Non-iterable Object After \__init__ Array in Python Class - python

Say I would like to create a python class that behave as array of another class. While the __init__ is called, it recognizes itself as an array (iterable); however, when I call it again through some other method, or even call by the index, the object becomes non-iterable. I wonder which part I got it wrong, or perhaps, there's DO and DON'T for python class?
Last but not least, this is an attempt to simplify one object type to another (trying to cast from one class to another). Perhaps the code below will give a better clarification.
The example is below:
Say I have an object FOO
FOO.name = "john"
FOO.records[0].a = 1
FOO.records[0].b = 2
FOO.records[1].a = 4
FOO.records[1].b = 5
And I create a python class
class BAR:
__init__(self, record):
self.a = int(record.a)
self.b = int(record.b)
and another class which would like to store BAR class as array
class BARS:
__init__(self,bars):
self = numpy.array([]) # regardless the array type whether python native or Numpy it does not work
for item in bars:
self = numpy.append(self, BAR(item))
so what I would expect this code to perform would be that if I call
A = BARS(FOO.records)
I would get an iterable A. But this does not work, though if I call SELF in BARS __init__, it would see SELF as iterable object.
If one should not expect python class to behave in this manner, at least I hope you could help pointing me out, what would be the alternative logical and pythonic way to achieve it.

Perhaps answering my own question after a hint from comment above would be good.
It turns out that assining self in class as itself is a DON'T (silly me trying to get a shortcut).
To achieve an iterable class, one would require __iter__ method alongside with __next__, and __getitem__ to fulfill (maybe some others methods as well, but let's stick to these three for now).
So, the code above should look like this
class BARS:
def __init__(self, records):
self.records = [] # Use list for simplicity
for record in records:
self.records.append(BAR(record))
def __iter__(self):
self.n = 0
return self
def __next__(self):
if self.n < len(self.records):
result = self.records[self.n]
self.n += 1
return result
else:
raise StopIteration
def __getitem__(self, key):
return self.records[key]
Eventually, this will yield a iteration and index accessible object.

Related

TypeError: __init__() missing 1 required positional argument: 'lists'

I created a class, something like below -
class child:
def __init__(self,lists):
self.myList = lists
def find_mean(self):
mean=np.mean(self.myList)
return mean
and when I create an onject something like below -
obj=child()
it gives the error -
TypeError: __init__() missing 1 required positional argument: 'lists'
if I create object like below then it works well -
obj=child([44,22,55)
or If I create the class like below -
class child:
def find_mean(self,myList):
mean=np.mean(myList)
return mean
and then I create the object like below -
obj=child()
then also it works well, however I need to make it in the way I explained in the very begining. Can you please help me understand this context?
In the first example, the __init__ method expects two parameters:
self is automatically filled in by Python.
lists is a parameter which you must give it. It will try to assign this value to a new variable called self.myList, and it won't know what value it is supposed to use if you don't give it one.
In the second example, you have not written an __init__ method. This means that Python creates its own default __init__ function which will not require any parameters. However, the find_mean method now requires you to give it a parameter instead.
When you say you want to create it in the way you explained at the beginning, this is actually impossible: the class requires a value, and you are not giving it one.
Therefore, it is hard for me to tell what you really want to do. However, one option might be that you want to create the class earlier, and then add a list to it later on. In this case, the code would look like this:
import numpy as np
class Child:
def __init__(self, lists=None):
self.myList = lists
def find_mean(self):
if self.myList is None:
return np.nan
mean = np.mean(self.myList)
return mean
This code allows you to create the object earlier, and add a list to it later. If you try to call find_mean without giving it a list, it will simply return nan:
child = Child()
print(child.find_mean()) # Returns `nan`
child.myList = [1, 2, 3]
print(child.find_mean()) # Returns `2`
the code you have at the top of your question defines a class called child, which has one attribute, lists, which is assigned at the time of instance creation in the __init__ method. This means that you must supply a list when creating an instance of child.
class child:
def __init__(self, lists):
self.myList = lists
def find_mean(self):
mean=np.mean(self.myList)
return mean
# works because a list is provided
obj = child([44,22,55])
# does not work because no list is given
obj = child() # TypeError
If you create the class like in your second example, __init__ is no longer being explicitly specified, and as such, the object has no attributes that must be assigned at instance creation:
class child:
def find_mean(self, myList):
mean=np.mean(myList)
return mean
# does not work because `child()` does not take any arguments
obj = child([44,22,55]) # TypeError
# works because no list is needed
obj = child()
The only way to both have the myList attribute, and not need to specify it at creation would be to assign a default value to it:
class child:
def find_mean(self,myList=None):
mean=np.mean(myList)
return mean
# now this will work
obj = child()
# as will this
obj = child([24, 35, 27])

