I am trying to understand what does this class
class undo:
def __init__(self, ss):
self.ss = ss
In my head it should simply put the value of ss uniquely in the variables i decide to use,but when I'm using it it rewrites all the variables, as if it was shared.
sum_expenses[100][0] = 100
sum_expenses[99][2] = 99
s = 1
a = [0 for i in range(100)]
a[s] = undo(sum_expenses)
output(a[1].ss)
sum_expenses[100][0] = 0
b = undo(sum_expenses)
print " "
print b.ss
print " "
sum_expenses[99][2] = 1
a[2] = undo(sum_expenses)
print a[2].ss
I do not understand why it overwrites all the variables with the current values of sum_expense, when I try to put it individually so that I can use the past values of sum_expenses.
Thank you and have a good day!
It happens because you're giving __init__ a reference to the list. If you change the list somewhere else, the reference in .ss still points to the same list, so the changes are visible there, too.
You could copy the list, since it's 2D try deepcopy.
Everytime you call this function it overrides reference to thr whole array ss, changing it to the new one you just passed to the constructor.
You can also create this array within the class and pass indexes and value to it like so:
undo.add(index1,index2,value)
Or you can make another variable ss_old and have make the function return that variable before you set it to a new value.
Related
I have a bit of python code that's set to run on a schedule. (I think my problem is the same as if it were within a loop.)
Let's say that in its most basic form, the code snippet looks something like this:
A = 1
B = 2
renameMe = A + B
Let's say the scheduler runs the same snippet of code every 5 minutes. The values of variables A & B are different each time the code is run, but the operation renameMe = A + B is always the same.
The values for A & B are grabbed out of a dataframe that's updated every 5 minutes, so I don't know what they are in advance, but if I need to do something with them beforehand instead of assigning them to A & B right away, I can.
I recently found out that for other things to work, I need to be able to rename the variable renameMe every time that snippet of code runs. In other words, I want the variable's name to be renameMe1 the first time the code snippet runs, then renameMe2 when it runs 5 minutes later, and so on.
It doesn't really matter in which way the variable's name changes (ints, strs, whatever) as long as I'm able to find out what the new variable name is, and use it elsewhere.
Do NOT use a variable variable name, you will have problems, use a container:
a list:
# first time
container = []
# each loop/run
container.append(A+B)
## last value
container[-1]
a dictionary:
# first time
container = {}
# each loop/run
container['new_id'] = A+B
# access arbitrary value
container['my_previous_id']
If you need persistence, use a flat file or a database.
I think it is suitable to use a class so that setattr can be used:
class newVal:
def __init__(self):
self.n = 1
def addVal(self, a, b):
setattr(self, f”val{self.n}”, a+b)
self.n += 1
Values = newVal()
Values.addVal(a, b)
Values.val1 would now be assigned
I aggree with Mozway when saying variables names are likely to cause problems, but this is also something you could strictly manage.
globals() stores all variables names and values in the form of a collection of 2-tuples, like this one :
dict_items([('__name__', '__main__'), ..., ('thisName', 'renaMe1'), ('renaMe18', 10)])
So you should register your new variable name but not forget to delete the previous one in order to avoid overloading.
If you follow a natural law of equal births and deaths, you will avoid overpopulation.
I propose you this bunch of code (with comments inside) :
basename = 'renaMe'
def varUpdate():
# Get previous variable name
thisName = [i for i, j in globals().items() if i[:len(basename)] == basename][0]
# Define the new variable name
newName = basename + '%d'%sum([int(thisName[len(basename):]), 1])
# Register the new variable name
globals()[newName] = globals()[thisName]
# Delete previous variable name from global
del globals()[thisName]
def process(i):
# Isolate from process content for readibility
varUpdate()
# PROCESS BELOW
# ....
newVar = [i for i, j in globals().items() if i[:len(basename)] == basename][0]
print(newVar, " : ", globals()[newVar])
# With this for` loop we simulate 4 entries in process
for i in range(4):
### we enter in the process
process(i)
Test in the shell
First restart your shell and let's suppose we have at the beginning renaMe12 = 12 :
>>> renaMe12 = 12
>>> Proposed Script ...
Result
Variable increments it's proper name at each iteration.
renaMe13 : 12
renaMe14 : 12
renaMe15 : 12
renaMe16 : 12
If you check in the shell now, you could see at the end of iteration, renaMe12 to renaMe15 no longer exist.
