Javascript – Lazy loading items below the fold

In: Javascript

10 Jul 2012

Quite often there are a number of heavy items that are loaded on a web page which is located below the fold. These items such as flash movies located at the bottom of a page, or in some instances facebook activity feeds which are located below the fold, simply add to a pages load and response time.

This is especially true for website landing pages where users more often than not are only interested in clicking through to some feature article located above the fold.

Here is a “mini” javascript library which will allow you to lazy load these items below the fold when a user first scrolls down the page. I’ve tested it in IE7, IE8, IE9, FF, Chrome, Safari, Opera etc.

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var Utilities = {
    RegisteredScrollFuncs: [],
    Timeout: 100,    
    GetScrollPosition: function() {
        var position = [0, 0];
        if (typeof window.pageYOffset != 'undefined') {
            position = [
                window.pageXOffset,
                window.pageYOffset
            ];
        }
        else if (typeof document.documentElement.scrollTop
            != 'undefined' && document.documentElement.scrollTop > 0) {
            position = [
                document.documentElement.scrollLeft,
                document.documentElement.scrollTop
            ];
        }
        else if (typeof document.body.scrollTop != 'undefined') {
            position = [
                document.body.scrollLeft,
                document.body.scrollTop
            ];
        }
        return position;
    },
    RegisterScrollListener: function(func) {
        this.RegisteredScrollFuncs.push(func);
 
        if(this.RegisteredScrollFuncs.length == 1)
            this.PollRegisteredListeners();
    },
    PollRegisteredListeners: function(e) {
 
        if (Utilities.GetScrollPosition()[1] > 0 && Utilities.RegisteredScrollFuncs.length > 0) {
            for (var i = 0; i < Utilities.RegisteredScrollFuncs.length; i++) {
                Utilities.RegisteredScrollFuncs[i]();
            }
            Utilities.RegisteredScrollFuncs = [];            
        }
        else {
            window.setTimeout(Utilities.PollRegisteredListeners, Utilities.Timeout);            
        }   
    },
    LoadFacebookActivity: function(d, s, id) {
        var js, fjs = d.getElementsByTagName(s)[0];
        if (d.getElementById(id)) return;
        js = d.createElement(s); js.id = id;
        js.src = "//connect.facebook.net/en_US/all.js#xfbml=1&appId=122480627837535";
        fjs.parentNode.insertBefore(js, fjs);
    }
}

The code above is actually very simple.

Stepping through the code

  1. RegisterScrollListener accepts a function as an argument and adds that function to an array.
  2. On the very first item which is added to the array it then kicks off the timer to poll the scroll bar position every 100ms.
  3. Once the scroll bar has moved, it will then run through the array of functions calling each one in turn.

And there we have it, a lazy polling solution that will allow us to perform any action that we desire when the user scrolls down the page.

Usage:

To use the library is very simple, there is no need to add anything to an onload method. Merely call 

Utilities.RegisterScrollListener(callback);

where callback is a pre-defined function you want to occur once the user has scrolled down the page.

In this instance we’re going to load the facebook activity widget.

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<div id="onfacebook" class="onfacebook"></div>      
    <script type="text/javascript">
        var onfacebook = '<h2>Your site on <b>Facebook</b></h2>'
                + '<div class="fb-like-box" data-href="http://www.facebook.com/YourSite" data-width="312" data-show-faces="true" data-stream="true" data-header="false"></div>';
 
            Utilities.RegisterScrollListener(function() {
                Utilities.LoadFacebookActivity(document, 'script', 'facebook-jssdk');
                document.getElementById("onfacebook").innerHTML = onfacebook;
            });            
    </script>

So there you have it, let me know if you find this useful.

Essays – Software Craftsmanship

In: Essays|Software Craftsmanship

28 Jun 2011

What is software craftsmanship?

In a previous blog post I attempted to define some of the fundamental concepts of what it is that I do on a daily basis. In the process of defining said foundations, I stumbled and stubbed my toe on another concept. Hidden inside the other, not unlike the layers of a matryoshka doll. The concept of software craftsmanship.

