I'm currently learning python operator overloading (__radd__ and __add__ to be exact) and I have the following code
class Commuter1:
def __init__(self, val):
self.val = val
def __add__(self, other):
print('add', self.val, other)
return self.val + other
def __radd__(self, other):
print('radd', self.val, other)
return other + self.val
x = Commuter1(88)
y = Commuter1(99)
print(x + y)
I have got the following result
When used separately, I understand how __radd__ and __add__ works. But for the line x + y, I'm not sure why both __radd__ and __add__ methods are evoked.
First, Python looks at the types of x and y to decide whether to call x.__add__ or y.__radd__. Since they're both the same type Commuter1, it tries x.__add__ first.
Then, inside your __add__ method, you do this:
return self.val + other
So, Python looks at the types of self.val and other to decide whether to call self.val.__add__ or other.__radd__. Since they're unrelated types int and Commuter1, it tries int.__add__ first.
But int.__add__ returns NotImplemented for a type it doesn't know about, so Python falls back to calling other.__radd__.
Inside your __radd__ method, you do this:
return other + self.val
So, Python looks at the types of other and self.val to decide whether to call other.__add__ or self.val.__radd__. Since they both the same type int, it tries __add__ first.
And of course int.__add__ works on another int, so it returns a value for the inner + inside your __radd__, which you return, which returns a value for the + inside __add__, which you return, which returns a value for the top-level +, which you print.
Related
How do you go about overloading the addition, subtraction, and multiplication operator so we can add, subtract, and multiply two vectors of different or identical sizes? For example, if the vectors are different sizes we must be able to add, subtract, or multiply the two vectors according to the smallest vector size?
I've created a function that allows you to modify different vectors, but now I'm struggling to overload the operators and haven't a clue on where to begin. I will paste the code below. Any ideas?
def __add__(self, y):
self.vector = []
for j in range(len(self.vector)):
self.vector.append(self.vector[j] + y.self.vector[j])
return Vec[self.vector]
You define the __add__, __sub__, and __mul__ methods for the class, that's how. Each method takes two objects (the operands of +/-/*) as arguments and is expected to return the result of the computation.
Nothing wrong with the accepted answer on this question but I'm adding some quick snippets to illustrate how this can be used. (Note that you could also "overload" the method to handle multiple types.)
"""Return the difference of another Transaction object, or another
class object that also has the `val` property."""
class Transaction(object):
def __init__(self, val):
self.val = val
def __sub__(self, other):
return self.val - other.val
buy = Transaction(10.00)
sell = Transaction(7.00)
print(buy - sell)
# 3.0
"""Return a Transaction object with `val` as the difference of this
Transaction.val property and another object with a `val` property."""
class Transaction(object):
def __init__(self, val):
self.val = val
def __sub__(self, other):
return Transaction(self.val - other.val)
buy = Transaction(20.00)
sell = Transaction(5.00)
result = buy - sell
print(result.val)
# 15
"""Return difference of this Transaction.val property and an integer."""
class Transaction(object):
def __init__(self, val):
self.val = val
def __sub__(self, other):
return self.val - other
buy = Transaction(8.00)
print(buy - 6.00)
# 2
docs have the answer. Basically there are functions that get called on an object when you add or multiple, etc. for instance __add__ is the normal add function.
I want to subclass from float but don't want it to init soon. I also don't want to explicitly call float() for my object.
For example, I don't want to calculate anything before it is required. I want only to do an object that behaves like float. Here is how I want to create class:
class MassiveAverage(float):
def __init__(self, floats: list[float]):
self.floats = floats
def __float__(self) -> float:
return sum(self.floats) / len(self.floats)
And this is how I want to use it:
massive_average = MassiveAverage([1.1, 2.2]) # no any calculations
massive_sum = massive_average * 2 # this is were it calculates its float value
For the answer to this question I am going to assume you are already familiar with python's "magic methods". #gftea's answer has a link to the documentation for some of the magic methods if you are not familiar.
You are going to have to manually define each "magic function" __mul__, __add__, __sub__, etc.
class MassiveAverage:
def __init__(self, floats):
self._avg = sum(floats)/len(floats)
def __mul__(self, other):
return self._avg * other
def __sub__(self, other):
return self._avg - other
def __add__(self, other):
return self._avg + other
...
