does not change the attribute, it just changes the value that the attribute points to.
Now if you were to write an example that superficially looks the same:
c1.the_list += [ 42 ]
It would work identical to
original = getattr(c1, 'the_list')
new_value = original + [ 42 ]
setattr(c1, 'the_list', new_value)
And do a completely different thing: first of all the original + [ 42 ] would create a new list object. Then the attribute the_list would be created in c1, and set to point to this new list. That is, in case of instance.attribute, if the attribute is "read from", it can be looked up in the class (or superclass) if not set in the instance, but if it is written to, as in instance.attribute = something, it will always be set on the instance.
As for this:
class Test1(object):
self.i = 1
Such thing does not work in Python, because there is no self defined when the class body (that is all lines of code within the class) is executed - actually, the class is created only after all the code in the class body has been executed. The class body is just like any other piece of code, only the defs and variable assignments will create methods and attributes on the class instead of setting global variables.
I understood my newly added question. Thanks to Antti Haapala.
Now, when Python does the get attribute (as in print(instance.i) operation, it first looks for the attribute named i that is set on the instance). If that fails, the i attribute is looked up on type(i) instead (that is, the class attribute i).
I'm clear about why is:
j1 = Test4()
j2 = Test4()
>>> j1.i = 3
>>> j2.i
1
after few tests. The code
j1.3 = 3
actually creates a new instance variable for j1 without changing the class variable. That's the difference between "=" and methods like "append".
I'm a newbie of Python coming from c++. So, at the first glance, that's weird to me, since I never thought of creating a new instance variable which is not created in the class just using the "=". It's really a big difference between c++ and Python.
Now I got it, thank you all.
I need help on creating an object (a sequence of numbers) in respect to some parameters of a class. Lets say I typed in to the Python IDLE shell:
SuperLotto = make_lottery_set_type('SuperLotto', 6, (1,50))
#means user can create a 'SuperLotto' with 6 numbers in range of 1 to 50
It would make 'SuperLotto' as a new class instance of a class called 'LotteryGameType'.
This is using the code so far:
class LotterySetError(Exception):
pass
def make_lottery_set_type(name:str, size:int, minmax:tuple):
if minmax[0] > minmax[1]:
raise LotterySetError('Illegal range for tuple')
else:
name = LotteryGameType(name, size, minmax[0], minmax[1])
return name
class LotteryGameType:
def __init__(self, name, set_size, min_set_number, max_set_number):
self.name = name
self.set_size = set_size
self.min_set_number = min_set_number
self.max_set_number = max_set_number
I want to be able to create a sequence of numbers and storing it for later use so I can use it with things like overload operators (e.g. eq and ne).
I want to be able to type into the Python IDLE shell:
SuperLotto([3, 4, 19, 23, 46, 27])
This would create an object under the parameters of SuperLotto, if not under parameters of 'SuperLotto' (say more than 6 numbers), it would raise an error. Any approach would be fine. Does anyone have any ideas on how to approach this?
It sounds like what you want is for make_lottery_set_type to return a new class, presumably one that's a subclass of LotteryGameType, rather than returning an instance of that type.
This is actually pretty easy to do in Python. Class definitions are just normal code, that you can run anywhere, even in the middle of a function. And they have access to the local environment while they're running. And classes themselves are "first-class values", meaning you can pass them around and return them from functions. So:
def make_lottery_set_type(name:str, size:int, minmax:tuple):
if minmax[0] > minmax[1]:
raise LotterySetError('Illegal range for tuple')
else:
class NewLotteryGameType(LotteryGameType):
def __init__(self, numbers):
super().__init__(name, size, minmax[0], minmax[1])
self.numbers = numbers
return NewLotteryGameType
If you want to add other methods, that's the same as adding methods to any other class. For example:
def make_lottery_set_type(name:str, size:int, minmax:tuple):
if minmax[0] > minmax[1]:
raise LotterySetError('Illegal range for tuple')
else:
class NewLotteryGameType(LotteryGameType):
def __init__(self, numbers):
super().__init__(name, size, minmax[0], minmax[1])
self.numbers = numbers
def __eq__(self, rhs):
return set(self.numbers) == set(rhs.numbers)
return NewLotteryGameType
So:
>>> SuperLotto = make_lottery_set_type('SuperLotto', 6, (1,50))
>>> super1 = SuperLotto([1,2,3,4,5,6])
>>> super2 = SuperLotto([6,5,4,3,2,1])
>>> super3 = SuperLotto([7,8,9,10,11,12])
>>> super1 == super2
True
>>> super1 == super3
False
(Obviously you can define __eq__ however you want, if set-equality isn't the right rule for your use.)