Software craftsmanship is a bottom up approach to software development by emphasizing the coding skills of the developers themselves. Traditionally software engineering practictioners were encouraged to see themselves as part of a well defined statistical analysis and mathematical rigor of an engineer with the benefits of introducing professionalism, predictability, precision, and mitigated risk.

The reason that this approach is fundamentally flawed is unquestionable. Software engineering as a field of study is far too immature and is constantly in a state of flux.

For civil engineering there exists well defined and well understood ways for constructing bridges and buildings that is safe for people to use and inhabit. A person who designs a bridge can be certain that the people constructing that bridge know how to read the blueprint, and what all the symbols and formulae mean.

No such generally accepted blueprints exist for software engineering. Everything can be done in a multitude of ways with different methods and ideology at its core.

Not unlike the guild traditions of medieval europe software development is a craft that has developed a body of wisdom, most of which isn’t taught at universities nor in certification classes. Most developers arrive at these tricks of the trade by independent experimentation, or more recently from learning from their peers and mentors.

Tools of the Software Craftsman

Learning how to use the tools of the trade is a core concept for producing quality code. Here is a list of some of the tools used to increase the quality, extendability, reliability of code.

  1. Use a version control system, like subversion, mercurial or git
    Source control is like a time machine for your code, you can always go back in time.
  2. Use a continuous integration tool like cruise control
    Continuous integration implements a continuous process of applying quality control to daily or nightly builds.
  3. Have a centralized bug tracking system like RT or BugTrac
    This is essential to maintaining software.
  4. For web development, use an automated build and deploy script
    If you don’t have an automated build and deploy script you may have problems
  5. Design software to be easily tested (Test Driven Development)
    Loose coupling promotes software that is more modular, and is easier to extend and maintain.
  6. Refactor early, refactor often
    Just as you would maintain a 747, fix the root of the problem when it needs it.
  7. Be pragmatic with project management
    Good, fast, cheap, pick TWO.
  8. Be aware of technical debt
    Technical debt is a balancing act, be sure to pay off your debts before they crush you.
  9. DRY – Dont repeat yourself
    Knowledge must have a single, unambiguous, authoritative representation within a system.
  10. YAGNI – You Aint Gonna Need It
    Implement features when you actually need them, not when you forsee you need them.
  11. Fix broken windows
    Fix broken design and poor code whenever you see them.
  12. Reduce cyclomatic complexity
    Reducing nested brackets will reduce cyclomatic complexity and increase readability and maintainability.
  13. Estimate before you start
    This will help you to spot potential problems up front
  14. Iterate your project schedule with code
    Use experience gained with the project to redefine the project time scales.
  15. Use an ubiquitous language
    Design and code in a common language that your users understand.
  16. Use exceptions for exceptional circumstances
    Handle anticipated problems in code. Reserve exceptions for exceptional things.
  17. Refactor to patterns
    See Gang of Four Design Patterns at the bottom of this essay.

Read the rest of this entry »

MapReduce in C#

In: C#|Functional Programming

25 Jun 2011

MapReduce is one of “those” buzz words that is going around at the moment. Mostly in part due to Google using it so successfully for their distributed indexing algorithms.

So what is MapReduce?

According to Wikipedia [http://en.wikipedia.org/wiki/MapReduce]

So MapReduce is an amalgamation of two higher order functions taken from functional programming.

Map and Reduce :. MapReduce.

Google took the concepts of Map and Reduce and designed a distributed computing framework around those two concepts. As it’s almost infinitely horizontally scalable, it lends itself to distributed computing quite easily.

So lets break up MapReduce into its 2 main components.
Read the rest of this entry »

Essays – What is software engineering?

In: Essays|Software Engineering

23 Jun 2011

What is software engineering?

If you’re in the industry or looking to get into the industry you’ll find yourself a little confused as to some of the labels and roles given to computer programmers.

  • Programmer
  • Developer
  • Analyst
  • Architect
  • Engineer

The first two terms are freely interchangeable, the dictionary term for a programmer is one who programs, the term for developer is one who develops. So is there a difference in the terms or the roles? No effectively these two terms are identical and is merely a preference in terminology. Even microsoft uses these terms interchangeably for their internal developers.

