Python: iterating through a list of objects within a list of objects

I've made two classes called House and Window. I then made a list containing four Houses. Each instance of House has a list of Windows. I'm trying to iterate over the windows in each house and print it's ID. However, I seem to get some odd results :S I'd greatly appreciate any help.

#!/usr/bin/env python

# Minimal house class
class House:
    ID = ""
    window_list = []

# Minimal window class
class Window:
    ID = ""

# List of houses
house_list = []

# Number of windows to build into each of the four houses
windows_per_house = [1, 3, 2, 1]

# Build the houses
for new_house in range(0, len(windows_per_house)):

    # Append the new house to the house list
    house_list.append(House())

    # Give the new house an ID
    house_list[new_house].ID = str(new_house)  

    # For each new house build some windows
    for new_window in range(0, windows_per_house[new_house]):

        # Append window to house's window list
        house_list[new_house].window_list.append(Window())

        # Give the window an ID
        house_list[new_house].window_list[new_window].ID = str(new_window)

#Iterate through the windows of each house, printing house and window IDs.
for house in house_list:
    print "House: " + house.ID

    for window in house.window_list:
        print "   Window: " + window.ID

####################
开发者_运维百科# Desired output:
#
# House: 0
#    Window: 0
# House: 1
#    Window: 0
#    Window: 1
#    Window: 2
# House: 2
#    Window: 0
#    Window: 1
# House: 3
#    Window: 0  
####################

Currently you are using class attributes instead of instance attributes. Try changing your class definitions to the following:

class House:
    def __init__(self):
        self.ID = ""
        self.window_list = []

class Window:
    def __init__(self):
        self.ID = ""

The way your code is now all instances of House are sharing the same window_list.

C++, Java, C# etc. have this really strange behaviour regarding instance variables, whereby data (members, or fields, depending on which culture you belong to) that's described within a class {} block belongs to instances, while functions (well, methods, but C++ programmers seem to hate that term and say "member functions" instead) described within the same block belong to the class itself. Strange, and confusing, when you actually think about it.

A lot of people don't think about it; they just accept it and move on. But it actually causes confusion for a lot of beginners, who assume that everything within the block belongs to the instances. This leads to bizarre (to experienced programmers) questions and concerns about the per-instance overhead of these methods, and trouble wrapping their heads around the whole "vtable" implementation concept. (Of course, it's mostly the teachers' collective fault for failing to explain that vtables are just one implementation, and for failing to make clear distinctions between classes and instances in the first place.)

Python doesn't have this confusion. Since in Python, functions (including methods) are objects, it would be bizarrely inconsistent for the compiler to make a distinction like that. So, what happens in Python is what you should intuitively expect: everything within the class indented block belongs to the class itself. And, yes, Python classes are themselves objects as well (which gives a place to put those class attributes), and you don't have to jump through standard library hoops to use them reflectively. (The absence of manifest typing is quite liberating here.)

So how, I hear you protest, do we actually add any data to the instances? Well, by default, Python doesn't restrict you from adding anything to any instance. It doesn't even require you to make different instances of the same class contain the same attributes. And it certainly doesn't pre-allocate a single block of memory to contain all the object's attributes. (It would only be able to contain references, anyway, given that Python is a pure reference-semantics language, with no C# style value types or Java style primitives.)

But obviously, it's a good idea to do things that way, so the usual convention is "add all the data at the time that the instance is constructed, and then don't add any more (or delete any) attributes".

"When it's constructed"? Python doesn't really have constructors in the C++/Java/C# sense, because this absence of "reserved space" means there's no real benefit to considering "initialization" as a separate task from ordinary assignment - except of course the benefit of initialization being something that automatically happens to a new object.

So, in Python, our closest equivalent is the magic __init__ method that is automatically called upon newly-created instances of the class. (There is another magic method called __new__, which behaves more like a constructor, in the sense that it's responsible for the actual creation of the object. However, in nearly every case we just want to delegate to the base object __new__, which calls some built-in logic to basically give us a little pointer-ball that can serve as an object, and point it to a class definition. So there's no real point in worrying about __new__ in almost every case. It's really more analogous to overloading the operator new for a class in C++.) In the body of this method (there are no C++-style initialization lists, because there is no pre-reserved data to initialize), we set initial values for attributes (and possibly do other work), based on the parameters we're given.

Now, if we want to be a little bit neater about things, or efficiency is a real concern, there is another trick up our sleeves: we can use the magic __slots__ attribute of the class to specify class attribute names. This is a list of strings, nothing fancy. However, this still doesn't pre-initialize anything; an instance doesn't have an attribute until you assign it. This just prevents you from adding attributes with other names. You can even still delete attributes from an object whose class has specified __slots__. All that happens is that the instances are given a different internal structure, to optimize memory usage and attribute lookup.

The __slots__ usage requires that we derive from the built-in object type, which we should do anyway (although we aren't required in Python 2.x, this is intended only for backwards-compatibility purposes).

