I've been going through all the Stackoverflow answers on dynamic property setting, but for whatever reason I can't seem to get this to work.
I have a class, Evolution_Base, that in its init creates an instance of Value_Differences. Value_Differences should be dynamically creating properties, based on the list I pass, that returns the function value from _get_df_change:
from pandas import DataFrame
from dataclasses import dataclass
import pandas as pd
class Evolution_Base():
def __init__(self, res_date_0 : DataFrame , res_date_1 : DataFrame):
#dataclass
class Results_Data():
res_date_0_df : DataFrame
res_date_1_df : DataFrame
self.res = Results_Data(res_date_0_df= res_date_0,
res_date_1_df= res_date_1)
property_list = ['abc', 'xyz']
self.difference = Value_Differences(parent = self, property_list=property_list)
# Shared Functions
def _get_df_change(self, df_name, operator = '-'):
df_0 = getattr(self.res.res_date_0_df, df_name.lower())
df_1 = getattr(self.res.res_date_1_df, df_name.lower())
return self._df_change(df_1, df_0, operator=operator)
def _df_change(self, df_1 : pd.DataFrame, df_0 : pd.DataFrame, operator = '-') -> pd.DataFrame:
"""
Returns df_1 <operator | default = -> df_0
"""
# is_numeric mask
m_1 = df_1.select_dtypes('number')
m_0 = df_0.select_dtypes('number')
def label_me(x):
x.columns = ['t_1', 't_0']
return x
if operator == '-':
return label_me(df_1[m_1] - df_0[m_0])
elif operator == '+':
return label_me(df_1[m_1] + df_0[m_0])
class Value_Differences():
def __init__(self, parent : Evolution_Base, property_list = []):
self._parent = parent
for name in property_list:
def func(self, prop_name):
return self._parent._get_df_change(name)
# I've tried the following...
setattr(self, name, property(fget = lambda cls_self: func(cls_self, name)))
setattr(self, name, property(func(self, name)))
setattr(self, name, property(func))
Its driving me nuts... Any help appreciated!
My desired outcome is for:
evolution = Evolution_Base(df_1, df_2)
evolution.difference.abc == evolution._df_change('abc')
evolution.difference.xyz == evolution._df_change('xyz')
EDIT: The simple question is really, how do I setattr for a property function?
As asked
how do I setattr for a property function?
To be usable as a property, the accessor function needs to be wrapped as a property and then assigned as an attribute of the class, not the instance.
That function, meanwhile, needs to have a single unbound parameter - which will be an instance of the class, but is not necessarily the current self. Its logic needs to use the current value of name, but late binding will be an issue because of the desire to create lambdas in a loop.
A clear and simple way to work around this is to define a helper function accepting the Value_Differences instance and the name to use, and then bind the name value eagerly.
Naively:
from functools import partial
def _get_from_parent(name, instance):
return instance._parent._get_df_change(name)
class Value_Differences:
def __init__(self, parent: Evolution_Base, property_list = []):
self._parent = parent
for name in property_list:
setattr(Value_Differences, name, property(
fget = partial(_get_from_parent, name)
))
However, this of course has the issue that every instance of Value_Differences will set properties on the class, thus modifying what properties are available for each other instance. Further, in the case where there are many instances that should have the same properties, the setup work will be repeated at each instance creation.
The apparent goal
It seems that what is really sought, is the ability to create classes dynamically, such that a list of property names is provided and a corresponding class pops into existence, with code filled in for the properties implementing a certain logic.
There are multiple approaches to this.
Factory A: Adding properties to an instantiated template
Just like how functions can be nested within each other and the inner function will be an object that can be modified and returned (as is common when creating a decorator), a class body can appear within a function and a new class object (with the same name) is created every time the function runs. (The code in the OP already does this, for the Results_Data dataclass.)
def example():
class Template:
pass
return Template
>>> TemplateA, TemplateB = example(), example()
>>> TemplateA is TemplateB
False
>>> isinstance(TemplateA(), TemplateB)
False
>>> isinstance(TemplateB(), TemplateA)
False
So, a "factory" for value-difference classes could look like
from functools import partial
def _make_value_comparer(property_names, access_func):
class ValueDifferences:
def __init__(self, parent):
self._parent = parent
for name in property_names:
setattr(Value_Differences, name, property(
fget = partial(access_func, name)
))
return ValueDifferences
Notice that instead of hard-coding a helper, this factory expects to be provided with a function that implements the access logic. That function takes two parameters: a property name, and the ValueDifferences instance. (They're in that order because it's more convenient for functools.partial usage.)
Factory B: Using the type constructor directly
The built-in type in Python has two entirely separate functions.
With one argument, it discloses the type of an object.