An analyst might not actually write code, in a lot of instances this will be a business analyst, someone who understands the business and also understands how to translate the business needs into terms that can be digested by a team of programmers or engineers. An analysts primary function is to write the specification or requirements documents required for a new project.

A software architect, is very much like the traditional architect. They are responsible for building the framework and designing the tools that the team will be using to develop the project. Software architects are senior level developers who have had years of experience in developing software and can quickly turn a functional specification into a framework which is maintainable and future proof. A software architect can also be responsible for mentoring the rest of the development team in how to use the framework.

An engineer is none of the above and could be any of the above. A software engineer is someone that subscribes to an engineering discipline.

Definition of software engineering

Software engineering is the “systematic approach to the analysis, design, assessment, implementation, test, maintenance and reengineering of software, that is, the application of engineering to software” [1]

Universities can’t teach you software engineering.

University

This is a crucial distinction to make because after 3-4 years of going to university to earn your degree and learning how to program computers in various languages. Designing relational database models, writing functional and requirements specifications, you are not actually qualified to start writing production quality code. Not without someone to mentor you. Or for that matter you are definitely not experienced enough to architect a solution for a company.

Read the rest of this entry »

Project Euler – Problem 2 (Haskell vs C#)

In: C#|Functional Programming|Haskell

19 Jun 2011

Problems with the .NET 3.5 implementation

During implementation of the same algorithm from Haskell to (Functional) C#, I found that I hit quite a large snag with .NET (3.5) number types. A fibonacci sequence very quickly accumulates into integers larger than an Unsigned Long can contain, in which case you would have to move to using .NET 4.0 / F# BigInt to get the benefits of using their operators. The below code works very well within the problem domain, however you will need to refactor this to use BigInt if you wish to move into larger Fibonnaci sequences.

Project Euler – Problem 2

Each new term in the Fibonacci sequence is generated by adding the previous two terms. By starting with 1 and 2, the first 10 terms will be:
1, 2, 3, 5, 8, 13, 21, 34, 55, 89, …
By considering the terms in the Fibonacci sequence whose values do not exceed four million, find the sum of the even-valued terms.

Haskell

module Main where
main = do
  let fibs = map fst $ iterate(\(a,b) -> (b,a+b)) (1,2)
  print $ sum(takeWhile(< 4000000) (filter even fibs))
Function Description
\ The backslash in this context is representing that the following code is a lambda (λ)
iterate Creates an infinite list where the first item is calculated by applying the function on the secod argument, the second item by applying the function on the previous result and so on.
$ The ‘$’ operator is for substituting parenthesis. Anything appearing after it will take precedence over anything that comes before.
fst Returns the first item in a tuple eg. fst (1,2) returns 1
map Returns a list constructed by applying a function (the first argument) to all items in a list passed as the second argument
filter returns a list constructed from members of a list (the second argument) fulfilling a condition given by the first argument
even returns True if the integral is even, False otherwise.
takeWhile creates a list from another one, it inspects the original list and takes from it its elements to the moment when the condition fails, then it stops processing
sum computes a sum of all elements in the list

Armed with the knowledge of what each of the above functions do, we can now translate the above code. Like most functional programs we read the code right to left meaning that the code on the right is passed to the code to the left of the chain.

given a list of even fibonnaci numbers
whose number doesn’t exceed 4 million
return the sum

Which is almost identical to the c# implementation using a YCombinator.

