Related
It's not obvious to me from reading the current API design guideline, which of the following version is better.
class MediaLoader {}
class MediaRequest {}
let mediaLoader = MediaLoader()
let mediaRequest = MediaRequest()
// Option 1
mediaLoader.add(request: mediaRequest)
// Option 2
mediaLoader.add(mediaRequest: mediaRequest)
// Option 3
mediaLoader.addRequest(mediaRequest)
// Option 4
mediaLoader.add(mediaRequest)
Which of the above conforms to the current API design guideline the best?
The answer really depends on the purpose and semantics of MediaLoader. If MediaLoader is only a collection of mediaRequests, then .add(mediaRequest) is the way to go because it would flow grammatically and be meaningful in context.
On the other hand, if a mediaRequest is merely one of many different things contributing to its purpose, then .add() alone would not convey enough context to properly read the statement. For example, if you could also add display channels or filters, then merely saying .add(something) would not be clear enough. This is when you would use an extended name that describes the relationship. e.g. .addRequest(), addChannel(), addFilter().
But not .add(request:...), because, using a name for the first parameter is not the ideal way to distinguish between relationships. It should be used instead to clarify the method by which the addition will be performed or the way the request will be accessed. This will leave the "nameless" variant for the most frequent and straightforward use case. e.g. .add(fromTemplate:webRequesTemplate) or .addRequest(fromTemplate:webTemplate).
I have a lot to learn in the way of OO patterns and this is a problem I've come across over the years. I end up in situations where my classes' sole purpose is procedural, just basically wrapping a procedure up in a class. It doesn't seem like the right OO way to do things, and I wonder if someone is experienced with this problem enough to help me consider it in a different way. My specific example in the current application follows.
In my application I'm taking a set of points from engineering survey equipment and normalizing them to be used elsewhere in the program. By "normalize" I mean a set of transformations of the full data set until a destination orientation is reached.
Each transformation procedure will take the input of an array of points (i.e. of the form class point { float x; float y; float z; }) and return an array of the same length but with different values. For example, a transformation like point[] RotateXY(point[] inList, float angle). The other kind of procedure wold be of the analysis type, used to supplement the normalization process and decide what transformation to do next. This type of procedure takes in the same points as a parameter but returns a different kind of dataset.
My question is, what is a good pattern to use in this situation? The one I was about to code in was a Normalization class which inherits class types of RotationXY for instance. But RotationXY's sole purpose is to rotate the points, so it would basically be implementing a single function. This doesn't seem very nice, though, for the reasons I mentioned in the first paragraph.
Thanks in advance!
The most common/natural approach for finding candidate classes in your problem domain is to look for nouns and then scan for the verbs/actions associated with those nouns to find the behavior that each class should implement. While this is generally a good advise, it doesn't mean that your objects must only represent concrete elements. When processes (which are generally modeled as methods) start to grow and become complex, it is a good practice to model them as objects. So, if your transformation has a weight on its own, it is ok to model it as an object and do something like:
class RotateXY
{
public function apply(point p)
{
//Apply the transformation
}
}
t = new RotateXY();
newPoint = t->apply(oldPoint);
in case you have many transformations you can create a polymorphic hierarchy and even chain one transformation after another. If you want to dig a bit deeper you can also take a look at the Command design pattern, which closely relates to this.
Some final comments:
If it fits your case, it is a good idea to model the transformation at the point level and then apply it to a collection of points. In that way you can properly isolate the transformation concept and is also easier to write test cases. You can later even create a Composite of transformations if you need.
I generally don't like the Utils (or similar) classes with a bunch of static methods, since in most of the cases it means that your model is missing the abstraction that should carry that behavior.
HTH
Typically, when it comes to classes that contain only static methods, I name them Util, e.g. DbUtil for facading DB access, FileUtil for file I/O etc. So find some term that all your methods have in common and name it that Util. Maybe in your case GeometryUtil or something along those lines.
Since the particulars of the transformations you apply seem ad-hoc for the problem and possibly prone to change in the future you could code them in a configuration file.
The point's client would read from the file and know what to do. As for the rotation or any other transformation method, they could go well as part of the Point class.
I see nothing particularly wrong with classes/interfaces having just essentially one member.
In your case the member is an "Operation with some arguments of one type that returns same type" - common for some math/functional problems. You may find convenient to have interface/base class and helper methods that combine multiple transformation classes together into more complex transformation.
Alternative approach: if you language support it is just go functional style altogether (similar to LINQ in C#).