With three arguments, it creates a new type. The class syntax is in fact syntactic sugar for a call to this builtin. The arguments are:
a string name (will be set as the __name__ attribute)
a list of classes to use as superclasses (will be set as __bases__)
a dict mapping attribute names to their values (including methods and properties - will become the __dict__, roughly)
In this style, the same factory could look something like:
from functools import partial
def _make_value_comparer(property_names, access_func):
methods = {
name: property(fget = partial(access_func, name)
for name in property_names
}
methods['__init__'] = lambda self, parent: setattr(self, '_parent', parent)
return type('ValueDifferences', [], methods)
Using the factory
In either of the above cases, EvolutionBase would be modified in the same way.
Presumably, every EvolutionBase should use the same ValueDifferences class (i.e., the one that specifically defines abc and xyz properties), so the EvolutionBase class can cache that class as a class attribute, and use it later:
class Evolution_Base():
def _get_from_parent(name, mvd):
# mvd._parent will be an instance of Evolution_Base.
return mvd._parent._get_df_change(name)
_MyValueDifferences = _make_value_comparer(['abc', 'xyz'], _get_from_parent)
def __init__(self, res_date_0 : DataFrame , res_date_1 : DataFrame):
#dataclass
class Results_Data():
res_date_0_df : DataFrame
res_date_1_df : DataFrame
self.res = Results_Data(res_date_0_df= res_date_0,
res_date_1_df= res_date_1)
self.difference = _MyValueDifferences(parent = self)
Notice that the cached _MyValueDifferences class no longer requires a list of property names to be constructed. That's because it was already provided when the class was created. The actual thing that varies per instance of _MyValueDifferences, is the parent, so that's all that gets passed.
Simpler approaches
It seems that the goal is to have a class whose instances are tightly associated with instances of Evolution_Base, providing properties specifically named abc and xyz that are computed using the Evolution_Base's data.
That could just be hard-coded as a nested class:
class Evolution_Base:
class EBValueDifferences:
def __init__(self, parent):
self._parent = parent
#property
def abc(self):
return self._parent._get_df_change('abc')
#property
def xyz(self):
return self._parent._get_df_change('xyz')
def __init__(self, res_date_0 : DataFrame , res_date_1 : DataFrame):
#dataclass
class Results_Data():
res_date_0_df : DataFrame
res_date_1_df : DataFrame
self.res = Results_Data(res_date_0_df = res_date_0,
res_date_1_df = res_date_1)
self.difference = EBValueDifferences(self)
# _get_df_change etc. as before
Even simpler, provide corresponding properties directly on Evolution_Base:
class Evolution_Base:
#property
def abc_difference(self):
return self._get_df_change('abc')
#property
def xyz_difference(self):
return self._get_df_change('xyz')
def __init__(self, res_date_0 : DataFrame , res_date_1 : DataFrame):
#dataclass
class Results_Data():
res_date_0_df : DataFrame
res_date_1_df : DataFrame
self.res = Results_Data(res_date_0_df = res_date_0,
res_date_1_df = res_date_1)
# _get_df_change etc. as before
# client code now calls my_evolution_base.abc_difference
# instead of my_evolution_base.difference.abc
If there are a lot of such properties, they could be attached using a much simpler dynamic approach (that would still be reusable for other classes that define a _get_df_change):
def add_df_change_property(name, cls):
setattr(
cls, f'{name}_difference',
property(fget = lambda instance: instance._get_df_change(name))
)
which can also be adapted for use as a decorator:
from functools import partial
def exposes_df_change(name):
return partial(add_df_change_property, name)
#exposes_df_change('abc')
#exposes_df_change('def')
class Evolution_Base:
# `self.difference` can be removed, no other changes needed
This is quite the rabbit hole. Impossible is a big call, but I will say this: they don't intend you to do this. The 'Pythonic' way of achieving your example use case is the __getattr__ method. You could also override the __dir__ method to insert your custom attributes for discoverability.
This is the code for that:
class Value_Differences():
def __init__(self, parent : Evolution_Base, property_list = []):
self._parent = parent
self._property_list = property_list
def __dir__(self):
return sorted(set(
dir(super(Value_Differences, self)) + \
list(self.__dict__.keys()) + self._property_list))
def __getattr__(self, __name: str):
if __name in self._property_list:
return self._parent._get_df_change(__name)
But that wasn't the question, and respect for a really, really interesting question. This is one of those things that you look at and say 'hmm, should be possible' and can get almost to a solution. I initially thought what you asked for was technically possible, just very hacky to achieve. But it turns out that it would be very, very weird hackery if it was possible.
Two small foundational things to start with:
Remind ourselves of the hierarchy of Python objects that the runtime is working with when defining and instantiating classes:
The metaclass (defaulting to type), which is used to build classes. I'm going to refer to this as the Metaclass Type Object (MTO).