C# Implementation using YCombinator

public void Main()
{
	var sum = Fibbonacci(1, 2, Int32.MaxValue)
				.TakeWhile(x => x < 4000000)
				.Where(x => x % 2 == 0)
				.Sum();
 
     Console.WriteLine(sum);              
     Console.ReadLine();
}
 
 private delegate Func<TA, TB, TC, TR> Recursive<TA, TB, TC, TR>(Recursive<TA, TB, TC, TR> r);
 
  // Y Combinator
  private static Func<TA, TB, TC, TR> Y<TA,TB,TC,TR>(Func<Func<TA,TB,TC,TR>, Func<TA,TB,TC,TR>> f)
  {
        Recursive<TA,TB,TC,TR> rec = r => (a, b, c) => f(r(r))(a, b, c);
        return rec(rec);
  }
 
  private readonly Func<long, long, long, IEnumerable<long>> Fibbonacci = Y<long, long, long, IEnumerable<long>>(
        f => (n, m, cap) => n + m > cap
              ? Enumerable.Empty<long>()
              : Enumerable.Repeat(n + m, 1).Concat(f(m, n + m, cap))
  );

This c# solution does have a few issues, as pointed out earlier, additionally it doesn’t produce a real fibonnaci sequence even though it returns the same answer it drops the first two elements of the sequence.

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  return new List<long> {1,1}.Concat(Fibbonacci(1, 1, Int32.MaxValue))

Additionally you’ll notice that I’ve put in a check there so that we don’t cause stack overflow errors in adding numbers larger than Int.MaxValue. I believe refactoring to use BigInt should alleviate the need for this check.

If you’re wondering what is this YCombinator, see my previous post => Recursive lambda expressions in C# using YCombinator

Recursive lambda expressions in C# using YCombinator

In: C#|Functional Programming

17 Jun 2011

Lambda calculus can be summed up doing very much with very little, sacrificing only readability.

Personally i’ve found the inability to peform recusion with a lambda expression to be a little pain in what should be an elegant solution. Lets take a factorial for instance, how to write that as a lambda expression? The fathers of lambda calculus who invented lambda expressions in the 1930’s came up with a solution.

What is a lambda expression

A lambda expression simply put is an anonymous function that contains expressions or statements, it can be used to create delegates or expression tree types. All lambda expressions use the lambda operator =>, which reads ‘goes to’.

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x => x * 2;

Would read, x goes to x times 2.

Lambda recursion using self replication and self application

The basics of getting a lambda expression to recurse upon itself uses self application. Take a function, that accepts a function and applies that to itself.

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f => f(f);

For this situation we can’t really give it a Func<> type, so we define a special delegate.

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delegate T Recursive<T>(Recursive<T> self);
 
// We can now apply the self application
Recursive<int> lambda = f => f(f);
 
// What happens if we do this
lambda(lambda);  // Infinite recursion.

This while not practical is useful in knowing that we can get a lambda to call iteself. Now all we need to do is make it useful.

Currying
Lamdas give us great syntax for creating delegates or little functions you can assign to a variable.

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Func<int, int, int> add = (x, y) => x + y;
int a = add(3,4);  // a = 7

You can use the lambda syntax to build an add function that within it returns a function that is waiting for the other side of the add expression

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Func<int, Func<int, int>> curriedAdd = x => y => x + y;
int b = curriedAdd(2)(3); // b = 5

The result is the same, aside from the syntax.

We can now curry the curriedAdd function by supplying one argument and then use our new add6 function as many times as we like.

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var add6 = curriedAdd(6);
 
int c = add6(3);  // c = 9
int d = add6(5); // d = 11

Thankfully you don’t have to define your curried function when you’ve got a ‘Curry’ function to create it for you. Take an example that adds 4 things together.

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Func<int, int, int, int, int> addFourThings = (a, b, c, d) => a + b + c + d;
 
var curriedAddFourThings = Curry(addFourThings);
 
int result = curriedAddFourThings(1)(2)(3)(4); // result = 10
 
var addOne = curriedAddFourThings(1);
var addOneTwo = addOne(2);
var addOneTwoThree = addOneTwo(3);
 
int result2 = addOneTwoThree(4); // result 2 = 10

Here is the set of Curry function overloads

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public Func<T1, Func<T2, T3>> Curry<T1, T2, T3>(Func<T1, T2, T3> function)
{
    return a => b => function(a, b);
}
 
public Func<T1, Func<T2, Func<T3, T4>>> Curry<T1, T2, T3, T4>(Func<T1, T2, T3, T4> function)
{
    return a => b => c => function(a, b, c);
}
 
public Func<T1, Func<T2, Func<T3, Func<T4, T5>>>> Curry<T1, T2, T3, T4, T5>(Func<T1, T2, T3, T4, T5> function)
{
    return a => b => c => d => function(a, b, c, d);
}

You may noticed that we’re going to be using currying for the next section.

