Indexer with two keys in python - python

I'm newbie with python. I want to write a class with two keys as indexer. also need to be able to use them inside of class like this:
a = Cartesian(-10,-10,10,10) # Cartesian is the name of my class
a[-5][-1]=10
and in the Cartesian class:
def fill(self,value):
self[x][y] = x*y-value
I try with
def __getitem__(self,x,y):
return self.data[x-self.dx][y-self.dy]
but doesn't work.

If you just need a lightweight application, you can have __getitem__ accept a tuple:
def __getitem__(self, c):
x, y = c
return self.data[x-self.dx][y-self.dy]
def __setitem__(self, c, v):
x, y = c
self.data[x-self.dx][y-self.dy] = v
and use like this:
a[-5,-1] = 10
However, if you are doing a lot of numeric computation or this is integral to your application, consider using Numpy and just represent this coordinate as a vector: Link

Is there any reason you actually need to explicitly define a Cartesian() class? For example, are there calculation methods on it? If not, then just use a lists within lists to use this type of syntax.
If you do need a class, then consider adding a .coordinate(x, y) method to it instead and don't bother trying to do the list syntax.

Accept a tuple:
>>> class Foo(object):
... def __getitem__(self, key):
... x, y = key
... print x, y
... f = Foo()
... f[1,2]
1 2

Related

Iterating through a dictionary of a class object without mixin - python

The main function of the class is a dictionary with words as keys and id numbers as values (note: id is not in sequential because some of the entries are removed):
x = {'foo':0, 'bar':1, 'king':3}
When i wrote the iterator function for a customdict class i created, it breaks when iterating through range(1 to infinity) because of a KeyError.
class customdict():
def __init__(self,dic):
self.cdict = dic
self.inverse = {}
def keys(self):
# this is necessary when i try to overload the UserDict.Mixin
return self.cdict.values()
def __getitem__(self, valueid):
""" Iterator function of the inversed dictionary """
if self.inverse == {}:
self.inverse = {v:k for k,v in self.cdict.items()}
return self.inverse[valueid]
x = {'foo':0, 'bar':1, 'king':3}
y = customdict(x)
for i in y:
print i
Without try and except and accessing the len(x), how could I resolve the iteration of the dictionary within the customdict class? Reason being x is >>>, len(x) will take too long for realtime.
I've tried UserDict.DictMixin and suddenly it works, why is that so?:
import UserDict.DictMixin
class customdict(UserDict.DictMixin):
...
Is there a way so that i don't use Mixin because somehow in __future__ and python3, mixins looks like it's deprecated?
Define following method.
def __iter__(self):
for k in self.keys():
yield k
I've tried UserDict.DictMixin and suddenly it works, why is that so?:
Because DictMixin define above __iter__ method for you.
(UserDict.py source code.)
Just share another way:
class customdict(dict):
def __init__(self,dic):
dict.__init__(self,{v:k for k,v in dic.items()})
x = {'foo':0, 'bar':1, 'king':3}
y = customdict(x)
for i in y:
print i,y[i]
result:
0 foo
1 bar
3 king
def __iter__(self):
return iter(self.cdict.itervalues())
In Python3 you'd call values() instead.
You're correct that UserDict.DictMixin is out of date, but it's not the fact that it's a mixin that's the problem, it's the fact that collections.Mapping and collections.MutableMapping use a more sensible underlying interface. So if you want to update from UserDict.DictMixin, you should switch to collections.Mapping and implement __iter__() and __len__() instead of keys().

Python nested Classes - returning multiple values

I'm fairly new to classes in python, so please be gentle. My script is a tad more complicated than this, but this is essentially what it boils down to:
class primary_state:
def __init__(self,x,y,z):
self.x = x
self.y = y
self.z = z
self.substates=[]
def add_substate(self,i,j,k):
self.substates.append(self.substate(i,j,k))
class substate:
def __init__(self,i,j,k):
self.i = i
self.j = j
self.k = k
state = primary_state(1,2,3)
state.add_substate(4,5,6)
state.add_substate(7,8,9)
Now my question is: is it possible to return an array of values from each object? So for example I'd like to do:
state.substates[:].i
and have it return the values of 4 and 7, but alas substates is a list so it can't handle it. There also must be a more efficient way to do this but I haven't quite figured that out yet. Any advice/thoughts would be greatly appreciated! Thanks.
Use a list comprehension.
[sub.i for sub in state.substates]
This is roughly equivalent to the following:
x = []
for sub in state.substates:
x.append(sub.i)
except shorter, and it's an expression that you can embed in other expressions instead of a series of statements.
You can get the list of substates by calling:
[substate.i for substate in self.substates]
list comprehensions are the way to do it as the other answers point out.
If the only job of the primary state class is to hold subclasses, you can make your class behave like an iterable. In the example you give this is mostly syntactic sugar, but it can be useful. Complete instructions on how to do it are here but it's pretty simple:
class PrimaryState(object): #always use "new style" classes! its 2013!
def __init__(self,x,y,z):
self.x = x
self.y = y
self.z = z
self.substates=[]
def __len__(self):
return len(self.substates)
def __getitem__(self, index):
return self.substates[index]
def __iter__(self):
for sub in substates: yield sub
def __contains__(self, item):
return item in self.substates
def add(self, item):
self.substates.append(item)
This way you can do:
primary = PrimaryState(1,2,3)
primary.add(SubState(4,5,6))
primary.add(SubState(7,8,9))
for item in primary:
print item
# Substate 4,5,6
# Substate 7,8,9
PS: Check out PEP-8, the standard python style guide for naming classes and so on. And use new style classes (inheriting from object). Down the road it's important!