The class definition, which is used to build objects. I'm going to refer to this as the Class Type Object (CTO).
And the class instance or object, which I'll refer to as the Class Instance Object (CIO).
MTOs are subclasses of type. CTOs are subclasses of object. CIOs are instances of CTOs, but instantiated by MTOs.
Python runs code inside class definitions as if it was running a function:
class Class1:
print("1")
def __init__(self, v1):
print("4")
print("2")
print("3")
c1 = Class1("x")
print("5")
gives 1, 2, 3, 4, 5
Put these two things together with:
class Class1:
def attr1_get(self):
return 'attr1 value'
attr1 = property(attr1_get)
we are defining a function attr1_get as part of the class definition. We are then running an inline piece of code that creates an object of type property. Note that this is just the name of the object's type - it isn't a property as you would describe it. Just an object with some attributes, being references to various functions. We then assign that object to an attribute in the class we are defining.
In the terms I used above, once that code is run we have a CTO instantiated as an object in memory that contains an attribute attr1 of type property (an object subclass, containing a bunch of attributes itself - one of which is a reference to the function attr1_get).
That can be used to instantiate an object, the CIO.
This is where the MTO comes in. You instantiate the property object while defining the CTO so that when the runtime applies the MTO to create the CIO from the CTO, an attribute on the CIO will be formed with a custom getter function for that attribute rather than the 'standard' getter function the runtime would use. The property object means something to the type object when it is building a new object.
So when we run:
c1 = Class1()
we don't get a CIO c1 with an attribute attr1 that is an object of type property. The metaclass of type type formed a set of references against the attribute's internal state to all the functions we stored in the property object. Note that this is happening inside the runtime, and you can't call this directly from your code - you just tell the type metaclass to do it by using the property wrapper object.
So if you directly assign a property() result to an attribute of a CIO, you have a Pythonic object assigned that references some functions, but the internal state for the runtime to use to reference the getter, setter, etc. is not set up. The getter of an attribute that contains a property object is the standard getter and so returns the object instance, and not the result of the functions it wraps,
This next bit of code demonstrates how this flows:
print("Let's begin")
class MetaClass1(type):
print("Starting to define MetaClass1")
def __new__(cls, name, bases, dct):
x = super().__new__(cls, name, bases, dct)
print("Metaclass1 __new__({})".format(str(cls)))
return x
print("__new__ of MetaClass1 is defined")
def __init__(cls, name, bases, dct):
print("Metaclass1 __init__({})".format(str(cls)))
print("__init__ of MetaClass1 is defined")
print("Metaclass is defined")
class Class1(object,metaclass=MetaClass1):
print("Starting to define Class1")
def __new__(cls, *args, **kwargs):
print("Class1 __new__({})".format(str(cls)))
return super(Class1, cls).__new__(cls, *args, **kwargs)
print("__new__ of Class1 is defined")
def __init__(self):
print("Class1 __init__({})".format(str(self)))
print("__init__ of Class1 is defined")
def g1(self):
return 'attr1 value'
print("g1 of Class1 is defined")
attr1 = property(g1)
print("Class1.attr1 = ", attr1)
print("attr1 of Class1 is defined")
def addProperty(self, name, getter):
setattr(self, name, property(getter))
print("self.", name, " = ", getattr(self, name))
print("addProperty of Class1 is defined")
print("Class is defined")
c1 = Class1()
print("Instance is created")
print(c1.attr1)
def g2(cls):
return 'attr2 value'
c1.addProperty('attr2', g2)
print(c1.attr2)
I have put all those print statements there to demonstrate the order in which things happen very clearly.
In the middle, you see:
g1 of Class1 is defined
Class1.attr1 = <property object at 0x105115c10>
attr1 of Class1 is defined
We have created an object of type property and assigned it to a class attribute.
Continuing:
addProperty of Class1 is defined
Metaclass1 __new__(<class '__main__.MetaClass1'>)
Metaclass1 __init__(<class '__main__.Class1'>)
Class is defined
The metaclass got instantiated, being passed first itself (__new__) and then the class it will work on (__init__). This happened right as we stepped out of the class definition. I have only included the metaclass to show what will happen with the type metaclass by default.
Then:
Class1 __new__(<class '__main__.Class1'>)
Class1 __init__(<__main__.Class1 object at 0x105124c10>)
Instance is created
attr1 value
self. attr2 = <property object at 0x105115cb0>
<property object at 0x105115cb0>
Class1 is instantiated, providing first its type to __new__ and then its instance to __init__.
We see that attr1 is instantiated properly, but attr2 is not. That is because setattr is being called once the class instance is already constructed and is just saying attr2 is an instance of the class property and not defining attr2 as the actual runtime construct of a property.