Only the variable renaMe16 exists with value 12.
>>> renaMe16
12
>>>> renaMe15
Retraçage (dernier appel le plus récent) :
Shell Python, prompt 4, line 1
builtins.NameError: name 'renaMe15' is not defined
Conclusion
This discussion is just for the sake of experimentation, but if I were you I would do my possible to avoid such code complexification unless it's necessary.
I agree Mozway when thinking you should avoid pain headaches...
Within pytorch, creating layers, can be semi automated, thus the reason for using a for loop.
One of the main issues is that these layers cannot stored within a list or dictionary or else back propagation will not work.
Thus the reason for a work around.
Within the object, assigning new self attributes
How do i replace this
self.res1 = 1
self.res2 = 2
self.res3 = 3
with this
for i in range(2):
res_name = 'res'+str(i+1)
self.res_name = i
Now that i have created objects this way, how can I access them in the same way. For example, if we assume self.res_name is now an object?
for i in range(2):
res_name = 'res'+str(i+1)
out = self.res_name(out)
You probably should use a dict or list instead. But if you really want this for some reason, you can try setattr(x, attr, 'magic').
Thus, in your case, it's
for i in range(1, 4):
res_name = 'res' + str(i)
setattr(self, res_name, i)
See this related question for more info.
When I assign a value into an array the scope of the variable remain local (see loc()).
However if I access the element of an array the scope becomes global ( see glob())
import numpy as np
M = np.array([1])
def loc():
M = 2
return 0
def glob():
M[0] = 3
return 0
loc()
print M
>>> [1]
glob()
print M
>>> [3]
Why does this happen ? How can i locally modify the elements of an array without modifying the array globally? I need to have a loop inside my function changing one element at a time.
You're mixing several things here.
First of all, M = 2 creates a local variable named M (you can see it in locals()) and prevents you from accessing the original M later on (although you're not doing it... But just to make a point). That's sometimes referred to as "shadowing".
Second of all, the np.array is a mutable object (the opposite of an immutable object), and changes to it will reflect in any reference to it. What you have in your glob function is a reference to M.
You can look at an np.array as a piece of memory that has many names, and if you changed it, the changes will be evident no matter what name you're using to access it. M[0] is simply a reference to a specific part of this memory. This reflects the object's "state".
If you'd do something like:
M = np.array([1])
def example()
another_name_for_M = M
M = 2
another_name_for_M[0] = 2
you would still see the global M changing, but you're using a new name to access it.
If you would use a string, a tuple, a frozenset and the likes, which are all immutable objects that can not be (easily) changed, you wouldn't be able to actually change their state.
Now to your question, if you don't want the function to mutate the array just send a copy of it using np.copy, and not the actual one:
import numpy as np
my_array = np.array([1])
def array_mutating_function(some_array):
some_array[0] = 1337
print some_array # prints [1337]
# send copy to prevent mutating the original array
array_mutating_function(np.copy(my_array))
print my_array # prints [1]
This will effectively make it immutable on the outer scope, since the function will not have a reference to it unless it's using it's name on the outer scope, which is probably not a good idea regardless.
If the function should never change any array, move the copy to be made on inside the function no matter what array is sent, preventing it from changing any array that was sent to it:
def array_mutating_function(some_array):
some_array = np.copy(some_array)
some_array[0] = 1337
SImply explaining.:
cannot update a global varaible inside a funcion unless access it as global inside function.
But it can modify
Check:
import numpy as np
M = np.array([1])
def loc():
global M
M = 2
return 0
def glob():
M[0] = 3
return 0
loc()
print M
>>>2
I want to use a while loop to initialize class objects with a simple incremented naming convention. The goal is to be able to scale the number of class objects at will and have the program generate the names automatically. (ex. h1...h100...h1000...) Each h1,h2,h3... being its own instance.
Here is my first attempt... have been unable to find a good example.
class Korker(object):
def __init__(self,ident,roo):
self.ident = ident
self.roo = roo
b = 1
hwinit = 'h'
hwstart = 0
while b <= 10:
showit = 'h' + str(b)
print(showit) #showit seems to generate just fine as demonstrated by print
str(showit) == Korker("test",2) #this is the line that fails
b += 1
The errors I get range from a string error to a cannot use function type error.... Any help would be greatly appreciated.