On functional style suggestion: I's start with following basic functions (probably just find them in standard libraries for the language)
collection = map(collection, perItemFunction) to transform all items in a collection (Select in C#)
item = reduce (collection, agregateFunction) to reduce all items into single entity (Aggregate in C#)
combine 2 functions on item funcOnItem = combine(funcFirst, funcSecond). Can be expressed as lambda in C# Func<T,T> combined = x => second(first(x)).
"bind"/curry - fix one of arguments of a function functionOfOneArg = curry(funcOfArgs, fixedFirstArg). Can be expressed in C# as lambda Func<T,T> curried = x => funcOfTwoArg(fixedFirstArg, x).
This list will let you do something like "turn all points in collection on a over X axis by 10 and shift Y by 15": map(points, combine(curry(rotateX, 10), curry(shiftY(15))).
The syntax will depend on language. I.e. in JavaScript you just pass functions (and map/reduce are part of language already), C# - lambda and Func classes (like on argument function - Func<T,R>) are an option. In some languages you have to explicitly use class/interface to represent a "function" object.
Alternative approach: If you actually dealing with points and transformation another traditional approach is to use Matrix to represent all linear operations (if your language supports custom operators you get very natural looking code).
Object oriented programming in one way or another is very much possible in R. However, unlike for example Python, there are many ways to achieve object orientation:
The R.oo package
S3 and S4 classes
Reference classes
the proto package
My question is:
What major differences distinguish these ways of OO programming in R?
Ideally the answers here will serve as a reference for R programmers trying to decide which OO programming methods best suits their needs.
As such, I am asking for detail, presented in an objective manner, based on experience, and backed with facts and reference. Bonus points for clarifying how these methods map to standard OO practices.
S3 classes
Not really objects, more of a naming convention
Based around the . syntax: E.g. for print, print calls print.lm print.anova, etc. And if not found,print.default
S4 classes
Can dispatch on multiple arguments
More complicated to implement than S3
Reference classes
Primarily useful to avoid making copies of large objects (pass by reference)
Description of reasons to use RefClasses
proto
ggplot2 was originally written in proto, but will eventually be rewritten using S3.
Neat concept (prototypes, not classes), but seems tricky in practice
Next version of ggplot2 seems to be moving away from it
Description of the concept and implementation
R6 classes
By-reference
Does not depend on S4 classes
"Creating an R6 class is similar to the reference class, except that there’s no need to separate the fields and methods, and you can’t specify the types of the fields."
Edit on 3/8/12: The answer below responds to a piece of the originally posted question which has since been removed. I've copied it below, to provide context for my answer:
How do the different OO methods map to the more standard OO methods used in e.g. Java or Python?
My contribution relates to your second question, about how R's OO methods map to more standard OO methods. As I've thought about this in the past, I've returned again and again to two passages, one by Friedrich Leisch, and the other by John Chambers. Both do a good job of articulating why OO-like programming in R has a different flavor than in many other languages.
First, Friedrich Leisch, from "Creating R Packages: A Tutorial" (warning: PDF):
S is rare because it is both interactive and has a system for object-orientation. Designing classes clearly is programming, yet to make S useful as an interactive data analysis environment, it makes sense that it is a functional language. In "real" object-oriented programming (OOP) languages like C++ or Java class and method definitions are tightly bound together, methods are part of classes (and hence objects). We want incremental and interactive additions like user-defined methods for pre-defined classes. These additions can be made at any point in time, even on the fly at the command line prompt while we analyze a data set. S tries to make a compromise between object orientation and interactive use, and although compromises are never optimal with respect to all goals they try to reach, they often work surprisingly well in practice.
The other passage comes from John Chambers' superb book "Software for Data Analysis". (Link to quoted passage):
The OOP programming model differs from the S language in all but the first
point, even though S and some other functional languages support classes
and methods. Method definitions in an OOP system are local to the class;
there is no requirement that the same name for a method means the same
thing for an unrelated class. In contrast, method definitions in R do not
reside in a class definition; conceptually, they are associated with the generic
function. Class definitions enter in determining method selection, directly
or through inheritance. Programmers used to the OOP model are sometimes
frustrated or confused that their programming does not transfer to R directly,
but it cannot. The functional use of methods is more complicated but also
more attuned to having meaningful functions, and can't be reduced to the
OOP version.