Which is made more clear if we run:
print(c1.attr2.fget(c1))
print(c1.attr1.fget(c1))
attr2 (a property object) isn't aware of the class or instance of the containing attribute's parent. The function it wraps still needs to be given the instance to work on.
attr1 doesn't know what to do with that, because as far as it is concerned it is a string object, and has no concept of how the runtime is mapping its getter.
The fundamental reason why what you tried doesn't work is that a property, a use case of a descriptor, by design must be stored as a class variable, not as an instance attribute.
Excerpt from the documentation of descriptor:
To use the descriptor, it must be stored as a class variable in
another class:
To create a class with dynamically named properties that has access to a parent class, one elegant approach is to create the class within a method of the main class, and use setattr to create class attributes with dynamic names and property objects. A class created in the closure of a method automatically has access to the self object of the parent instance, avoiding having to manage a clunky _parent attribute like you do in your attempt:
class Evolution_Base:
def __init__(self, property_list):
self.property_list = property_list
self._difference = None
#property
def difference(self):
if not self._difference:
class Value_Differences:
pass
for name in self.property_list:
# use default value to store the value of name in each iteration
def func(obj, prop_name=name):
return self._get_df_change(prop_name) # access self via closure
setattr(Value_Differences, name, property(func))
self._difference = Value_Differences()
return self._difference
def _get_df_change(self, df_name):
return f'df change of {df_name}' # simplified return value for demo purposes
so that:
evolution = Evolution_Base(['abc', 'xyz'])
print(evolution.difference.abc)
print(evolution.difference.xyz)
would output:
df change of abc
df change of xyz
Demo: https://replit.com/#blhsing/ExtralargeNaturalCoordinate
Responding directly to your question, you can create a class:
class FooBar:
def __init__(self, props):
def make_prop(name):
return property(lambda accessor_self: self._prop_impl(name))
self.accessor = type(
'Accessor',
tuple(),
{p: make_prop(p) for p in props}
)()
def _prop_impl(self, arg):
return arg
o = FooBar(['foo', 'bar'])
assert o.accessor.foo == o._prop_impl('foo')
assert o.accessor.bar == o._prop_impl('bar')
Further, it would be beneficiary to cache created class to make equivalent objects more similar and eliminate potential issues with equality comparison.
That said, I am not sure if this is desired. There's little benefit of replacing method call syntax (o.f('a')) with property access (o.a). I believe it can be detrimental on multiple accounts: dynamic properties are confusing, harder to document, etc., finally while none of this is strictly guaranteed in crazy world of dynamic python -- they kind of communicate wrong message: that the access is cheap and does not involve computation and that perhaps you can attempt to write to it.
I think that when you define the function func in the loop, it closes over the current value of the name variable, not the value of the name variable at the time the property is accessed. To fix this, you can use a lambda function to create a closure that captures the value of name at the time the property is defined.
class Value_Differences():
def __init__(self, parent : Evolution_Base, property_list = []):
self._parent = parent
for name in property_list:
setattr(self, name, property(fget = lambda self, name=name: self._parent._get_df_change(name)))
Does this help you ?
The simple question is really, how do I setattr for a property function?
In python we can set dynamic attributes like this:
class DynamicProperties():
def __init__(self, property_list):
self.property_list = property_list
def add_properties(self):
for name in self.property_list:
setattr(self.__class__, name, property(fget=lambda self: 1))
dync = DynamicProperties(['a', 'b'])
dync.add_properties()
print(dync.a) # prints 1
print(dync.b) # prints 1
Correct me if I am wrong but from reviewing your code, you want to create a dynamic attributes then set their value to a specific function call within the same class, where the passed in data is passed in attributes in the constructor " init " this is achievable, an example:
class DynamicProperties():
def __init__(self, property_list, data1, data2):
self.property_list = property_list
self.data1 = data1
self.data2 = data2
def add_properties(self):
for name in self.property_list:
setattr(self.__class__, name, property(fget=lambda self: self.change(self.data1, self.data2) ))
def change(self, data1, data2):
return data1 - data2
dync = DynamicProperties(['a', 'b'], 1, 2)
dync.add_properties()
print(dync.a == dync.change(1, 2)) # prints true
print(dync.b == dync.change(1,2)) # prints true
You just have to add more complexity to the member, __getattr__ / __setattr__ gives you the string, so it can be interpreted as needed. The biggest "problem" doing this is that the return might no be consistent and piping it back to a library that expect an object to have a specific behavior can cause soft errors.
This example is not the same as yours, but it has the same concept, manipulate columns with members. To get a copy with changes a set is not needed, with a copy, modify and return, the new instance can be created with whatever needed.