Y combinator

Haskell Curry and Alan Turing both came up with ways to write lambda expressions that has the same self application and replication as lambda specified above. Their version however also replicates something else, the application of a given function (these have come to be known as Y-Combinators).

A Y-Combinator can be described roughly as “Give me myself and a higher order function f, and i’ll return a function that is a fixed point of f”

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class Program
{
	static void Main()
	{		
		Console.WriteLine(fact(6));
		Console.ReadKey();
	}
 
	delegate Func<T1, T2> Recursive<T1, T2>(Recursive<T1, T2> r);
 
	// The Y Combinator
	static Func<T1, T2> Y<T1, T2>(Func<Func<T1, T2>, Func<T1, T2>> f)
	{
		Recursive<T1, T2> rec = r => a => f(r(r))(a);
		return rec(rec);
	}
 
	// The Fixed Point Generator
	static Func<long, long> fact = Y<long, long>(f => n => n > 1 ? n * f(n - 1) : 1);
}

Note that we are passing in the lambda expression into the Y Combinator

So what’s actually occurring above?

First Y is a lambda expression, so there’s nothing to evaluate or execute.

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 Y = y => f => x => f(y(y)(f))(x)

Next we evaluate the fixed point function (which I’ve actually summarised into the return statement of the Y Combinator).

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 F = Y(Y) = f => x => f(Y(Y))(f))(x)

The higher order function F is a lambda so nothing to evaluate:

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 F = fac => x => x > 1 ? x * fac(x - 1) : 1

Finally it gets to the lambda expression and then recurses through itself, because it’s defined as taking itself and an argument and applying it.

Now that you’re armed with the Y-Combinator see if you can do Project Euler – Problem 2 using the Y-Combinator. I’ll be posting my answer shortly.

Project Euler – Problem 4 (Haskell vs C#)

In: C#|Functional Programming|Haskell

16 Jun 2011

Learning a new programming language is perhaps one of the most rewarding experiences. You can learn about how another language performs a task, if it seems simpler how does this compare to your current language?

Problem 4 from Project Euler goes something like the folowing.

A palindromic number reads the same both ways.

The largest palindrome made from the product of two 2-digit numbers is 9009 = 91 × 99.

Find the largest palindrome made from the product of two 3-digit numbers.

Haskell

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module Main where
 
main = putStrLn output
output = show result
 
largestpalindrome :: Int
largestpalindrome = maximum [ p | i <- [100..999],
                           j <- [i..999],
                           let p = i * j,
                           let t = show p,
                           t == reverse t]
 
result = largestpalindrome

I almost missed this part in the actual question “A palindromic number reads the same both ways”. So a number is a palindrome if its string representation is equal to its reversed string representation.

The solution in Haskell relies on Generators and List Comprehension. In this case we’re generating a list of numbers using sequences, and then filtering that list by the numbers which read the same back to front.

In the above case you can read the function as follows.

Select the largest number from
the product of 2 3 digit numbers
where string of the product is equal to the reverse of the string of product

Based on that algorithm, here’s the c# version using linq

C# using Linq

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static void Main()
{		
	Console.WriteLine(
		string.Format("Largest Palindrome of the product of 3 digit numbers is: {0}", 
			Palindrome(ThreeDigitProducts()).Max())
		);
	Console.ReadKey();
}
 
private static IEnumerable<int> ThreeDigitProducts()
{
	return from i in Sequence(100, 999)
		 from j in Sequence(i, 999)
		 select i*j;				   				   
}
 
private static IEnumerable<int> Palindrome(IEnumerable<int> seedProducts)
{
	return from p in seedProducts
	       where p.ToString() == new string (p.ToString().Reverse().ToArray())
	       select p;
}
 
private static IEnumerable<int> Sequence(int from, int to)
{
	return Enumerable.Range(from, to).Where(x => x < to);
}

I have to say that I was quite surprised at how easy it was to generate near functional syntax in c# using linq.