Python - is there a way to implement __getitem__ for multidimension array?

I would like use something like that:
class Board():
...
def __getitem__(self, y, x):
return self.board[y][x]
but unfortunatelly, when I call:
board[x][y]
I get:
TypeError: __getitem__() takes exactly 3 arguments (2 given)
When you do board[x][y] you will cause two calls to __getitem__ because you are doing two separate accesses: [x] is one and [y] is another. There's no way to handle this directly in __getitem__; you'd have to have board[x] return some kind of sub-object that you could use [y] on to get the individual item. What you probably want is to have __getitem__ accept a tuple:
def __getitem__(self, tup):
y, x = tup
return self.board[y][x]
Then do:
board[x, y]
(Note that you have the order of x and y switched between __getitem__ and board[x][y] --- is that intentional?)
You might want to consider using this syntax:
board[(x, y)]
It's less pretty, but it allows you to have multidimensional arrays simply. Any number of dimensions in fact:
board[(1,6,34,2,6)]
By making board a defaultdict you can even have sparse dictionaries:
board[(1,6,34,2,6)]
>>> from collections import defaultdict
>>> board = defaultdict(lambda: 0)
>>> board[(1,6,8)] = 7
>>> board[(1,6,8)]
7
>>> board[(5,6,3)]
0
If you want something more advanced than that you probably want NumPy.
board[x][y] means board.__getitem__(x).__getitem__(y), so Board.__getitem__ has to return some kind of view that also supports __getitem__ and remembers x. This is a bit of work, but for some use cases (anything involving passing that view around) it's very convenient.
Another option is board[x, y], which means board.__getitem__((x, y)). Note that this passes a tuple to __getitem__, which you'll have to unpack manually (there is syntactic sugar for doing this in 2.x, but it's a bit obscure and also gone in 3.x, so you may want to avoid it in the interest of future porting work).
Just do:
class Board():
def __getitem__(self, x):
return self.board[x]
because when you call b[x][y] it actually calls __getitem__() twice, as showed below:
import numpy as np
b = Board()
b.board = np.random.random((3,3,3))
print (b[2][0]==(b[2])[0]).all()
#True
But the best would be to subclass np.ndarray, so that you don't have to re-implement this method:
class Board(np.ndarray):
pass
Say b is the class object b = Board(). When you are looking for B[0][0] __getitem__ won't normally work. Instead what we can do is set b's data equal to a new variable.
boardData = b.data
print(boardData[0][0])

Using super to make a pipeline?

