In python, is it possible to chain together class methods and functions together? For example, if I want to instantiate a class object and call a method on it that affects an instance variable's state, could I do that? Here is an example:
class Test(object):
def __init__(self):
self.x = 'Hello'
#classmethod
def make_upper(y):
y.x = y.x.upper()
What I'm wanting to do is this:
h = Test().make_upper()
I want to instantiate a class object and affect the state of a variable in one line of code, but I would also like to be able to chain together multiple functions that can affect state or do something else on the object. Is this possible in python like it is in jQuery?
Yes, sure. Just return self from the instance methods you are interested in:
class Test(object):
def __init__(self):
self.x = 'Hello'
def make_upper(self):
self.x = self.x.upper()
return self
def make_lower(self):
self.x = self.x.lower()
return self
h = Test().make_upper()
print(h.x)
Output:
HELLO
Yes and no. The chaining certainly works, but h is the return value of make_upper(), not the object returned by Test(). You need to write this as two lines.
h = Test()
h.make_upper()
However, PEP-572 was recently accepted for inclusion in Python 3.8, which means someday you could write
(h := Test()).make_upper()
The return value of Test() is assigned to h in the current scope and used as the value of the := expression, which then invokes its make_upper method. I'm not sure I would recommend using := in this case, though; the currently required syntax is much more readable.
Related
I am trying to modify an already defined class by changing an attribute's value. Importantly, I want this change to propagate internally.
For example, consider this class:
class Base:
x = 1
y = 2 * x
# Other attributes and methods might follow
assert Base.x == 1
assert Base.y == 2
I would like to change x to 2, making it equivalent to this.
class Base:
x = 2
y = 2 * x
assert Base.x == 2
assert Base.y == 4
But I would like to make it in the following way:
Base = injector(Base, x=2)
Is there a way to achieve this WITHOUT recompile the original class source code?
The effect you want to achieve belongs to the realm of "reactive programing" - a programing paradigm (from were the now ubiquitous Javascript library got its name as an inspiration).
While Python has a lot of mechanisms to allow that, one needs to write his code to actually make use of these mechanisms.
By default, plain Python code as the one you put in your example, uses the Imperative paradigm, which is eager: whenever an expression is encoutered, it is executed, and the result of that expression is used (in this case, the result is stored in the class attribute).
Python's advantages also can make it so that once you write a codebase that will allow some reactive code to take place, users of your codebase don't have to be aware of that, and things work more or less "magically".
But, as stated above, that is not free. For the case of being able to redefine y when x changes in
class Base:
x = 1
y = 2 * x
There are a couple paths that can be followed - the most important is that, at the time the "*" operator is executed (and that happens when Python is parsing the class body), at least one side of the operation is not a plain number anymore, but a special object which implements a custom __mul__ method (or __rmul__) in this case. Then, instead of storing a resulting number in y, the expression is stored somewhere, and when y is retrieved either as a class attribute, other mechanisms force the expression to resolve.
If you want this at instance level, rather than at class level, it would be easier to implement. But keep in mind that you'd have to define each operator on your special "source" class for primitive values.
Also, both this and the easier, instance descriptor approach using property are "lazily evaluated": that means, the value for y is calcualted when it is to be used (it can be cached if it will be used more than once). If you want to evaluate it whenever x is assigned (and not when y is consumed), that will require other mechanisms. Although caching the lazy approach can mitigate the need for eager evaluation to the point it should not be needed.
1 - Before digging there
Python's easiest way to do code like this is simply to write the expressions to be calculated as functions - and use the property built-in as a descriptor to retrieve these values. The drawback is small:
you just have to wrap your expressions in a function (and then, that function
in something that will add the descriptor properties to it, such as property). The gain is huge: you are free to use any Python code inside your expression, including function calls, object instantiation, I/O, and the like. (Note that the other approach requires wiring up each desired operator, just to get started).
The plain "101" approach to have what you want working for instances of Base is:
class Base:
x = 1
#property
def y(self):
return self.x * 2
b = Base()
b.y
-> 2
Base.x = 3
b.y
-> 6
The work of property can be rewritten so that retrieving y from the class, instead of an instance, achieves the effect as well (this is still easier than the other approach).
If this will work for you somehow, I'd recommend doing it. If you need to cache y's value until x actually changes, that can be done with normal coding
2 - Exactly what you asked for, with a metaclass
as stated above, Python'd need to know about the special status of your y attribute when calculcating its expression 2 * x. At assignment time, it would be already too late.
