I'm new to both Django and Python.. I just started using them a few days ago and I can't quite figure out how to call a method other than the __init__ method for a class.
Here is the code for user.py
class User:
def __init__(self, number):
self.num = number
class Create:
def __init__(self, something):
self.test = something[1]
def other(self, one):
self.two = one
I can get __init__ to work by calling..
list = [3, 4, 5]
y = Create(list)
arrayelem = y.test
But I can't quite figure out how to call a method inside of the class Create. I've tried various methods and always end up with errors. Can somehow show me some syntactically correct methods of calling the method "other".
Note: I know the spacing is weird.. I can't get the spacing to work properly on stackoverflow for whatever reason..
Good news - it's a simple one! To call other() on create, you'd do this:
list = [3, 4, 5]
y = Create(list)
y.other('one')
You just need to pass the parameters inside the parentheses, after the name of the method.
EDIT: I've just noticed you want to call other from inside the Create class. That'd look like this:
class Create:
def __init__(self, something):
self.test = something[1]
self.other(123)
def other(self, one):
self.two = one
It's also worth bearing in mind that self.two won't exist when you get to the other() method.
Related
I was looking at some link about Python.
https://medium.com/the-renaissance-developer/python-101-object-oriented-programming-part-1-7d5d06833f26
And there are decorators used in there to create(?) properties and a setter method for it. Below is the code:
class Vehicle:
def __init__(self, number_of_wheels, type_of_tank, seating_capacity, maximum_velocity):
self.number_of_wheels = number_of_wheels
self.type_of_tank = type_of_tank
self.seating_capacity = seating_capacity
self.maximum_velocity = maximum_velocity
#property
def number_of_wheels(self):
return self.number_of_wheels
#number_of_wheels.setter
def number_of_wheels(self, number):
self.number_of_wheels = number
And this is the usage from the link as well.
tesla_model_s = Vehicle(4, 'electric', 5, 250)
print(tesla_model_s.number_of_wheels) # 4
tesla_model_s.number_of_wheels = 2 # setting number of wheels to 2
print(tesla_model_s.number_of_wheels) # 2
So, I was trying to understand why should I use it, instead of, you know, directly accessing class variable itself. I tried to run the code but I got RecursionError.
File "C:/Users/Brandon/Desktop/Python/tryit.py", line 16, in number_of_wheels
self.number_of_wheels = number
[Previous line repeated 491 more times]
RecursionError: maximum recursion depth exceeded while calling a Python object
Finally my question is, how can this code work(what is wrong with it maybe?) and more importantly why should I use setter instead of accessing class variable directly?
ps. Any pointers like links to read or keywords for search are welcomed.
The property and attribute should not have the same name, otherwise, the setters and getters will keep calling themselves over and over. Conventionally, you would prepend a leading underscore to privatize (though it's not private) the attribute you're creating a property for.
class Vehicle(object):
def __init__(self, number_of_wheels, type_of_tank, seating_capacity, maximum_velocity):
self._number_of_wheels = number_of_wheels
...
#property
def number_of_wheels(self):
return self._number_of_wheels
#number_of_wheels.setter
def number_of_wheels(self, number):
self._number_of_wheels = number
Also remember to subclass object in Python 2, to make your class work with property.
I have the following problem and I need advice on how to solve it the best technically in Python. As I am new to programming I would like to have some advice.
So I will have the following object and they should store something. Here is an example:
object 1: cash dividends (they will have the following properties)
exdate (will store a list of dates)
recorddate (will store a list of dates)
paydate (will store a list of dates)
ISIN (will store a list of text)
object 2: stocksplits (they will have the following prpoerties)
stockplitratio (will be some ration)
exdate(list of dates)
...
I have tried to solve it like this:
class cashDividends(object):
def __init__(self, _gross,_net,_ISIN, _paydate, _exdate, _recorddate, _frequency, _type, _announceddate, _currency):
self.gross = _gross
self.net = _net
self.ISIN = _ISIN
self.paydate = _paydate
self.exdate = _exdate
self.recorddate = _recorddate
self.frequency = _frequency
self.type = _type
self.announceddate = _announceddate
self.currency = _currency
So if I have this I would have to create another class named stockplits and then define an __init__ function again.
However is there a way where I can have one class like "Corporate Actions" and then have stock splits and cashdividends in there ?
Sure you can! In python you can pass classes to other classes.
Here a simple example:
class A():
def __init__(self):
self.x = 0
class B():
def __init__(self):
self.x = 1
class Container():
def __init__(self, objects):
self.x = [obj.x for obj in objects]
a = A()
b = B()
c = Container([a,b])
c.x
[0,1]
If I understood correctly what you want is an object that has other objects from a class you created as property?
class CorporateActions(object):
def __init__(self, aCashDividend, aStockSplit):
self.cashDividend = aCashDividend
self.stockSplit = aStockSplit
myCashDividends = CashDividends(...) #corresponding parameters here
myStockSplit = StockSplit(...)
myCorporateActions = CorporateActions(myCashDividends, myStockSplit)
Strictly speaking this answer isn't an answer for the final question. However, it is a way to make your life slightly easier.