For example, the __getattr__ in this line will:
Check and interpret the string xyz_mull_0
Validate that the members and the operand exists
Make a copy of data_a
Modify the copy and return it
var = data_a.xyz_mull_0()
This looks more complex that it actually is, with the same instance members its clear what it is doing, but the _of modifier needs a callback, this is because the __getattr__ can only have one parameter, so it needs to save the attr and return a callback to be called with the other instance that then will call back to the __getattr__ and complete the rest of the function.
import re
class FlexibleFrame:
operand_mod = {
'sub': lambda a, b: a - b,
'add': lambda a, b: a + b,
'div': lambda a, b: a / b,
'mod': lambda a, b: a % b,
'mull': lambda a, b: a * b,
}
#staticmethod
def add_operand(name, func):
if name not in FlexibleFrame.operand_mod.keys():
FlexibleFrame.operand_mod[name] = func
# This makes this class subscriptable
def __getitem__(self, item):
return self.__dict__[item]
# Uses:
# -> object.value
# -> object.member()
# -> object.<name>_<operand>_<name|int>()
# -> object.<name>_<operand>_<name|int>_<flow>()
def __getattr__(self, attr):
if re.match(r'^[a-zA-Z]+_[a-zA-Z]+_[a-zA-Z0-9]+(_of)?$', attr):
seg = attr.split('_')
var_a, operand, var_b = seg[0:3]
# If there is a _of: the second operand is from the other
# instance, the _of is removed and a callback is returned
if len(seg) == 4:
self.__attr_ref = '_'.join(seg[0:3])
return self.__getattr_of
# Checks if this was a _of attribute and resets it
if self.__back_ref is not None:
other = self.__back_ref
self.__back_ref = None
self.__attr_ref = None
else:
other = self
if var_a not in self.__dict__:
raise AttributeError(
f'No match of {var_a} in (primary) {__class__.__name__}'
)
if operand not in FlexibleFrame.operand_mod.keys():
raise AttributeError(
f'No match of operand {operand}'
)
# The return is a copy of self, if not the instance
# is getting modified making x = a.b() useless
ret = FlexibleFrame(**self.__dict__)
# Checks if the second operand is a int
if re.match(r'^\d+$', var_b) :
ref_b_num = int(var_b)
for i in range(len(self[var_a])):
ret[var_a][i] = FlexibleFrame.operand_mod[operand](
self[var_a][i], ref_b_num
)
elif var_b in other.__dict__:
for i in range(len(self[var_a])):
# out_index = operand[type](in_a_index, in_b_index)
ret[var_a][i] = FlexibleFrame.operand_mod[operand](
self[var_a][i], other[var_b][i]
)
else:
raise AttributeError(
f'No match of {var_b} in (secondary) {__class__.__name__}'
)
# This swaps the .member to a .member()
# it also adds and extra () in __getattr_of
return lambda: ret
# return ret
if attr in self.__dict__:
return self[attr]
raise AttributeError(
f'No match of {attr} in {__class__.__name__}'
)
def __getattr_of(self, other):
self.__back_ref = other
return self.__getattr__(self.__attr_ref)()
def __init__(self, **kwargs):
self.__back_ref = None
self.__attr_ref = None
#TODO: Check if data columns match in size
# if not, implement column_<name>_filler=<default>
for i in kwargs:
self.__dict__[i] = kwargs[i]
if __name__ == '__main__':
data_a = FlexibleFrame(**{
'abc': [i for i in range(10)],
'nmv': [i for i in range(10)],
'xyz': [i for i in range(10)],
})
data_b = FlexibleFrame(**{
'fee': [i + 10 for i in range(10)],
'foo': [i + 10 for i in range(10)],
})
FlexibleFrame.add_operand('set', lambda a, b: b)
var = data_a.xyz_mull_0()
var = var.abc_set_xyz()
var = var.xyz_add_fee_of(data_b)
As a extra thing, lambdas in python have this thing, so it can make difficult using them when self changes.
It seems you're bending the language to do weird things. I'd take it as a smell that your code is probably getting convoluted but I'm not saying there would never be a use-case for it so here is a minimal example of how to do it:
class Obj:
def _df_change(self, arg):
print('change', arg)
class DynAttributes(Obj):
def __getattr__(self, name):
return self._df_change(name)
class Something:
difference = DynAttributes()
a = Something()
b = Obj()
assert a.difference.hello == b._df_change('hello')
When calling setattr , use self.__class__ instead of self
Code sample:
class A:
def __init__(self,names : List[str]):
for name in names:
setattr(self.__class__,name,property(fget=self.__create_getter(name)))
def __create_getter(self,name: str):
def inner(self):
print(f"invoking {name}")
return 10
return inner
a = A(['x','y'])
print(a.x + 1)
print(a.y + 2)
I am using python and have an object, that object has a method. I am looking for a simple way, to replace the entire object from within that function.
E.g
class a():
def b(self):
self = other_object
How can you do that?