Fortunately Python 3 allow class bodies to run in a custom namespace for the attribute assignment by implementing the __prepare__ method in a metaclass, and then recording all that takes place, and replacing primitive attributes of interest by special crafted objects implementing __mul__ and other special methods.
Going this way could even allow values to be eagerly calculated, so they can work as plain Python objects, but register information so that a special injector function could recreate the class redoing all the attributes that depend on expressions. It could also implement lazy evaluation, somewhat as described above.
from collections import UserDict
import operator
class Reactive:
def __init__(self, value):
self._initial_value = value
self.values = {}
def __set_name__(self, owner, name):
self.name = name
self.values[owner] = self._initial_value
def __get__(self, instance, owner):
return self.values[owner]
def __set__(self, instance, value):
raise AttributeError("value can't be set directly - call 'injector' to change this value")
def value(self, cls=None):
return self.values.get(cls, self._initial_value)
op1 = value
#property
def result(self):
return self.value
# dynamically populate magic methods for operation overloading:
for name in "mul add sub truediv pow contains".split():
op = getattr(operator, name)
locals()[f"__{name}__"] = (lambda operator: (lambda self, other: ReactiveExpr(self, other, operator)))(op)
locals()[f"__r{name}__"] = (lambda operator: (lambda self, other: ReactiveExpr(other, self, operator)))(op)
class ReactiveExpr(Reactive):
def __init__(self, value, op2, operator):
self.op2 = op2
self.operator = operator
super().__init__(value)
def result(self, cls):
op1, op2 = self.op1(cls), self.op2
if isinstance(op1, Reactive):
op1 = op1.result(cls)
if isinstance(op2, Reactive):
op2 = op2.result(cls)
return self.operator(op1, op2)
def __get__(self, instance, owner):
return self.result(owner)
class AuxDict(UserDict):
def __init__(self, *args, _parent, **kwargs):
self.parent = _parent
super().__init__(*args, **kwargs)
def __setitem__(self, item, value):
if isinstance(value, self.parent.reacttypes) and not item.startswith("_"):
value = Reactive(value)
super().__setitem__(item, value)
class MetaReact(type):
reacttypes = (int, float, str, bytes, list, tuple, dict)
def __prepare__(*args, **kwargs):
return AuxDict(_parent=__class__)
def __new__(mcls, name, bases, ns, **kwargs):
pre_registry = {}
cls = super().__new__(mcls, name, bases, ns.data, **kwargs)
#for name, obj in ns.items():
#if isinstance(obj, ReactiveExpr):
#pre_registry[name] = obj
#setattr(cls, name, obj.result()
for name, reactive in pre_registry.items():
_registry[cls, name] = reactive
return cls
def injector(cls, inplace=False, **kwargs):
original = cls
if not inplace:
cls = type(cls.__name__, (cls.__bases__), dict(cls.__dict__))
for name, attr in cls.__dict__.items():
if isinstance(attr, Reactive):
if isinstance(attr, ReactiveExpr) and name in kwargs:
raise AttributeError("Expression attributes can't be modified by injector")
attr.values[cls] = kwargs.get(name, attr.values[original])
return cls
class Base(metaclass=MetaReact):
x = 1
y = 2 * x
And, after pasting the snippet above in a REPL, here is the
result of using injector:
In [97]: Base2 = injector(Base, x=5)
In [98]: Base2.y
Out[98]: 10
The idea is complicated with that aspect that Base class is declared with dependent dynamically evaluated attributes. While we can inspect class's static attributes, I think there's no other way of getting dynamic expression except for parsing the class's sourcecode, find and replace the "injected" attribute name with its value and exec/eval the definition again. But that's the way you wanted to avoid. (moreover: if you expected injector to be unified for all classes).
If you want to proceed to rely on dynamically evaluated attributes define the dependent attribute as a lambda function.
class Base:
x = 1
y = lambda: 2 * Base.x
Base.x = 2
print(Base.y()) # 4
Please guide to an explain of the difference between
object = class()
and
var = class method returning a class:
class Countsome(object):
#classmethod
def get(cls, x, y):
self = cls()
sum = self.add2(x, y)
print sum
return cls
def add2(self, x, y):
sum = x+y
return sum
xyz = Countsome.get(5, 9)
==========================================
class CountSome(object):
def __init__(self):
pass
def add2(self, x, y):
sum = x+y
print sum
xyz = CountSome()
xyz.add2(5, 9)
Looking to understand where I should use one, I am just printing the sum so not returning, so please assume I am asking this question for these kind of tasks(where returning results like sum is not important).