Consider creating a sort-of template class (I'm using this term loosely; there's no such thing in Python) that does the __init__ work for you. Like this:
class KwargAttrs():
def __init__(self, **kwargs):
for k,v in kwargs.items():
setattr(self, k, v)
def _update(self, **kwargs):
args_dict = {k:(kwargs[k] if k in kwargs else self.__dict__[k]) for k in self.__dict__}
self.__dict__.update(args_dict)
This class uses every supplied keyword argument as an object attribute. Use it this way:
class CashDividends(KwargAttrs):
def __init__(self, gross, net, ISIN, paydate, exdate, recorddate, frequency, type, announceddate, currency):
# save the namespace before it gets polluted
super().__init__(**locals())
# work that might pollute local namespace goes here
# OPTIONAL: update the argument values in case they were modified:
super()._update(**locals())
Using a method like this, you don't have to go through the argument list and assign every single object attribute; it happens automatically.
We bookend everything you need to accomplish in the __init__ method with method calls to the parent-class via super(). We do this because locals() returns a dict every variable in the function's current namespace, so you need to 1.) capture that namespace before any other work pollutes it and 2.) update the namespace in case any work changes the argument values.
The call to update is optional, but the values of the supplied arguments will not be updated if something is done to them after the call to super().__init__() (that is, unless you change the values using setattr(self, 'argname, value)`, which is not a bad idea).
You can continue using this class like so:
class StockSplits(KwargAttrs):
def __init__(self, stocksplitratio, gross, net, ISIN, paydate, exdate, recorddate, frequency, type, announceddate, currency):
super().__init__(**locals())
As mentioned in the other answers you can create a container for our other classes, but you can even do that using this same template class:
class CorporateActions(KwargAttrs):
def __init__(self, stock_splits , cash_dividends):
super().__init__(**locals())
ca = CorporateActions(stock_splits = StockSplits(<arguments>), cash_dividends = CashDividends(<arguments>) )
Question
How can you extend a python property?
A subclass can extend a super class's function by calling it in the overloaded version, and then operating on the result. Here's an example of what I mean when I say "extending a function":
# Extending a function (a tongue-in-cheek example)
class NormalMath(object):
def __init__(self, number):
self.number = number
def add_pi(self):
n = self.number
return n + 3.1415
class NewMath(object):
def add_pi(self):
# NewMath doesn't know how NormalMath added pi (and shouldn't need to).
# It just uses the result.
n = NormalMath.add_pi(self)
# In NewMath, fractions are considered too hard for our users.
# We therefore silently convert them to integers.
return int(n)
Is there an analogous operation to extending functions, but for functions that use the property decorator?
I want to do some additional calculations immediately after getting an expensive-to-compute attribute. I need to keep the attribute's access lazy. I don't want the user to have to invoke a special routine to make the calculations. basically, I don't want the user to ever know the calculations were made in the first place. However, the attribute must remain a property, since i've got legacy code I need to support.
Maybe this is a job for decorators? If I'm not mistaken, decorator is a function that wraps another function, and I'm looking to wrap a property with some more calculations, and then present it as a property again, which seems like a similar idea... but I can't quite figure it out.
My Specific Problem
I've got a base class LogFile with an expensive-to-construct attribute .dataframe. I've implemented it as a property (with the property decorator), so it won't actually parse the log file until I ask for the dataframe. So far, it works great. I can construct a bunch (100+) LogFile objects, and use cheaper methods to filter and select only the important ones to parse. And whenever I'm using the same LogFile over and over, i only have to parse it the first time I access the dataframe.
Now I need to write a LogFile subclass, SensorLog, that adds some extra columns to the base class's dataframe attribute, but I can't quite figure out the syntax to call the super class's dataframe construction routines (without knowing anything about their internal workings), then operate on the resulting dataframe, and then cache/return it.
# Base Class - rules for parsing/interacting with data.
class LogFile(object):
def __init__(self, file_name):
# file name to find the log file
self.file_name = file_name
# non-public variable to cache results of parse()
self._dataframe = None
def parse(self):
with open(self.file_name) as infile:
...
...
# Complex rules to interpret the file
...
...
self._dataframe = pandas.DataFrame(stuff)
#property
def dataframe(self):
"""
Returns the dataframe; parses file if necessary. This works great!