If you try to inspect the values you're generating, they don't look quite as pretty as you might like. For example, you'd probably rather see SuperLotto rather than NewLotteryGameType in places like this:
>>> super1
<__main__.NewLotteryGameType at 0x10259e490>
>>> SuperLotto.__name__
'NewLotteryGameType'
For that, just add NewLotteryGameType.__name__ = name. You might also want to copy over the docstring from the parent class, or various other things.
More generally, look at functools.update_wrapper (which is designed for wrapping up functions, not classes, but many of the details are the same) for inspiration, and the inspect module docs from your Python version for all of the attributes that classes can have.
In a comment, you ask:
The only problem is that I want NewLotteryGameType to inherit the parameters such as name, set_size, min_set_number, max_set_number from LotteryGameType. So lets say I wanted to type in NewLotteryGameType.set_size in to the Python Shell. I want it to return back to me 6.
That's contradictory. If you want to inherit the instance attributes of LotteryGameType… well, you already do. For example:
>>> super1.set_size
6
If you want them to be accessible off the class, then they can't be instance attributes, they have to be class attributes. And just changing set_size to a class attribute of LotteryGameType and inheriting it won't work, because the whole point of a class attribute is that the same value shared by all instances of the class or any of its subclasses, and the subclasses all need different values.
But you could do something like this:
class LotteryGameType:
def __init__(self, min_set_number, max_set_number):
self.min_set_number = min_set_number
self.max_set_number = max_set_number
def make_lottery_set_type(lottery_name:str, size:int, minmax:tuple):
if minmax[0] > minmax[1]:
raise LotterySetError('Illegal range for tuple')
else:
class NewLotteryGameType(LotteryGameType):
name = lottery_name
set_size = size
def __init__(self, numbers):
super().__init__(minmax[0], minmax[1])
self.numbers = numbers
def __eq__(self, rhs):
return set(self.numbers) == set(rhs.numbers)
return NewLotteryGameType
(Notice that I had to rename the first make_ parameter to lottery_name so it was different from the class attribute name, because of the way scopes work.) Now, name and set_size are not instance attributes, nor are they class attributes of LotteryGameType—but they're class attributes of each NewLotteryGameType. So:
>>> SuperLotto = make_lottery_set_type('SuperLotto', 6, (1,50))
>>> SuperDuperLotto = make_lottery_set_type('SuperDuperLotto', 8, (1,100))
>>> SuperLotto.set_size
6
>>> SuperDuperLotto.set_size
8
What if you create instances of those types? Well, Python looks for attributes in the instance, then in the most-derived class, and then the base classes. So as long as you don't create instance attributes with the same name (notice that I removed the extra params, and the code that set instance attributes, from the LotteryGameType.__init__ method), it does just what you'd want:
>>> super1 = SuperLotto([1,2,3,4,5,6])
>>> super1.set_size
6
>>> duper1 = SuperDuperLotto([1,2,3,4,5,6,7,8])
>>> duper1.set_size
8
Of course this means that LotteryGameType is no longer a usable type on its own; only its subclasses are usable. But that's probably what you wanted anyway, right? You could even consider making it explicitly an abstract base class to make sure nobody accidentally tries to use a direct LotteryGameType instance.
If you're feeling brave, you might want to read up on metaclasses and see how you could adapt this whole design into use a LotteryGameMetaclass, so each new class is an instance of that metaclass instead of a subclass of the (abstract) base class. The source for the new enum module in 3.4, or the near-equivalent external flufl.enum package, might make good sample code. Then you can play with both and see how similar and how different they are.
This question already has answers here:
Closed 10 years ago.
Possible Duplicate:
“Least Astonishment” in Python: The Mutable Default Argument
In Python 2.7, consider I have the following code:
class Base(object):
# Variant 1
def __init__(self, records=[]):
self._records = records
# Variant 2
# def __init__(self, records=[]):
# self._records = []
# if records:
# self._records = records
def append(self, value):
self._records.append(value)
class ChildA(Base):
pass
class ChildB(Base):
pass
a = ChildA()
b = ChildB()
a.append(100)
b.append(200)
print a._records
print b._records
If I use variant 1 to initialize my base class, self._records behaves like a class variable. Executing the code using variant 1 to initialize my base class, I get the ouput:
[100, 200]
[100, 200]
Using variant 2 to initialize my base class, self._records behaves like a instance variable (as expected). Executing the code using variant 2 to initialize my base class, I get the output:
[100]
[200]
What is the difference between these both variants? Why does variant 1 work different to variant 2? Thanks a lot for your help!