If you want to generate a number of objects, why not simply put them in an array / hash where they can be looked up later on:
objects = {}
for b in range(1,11):
objects['h'+str(b)] = Korker("test", 2)
# then access like this:
objects['h3']
Of course there are ways to make the names available locally, but that's not a very good idea unless you know why you need it (via globals() and locals()).
Variables are names that point to objects that hold data. You are attempting to stick data into the variable names. That's the wrong way around.
instead of h1 to h1000, just call the variable h, and make it a list. Then you get h[0] to h[999].
Slightly different solution to viraptor's: use a list.
h = []
for i in range(10):
h.append(Korker("test",2))
In fact, you can even do it on one line with a list comprehension:
h = [Korker("test", 2) for i in range(10)]
Then you can get at them with h[0], h[1] etc.
I'm trying to create a Python script that opens several databases and compares their contents. In the process of creating that script, I've run into a problem in creating a list whose contents are objects that I've created.
I've simplified the program to its bare bones for this posting. First I create a new class, create a new instance of it, assign it an attribute and then write it to a list. Then I assign a new value to the instance and again write it to a list... and again and again...
Problem is, it's always the same object so I'm really just changing the base object. When I read the list, I get a repeat of the same object over and over.
So how do you write objects to a list within a loop?
Here's my simplified code
class SimpleClass(object):
pass
x = SimpleClass
# Then create an empty list
simpleList = []
#Then loop through from 0 to 3 adding an attribute to the instance 'x' of SimpleClass
for count in range(0,4):
# each iteration creates a slightly different attribute value, and then prints it to
# prove that step is working
# but the problem is, I'm always updating a reference to 'x' and what I want to add to
# simplelist is a new instance of x that contains the updated attribute
x.attr1= '*Bob* '* count
print "Loop Count: %s Attribute Value %s" % (count, x.attr1)
simpleList.append(x)
print '-'*20
# And here I print out each instance of the object stored in the list 'simpleList'
# and the problem surfaces. Every element of 'simpleList' contains the same attribute value
y = SimpleClass
print "Reading the attributes from the objects in the list"
for count in range(0,4):
y = simpleList[count]
print y.attr1
So how do I (append, extend, copy or whatever) the elements of simpleList so that each entry contains a different instance of the object instead of all pointing to the same one?
You demonstrate a fundamental misunderstanding.
You never created an instance of SimpleClass at all, because you didn't call it.
for count in xrange(4):
x = SimpleClass()
x.attr = count
simplelist.append(x)
Or, if you let the class take parameters, instead, you can use a list comprehension.
simplelist = [SimpleClass(count) for count in xrange(4)]
A list comprehension can be used to fill a list with separate instances of a class, like so:
instancelist = [MyClass() for i in range(29)]
This avoids the problem with multiplying a list of one element with *, which re-uses the same object.
It shouldn't be necessary to recreate the SimpleClass object each time, as some are suggesting, if you're simply using it to output data based on its attributes. However, you're not actually creating an instance of the class; you're simply creating a reference to the class object itself. Therefore, you're adding a reference to the same class attribute to the list (instead of instance attribute), over and over.
Instead of:
x = SimpleClass
you need:
x = SimpleClass()
Create a new instance each time, where each new instance has the correct state, rather than continually modifying the state of the same instance.
Alternately, store an explicitly-made copy of the object (using the hint at this page) at each step, rather than the original.
If I understand correctly your question, you ask a way to execute a deep copy of an object.
What about using copy.deepcopy?
import copy
x = SimpleClass()
for count in range(0,4):
y = copy.deepcopy(x)
(...)
y.attr1= '*Bob* '* count
A deepcopy is a recursive copy of the entire object. For more reference, you can have a look at the python documentation: https://docs.python.org/2/library/copy.html
I think this simply demonstrates what you are trying to achieve:
# coding: utf-8
class Class():
count = 0
names = []
def __init__(self,name):
self.number = Class.count
self.name = name
Class.count += 1
Class.names.append(name)
l=[]
l.append(Class("uno"))
l.append(Class("duo"))
print l
print l[0].number, l[0].name
print l[1].number, l[1].name
print Class.count, Class.names
Run the code above and you get:-
[<__main__.Class instance at 0x6311b2c>,
<__main__.Class instance at 0x63117ec>]
0 uno
1 duo
2 ['uno', 'duo']