Thanks
You use a proxy/facade object to hold a reference to the actual object, the self if you wish and that proxy (better term than Facade, but not changing my code now) is what the rest of your codebase sees. However, any attribute/method access is forwarded on to the actual object, which is swappable.
Code below should give you a rough idea. Note that you need to be careful about recursion around __the_instance, which is why I am assigning to __dict__ directly. Bit messy, since it's been a while I've written code that wraps getattr and setattr entirely.
class Facade:
def __init__(self, instance):
self.set_obj(instance)
def set_obj(self, instance):
self.__dict__["__theinstance"] = instance
def __getattr__(self, attrname):
if attrname == "__theinstance":
return self.__dict__["__theinstance"]
return getattr(self.__dict__["__theinstance"], attrname)
def __setattr__(self, attrname, value):
if attrname == "__theinstance":
self.set_obj(value)
return setattr(self.__dict__["__theinstance"], attrname, value)
class Test:
def __init__(self, name, cntr):
self.name = name
self.cntr = cntr
def __repr__(self):
return "%s[%s]" % (self.__class__.__name__, self.__dict__)
obj1 = Test("first object", 1)
obj2 = Test("second", 2)
obj2.message = "greetings"
def pretend_client_code(facade):
print(id(facade), facade.name, facade.cntr, getattr(facade, "value", None))
facade = Facade(obj1)
pretend_client_code(facade)
facade.set_obj(obj2)
pretend_client_code(facade)
facade.value = 3
pretend_client_code(facade)
facade.set_obj(obj1)
pretend_client_code(facade)
output:
4467187104 first object 1 None
4467187104 second 2 None
4467187104 second 2 3
4467187104 first object 1 None
So basically, the "client code" always sees the same facade object, but what it is actually accessing depends on what your equivalent of def b is has done.
Facade has a specific meaning in Design Patterns terminology and it may not be really applicable here, but close enough. Maybe Proxy would have been better.
Note that if you want to change the class on the same object, that is a different thing, done through assigning self.__class__ . For example, say an RPG game with an EnemyClass who gets swapped to DeadEnemyClass once killed: self.__class__ = DeadEnemyClass
You can't directly do that. What you can do is save it as an instance variable.
class A():
def __init__(self, instance=None):
self.instance = val or self
# yes, you can make it a property as well.
def set_val(self, obj):
self.instance = obj
def get_val(self):
return self.instance
It is unlikely that replacing the 'self' variable will accomplish
whatever you're trying to do, that couldn't just be accomplished by
storing the result of func(self) in a different variable. 'self' is
effectively a local variable only defined for the duration of the
method call, used to pass in the instance of the class which is being
operated upon. Replacing self will not actually replace references to
the original instance of the class held by other objects, nor will it
create a lasting reference to the new instance which was assigned to
it.
Original source: Is it safe to replace a self object by another object of the same type in a method?
One of my classes does a lot of aggregate calculating on a collection of objects, then assigns an attribute and value appropriate to the specific object: I.e.
class Team(object):
def __init__(self, name): # updated for typo in code, added self
self.name = name
class LeagueDetails(object):
def __init__(self): # added for clarity, corrected another typo
self.team_list = [Team('name'), ...]
self.calculate_league_standings() # added for clarity
def calculate_league_standings(self):
# calculate standings as a team_place_dict
for team in self.team_list:
team.place = team_place_dict[team.name] # a new team attribute
I know, as long as the calculate_league_standings has been run, every team has team.place. What I would like to be able to do is to scan the code for class Team(object) and read all the attributes, both created by class methods and also created by external methods which operate on class objects. I am getting a little sick of typing for p in dir(team): print p just to see what the attribute names are. I could define a bunch of blank attributes in the Team __init__. E.g.
class Team(object):
def __init__(self, name): # updated for typo in code, added self
self.name = name
self.place = None # dummy attribute, but recognizable when the code is scanned
It seems redundant to have calculate_league_standings return team._place and then add
#property
def place(self): return self._place
I know I could comment a list of attributes at the top class Team, which is the obvious solution, but I feel like there has to be a best practice here, something pythonic and elegant here.
If I half understand your question, you want to keep track of which attributes of an instance have been added after initialization. If this is the case, you could use something like this:
#! /usr/bin/python3.2
def trackable (cls):
cls._tracked = {}
oSetter = cls.__setattr__
def setter (self, k, v):
try: self.initialized
except: return oSetter (self, k, v)
try: self.k
except:
if not self in self.__class__._tracked:
self.__class__._tracked [self] = []
self.__class__._tracked [self].append (k)
return oSetter (self, k, v)
cls.__setattr__ = setter
oInit = cls.__init__
def init (self, *args, **kwargs):
o = oInit (self, *args, **kwargs)
self.initialized = 42
return o
cls.__init__ = init
oGetter = cls.__getattribute__
def getter (self, k):
if k == 'tracked': return self.__class__._tracked [self]
return oGetter (self, k)
cls.__getattribute__ = getter
return cls
#trackable
class Team:
def __init__ (self, name, region):
self.name = name
self.region = region
#set name and region during initialization
t = Team ('A', 'EU')
#set rank and ELO outside (hence trackable)
#in your "aggregate" functions
t.rank = 4 # a new team attribute
t.ELO = 14 # a new team attribute
#see witch attributes have been created after initialization
print (t.tracked)
If I did not understand the question, please do specify which part I got wrong.