self in Python classes

I know first argument in Python methods will be an instance of this class. So we need use "self" as first argument in methods. But should we also specify attribures (variables) in method starting with "self."?
My method work even if i don't specify self in his attributes:
class Test:
def y(self, x):
c = x + 3
print(c)
t = Test()
t.y(2)
5
and
class Test:
def y(self, x):
self.c = x + 3
print(self.c)
t = Test()
t.y(2)
5
For what i would need specify an attribute in methods like "self.a" instead of just "a"?
In which cases first example will not work but second will? Want to see situation which shows really differences between two of them, because now they behave the same from my point of view.
The reason you do self.attribute_name in a class method is to perform computation on that instances attribute as opposed to using a random variable.For Example
class Car:
def __init__(self,size):
self.size = size
def can_accomodate(self,number_of_people):
return self.size> number_of_people
def change_size(self,new_size):
self.size=new_size
#works but bad practice
def can_accomodate_v2(self,size,number_of_people):
return size> number_of_people
c = Car(5)
print(c.can_accomodate(2))
print(c.can_accomodate_v2(4,2))
In the above example you can see that the can_accomodate use's self.size while can_accomodate_v2 passes the size variable which is bad practice.Both will work but the v2 is a bad practice and should not be used.You can pass argument into a class method not related to the instance/class for example "number_of_people" in can_accomodate funtion.
Hope this helps.

How to calculate hash of a python class object

In python3, I have a class. Like below:
class Foo:
def __init__(self):
self.x = 3
def fcn(self, val):
self.x += val
Then I instantiate objects of that class, like so:
new_obj = Foo()
new_obj2 = Foo()
Now when I hash these objects, I get different hash values. I need them to return the same hash, as they are the same objects (in theory).
Any idea how I can do this?
Thank you to all who answered. You're right that instantiating a new instance of the same class object is not actually the same, as it occupies a different place in memory. What I ended up doing is similar to what #nosklo suggested.
I created a 'get_hashables' function that returned a dictionary with all the properties of the class that would constitute a unique class object, like so:
def get_hashables(self):
return {'data': self.data, 'result': self.result}
Then my main method would take these 'hashable' variables, and hash them to produce the hash itself.
class Foo:
def __init__(self):
self.x = 3
def fcn(self, val):
self.x += val
def __hash__(self):
return hash(self.x)
This will calculate the hash using self.x; That means the hash will be the same when self.x is the same. You can return anything from __hash__, but to prevent consistency bugs you should return the same hash if the objects compare equal. More about that in the docs.
They are not the same object. The expression Foo() invokes the class constructor, Foo.__init__, which returns a new, unique instance of the object on each call. Your two calls return two independent objects, residing in different memory locations, each containing its own, private instance of the x attribute.
You might want to read up on Python class and instance theory.

Inheritance of from_<type> in Python

Edit: There was some confusion, but I want to ask a general question about object oriented design in Python.
Consider a class that lets you map data values to counts or frequencies:
class DataMap(dict):
pass
Now consider a subclass that allows you to construct a histogram from a list of data:
class Histogram(DataMap):
def __init__(self, list_of_values):
# 1. Put appropriate super(...) call here if necessary
# 2. Build the map of values to counts in self
pass
Now consider a class that lets you make a smoothed probability mass table rather than a Histogram.
class ProbabilityMass(DataMap):
pass
What is the best way to allow a ProbabilityMass to be constructed from either a Histogram or a list of values?
I "grew up" programming in C++, and in this case I would use an overloaded constructor. In Python I've thought of doing this with:
The constructor takes multiple arguments (all but one of these should == None)
I define from_Histogram and from_list methods
In the second case (which I believe is better), what is the best way to allow the from_list method to use the shared code from the Histogram constructor? A ProbabilityMass table is nearly identical to a Histogram table, but it is scaled so that the sum of all value is 1.0.
If you have come across a similar problem, please share your expertise!
To start with, if you think you want #staticmethod, you almost always don't. Either the function is not part of the class, in which case it should just be a free function, or it is part of the class, but not tied to an instance, and it should be a #classmethod. Your named constructor is a good candidate for a #classmethod.
Also note that you should invoke A.__init__ from B via super(), otherwise multiple inheritance can bite you bad.
class A:
def __init__(self, data):
self.values_to_counts = {}
for val in data:
if val in self.values_to_counts:
self.values_to_counts[val] += 1
else:
self.values_to_counts[val] = 1
#classmethod
def from_values_to_counts(cls, values_to_counts):
self = cls([])
self.values_to_counts = values_to_counts
return self
class B(A):
def __init__(self, data, parameter):
super(B, self).__init__(data)
self.parameter = parameter
def print_parameter(self):
print self.parameter
In this case, you don't need a B.from_values_to_counts, it inherits from A, and it will return an instance of B, since that's how it was called.
If you need to do more complex initialization in B, you can, using super(), which looks very similar to the way it would when you use it with instances. after all, a classmethod really isn't anything more complex than an instancemethod where the im_self attribute is assigned to the class itself.
class A:
def __init__(self, data):
self.values_to_counts = {}
for val in data:
if val in self.values_to_counts:
self.values_to_counts[val] += 1
else:
self.values_to_counts[val] = 1
#classmethod
def from_values_to_counts(cls, values_to_counts):
self = cls([])
self.values_to_counts = values_to_counts
return self
class B(A):
def __init__(self, data, parameter):
super(B, self).__init__(data)
self.parameter = parameter
def print_parameter(self):
print self.parameter
#classmethod
def from_values_to_counts(cls, values_to_counts):
self = super(B, cls).from_values_to_counts(values_to_counts)
do_more_initialization(self)
return self

