Hello Pythoneers: the following code is only a mock up of what I'm trying to do, but it should illustrate my question.
I would like to know if this is dirty trick I picked up from Java programming, or a valid and Pythonic way of doing things: basically I'm creating a load of instances, but I need to track 'static' data of all the instances as they are created.
class Myclass:
counter=0
last_value=None
def __init__(self,name):
self.name=name
Myclass.counter+=1
Myclass.last_value=name
And some output of using this simple class , showing that everything is working as I expected:
>>> x=Myclass("hello")
>>> print x.name
hello
>>> print Myclass.last_value
hello
>>> y=Myclass("goodbye")
>>> print y.name
goodbye
>>> print x.name
hello
>>> print Myclass.last_value
goodbye
So is this a generally acceptable way of doing this kind of thing, or an anti-pattern ?
[For instance, I'm not too happy that I can apparently set the counter from both within the class(good) and outside of it(bad); also not keen on having to use full namespace 'Myclass' from within the class code itself - just looks bulky; and lastly I'm initially setting values to 'None' - probably I'm aping static-typed languages by doing this?]
I'm using Python 2.6.2 and the program is single-threaded.
Class variables are perfectly Pythonic in my opinion.
Just watch out for one thing. An instance variable can hide a class variable:
x.counter = 5 # creates an instance variable in the object x.
print x.counter # instance variable, prints 5
print y.counter # class variable, prints 2
print myclass.counter # class variable, prints 2
Do. Not. Have. Stateful. Class. Variables.
It's a nightmare to debug, since the class object now has special features.
Stateful classes conflate two (2) unrelated responsibilities: state of object creation and the created objects. Do not conflate responsibilities because it "seems" like they belong together. In this example, the counting of created objects is the responsibility of a Factory. The objects which are created have completely unrelated responsibilities (which can't easily be deduced from the question).
Also, please use Upper Case Class Names.
class MyClass( object ):
def __init__(self, name):
self.name=name
def myClassFactory( iterable ):
for i, name in enumerate( iterable ):
yield MyClass( name )
The sequence counter is now part of the factory, where the state and counts should be maintained. In a separate factory.
[For folks playing Code Golf, this is shorter. But that's not the point. The point is that the class is no longer stateful.]
It's not clear from question how Myclass instances get created. Lacking any clue, there isn't much more than can be said about how to use the factory. An iterable is the usual culprit. Perhaps something that iterates through a list or a file or some other iterable data structure.
Also -- for folks just of the boat from Java -- the factory object is just a function. Nothing more is needed.
Since the example on the question is perfectly unclear, it's hard to know why (1) two unique objects are created with (2) a counter. The two unique objects are already two unique objects and a counter isn't needed.
For example, the static variables in the Myclass are never referenced anywhere. That makes it very, very hard to understand the example.
x, y = myClassFactory( [ "hello", "goodbye" ] )
If the count or last value where actually used for something, then a perhaps meaningful example could be created.
You can solve this problem by splitting the code into two separate classes.
The first class will be for the object you are trying to create:
class MyClass(object):
def __init__(self, name):
self.Name = name
And the second class will create the objects and keep track of them:
class MyClassFactory(object):
Counter = 0
LastValue = None
#classmethod
def Build(cls, name):
inst = MyClass(name)
cls.Counter += 1
cls.LastValue = inst.Name
return inst
This way, you can create new instances of the class as needed, but the information about the created classes will still be correct.
>>> x = MyClassFactory.Build("Hello")
>>> MyClassFactory.Counter
1
>>> MyClassFactory.LastValue
'Hello'
>>> y = MyClassFactory.Build("Goodbye")
>>> MyClassFactory.Counter
2
>>> MyClassFactory.LastValue
'Goodbye'
>>> x.Name
'Hello'
>>> y.Name
'Goodbye'
Finally, this approach avoids the problem of instance variables hiding class variables, because MyClass instances have no knowledge of the factory that created them.
>>> x.Counter
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'MyClass' object has no attribute 'Counter'
You don't have to use a class variable here; this is a perfectly valid case for using globals:
_counter = 0
_last_value = None
class Myclass(obj):
def __init__(self, name):
self.name = name
global _counter, _last_value
_counter += 1
_last_value = name
I have a feeling some people will knee-jerk against globals out of habit, so a quick review may be in order of what's wrong--and not wrong--with globals.