But, this doesn't handle your lazy evaluation use case. Instead, we could maintain an internal cache, and on the first time one of these magic methods are evaluated, we could run the average function.
class MassiveAverage:
def __init__(self, floats):
self._floats = floats
self._avg = None
#property
def avg(self):
if self._avg is None:
self._avg = sum(self._floats) / len(self._floats)
return self._avg
Then, we can replace our magic functions and use self.avg.
def __mul__(self, other):
return self.avg * other
def __add__(self, other):
return self.avg + other
def __sub__(self, other):
return self.avg - other
...
Unfortunately, you cannot subclass float in the manner you want. Because you are specifying lazy evaluation, you are fundamentally changing how the methods in the float class work (since they don't need lazy evaluation). You would still have to manually change each magic method.
you should overwrite the operator, for example, to overwrite *, you can overwrite the __mul__ method
def __mul__(self, float): ...
see below for methods can be defined to emulate numeric objects
https://docs.python.org/3/reference/datamodel.html?highlight=rmul#emulating-numeric-types
__float__ is used for exactly one purpose: to define the behavior of float(x) as x.__float__(). There is no implicit conversion in an expression like massive_average * 2. This could mean any number of things:
massive_average.__int__() * 2
massive_average.__float__() * 2
massive_average.__complex__() * 2
massive_avarge.__str__() * 2
so Python refuses to guess. It will try massive_average.__mul__(2), and failing that, (2).__rmul__(massive_average), before giving up.
Each of the type-specific "conversion" methods are used only by the corresponding type itself. print, for example, does not call __str__ (directly); it only is defined to call str on each of its arguments, and str takes care of calling __str__.
How do you go about overloading the addition, subtraction, and multiplication operator so we can add, subtract, and multiply two vectors of different or identical sizes? For example, if the vectors are different sizes we must be able to add, subtract, or multiply the two vectors according to the smallest vector size?
I've created a function that allows you to modify different vectors, but now I'm struggling to overload the operators and haven't a clue on where to begin. I will paste the code below. Any ideas?
def __add__(self, y):
self.vector = []
for j in range(len(self.vector)):
self.vector.append(self.vector[j] + y.self.vector[j])
return Vec[self.vector]
You define the __add__, __sub__, and __mul__ methods for the class, that's how. Each method takes two objects (the operands of +/-/*) as arguments and is expected to return the result of the computation.
Nothing wrong with the accepted answer on this question but I'm adding some quick snippets to illustrate how this can be used. (Note that you could also "overload" the method to handle multiple types.)
"""Return the difference of another Transaction object, or another
class object that also has the `val` property."""
class Transaction(object):
def __init__(self, val):
self.val = val
def __sub__(self, other):
return self.val - other.val
buy = Transaction(10.00)
sell = Transaction(7.00)
print(buy - sell)
# 3.0
"""Return a Transaction object with `val` as the difference of this
Transaction.val property and another object with a `val` property."""
class Transaction(object):
def __init__(self, val):
self.val = val
def __sub__(self, other):
return Transaction(self.val - other.val)
buy = Transaction(20.00)
sell = Transaction(5.00)
result = buy - sell
print(result.val)
# 15
"""Return difference of this Transaction.val property and an integer."""
class Transaction(object):
def __init__(self, val):
self.val = val
def __sub__(self, other):
return self.val - other
buy = Transaction(8.00)
print(buy - 6.00)
# 2
docs have the answer. Basically there are functions that get called on an object when you add or multiple, etc. for instance __add__ is the normal add function.
So, I've got a custom class that has a __mul__ function which works with ints. However, in my program (in libraries), it's getting called the other way around, i.e., 2 * x where x is of my class. Is there a way I can have it use my __mul__ function for this?
Just add the following to the class definition and you should be good to go:
__rmul__ = __mul__
Implement __rmul__ as well.
class Foo(object):
def __mul__(self, other):
print '__mul__'
return other
def __rmul__(self, other):
print '__rmul__'
return other
x = Foo()
2 * x # __rmul__
x * 2 # __mul__
How Python chooses which object to use the method overload?
For example:
class a:
def __init__(self, other):
self.data = other
def __add__(self, other):
return self.data + other
def __radd__(self,other):
return self.data + other
X = a(1)
X+1
1+X
Why in X + 1 expression , calls a method __add__ in object at the left, and in expression 1 + X method __add__ is called at object on the right?
X+1
first, calls:
X.__add__(1)
That succeeds, so no further work is needed.
On the other hand, this:
1+X
calls
(1).__add__(X)
That fails because int doesn't know how to interface with a class a. "As a last resort" this is tried instead:
X.__radd__(1)
From the docs on __radd__:
These functions are only called if the left operand does not support the corresponding operation and the operands are of different types.