Ok, so now we can make the code work. But how do we make it right for Python?

First off, just as with any other language, constantly commenting to explain already-self-explanatory things is a bad idea. It distracts the user, and doesn't really help you as a learner of the language, either. You're supposed to know what a class definition looks like, and if you need a comment to tell you that a class definition is a class definition, then reading the code comments isn't the kind of help you need.

With this whole "duck typing" thing, it's poor form to include data type names in variable (or attribute) names. You're probably protesting, "but how am I supposed to keep track of the type otherwise, without the manifest type declaration"? Don't. The code that uses your list of windows doesn't care that your list of windows is a list of windows. It just cares that it can iterate over the list of windows, and thus obtain values that can be used in certain ways that are associated with windows. That's how duck typing works: stop thinking about what the object is, and worry about what it can do.

You'll notice in the code below that I put the string conversion code into the House and Window constructors themselves. This serves as a primitive form of type-checking, and also makes sure that we can't forget to do the conversion. If someone tries to create a House with an ID that can't even be converted to a string, then it will raise an exception. Easier to ask for forgiveness than permission, after all. (Note that you actually have to go out of your way a bit in Python to create

As for the actual iteration... in Python, we iterate by actually iterating over the objects in a container. Java and C# have this concept as well, and you can get at it with the C++ standard library too (although a lot of people don't bother). We don't iterate over indices, because it's a useless and distracting indirection. We don't need to number our "windows_per_house" values in order to use them; we just need to look at each value in turn.

How about the ID numbers, I hear you ask? Simple. Python provides us with a function called 'enumerate', which gives us (index, element) pairs given an input sequence of elements). It's clean, it lets us be explicit about our need for the index to solve the problem (and the purpose of the index), and it's a built-in that doesn't need to be interpreted like the rest of the Python code, so it doesn't incur all that much overhead. (When memory is a concern, it's possible to use a lazy-evaluation version instead.)

But even then, iterating to create each house, and then manually appending each one to an initially-empty list, is too low-level. Python knows how to construct a list of values; we don't need to tell it how. (And as a bonus, we typically get better performance by letting it do that part itself, since the actual looping logic can now be done internally, in native C.) We instead describe what we want in the list, with a list comprehension. We don't have to walk through the steps of "take each window-count in turn, make the corresponding house, and add it to the list", because we can say "a list of houses with the corresponding window-count for each window-count in this input list" directly. That's arguably clunkier in English, but much cleaner in a programming language like Python, because you can skip a bunch of the little words, and you don't have to expend effort to describe the initial list, or the act of appending the finished houses to the list. You don't describe the process at all, just the result. Made-to-order.

Finally, as a general programming concept, it makes sense, whenever possible, to delay the construction of an object until we have everything ready that's needed for that object's existence. "Two-phase construction" is ugly. So we make the windows for a house first, and then the house (using those windows). With list comprehensions, this is simple: we just nest the list comprehensions.

class House(object):
    __slots__ = ['ID', 'windows']
    def __init__(self, id, windows):
        self.ID = str(id)
        self.windows = windows

class Window(object):
    __slots__ = ['ID']
    def __init__(self, id):
        self.ID = str(id)

windows_per_house = [1, 3, 2, 1]

# Build the houses.
houses = [
    House(house_id, [Window(window_id) for window_id in range(window_count)])
    for house_id, window_count in enumerate(windows_per_house)
]
# See how elegant the list comprehensions are?
# If you didn't quite follow the logic there, please try **not** 
# to imagine the implicitly-defined process as you trace through it.
# (Pink elephants, I know, I know.) Just understand what is described.

# And now we can iterate and print just as before.
for house in houses:
    print "House: " + house.ID
    for window in house.windows:
        print "   Window: " + window.ID

Here's the updated code.

# Minimal house class
class House:
    def __init__(self, id):
        self.ID = id
        self.window_list = []

# Minimal window class
class Window:
    ID = ""

# List of houses
house_list = []

# Number of windows to build into each of the for houses
windows_per_house = [1, 3, 2, 1]

# Build the houses
for new_house in range(len(windows_per_house)):

    # Append the new house to the house list
    house_list.append(House(str(new_house)))

    # For each new house build some windows
    for new_window in range(windows_per_house[new_house]):

        # Append window to house's window list
        house_list[new_house].window_list.append(Window())

        # Give the window an ID
        house_list[new_house].window_list[new_window].ID = str(new_window)

#Iterate through the windows of each house, printing house and window IDs.
for house in house_list:
    print "House: " + house.ID

    for window in house.window_list:
        print "   Window: " + window.ID

The actual problem is that the window_list attribute is mutable, so when the different instances are using it, they end up sharing the same one. By moving window_list into __init__ each instance gets its own.

Apart from some indentation errors, you're assigning the IDs and window_lists to the class and not the instances.

You want something like

class House():
    def __init__(self, ID):
        self.ID = ID
        self.window_list = []

etc.

Then, you can do house_list.append(House(str(newHouse))) and so on.