S3 and S4 seem to be the official (i.e. built in) approaches for OO programming. I have begun using a combination of S3 with functions embedded in constructor function/method. My goal was to have a object$method() type syntax so that I have semi-private fields. I say semi-private because there is no way of really hiding them (as far as I know). Here is a simple example that doesn't actually do anything:
#' Constructor
EmailClass <- function(name, email) {
nc = list(
name = name,
email = email,
get = function(x) nc[[x]],
set = function(x, value) nc[[x]] <<- value,
props = list(),
history = list(),
getHistory = function() return(nc$history),
getNumMessagesSent = function() return(length(nc$history))
)
#Add a few more methods
nc$sendMail = function(to) {
cat(paste("Sending mail to", to, 'from', nc$email))
h <- nc$history
h[[(length(h)+1)]] <- list(to=to, timestamp=Sys.time())
assign('history', h, envir=nc)
}
nc$addProp = function(name, value) {
p <- nc$props
p[[name]] <- value
assign('props', p, envir=nc)
}
nc <- list2env(nc)
class(nc) <- "EmailClass"
return(nc)
}
#' Define S3 generic method for the print function.
print.EmailClass <- function(x) {
if(class(x) != "EmailClass") stop();
cat(paste(x$get("name"), "'s email address is ", x$get("email"), sep=''))
}
And some test code:
test <- EmailClass(name="Jason", "jason#bryer.org")
test$addProp('hello', 'world')
test$props
test
class(test)
str(test)
test$get("name")
test$get("email")
test$set("name", "Heather")
test$get("name")
test
test$sendMail("jbryer#excelsior.edu")
test$getHistory()
test$sendMail("test#domain.edu")
test$getNumMessagesSent()
test2 <- EmailClass("Nobody", "dontemailme#nowhere.com")
test2
test2$props
test2$getHistory()
test2$sendMail('nobody#exclesior.edu')
Here is a link to a blog post I wrote about this approach: http://bryer.org/2012/object-oriented-programming-in-r I would welcome comments, criticisms, and suggestions to this approach as I am not convinced myself if this is the best approach. However, for the problem I was trying to solve it has worked great. Specifically, for the makeR package (http://jbryer.github.com/makeR) I did not want users to change data fields directly because I needed to ensure that an XML file that represented my object's state would stay in sync. This worked perfectly as long as the users adhere to the rules I outline in the documentation.
Using online dictionary tools doesn't really help. I think the way encapsulate is use in computer science doesn't exactly match its meaning in plain English.
What is the antonym of computer science's version of encaspulate? More specifically, what is an antonym for encapsulate that would work as a function name.
Why should I care? Here's my motivation:
// A class with a private member variable;
class Private
{
public:
// Test will be able to access Private's private members;
class Test;
private:
int i;
}
// Make Test exactly like Private
class Private::Test : public Private
{
public:
// Make Private's copy of i available publicly in Test
using Private::i;
};
// A convenience function to quickly break encapsulation on a class to be tested.
// I don't have good name for what it does
Private::Test& foo( Private& p )
{ return *reinterpret_cast<Private::Test*>(&p); } // power cast
void unit_test()
{
Private p;
// using the function quickly grab access to p's internals.
// obviously it would be evil to use this anywhere except in unit tests.
assert( foo(p).i == 42 );
}
The antonym is "C".
Ok, just kidding. (Sort of.)
The best terms I can come up with are "expose" and "violate".
The purpose behind encapsulation is to hide/cover/protect. The antonym would be reveal/expose/make public.
How about Decapsulation..
Though it aint a computer science term, but in medical science, Surgical removal of a capsule or enveloping membrane.. Check out here..
"Removing/Breaking encapsulation" is about the closest thing I've seen, honestly.
If you think of the word in the English sense, to encapsulate means to enclose within something. But in the CS sense, there's this concept of protection levels and it looks like you want to imply circumventing the access levels as well, so something like "extraction" doesn't really convey the meaning you're looking for.
But if you just think of it in terms of what the access levels are, it looks like you're making something public so, how about "publicizing"?
This is not such a simple question - Scott Meyers had an interesting article to demonstrate some of the nuances around encapsulation here.
I'll start with the punchline: If
you're writing a function that can be
implemented as either a member or as a
non-friend non-member, you should
prefer to implement it as a non-member
function. That decision increases
class encapsulation. When you think
encapsulation, you should think
non-member functions.
How about "Bad Idea"?
The true antonym of "Encapsulation" is "Global State".
The general opposite of encapsulation is coupling and we often talk about systems that are tightly coupled or loosely coupled.
The reason you'd want components to be encapsulated is because it makes it easier to reason about how they work.
Take the analogy of trains: the consequence of coupling the railcars is that the driver must consider the characteristics (inertia, length) of the entire train.
Obviously, though, we couple systems because we need them to work together.