Your default argument is [], which is a common pitfall with Python. See more in the tutorial:
Important warning: The default value is evaluated only once. This
makes a difference when the default is a mutable object such as a
list, dictionary, or instances of most classes.
It has nothing to do with inheritance, class or instance variables. Consider the next code:
>>> def f(a=[]):
... a.append(1)
... print a
...
>>> f.func_defaults
([],)
>>> f()
[1]
>>> f()
[1, 1]
>>> f.func_defaults
([1, 1],)
Default values for function parameters are evaluated only ones and stored within function object. Each time f is called it operates with the same list. Right as in your case.
As the others had put - this has to do with using an empty list as default value, not with class inheritance behavior at all.
The correct way to do it is:
class Base(object):
# Variant 1
def __init__(self, records=None):
if records is None:
records = []
self._records = records
Therefore ensuring a new list instance is created each time the Base class is instantiated. The way you put it in your code, a list object is instantiated when your class body is parsed by Python - and that one instance of list is used as the default parameter each time the __init__ method is run. As the objects hold a reference and change that same list, the change is visible in all other objects which share the Base class.
I have a class, and I would like to be able to create multiple objects of that class and place them in an array. I did it like so:
rooms = []
rooms.append(Object1())
...
rooms.append(Object4())
I then have a dict of functions, and I would like to pass the object to the function. However, I'm encountering some problems..For example, I have a dict:
dict = {'look': CallLook(rooms[i])}
I'm able to pass it into the function, however; in the function if I try to call an objects method it gives me problems
def CallLook(current_room)
current_room.examine()
I'm sure that there has to be a better way to do what I'm trying to do, but I'm new to Python and I haven't seen a clean example on how to do this. Anyone have a good way to implement a list of objects to be passed into functions? All of the objects contain the examine method, but they are objects of different classes. (I'm sorry I didn't say so earlier)
The specific error states: TypeError: 'NoneType' object is not callable
Anyone have a good way to implement a list of objects to be passed into functions? All of the objects contain the examine method, but they are objects of different classes. (I'm sorry I didn't say so earlier)
This is Python's plain duck-typing.
class Room:
def __init__(self, name):
self.name = name
def examine(self):
return "This %s looks clean!" % self.name
class Furniture:
def __init__(self, name):
self.name = name
def examine(self):
return "This %s looks comfortable..." % self.name
def examination(l):
for item in l:
print item.examine()
list_of_objects = [ Room("Living Room"), Furniture("Couch"),
Room("Restrooms"), Furniture("Bed") ]
examination(list_of_objects)
Prints:
This Living Room looks clean!
This Couch looks comfortable...
This Restrooms looks clean!
This Bed looks comfortable...
As for your specific problem: probably you have forgotten to return a value from examine()? (Please post the full error message (including full backtrace).)
I then have a dict of functions, and I would like to pass the object to the function. However, I'm encountering some problems..For example, I have a dict:
my_dict = {'look': CallLook(rooms[i])} # this is no dict of functions
The dict you have created may evaluate to {'look': None} (assuming your examine() doesn't return a value.) Which could explain the error you've observed.
If you wanted a dict of functions you needed to put in a callable, not an actual function call, e.g. like this:
my_dict = {'look': CallLook} # this is a dict of functions
if you want to bind the 'look' to a specific room you could redefine CallLook:
def CallLook(current_room)
return current_room.examine # return the bound examine
my_dict = {'look': CallLook(room[i])} # this is also a dict of functions
Another issue with your code is that you are shadowing the built-in dict() method by naming your local dictionary dict. You shouldn't do this. This yields nasty errors.
Assuming you don't have basic problems (like syntax errors because the code you have pasted is not valid Python), this example shows you how to do what you want:
>>> class Foo():
... def hello(self):
... return 'hello'
...
>>> r = [Foo(),Foo(),Foo()]
>>> def call_method(obj):
... return obj.hello()
...
>>> call_method(r[1])
'hello'
Assuming you have a class Room the usual way to create a list of instances would be using a list comprehension like this
rooms = [Room() for i in range(num_rooms)]
I think there are some things you may not be getting about this:
dict = {'look': CallLook(rooms[i])}
This creates a dict with just one entry: a key 'look', and a value which is the result of evaluating CallLook(rooms[i]) right at the point of that statement. It also then uses the name dict to store this object, so you can no longer use dict as a constructor in that context.
Now, the error you are getting tells us that rooms[i] is None at that point in the programme.
You don't need CallLook (which is also named non-standardly) - you can just use the expression rooms[i].examine(), or if you want to evaluate the call later rooms[i].examine.