"""
if self._dataframe is None:
self.parse()
return self._dataframe
#dataframe.setter
def dataframe(self,value):
self._dataframe = value
# Sub class - adds more information to data, but does't parse
# must preserve established .dataframe interface
class SensorLog(LogFile):
def __init__(self, file_name):
# Call the super's constructor
LogFile.__init__(self, file_name)
# SensorLog doesn't actually know about (and doesn't rely on) the ._dataframe cache, so it overrides it just in case.
self._dataframe = None
# THIS IS THE PART I CAN'T FIGURE OUT
# Here's my best guess, but it doesn't quite work:
#property
def dataframe(self):
# use parent class's getter, invoking the hidden parse function and any other operations LogFile might do.
self._dataframe = LogFile.dataframe.getter()
# Add additional calculated columns
self._dataframe['extra_stuff'] = 'hello world!'
return self._dataframe
#dataframe.setter
def dataframe(self, value):
self._dataframe = value
Now, when these classes are used in an interactive session, the user should be able to interact with either in the same way.
>>> log = LogFile('data.csv')
>>> print log.dataframe
#### DataFrame with 10 columns goes here ####
>>> sensor = SensorLog('data.csv')
>>> print sensor.dataframe
#### DataFrame with 11 columns goes here ####
I have lots of existing code that takes a LogFile instance which provides a .dataframe attribute and dos something interesting (mostly plotting). I would LOVE to have SensorLog instances present the same interface so they can use the same code. Is it possible to extend the super-class's dataframe getter to take advantage of existing routines? How? Or am I better off doing this a different way?
Thanks for reading that huge wall of text. You are an internet super hero, dear reader. Got any ideas?
You should be calling the superclass properties, not bypassing them via self._dataframe. Here's a generic example:
class A(object):
def __init__(self):
self.__prop = None
#property
def prop(self):
return self.__prop
#prop.setter
def prop(self, value):
self.__prop = value
class B(A):
def __init__(self):
super(B, self).__init__()
#property
def prop(self):
value = A.prop.fget(self)
value['extra'] = 'stuff'
return value
#prop.setter
def prop(self, value):
A.prop.fset(self, value)
And using it:
b = B()
b.prop = dict((('a', 1), ('b', 2)))
print(b.prop)
Outputs:
{'a': 1, 'b': 2, 'extra': 'stuff'}
I would generally recommend placing side-effects in setters instead of getters, like this:
class A(object):
def __init__(self):
self.__prop = None
#property
def prop(self):
return self.__prop
#prop.setter
def prop(self, value):
self.__prop = value
class B(A):
def __init__(self):
super(B, self).__init__()
#property
def prop(self):
return A.prop.fget(self)
#prop.setter
def prop(self, value):
value['extra'] = 'stuff'
A.prop.fset(self, value)
Having costly operations within a getter is also generally to be avoided (such as your parse method).
If I understand correctly what you want to do is call the parent's method from the child instance. The usual way to do that is by using the super built-in.
I've taken your tongue-in-cheek example and modified it to use super in order to show you:
class NormalMath(object):
def __init__(self, number):
self.number = number
def add_pi(self):
n = self.number
return n + 3.1415
class NewMath(NormalMath):
def add_pi(self):
# this will call NormalMath's add_pi with
normal_maths_pi_plus_num = super(NewMath, self).add_pi()
return int(normal_maths_pi_plus_num)
In your Log example, instead of calling:
self._dataframe = LogFile.dataframe.getter()
you should call:
self._dataframe = super(SensorLog, self).dataframe
You can read more about super here
Edit: Even thought the example I gave you deals with methods, to do the same with #properties shouldn't be a problem.
You have some possibilities to consider:
1/ Inherit from logfile and override parse in your derived sensor class. It should be possible to modify your methods that work on dataframe to work regardless of the number of members that dataframe has - as you are using pandas a lot of it is done for you.
2/ Make sensor an instance of logfile then provide its own parse method.
3/ Generalise parse, and possibly some of your other methods, to use a list of data descriptors and possibly a dictionary of methods/rules either set in your class initialiser or set by a methods.
4/ Look at either making more use of the methods already in pandas, or possibly, extending pandas to provide the missing methods if you and others think that they would be accepted into pandas as useful extensions.
Personally I think that you would find the benefits of options 3 or 4 to be the most powerful.
The problem is that you're missing a self going into the parent class. If your parent is a singleton then a #staticmethod should work.
class X():
x=1
#staticmethod
def getx():
return X.x
class Y(X):
y=2
def getyx(self):
return X.getx()+self.y
wx = Y()
wx.getyx()
3
I am trying to create a new MyClass instance in MyClass's definition.
Why does this code fail and how can achieve it?
class MyClass:
def __init__(self):
self.child=MyClass()
mc=MyClass()
Well, it fails because it has infinite recursion. Think about it, if every MyClass has a child which is a MyClass, it will go on for infinity!