I was thinking about how to use super to make a pipeline in python. I have a series of transformations I must do to a stream, and I thought that a good way to do it was something in the lines of:
class MyBase(object):
def transformData(self, x):
return x
class FirstStage(MyBase):
def transformData(self, x):
y = super(FirstStage, self).transformData(x)
return self.__transformation(y)
def __transformation(self, x):
return x * x
class SecondStage(FirstStage):
def transformData(self, x):
y = super(SecondStage, self).transformData(x)
return self.__transformation(y)
def __transformation(self, x):
return x + 1
It works as I intended, but there's a potential repetition. If I have N stages, I'll have N identical transformData methods where the only thing I change is the name of the current class.
Is there a way to remove this boilerplate? I tried a few things but the results only proved to me that I hadn't understood perfectly how super worked.
What I wanted was to define only the method __transformation and naturally inherit a transformData method that would go up in MRO, call that class' transformData method and then call the current class' __transformation on the result. Is it possible or do I have to define a new identical transformData for each child class?
I agree that this is a poor way of implementing a pipeline. That can be done with much simpler (and clearer) schemes. I thought of this as the least modification I could do on a existing model to get a pipeline out of the existing classes without modifying the code too much. I agree this is not the best way to do it. It would be a trick, and tricks should be avoided. Also I thought of it as a way of better understanding how super works.
Buuuut. Out of curiosity... is it possible to do it in the above scheme without the transformData repetition? This is a genuine doubt. Is there a trick to inherit transformData in a way that the super call in it is changed to be called on the current class?
It would be a tremendously unclear, unreadable, smart-ass trickery. I know. But is it possible?
I don't think using inheritance for a pipeline is the right way to go.
Instead, consider something like this -- here with "simple" examples and a parametrized one (a class using the __call__ magic method, but returning a closured function would do too, or even "JITing" one by way of eval).
def two_power(x):
return x * x
def add_one(x):
return x + 1
class CustomTransform(object):
def __init__(self, multiplier):
self.multiplier = multiplier
def __call__(self, value):
return value * self.multiplier
def transform(data, pipeline):
for datum in data:
for transform in pipeline:
datum = transform(datum)
yield datum
pipe = (two_power, two_power, add_one, CustomTransform(1.25))
print list(transform([1, 2, 4, 8], pipe))
would output
[2.5, 21.25, 321.25, 5121.25]
The problem is that using inheritance here is rather weird in terms of OOP. And do you really need to define the whole chain of transformations when defining classes?
But it's better to forget OOP here, the task is not for OOP. Just define functions for transformations:
def get_pipeline(*functions):
def pipeline(x):
for f in functions:
x = f(x)
return x
return pipeline
p = get_pipeline(lambda x: x * 2, lambda x: x + 1)
print p(5)
An even shorter version is here:
def get_pipeline(*fs):
return lambda v: reduce(lambda x, f: f(x), fs, v)
p = get_pipeline(lambda x: x * 2, lambda x: x + 1)
print p(5)
And here is an OOP solution. It is rather clumsy if compared to the previous one:
class Transform(object):
def __init__(self, prev=None):
self.prev_transform = prev
def transformation(self, x):
raise Exception("Not implemented")
def transformData(self, x):
if self.prev_transform:
x = self.prev_transform.transformData(x)
return self.transformation(x)
class TransformAdd1(Transform):
def transformation(self, x):
return x + 1
class TransformMul2(Transform):
def transformation(self, x):
return x * 2
t = TransformAdd1(TransformMul2())
print t.transformData(1) # 1 * 2 + 1

Returning an lvalue from a function in python

[Sorry, I'm new in Python. Although it seems to be a very basic question, I did my share of due diligence before asking this audience, trying to avoid really stupid questions].
I'm trying to figure out the correct idiom for returning an l-value from a function. Assume I've a container of 64 objects, and I want to be able to return a reference to these objects.
class ChessBoard:
def __init__(self):
self.squares = [None for x in range(64)]
square( row, col ):
return self.squares(row*8+col) <---- I'd like this to be l-value
Then, from outside the class I want to:
board = ChessBoard()
board.square(0,0) = Piece( Shapes.ROOK, Colors.White ) <-- I'm getting an error here
board.square(0,1) = Piece( Shapes.BISHOP, Colors.White )
... etc.
So, I would like the function 'at' to return a lvalue (Something like a reference in C++), but I can't find anything resembling a reference or a pointer in the language. If I stored a list in each square containing one Piece, it is possible I could do something like: board.square(0,0)[0] = Piece - but it seems crazy (or maybe not - as I said, I'm new to the language).
How would you approach this data structure?
In Python, everything is a reference. The only problem is that None is immutable, so you can't use the returned reference to change the value.
You also can't override the assignment operator, so you won't get this particular kind of behaviour. However, a good and very flexible solution would be to override the __setitem__ and __getitem__ methods to implement the subscription operator ([]) for the class:
class ChessBoard(object):
def __init__(self):
self.squares = [None] * 64
def __setitem__(self, key, value):
row, col = key
self.squares[row*8 + col] = value
def __getitem__(self, key):
row, col = key
return self.squares[row*8 + col]
Usage:
>>> c = ChessBoard()
>>> c[1,2] = 5
>>> c[1,2]
5
You can try something like this, at the cost of having to put bogus [:] indexers around:
class Board:
def __init__(self):
self.squares=[None for x in range(64)]
def square(self, row, col):
squares=self.squares
class Prox:
def __getitem__(self, i):
return squares[row*8+col]
def __setitem__(self, i, v):
squares[row*8+col]=v
return Prox()
Then you can do
b=Board()
b.square(2,3)[:]=Piece('Knight')
if b.square(x,y)[:] == Piece('King') ...
And so on. It doesn't actually matter what you put in the []s, it just has to be something.
(Got the idea from the Proxies Perl6 uses to do this)
As Niklas points out, you can't return an l-value.
However, in addition to overriding subscription, you can also use properties (an application of descriptors: http://docs.python.org/howto/descriptor.html) to create an object attribute, which when read from, or assigned to, runs code.
(Not answering your question in the title, but your "How would you approach this data structure?" question:) A more pythonic solution for your data structure would be using a list of lists:
# define a function that generates an empty chess board
make_chess_board = lambda : [[None for x in xrange(8)] for y in xrange(8)]
# grab an instance
b = make_chess_board()
# play the game!
b[0][0] = Piece(Shapes.ROOK, Colors.White)
b[0][1] = Piece(Shapes.BISHOP, Colors.White)
# Or use tuples:
b[0][0] = (Shapes.ROOK, Colors.White)
b[0][1] = (Shapes.BISHOP, Colors.White)

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