You probably don't need the dict at all.
That is not a must, but in some cases, using hasattr() is good... getattr() is another way to get an attribute off an object...
So:
rooms = [Obj1(),Obj2(),Obj3()]
if hasattr(rooms[i], 'examine'):#First check if our object has selected function or attribute...
getattr(rooms[i], 'examine') #that will just evaluate the function do not call it, and equals to Obj1().examine
getattr(rooms[i], 'examine')() # By adding () to the end of getattr function, we evalute and then call the function...
You may also pass parameters to examine function like:
getattr(rooms[i], 'examine')(param1, param2)
I'm not sure of your requirement, but you can use dict to store multiple object of a class.
May be this will help,
>>> class c1():
... print "hi"
...
hi
>>> c = c1()
>>> c
<__main__.c1 instance at 0x032165F8>
>>> d ={}
>>> for i in range (10):
... d[i] = c1()
...
>>> d[0]
<__main__.c1 instance at 0x032166E8>
>>> d[1]
<__main__.c1 instance at 0x032164B8>
>>>
It will create a object of c1 class and store it in dict. Obviously, in this case you can use list instead of dict.
This question already has answers here:
How to access (get or set) object attribute given string corresponding to name of that attribute
(3 answers)
Closed 3 years ago.
I have a Python class that have attributes named: date1, date2, date3, etc.
During runtime, I have a variable i, which is an integer.
What I want to do is to access the appropriate date attribute in run time based on the value of i.
For example,
if i == 1, I want to access myobject.date1
if i == 2, I want to access myobject.date2
And I want to do something similar for class instead of attribute.
For example, I have a bunch of classes: MyClass1, MyClass2, MyClass3, etc. And I have a variable k.
if k == 1, I want to instantiate a new instance of MyClass1
if k == 2, I want to instantiate a new instance of MyClass2
How can i do that?
EDIT
I'm hoping to avoid using a giant if-then-else statement to select the appropriate attribute/class.
Is there a way in Python to compose the class name on the fly using the value of a variable?
You can use getattr() to access a property when you don't know its name until runtime:
obj = myobject()
i = 7
date7 = getattr(obj, 'date%d' % i) # same as obj.date7
If you keep your numbered classes in a module called foo, you can use getattr() again to access them by number.
foo.py:
class Class1: pass
class Class2: pass
[ etc ]
bar.py:
import foo
i = 3
someClass = getattr(foo, "Class%d" % i) # Same as someClass = foo.Class3
obj = someClass() # someClass is a pointer to foo.Class3
# short version:
obj = getattr(foo, "Class%d" % i)()
Having said all that, you really should avoid this sort of thing because you will never be able to find out where these numbered properties and classes are being used except by reading through your entire codebase. You are better off putting everything in a dictionary.
For the first case, you should be able to do:
getattr(myobject, 'date%s' % i)
For the second case, you can do:
myobject = locals()['MyClass%s' % k]()
However, the fact that you need to do this in the first place can be a sign that you're approaching the problem in a very non-Pythonic way.
OK, well... It seems like this needs a bit of work. Firstly, for your date* things, they should be perhaps stored as a dict of attributes. eg, myobj.dates[1], so on.
For the classes, it sounds like you want polymorphism. All of your MyClass* classes should have a common ancestor. The ancestor's __new__ method should figure out which of its children to instantiate.
One way for the parent to know what to make is to keep a dict of the children. There are ways that the parent class doesn't need to enumerate its children by searching for all of its subclasses but it's a bit more complex to implement. See here for more info on how you might take that approach. Read the comments especially, they expand on it.
class Parent(object):
_children = {
1: MyClass1,
2: MyClass2,
}
def __new__(k):
return object.__new__(Parent._children[k])
class MyClass1(Parent):
def __init__(self):
self.foo = 1
class MyClass2(Parent):
def __init__(self):
self.foo = 2
bar = Parent(1)
print bar.foo # 1
baz = Parent(2)
print bar.foo # 2
Thirdly, you really should rethink your variable naming. Don't use numbers to enumerate your variables, instead give them meaningful names. i and k are bad to use as they are by convention reserved for loop indexes.
A sample of your existing code would be very helpful in improving it.
to get a list of all the attributes, try:
dir(<class instance>)
I agree with Daenyth, but if you're feeling sassy you can use the dict method that comes with all classes:
>>> class nullclass(object):
def nullmethod():
pass
>>> nullclass.__dict__.keys()
['__dict__', '__module__', '__weakref__', 'nullmethod', '__doc__']
>>> nullclass.__dict__["nullmethod"]
<function nullmethod at 0x013366A8>