Inverted encapsulation and data structures
There's another term that I've been digging for, which is how I came across this question, that refers to a non-standard style of data structures.
The standard style of encapsulation is exemplified by Java's LinkedList; the actual nodes of the list are designed to be inaccessible to the consumer. The theory is that this is an implementation detail and can change to improve performance, while existing code will continue to run.
Another style is the classic functional cons-list. This is a singly linked list, and the idea is that it's so simple that there's nothing to improve about the data structure, e.g.
data [a] = [] | a : [a] deriving (Eq, Ord)
-- Haskellers then work directly with the list
-- There's nothing to hide because it's so simple
typicalHaskell :: [a] -> b
typicalHaskell [] = emptyValue
typicalHaskell h : t = h `doAThing` (typicalHaskell t)
That's the definition from Haskell's standard prelude though the report notes that isn't valid Haskell syntax, and in practice [a] is defined in the guts of the compiler.
Then there's what I'm calling an "inverted" data structure, but I'm still looking for the correct term. This is, I think, really the opposite of encapsulation.
A good example of this is Python's heapq module. The data structure here is a binary heap, but there isn't a Heap class. Rather, you get a collection of functions that operate on generic Python lists and you're responsible for using those methods correctly to ensure the heap invariants are maintained.
How about "spaghetti"?
I'm designing a language, and I'm wondering if it's reasonable to make reference types non-nullable by default, and use "?" for nullable value and reference types. Are there any problems with this? What would you do about this:
class Foo {
Bar? b;
Bar b2;
Foo() {
b.DoSomething(); //valid, but will cause exception
b2.DoSomething(); //?
}
}
My current language design philosophy is that nullability should be something a programmer is forced to ask for, not given by default on reference types (in this, I agree with Tony Hoare - Google for his recent QCon talk).
On this specific example, with the unnullable b2, it wouldn't even pass static checks: Conservative analysis cannot guarantee that b2 isn't NULL, so the program is not semantically meaningful.
My ethos is simple enough. References are an indirection handle to some resource, which we can traverse to obtain access to that resource. Nullable references are either an indirection handle to a resource, or a notification that the resource is not available, and one is never sure up front which semantics are being used. This gives either a multitude of checks up front (Is it null? No? Yay!), or the inevitable NPE (or equivalent). Most programming resources are, these days, not massively resource constrained or bound to some finite underlying model - null references are, simplistically, one of...
Laziness: "I'll just bung a null in here". Which frankly, I don't have too much sympathy with
Confusion: "I don't know what to put in here yet". Typically also a legacy of older languages, where you had to declare your resource names before you knew what your resources were.
Errors: "It went wrong, here's a NULL". Better error reporting mechanisms are thus essential in a language
A hole: "I know I'll have something soon, give me a placeholder". This has more merit, and we can think of ways to combat this.
Of course, solving each of the cases that NULL current caters for with a better linguistic choice is no small feat, and may add more confusion that it helps. We can always go to immutable resources, so NULL in it's only useful states (error, and hole) isn't much real use. Imperative technqiues are here to stay though, and I'm frankly glad - this makes the search for better solutions in this space worthwhile.
Having reference types be non-nullable by default is the only reasonable choice. We are plagued by languages and runtimes that have screwed this up; you should do the Right Thing.
This feature was in Spec#. They defaulted to nullable references and used ! to indicate non-nullables. This was because they wanted backward compatibility.
In my dream language (of which I'd probably be the only user!) I'd make the same choice as you, non-nullable by default.
I would also make it illegal to use the . operator on a nullable reference (or anything else that would dereference it). How would you use them? You'd have to convert them to non-nullables first. How would you do this? By testing them for null.
In Java and C#, the if statement can only accept a bool test expression. I'd extend it to accept the name of a nullable reference variable:
if (myObj)
{
// in this scope, myObj is non-nullable, so can be used
}
This special syntax would be unsurprising to C/C++ programmers. I'd prefer a special syntax like this to make it clear that we are doing a check that modifies the type of the name myObj within the truth-branch.
I'd add a further bit of sugar:
if (SomeMethodReturningANullable() into anotherObj)
{
// anotherObj is non-nullable, so can be used
}
This just gives the name anotherObj to the result of the expression on the left of the into, so it can be used in the scope where it is valid.
I'd do the same kind of thing for the ?: operator.
string message = GetMessage() into m ? m : "No message available";
Note that string message is non-nullable, but so are the two possible results of the test above, so the assignment is value.