Due to Python's dynamic nature, I don't believe there is a general answer to your question. An attribute of an instance can be set in many ways, including pure assignment, setattr(), and writes to __dict__ . Writing a tool to statically analyze Python code and correctly determine all possible attributes of an class by analyzing all these methods would be very difficult.
In your specific case, as the programmer you know that class Team will have a place attribute in many instances, so you can decide to be explicit and write its constructor like so:
class Team(object):
def __init__(name ,place=None):
self.name = name
self.place = place
I would say there is no need to define a property of a simple attribute, unless you wanted side effects or derivations to happen at read or write time.
I have no idea what is wrong! This is a very simple program and I have done a lot head banging! Please someone enlighten me!
This a lab problem from the CSE 111 - Programming Language II course. They teach Java at the university and the code I wrote in Java works fine.
I just have to create a Student class with some fields to hold the basic information about a student with methods to get and set the attributes. Then create an instance of that class and tryout the methods.
But every time I run this program the following error occurs:
TypeError: set_name() takes exactly 1 positional argument (2 given)
Here is the code I wrote.
class Student:
'''Student class'''
name = None
id = 0
address = None
cgpa = None
def get_name():
return name
def set_name(n):
name = n
def get_id():
return id
def set_id(i):
id = i
def get_address():
return address
def set_address(a):
address = a
def get_cgpa():
return cgpa
def set_cgpa(c):
cgpa = c
#An object of Student class
jack = Student()
jack.set_name('jacky')
print(jack.get_name())
You're not accepting a reference to your instance as the first argument to that method, i.e. your set_name() should be written:
def set_name(self, n):
self.name = n
This is somewhat different from other languages where there is a built-in keyword (such as this) that refers to the current object. Python passes that reference explicitly, as an argument to the method.
All your other methods must be modified similarly.
Note that just setting name = n sets a local variable name which goes away when the method ends; it does not set anything on the instance. You have to explicitly set self.name if you want an instance attribute.
Also, and this is a matter of style, but you do not usually write set and get methods in Python. It is normal practice to set and get attributes directly. If you want to do validation of values, use a property instead. So basically, none of your methods are actually necessary in good style.
However, you don't have an __init__() method. Usually you would pass the desired attributes of the instance when instantiating the class and save these on the instance.
class Student:
def __init__(self, name, id, address, cgpa):
self.name = name
self.id = id
self.address = address
self.cgpa = cgpa
herman = Student("Herman Munster", 12345, "1313 Mockingbird Lane", 4.0)
Try this:
import sys
class Student:
'''Student class'''
self.name = None
self.id = 0
self.address = None
self.cgpa = None
def get_name(self):
return self.name
def set_name(self, n):
self.name = n
def get_id(self):
return self.id
def set_id(self, i):
self.id = i
def get_address(self):
return self.address
def set_address(self, a):
self.address = a
def get_cgpa(self):
return self.cgpa
def set_cgpa(self, c):
self.cgpa = c
You need to pass self as the first argument to each member function of the class. Member variables must then be referred to with self, i.e. self.name. Furthermore, you may wish to include an __init__() function; this serves usually to initialize any member variables, and is called at the instantiation of the class.
Take a look at the Python documentation here for some examples on well-formed classes: http://docs.python.org/tutorial/classes.html#random-remarks
In Python, you need to pass in self for each of your member functions. You also need to reference class variables as self.x, if you want them to take an effect.
Here are a couple examples that you need to apply to the rest of your code.
def set_name(self, n):
self.name = n
def get_cgpa(self):
return self.cgpa
There is some explanation for why this is the case in the documentation.
This is because first argument of methods is self - the class instance.
See What is the purpose of self?
and http://docs.python.org/tutorial/classes.html#class-objects
I would like to replace an object instance by another instance inside a method like this:
class A:
def method1(self):
self = func(self)
The object is retrieved from a database.
It is unlikely that replacing the 'self' variable will accomplish whatever you're trying to do, that couldn't just be accomplished by storing the result of func(self) in a different variable. 'self' is effectively a local variable only defined for the duration of the method call, used to pass in the instance of the class which is being operated upon. Replacing self will not actually replace references to the original instance of the class held by other objects, nor will it create a lasting reference to the new instance which was assigned to it.