Globals traditionally are variables which are visible and changeable, unscoped, from anywhere in the program. This is a problem with globals in languages like C. It's completely irrelevant to Python; these "globals" are scoped to the module. The class name "Myclass" is equally global; both names are scoped identically, in the module they're contained in. Most variables--in Python equally to C++--are logically part of instances of objects or locally scoped, but this is cleared shared state across all users of the class.
I don't have any strong inclination against using class variables for this (and using a factory is completely unnecessary), but globals are how I'd generally do it.
Is this pythonic? Well, it's definitely more pythonic than having global variables for a counter and the value of the most recent instance.
It's said in Python that there's only one right way to do anything. I can't think of a better way to implement this, so keep going. Despite the fact that many will criticize you for "non-pythonic" solutions to problems (like the needless object-orientation that Java coders like or the "do-it-yourself" attitude that many from C and C++ bring), in most cases your Java habits will not send you to Python hell.
And beyond that, who cares if it's "pythonic"? It works, and it's not a performance issue, is it?
Related
I am attempting to use LuaJ with Scala. Most things work (actually all things work if you do them correctly!) but the simple task of setting object values has become incredibly complicated thanks to Scala's setter implementation.
Scala:
class TestObject {
var x: Int = 0
}
Lua:
function myTestFunction(testObject)
testObject.x = 3
end
If I execute the script or line containing this Lua function and pass a coerced instance of TestObject to myTestFunction this causes an error in LuaJ. LuaJ is trying to direct-write the value, and Scala requires you to go through the implicitly-defined setter (with the horrible name x_=, which is not valid Lua so even attempting to call that as a function makes your Lua not parse).
As I said, there are workarounds for this, such as defining your own setter or using the #BeanProperty markup. They just make code that should be easy to write much more complicated:
Lua:
function myTestFunction(testObject)
testObject.setX(testObject, 3)
end
Does anybody know of a way to get luaj to implicitly call the setter for such assignments? Or where I might look in the luaj source code to perhaps implement such a thing?
Thanks!
I must admit that I'm not too familiar with LuaJ, but the first thing that comes to my mind regarding your issue is to wrap the objects within proxy tables to ease interaction with the API. Depending upon what sort of needs you have, this solution may or may not be the best, but it could be a good temporary fix.
local mt = {}
function mt:__index(k)
return self.o[k] -- Define how your getters work here.
end
function mt:__newindex(k, v)
return self.o[k .. '_='](v) -- "object.k_=(v)"
end
local function proxy(o)
return setmetatable({o = o}, mt)
end
-- ...
function myTestFunction(testObject)
testObject = proxy(testObject)
testObject.x = 3
end
I believe this may be the least invasive way to solve your problem. As for modifying LuaJ's source code to better suit your needs, I had a quick look through the documentation and source code and found this, this, and this. My best guess says that line 71 of JavaInstance.java is where you'll find what you need to change, if Scala requires a different way of setting values.
f.set(m_instance, CoerceLuaToJava.coerce(value, f.getType()));
Perhaps you should use the method syntax:
testObject:setX(3)
Note the colon ':' instead of the dot '.' which can be hard to distinguish in some editors.
This has the same effect as the function call:
testObject.setX(testObject, 3)
but is more readable.
It can also be used to call static methods on classes:
luajava.bindClass("java.net.InetAddress"):getLocalHost():getHostName()
The part to the left of the ':' is evaluated once, so a statement such as
x = abc[d+e+f]:foo()
will be evaluated as if it were
local tmp = abc[d+e+f]
x = tmp.foo(tmp)
One typical way of managing state in Lift is to create a singleton object extending SessionVar, like in this example taken from the documentation:
object MySnippetCompanion {
object mySessionVar extends SessionVar[String]("hello")
}
The case for using SessionVars is clear and I've been using them in practice as needed. I also roughly understand how they work inside.
Still, I can't help but wonder why the mechanism for "session variables", which are clearly associated with the current session (usually just one out of many sessions in the system), was designed to be used via a singleton? This goes so against my intuition that at first glance I was tempted to believe that Lift was somehow able to override Scala's language features and to make object mean something different that in regular Scala.
Even though I now understand how it works, I can't grasp the rationale for such a design, which, at least for me, breaks the rule of least astonishment. Can someone point out any advantages or perhaps explain why such a design decision could have been made?
Session variables in Lift use Scala's DynamicVariable. Basically they allow you to statically reference a variable in a code-block and then later on call the code and substitute a value:
import scala.util.DynamicVariable
val x = new DynamicVariable(1)
def printIt() {
println(x.value)
}
printIt()
//> 1
x.withValue(2)(printIt())
//> 2
So each time a request is handled, the scope of these dynamic variables is changed to the current session, completely hiding the state change of the current session to you as a programmer.