And looking for answers like, which one would be efficient, when.
What are the benefits of each and scenarios best suited for each. Guide to a source if possible
You kinda get it wrong. classmethod should be use when you need to perform action that doesn't need an instance but does need the cls object:
A class method receives the class as implicit first argument, just like an instance method receives the instance.
For example, if you have a COUNTER object in your class which counts how many instances were instantiated.
The second code is actually using staticmethod; that is a method defined in a class but don't need access to any class / instance attributes. staticmethod can be defined outside of a class but resides in it for convenience
This question already has answers here:
Why do you need explicitly have the "self" argument in a Python method? [duplicate]
(10 answers)
Closed 6 years ago.
Consider this code:
class example(object):
def __init__ (): # No self
test() # No self
def test(x,y): # No self
return x+y
def test1(x,y): # No self
return x-y
print(example.test(10,5))
print(example.test1(10,5))
15
5
This works as expected. I believe I can write a whole program not using self. What am I missing? What is this self; why is it needed in some practical way?
I have read a lot about it - (stack, Python documentation), but I just don't understand why it's needed, since I can obviously create a program without it.
You can perfectly create a program without it. But then you'd be missing one of the key features of classes. If you can do without self, I'd argue you can do without classes and just do something purely with functions :)
Classes allow you to create objects which have a PROPERTY associated to them, and self allows you to access those values. So say you have a square.
g code:
class Square(object):
def __init__ (self, length, height):
self.length = length # THIS square's length, not others
self.height = height # THIS square's height, not other
def print_length_and_height(self):
print(self.length, self.height) # THIS square's length and height
square1 = Square(2,2)
square2 = Square(4,4)
square1.print_length_and_height() # 2 2
square2.print_length_and_height() # 4 4
Now, this example is quite silly, of course, but i think it shows what SELF specifically is for: it refers to the particular instance of an object.
By all means, if you don't see the point to it, just do away with classes and just use functions, there nothing wrong with that.
You haven't utilised a class or object properly. Cutting out the garbage code, your program reduces to:
def test(x,y): #No class
return x+y
def test1(x,y): #No class
return x-y
print(example.test(10,5))
print(example.test1(10,5))
Output:
15
5
Your "class" is no more useful than if you wrapped your program in the nested structures:
if True:
for i in range(1):
...
A proper object will have attributes (data fields) and functions that operate on that data (see below). Your code has an empty object; hence, you have nothing on which to operate, no need for self, and no need for a class at all.
Rather, use a class when you need to encapsulate a data representation and associated operations. Below, I've reused some of your code to make example do some trivial complex number work. There are many extensions and improvements to make in this; I kept it relatively close to your original work.
class example(object):
def __init__(self, a, b):
self.a = a
self.b = b
def __repr__(self):
sign = ' + ' if self.b >= 0 else ' - '
return str(self.a) + sign + str(abs(self.b)) + 'i'
def add(self, x):
self.a += x.a
self.b += x.b
def sub(self, x):
self.a -= x.a
self.b -= x.b
complex1 = example(10, 5)
complex2 = example(-3, 2)
complex1.add(complex2)
print(complex1)
complex2.sub(complex1)
print(complex2)
Output:
7 + 7i
-10 - 5i
Are you familiar with Object-Oriented Paradigm?
If you don't you should check it. Python is a Object-Oriented Language and self lets you define your object properties.
An example:
You have a class named Vehicle. A vehicle could be a bike, a car, even a plane. So something you can include is a name and a type.
class Vehicle():
def init(self, name, type): # Constructor
self.name = name
self.type = type
def info(self):
print("I'm a ")
print(self.name)
That's all, now you have a vehicle with name and type. Every instance of Vehicle would have a name and a type different or not and every intance can access its own variables. I'm sorry I can't explain it better. Firstable you need to know Object-Oriented Paradigm knowledge. Please comment my answer if you have doubts & I'll answer you or give a link where it comes explained better.