sharing a string between two objects

I want two objects to share a single string object. How do I pass the string object from the first to the second such that any changes applied by one will be visible to the other? I am guessing that I would have to wrap the string in a sort of buffer object and do all sorts of complexity to get it to work.
However, I have a tendency to overthink problems, so undoubtedly there is an easier way. Or maybe sharing the string is the wrong way to go? Keep in mind that I want both objects to be able to edit the string. Any ideas?
Here is an example of a solution I could use:
class Buffer(object):
def __init__(self):
self.data = ""
def assign(self, value):
self.data = str(value)
def __getattr__(self, name):
return getattr(self.data, name)
class Descriptor(object):
def __get__(self, instance, owner):
return instance._buffer.data
def __set__(self, instance, value):
if not hasattr(instance, "_buffer"):
if isinstance(value, Buffer):
instance._buffer = value
return
instance._buffer = Buffer()
instance._buffer.assign(value)
class First(object):
data = Descriptor()
def __init__(self, data):
self.data = data
def read(self, size=-1):
if size < 0:
size = len(self.data)
data = self.data[:size]
self.data = self.data[size:]
return data
class Second(object):
data = Descriptor()
def __init__(self, data):
self.data = data
def add(self, newdata):
self.data += newdata
def reset(self):
self.data = ""
def spawn(self):
return First(self._buffer)
s = Second("stuff")
f = s.spawn()
f.data == s.data
#True
f.read(2)
#"st"
f.data
# "uff"
f.data == s.data
#True
s.data
#"uff"
s._buffer == f._buffer
#True
Again, this seems like absolute overkill for what seems like a simple problem. As well, it requires the use of the Buffer class, a descriptor, and the descriptor's impositional _buffer variable.
An alternative is to put one of the objects in charge of the string and then have it expose an interface for making changes to the string. Simpler, but not quite the same effect.
I want two objects to share a single
string object.
They will, if you simply pass the string -- Python doesn't copy unless you tell it to copy.
How do I pass the string object from
the first to the second such that any
changes applied by one will be visible
to the other?
There can never be any change made to a string object (it's immutable!), so your requirement is trivially met (since a false precondition implies anything).
I am guessing that I would have to
wrap the string in a sort of buffer
object and do all sorts of complexity
to get it to work.
You could use (assuming this is Python 2 and you want a string of bytes) an array.array with a typecode of c. Arrays are mutable, so you can indeed alter them (with mutating methods -- and some operators, which are a special case of methods since they invoke special methods on the object). They don't have the myriad non-mutating methods of strings, so, if you need those, you'll indeed need a simple wrapper (delegating said methods to the str(...) of the array that the wrapper also holds).
It doesn't seem there should be any special complexity, unless of course you want to do something truly weird as you seem to given your example code (have an assignment, i.e., a *rebinding of a name, magically affect a different name -- that has absolutely nothing to do with whatever object was previously bound to the name you're rebinding, nor does it change that object in any way -- the only object it "changes" is the one holding the attribute, so it's obvious that you need descriptors or other magic on said object).
You appear to come from some language where variables (and particularly strings) are "containers of data" (like C, Fortran, or C++). In Python (like, say, in Java), names (the preferred way to call what others call "variables") always just refer to objects, they don't contain anything except exactly such a reference. Some objects can be changed, some can't, but that has absolutely nothing to do with the assignment statement (see note 1) (which doesn't change objects: it rebinds names).
(note 1): except of course that rebinding an attribute or item does alter the object that "contains" that item or attribute -- objects can and do contain, it's names that don't.
Just put your value to be shared in a list, and assign the list to both objects.
class A(object):
def __init__(self, strcontainer):
self.strcontainer = strcontainer
def upcase(self):
self.strcontainer[0] = self.strcontainer[0].upper()
def __str__(self):
return self.strcontainer[0]
# create a string, inside a shareable list
shared = ['Hello, World!']
x = A(shared)
y = A(shared)
# both objects have the same list
print id(x.strcontainer)
print id(y.strcontainer)
# change value in x
x.upcase()
# show how value is changed in both x and y
print str(x)
print str(y)
Prints:
10534024
10534024
HELLO, WORLD!
HELLO, WORLD!
i am not a great expert in python, but i think that if you declare a variable in a module and add a getter/setter to the module for this variable you will be able to share it this way.

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