The other option would be to pass around a "sessionID" object which you would have to use when you want to access session specific data. Not really handy.
The reason you have to use the object keyword is that object is unique in that it defines both a value and a class. This allows Lift to call getClass to get a name that uniquely identifies this SessionVar vs. any other one, which Lift needs in order to serialize and deserialize every piece of session state in the right place(s). Furthermore if the SessionVar is in a class that has two instances (for instance a snippet rendered in two tabs), they will both refer to the same piece of session state. (The flip side of the coin is that the same SessionVar instance can be referenced by two different sessions and mean the right thing to each.)
Actually at times this is insufficient --- for instance, if you define a SessionVar in a trait, and have two different classes that inherit the trait, but you need them two have two different values. The solution in that case is to override the def for the "name salt", which is combined with getClass to identify the SessionVar.
My question is how to program in Python (2.6) a function that uses a namespace of an object, while the function is defined outside the object/class. In addition, that function should only change the variables in the object's namespace; it should not take over the namespace (because with multiple objects they will all use the same namespace).
My reason for pursuing this, is because I wish to write a very small class, where during construction all necessary functions for future use are already given and subsequent function calls (self.__call__) on the object itself can be directly applied.
I realize that this idea is not very pythonic (as they say), and I have thought of various other solutions (such as putting the functions in another class and connecting them), but I can't help but feel that each of these solutions is a lot more work than I would think makes sense.
One simple way that accomplishes what I want is the following:
class A:
def __init__(self, some_dict, func_a):
self.memory = some_dict
self.__call__ = func_a
def test_func(obj, some_input):
if some_input in obj.memory :
return obj.memory[some_input]
else :
obj.memory[some_input] = 0. # some default value
return 0.
first_object = A({}, test_func)
print first_object(first_object, '3')
This will work fine, but what aches me is that when I make function calls to the object, I will also have to give the object itself (see the last line). I hope to be able make calls as such:
print first_object('3')
So far, my ideas were unsuccesful to avoid this (e.g. copying the function method and link its namespace by self.__call__.memory = self.memory). I wish to find something to change the def __init__ part to 'adopt' a function and link their namespaces.
I have rigorously searched for an answer on the internet, but a definite solution has not yet been found. The following http://www.velocityreviews.com/forums/t738476-inserting-class-namespace-into-method-scope.html seeks the same, but is also not succesfull.
Anyone have a solution to tackle this?
How do I create a properly functional configurable object in Scala? I have watched Tony Morris' video on the Reader monad and I'm still unable to connect the dots.
I have a hard-coded list of Client objects:
class Client(name : String, age : Int){ /* etc */}
object Client{
//Horrible!
val clients = List(Client("Bob", 20), Client("Cindy", 30))
}
I want Client.clients to be determined at runtime, with the flexibility of either reading it from a properties file or from a database. In the Java world I'd define an interface, implement the two types of source, and use DI to assign a class variable:
trait ConfigSource {
def clients : List[Client]
}
object ConfigFileSource extends ConfigSource {
override def clients = buildClientsFromProperties(Properties("clients.properties"))
//...etc, read properties files
}
object DatabaseSource extends ConfigSource { /* etc */ }
object Client {
#Resource("configuration_source")
private var config : ConfigSource = _ //Inject it at runtime
val clients = config.clients
}
This seems like a pretty clean solution to me (not a lot of code, clear intent), but that var does jump out (OTOH, it doesn't seem to me really troublesome, since I know it will be injected once-and-only-once).
What would the Reader monad look like in this situation and, explain it to me like I'm 5, what are its advantages?
Let's start with a simple, superficial difference between your approach and the Reader approach, which is that you no longer need to hang onto config anywhere at all. Let's say you define the following vaguely clever type synonym:
type Configured[A] = ConfigSource => A
Now, if I ever need a ConfigSource for some function, say a function that gets the n'th client in the list, I can declare that function as "configured":
def nthClient(n: Int): Configured[Client] = {
config => config.clients(n)
}
So we're essentially pulling a config out of thin air, any time we need one! Smells like dependency injection, right? Now let's say we want the ages of the first, second and third clients in the list (assuming they exist):
def ages: Configured[(Int, Int, Int)] =
for {
a0 <- nthClient(0)
a1 <- nthClient(1)
a2 <- nthClient(2)
} yield (a0.age, a1.age, a2.age)
For this, of course, you need some appropriate definition of map and flatMap. I won't get into that here, but will simply say that Scalaz (or Rúnar's awesome NEScala talk, or Tony's which you've seen already) gives you all you need.