Suppose you have two classes, A and B. Class B is defined inside the class A. I want to access the variables and methods of the outer class while inside the inner class. The code here is a toy example but has the essentials of what I want to demonstrate:
class A:
a = 'even'
b = 'odd'
class B:
def __init__(self, n):
if n%2 == 0: self.num = a
if n%2 == 1: self.num = b
self.description = A.desc()
def __getitem__(self, i):
return self.B(i)
def desc(self):
return a + '-' + b
>>> c = A()
>>> d = c[4]
>>> TypeError: unbound method desc() must be called with A instance as first argument (got nothing instead)
Here the method desc does some work on the variables of the class A and produces output. Class A is initialized correctly and you can access the variables a and b, even from the inner scope, given that you don't define the description variable. However, I cannot find a way to call the outer scope class methods desc. Is it possible to use the method desc in B without instantiating class A?
Explanation on why I use such a pattern:
Variables a and b in my program are rather big. I only need to initialize them once. In addition, I don't want these variables to float around in the program but to be only accessible to the inner class. Adding to all these is the fact that I can use the A.__getitem__ to extract 'slices' of the big data when needed. So the outer class provides me with hiding/encapsulation of the data, the indexing operator (through __getitem__) and all the routines required for extraction of slices of data (here the method desc. The inner class, B, provides the bundling of useful information from the big data for each index. This, most likely, is not the optimal design for achieving the described task. I am open and eager to hear your opinion regarding the alternative patterns.
I can't see any reason for you to be using classes here, let alone nested ones. In any case, there is almost never a reason to nest classes in Python, since inner classes don't get any special access to the outer class.
However if you want to allow anything to access a method without instantiating the object, you can make it a classmethod:
#classmethod
def desc(self):
return a + '-' + b
But I can't see why you would do any of this. Also, nothing here is a closure.
The Question
I want to be able to initialize an object with a function that references the instance's attributes. What I want I tried to capture in this snippet, which produces a NameError: "global name 'self' is not defined":
class Test(object):
def __init__(self, function = None):
self.dicty = {1:{'height': 4, 'width': 2}, 2:{'height': 1, 'width': 2} }
if function == None:
self.function = lambda x : self.dicty[x]['height']
else:
self.function = function
if __name__ == '__main__':
def func1(x):
return self.dicty[x]['width']
def func2(x):
return self.dicty[x]['width']**2
G = Test(function = func1)
H = Test(function = func2)
I could solve the problem by creating a bunch of subclasses to Test, but that doesn't seem readable.
The Motivation
I am using NetworkX to do Python modeling and experiments. I was looking at the classic Albert-Barabasi Model and creating subclasses of the DiGraph class that included a Preference(self, node), Attachment(self, parent, child), and then a Grow(self, max_allowable_nodes). Instead of creating a whole bunch of subclasses like I mentioned before, I would love to be able to create an instance that modifies preference(). This would allow me to run numerical experiments without my code looking too much like Frankenstein. Looking forward to learning something new.
Edit:
Didn't know about the types class or the general idea of reflection. Obviously, still pretty new here. Really appreciate everyone answering my questions and pointing me in the right direction!
Given that the lambda you create in your __init__ refers to the instance (self), it looks like you want to attach a method to your instance, whereas here you're attaching a function. You need to create a method from the function and attach it to the instance:
import types
class Test(object):
def __init__(self, function = None):
self.dicty = {1:{'height': 4, 'width': 2}, 2:{'height': 1, 'width': 2} }
if function == None:
function = lambda self, x: self.dicty[x]['height']
self.function = types.MethodType(function, self)
A method is basically a function that is always passed the instance as the first argument, so you need to ensure any function you pass into your initialiser has self as the initial argument.
>>> t1 = Test()
>>> t1.function(1)
4
>>> t2 = Test(lambda self, x: self.dicty[x]['width'])
>>> t2.function(1)
2
When you define func1, there is no such thing as self. It's not an argument to the function, and it's not in any higher scope.
You could, instead, define a function that takes the dict you use as an argument and operates on that. In the Test class, you can then call the function on self.dicty. This would require you to change your lambda to also take dicty and x instead of just x.
def func1(dicty, x):
return dicty[x]['width']
...and in Test...
class Test(object):
# ... current code but with lambda tweak:
# lambda dicty, x: dicty[x]['height']
def do_something(self, x):
self.function(self.dicty, x)
Without seeing the rest of your code, it's hard to know what further simplifications you could make. But since all the functions seem to be using dicty[x] anyway, you could just write them to take that directly.