You can resolve this a couple of ways. First, you can have a parameter to the constructor:
class MyClass:
def __init__(self, create = True):
if create:
self.child = MyClass(False)
mc = MyClass()
Or, you can have another, external method:
class MyClass:
def set_child(self,child = None):
# I prefer to make child optional for ease of use.
child = MyClass() if child is None else child
self.child=child
mc=MyClass()
mc.set_child()
I personally prefer the first solution as it means that outside objects don't need to know anything about the class. Of course, you could combine the two:
class MyClass:
def __init__(self, create):
if create:
self.set_child(create=False)
def set_child(self,child = None, create = True):
child = MyClass(create) if child is None else child
self.child=child
mc=MyClass()
This way mc has a child by default and you have the option of setting the child whenever you like.
Then there is also the "let's create a certain number" approach:
class MyClass:
def __init__(self, count = 10):
count -= 1
if count:
# the first child gets the value 9.
# the second gets 8.
# when the count gets to 0, stop!
self.child = MyClass(count)
Aside: If you want to get an object's class, you can use the value obj.__class__. That will output MyClass in all of the examples above.
You're making an infinitely recursing call — MyClass is creating another MyClass during initialization, and thus it recurses infinitely.
You may want to do something like:
class MyClass:
def create_child(self):
self.child=MyClass()
mc=MyClass()
mc.create_child()
If you're feeling particularly naughty, you could try:
class MyClass(object):
#property
def child(self):
if self._child is None: self._child = MyClass()
return self._child
def __init__(self):
self._child=None
mc=MyClass()
What you did there is actualy recursive, the new isntance of MyClass will create a new instance that will in turn create a new one, etc ...
Soo I supose that is why your code fails, I can't tell for sure since you didn't post the error message.
I suggest to define two classes:
class MyClass(object):
def __init__(self):
self.child = MyChildClass()
...many other methods...
class MyChildClass(MyClass):
def __init__(self):
pass
I think that if two classes must behave in two different ways, they must be different (although one can subclass the other)
In Python is there any way to make a class, then make a second version of that class with identical dat,a but which can be changed, then reverted to be the same as the data in the original class?
So I would make a class with the numbers 1 to 5 as the data in it, then make a second class with the same names for sections (or very similar). Mess around with the numbers in the second class then with one function then reset them to be the same as in the first class.
The only alternative I've found is to make one aggravatingly long class with too many separate pieces of data in it to be readily usable.
A class is a template, it allows you to create a blueprint, you can then have multiple instances of a class each with different numbers, like so.
class dog(object):
def __init__(self, height, width, lenght):
self.height = height
self.width = width
self.length = length
def revert(self):
self.height = 1
self.width = 2
self.length = 3
dog1 = dog(5, 6, 7)
dog2 = dog(2, 3, 4)
dog1.revert()
Here's another answer kind of like pobk's; it uses the instance's dict to do the work of saving/resetting variables, but doesn't require you to specify the names of them in your code. You can call save() at any time to save the state of the instance and reset() to reset to that state.
class MyReset:
def __init__(self, x, y):
self.x = x
self.y = y
self.save()
def save(self):
self.saved = self.__dict__.copy()
def reset(self):
self.__dict__ = self.saved.copy()
a = MyReset(20, 30)
a.x = 50
print a.x
a.reset()
print a.x
Why do you want to do this? It might not be the best/only way.
Classes don't have values. Objects do. Is what you want basically a class that can reset an instance (object) to a set of default values?
How about just providing a reset method, that resets the properties of your object to whatever is the default?
I think you should simplify your question, or tell us what you really want to do. It's not at all clear.
I think you are confused. You should re-check the meaning of "class" and "instance".
I think you are trying to first declare a Instance of a certain Class, and then declare a instance of other Class, use the data from the first one, and then find a way to convert the data in the second instance and use it on the first instance...
I recommend that you use operator overloading to assign the data.
class ABC(self):
numbers = [0,1,2,3]
class DEF(ABC):
def __init__(self):
self.new_numbers = super(ABC,self).numbers
def setnums(self, numbers):
self.new_numbers = numbers
def getnums(self):
return self.new_numbers
def reset(self):
__init__()
Just FYI, here's an alternate implementation... Probably violates about 15 million pythonic rules, but I publish it per information/observation:
class Resettable(object):
base_dict = {}
def reset(self):
self.__dict__ = self.__class__.base_dict
def __init__(self):
self.__dict__ = self.__class__.base_dict.copy()
class SomeClass(Resettable):
base_dict = {
'number_one': 1,
'number_two': 2,
'number_three': 3,
'number_four': 4,
'number_five': 5,
}
def __init__(self):
Resettable.__init__(self)
p = SomeClass()
p.number_one = 100
print p.number_one
p.reset()
print p.number_one