The important point here is that the ConfigSource dependency and its so-called injection are mostly hidden. The only "hint" that we can see here is that ages is of type Configured[(Int, Int, Int)] rather than simply (Int, Int, Int). We didn't need to explicitly reference config anywhere.
As an aside, this is the way I almost always like to think about monads: they hide their effect so it's not polluting the flow of your code, while explicitly declaring the effect in the type signature. In other words, you needn't repeat yourself too much: you say "hey, this function deals with effect X" in the function's return type, and don't mess with it any further.
In this example, of course the effect is to read from some fixed environment. Another monadic effect you might be familiar with include error-handling: we can say that Option hides error-handling logic while making the possibility of errors explicit in your method's type. Or, sort of the opposite of reading, the Writer monad hides the thing we're writing to while making its presence explicit in the type system.
Now finally, just as we normally need to bootstrap a DI framework (somewhere outside our usual flow of control, such as in an XML file), we also need to bootstrap this curious monad. Surely we'll have some logical entry point to our code, such as:
def run: Configured[Unit] = // ...
It ends up being pretty simple: since Configured[A] is just a type synonym for the function ConfigSource => A, we can just apply the function to its "environment":
run(ConfigFileSource)
// or
run(DatabaseSource)
Ta-da! So, contrasting with the traditional Java-style DI approach, we don't have any "magic" occurring here. The only magic, as it were, is encapsulated in the definition of our Configured type and the way it behaves as a monad. Most importantly, the type system keeps us honest about which "realm" dependency injection is occurring in: anything with type Configured[...] is in the DI world, and anything without it is not. We simply don't get this in old-school DI, where everything is potentially managed by the magic, so you don't really know which portions of your code are safe to reuse outside of a DI framework (for example, within your unit tests, or in some other project entirely).
update: I wrote up a blog post which explains Reader in greater detail.
What kind of constructs need 'scalac' compile and how to make an equivalent that will work in interpreter?
Edit: I want to use scala instead of python as a scripting language. (with #!/usr/bin/scala)
You ought to be able to do anything in the REPL that you can do in outside code. Keep in mind that:
Things that refer to each other circularly need to be inside one block. So the following can't be entered as-is; you have to wrap it inside some other object:
class C(i : Int) { def succ = C(i+1) }
object C { def apply(i: Int) = new C(i) }
The execution environment is somewhat different, so benchmarking timings will not always come out the same way as if you run them from compiled code.
You enter the execution path a different way; if you want to call a main method, though, you certainly can from inside the REPL.
You can't just cut-and-paste an entire library into the REPL and have it work exactly like the library did; the REPL has a different structure than normal packages do. So drop the "package" declarations during testing.
EDIT: after reading your question again, I have to admit, that I didn't really answer it ;). But maybe it still helps.
I know of two limitations of interpreter (or REPL), when it comes to loading scala files (in order to interactively test them).
You can't load scala files with package definitions in them. REPL complains and does not load all class is the scala file to be loaded. It read that it has to do with the fact that files that are loaded into the REPL are treated as an object . . . which of course can't have any package definitions in them.
REPL is strange (or a little bit unpredictable) when there are class files of loaded scala files on the classpath. Check out this question by myself and especially my 2 last comments to the second answer.
Furthermore there is a problem with circular dependencies, that I don't know a workaround for: Suppose there is a Class A that uses Class B which again needs A to do it's job. Of course you can't define A since there is no definition of B and vice versa. Providing a dummy for one of those doesn't work either:
scala> class A {
| def alterString(s:String) = s
| def printStuff(s:String) = println(alterString(s))
| }
defined class A
scala> class B {
| val prefix = "this is a test: "
| def doJob() = new A() printStuff "1 2 3"
| }
defined class B
scala> class A {
| def alterString(s:String) = new B().prefix + s
| def printStuff(s:String) = println(alterString(s))
| }
defined class A
scala> new B().doJob()
1 2 3
scala>
Although I already provided a newer definition of A, class B still used the one that was present when I defined it.
I think everything in Scala will work from the interpreter as well (which I believe just calls the compiler under the hood anyway).
Do you suspect something to not work? Or is this a trick/interview question (I suppose anything that want to directly interact with the class loader or class files may behave differently in the two environments, but I have no idea really).