And then maybe a bit of sugar for the presumably common case of substituting a value for null:
string message = GetMessage() or "No message available";
Obviously or would only be validly applied to a nullable type on the left side, and a non-nullable on the right side.
(I'd also have a built-in notion of ownership for instance fields; the compiler would generate the IDisposable.Dispose method automatically, and the ~Destructor syntax would be used to augment Dispose, exactly as in C++/CLI.)
Spec# had another syntactic extension related to non-nullables, due to the problem of ensuring that non-nullables had been initialized correctly during construction:
class SpecSharpExampleClass
{
private string! _nonNullableExampleField;
public SpecSharpExampleClass(string s)
: _nonNullableExampleField(s)
{
}
}
In other words, you have to initialize fields in the same way as you'd call other constructors with base or this - unless of course you initialize them directly next to the field declaration.
Have a look at the Elvis operator proposal for Java 7. This does something similar, in that it encapsulates a null check and method dispatch in one operator, with a specified return value if the object is null. Hence:
String s = mayBeNull?.toString() ?: "null";
checks if the String s is null, and returns the string "null" if so, and the value of the string if not. Food for thought, perhaps.
A couple of examples of similar features in other languages:
boost::optional (C++)
Maybe (Haskell)
There's also Nullable<T> (from C#) but that is not such a good example because of the different treatment of reference vs. value types.
In your example you could add a conditional message send operator, e.g.
b?->DoSomething();
To send a message to b only if it is non-null.
Have the nullability be a configuration setting, enforceable in the authors source code. That way, you will allow people who like nullable objects by default enjoy them in their source code, while allowing those who would like all their objects be non-nullable by default have exactly that. Additionally, provide keywords or other facility to explicitly mark which of your declarations of objects and types can be nullable and which cannot, with something like nullable and not-nullable, to override the global defaults.
For instance
/// "translation unit 1"
#set nullable
{ /// Scope of default override, making all declarations within the scope nullable implicitly
Bar bar; /// Can be null
non-null Foo foo; /// Overriden, cannot be null
nullable FooBar foobar; /// Overriden, can be null, even without the scope definition above
}
/// Same style for opposite
/// ...
/// Top-bottom, until reset by scoped-setting or simply reset to another value
#set nullable;
/// Nullable types implicitly
#clear nullable;
/// Can also use '#set nullable = false' or '#set not-nullable = true'. Ugly, but human mind is a very original, mhm, thing.
Many people argue that giving everyone what they want is impossible, but if you are designing a new language, try new things. Tony Hoare introduced the concept of null in 1965 because he could not resist (his own words), and we are paying for it ever since (also, his own words, the man is regretful of it). Point is, smart, experienced people make mistakes that cost the rest of us, don't take anyones advice on this page as if it were the only truth, including mine. Evaluate and think about it.
I've read many many rants on how it's us poor inexperienced programmers who really don't understand where to really use null and where not, showing us patterns and antipatterns that are meant to prevent shooting ourselves in the foot. All the while, millions of still inexperienced programmers produce more code in languages that allow null. I may be inexperienced, but I know which of my objects don't benefit from being nullable.
Here we are, 13 years later, and C# did it.
And, yes, this is the biggest improvement in languages since Barbara and Stephen invented types in 1974.:
Programming With Abstract Data Types
Barbara Liskov
Massachusetts Institute of Technology
Project MAC
Cambridge, Massachusetts
Stephen Zilles
Cambridge Systems Group
IBM Systems Development Division
Cambridge, Massachusetts
Abstract
The motivation
behind the work in very-high-level languages is to ease the
programming task by providing the programmer with a language
containing primitives or abstractions suitable to his problem area.
The programmer is then able to spend his effort in the right place; he
concentrates on solving his problem, and the resulting program will be
more reliable as a result. Clearly, this is a worthwhile goal.
Unfortunately, it is very difficult for a designer to select in
advance all the abstractions which the users of his language might
need. If a language is to be used at all, it is likely to be used to
solve problems which its designer did not envision, and for which the
abstractions embedded in the language are not sufficient. This paper
presents an approach which allows the set of built-in abstractions to
be augmented when the need for a new data abstraction is discovered.
This approach to the handling of abstraction is an outgrowth of work
on designing a language for structured programming. Relevant aspects
of this language are described, and examples of the use and
definitions of abstractions are given.
I think null values are good: They are a clear indication that you did something wrong. If you fail to initialize a reference somewhere, you'll get an immediate notice.
The alternative would be that values are sometimes initialized to a default value. Logical errors are then a lot more difficult to detect, unless you put detection logic in those default values. This would be the same as just getting a null pointer exception.