As far as I understand, If you are trying to replace the current object with another object of same type (assuming func won't change the object type) from an member function. I think this will achieve that:
class A:
def method1(self):
newObj = func(self)
self.__dict__.update(newObj.__dict__)
It is not a direct answer to the question, but in the posts below there's a solution for what amirouche tried to do:
Python object conversion
Can I dynamically convert an instance of one class to another?
And here's working code sample (Python 3.2.5).
class Men:
def __init__(self, name):
self.name = name
def who_are_you(self):
print("I'm a men! My name is " + self.name)
def cast_to(self, sex, name):
self.__class__ = sex
self.name = name
def method_unique_to_men(self):
print('I made The Matrix')
class Women:
def __init__(self, name):
self.name = name
def who_are_you(self):
print("I'm a women! My name is " + self.name)
def cast_to(self, sex, name):
self.__class__ = sex
self.name = name
def method_unique_to_women(self):
print('I made Cloud Atlas')
men = Men('Larry')
men.who_are_you()
#>>> I'm a men! My name is Larry
men.method_unique_to_men()
#>>> I made The Matrix
men.cast_to(Women, 'Lana')
men.who_are_you()
#>>> I'm a women! My name is Lana
men.method_unique_to_women()
#>>> I made Cloud Atlas
Note the self.__class__ and not self.__class__.__name__. I.e. this technique not only replaces class name, but actually converts an instance of a class (at least both of them have same id()). Also, 1) I don't know whether it is "safe to replace a self object by another object of the same type in [an object own] method"; 2) it works with different types of objects, not only with ones that are of the same type; 3) it works not exactly like amirouche wanted: you can't init class like Class(args), only Class() (I'm not a pro and can't answer why it's like this).
Yes, all that will happen is that you won't be able to reference the current instance of your class A (unless you set another variable to self before you change it.) I wouldn't recommend it though, it makes for less readable code.
Note that you're only changing a variable, just like any other. Doing self = 123 is the same as doing abc = 123. self is only a reference to the current instance within the method. You can't change your instance by setting self.
What func(self) should do is to change the variables of your instance:
def func(obj):
obj.var_a = 123
obj.var_b = 'abc'
Then do this:
class A:
def method1(self):
func(self) # No need to assign self here
In many cases, a good way to achieve what you want is to call __init__ again. For example:
class MyList(list):
def trim(self,n):
self.__init__(self[:-n])
x = MyList([1,2,3,4])
x.trim(2)
assert type(x) == MyList
assert x == [1,2]
Note that this comes with a few assumptions such as the all that you want to change about the object being set in __init__. Also beware that this could cause problems with inheriting classes that redefine __init__ in an incompatible manner.
Yes, there is nothing wrong with this. Haters gonna hate. (Looking at you Pycharm with your in most cases imaginable, there's no point in such reassignment and it indicates an error).
A situation where you could do this is:
some_method(self, ...):
...
if(some_condition):
self = self.some_other_method()
...
return ...
Sure, you could start the method body by reassigning self to some other variable, but if you wouldn't normally do that with other parametres, why do it with self?
One can use the self assignment in a method, to change the class of instance to a derived class.
Of course one could assign it to a new object, but then the use of the new object ripples through the rest of code in the method. Reassiging it to self, leaves the rest of the method untouched.
class aclass:
def methodA(self):
...
if condition:
self = replace_by_derived(self)
# self is now referencing to an instance of a derived class
# with probably the same values for its data attributes
# all code here remains untouched
...
self.methodB() # calls the methodB of derivedclass is condition is True
...
def methodB(self):
# methodB of class aclass
...
class derivedclass(aclass):
def methodB(self):
#methodB of class derivedclass
...
But apart from such a special use case, I don't see any advantages to replace self.
You can make the instance a singleton element of the class
and mark the methods with #classmethod.
from enum import IntEnum
from collections import namedtuple
class kind(IntEnum):
circle = 1
square = 2
def attr(y): return [getattr(y, x) for x in 'k l b u r'.split()]
class Shape(namedtuple('Shape', 'k,l,b,u,r')):
self = None
#classmethod
def __repr__(cls):
return "<Shape({},{},{},{},{}) object at {}>".format(
*(attr(cls.self)+[id(cls.self)]))
#classmethod
def transform(cls, func):
cls.self = cls.self._replace(**func(cls.self))
Shape.self = Shape(k=1, l=2, b=3, u=4, r=5)
s = Shape.self
def nextkind(self):
return {'k': self.k+1}
print(repr(s)) # <Shape(1,2,3,4,5) object at 139766656561792>
s.transform(nextkind)
print(repr(s)) # <Shape(2,2,3,4,5) object at 139766656561888>