Comments?

Haskell – A better prime number list using turners sieve and lazy pattern matching

In: Functional Programming|Haskell

30 May 2011

Learning haskell has its challenges. Most notably the terseness of the function composition, giving IMO a longer learning curve to master the syntax. This terseness is due to its roots in mathematics and academia, and so the functions read unsurprisingly like algebraic formulas.

I’ve been working my way through Project Euler to learn haskell in a more in-depth way than I would following a tutorial.

One of the biggest challenges I faced was to generate prime numbers in a reasonable response time, as can be found in Problem 3. Researching I found that prime numbers can be generated using the sieve of eratosthenes.

My first naieve approach to generating prime numbers.

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primes :: [Integer]
primes =  sieve [2..]
  where sieve (p:xs) = p : sieve [x | x <- xs, x `mod` p > 0]

The above code worked fine with the example provided by problem 3, however it took too long to evaluate. My second naive approach was to reduce the amount of checking by eliminating even numbers (no even number can be a prime).

What else can be done to speed up this function? In mathematics there’s a rule which states if a prime factor exists that is GREATER than the square root of the number, then there must be one LESS than the square root. So how does that work?

By testing all primes less than the square root of N, and found none is a factor of N. We can stop, because we know there can be no prime factor of N that is greater than the square root of N. Because, if there were, then there would also be a prime factor less than the square root of N, and we have already found out that there is none.

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primes = 2: sieve [3,5..] where
  sieve (p:xs) = p : sieve [x | x <- xs, (x < p*p) || (x `mod` p > 0)]

Once again this took too long to evaluate, even with the square root short circuiting this only gave up to a 20% increase in speed.

So what can we do further?

I had to research this one, and found an answer on Haskell Wiki. We can add in a deferred filter. Note that I can’t take credit for the below code.

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primes :: [Integer]
primes = 2: 3: sieve (tail primes) [5,7..]  
 
sieve (p:ps) xs = h ++ sieve ps [x | x <- t, rem x p /=0]
  where (h,~(_:t)) = span(< p*p) xs

span – given a predicate and a list, splits the list into two lists (returned as a tuple) such that elements in the first list are taken from the head of the list while the predicate is satisfied, and elements in the second list are the remaining elements from the list once the predicate is not satisfied.

tilde ~ – the tilde forces the compiler to not evaluate the value of the 2nd argument until it is actually used.

What is occurring above is using the span function to evaluate the square roots of h, however the tilde ~ forces the compiler to perform lazy evaluation on t until its value is actually required.

Netsuperbrain.com has a very good article on lazy pattern matching.

Effectively by combining a short circuit, and lazy pattern matching. We can now generate large quantities of prime numbers very very quickly.

I thought this would be worth writing up for a couple of reasons. Trying to research what the tilde operator actually does was quite frustrating, I knew that I had to stop haskell from evaluating the 2nd argument in the case of a match to the first. In addition the sieve of eratosthenes and researching the nature of prime number factors, also combined into learning more about the problem domain and so a more efficient program by an order of magnitude of about 20x.

Let me know if I’ve gotten anything wrong?

Power of Haskell

In: C#|Functional Programming|Haskell

27 May 2011

Learning haskell recently has really highlighted the power of the built in classes of haskell.

Compare a function in haskell to captialize the first letter in a sentence, vs c#.

Haskell

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import Data.Char
 
sentenceCase :: [Char] -> [Char]
sentenceCase [] = []
sentenceCase (x:xs) = [toUpper x] ++ map toLower xs

I think to be fair I should explain what the above function does.

  1. The first line is the type definition, states that the function will accept a list of chars (a string) and return a list of chars.
  2. The second line is a pattern match, in that if an empty string is provided then it will return an empty string.
  3. The third line is also a pattern match, however will only be accepted if the first pattern is passed over
  4. So in this case it will be run when accepting a non-empty string as it’s input parameter.
Function Description
sentenceCase The name of the function
(x:xs) The brackets are grouping the notation x:xs together so it’s evaluated as a single argument.
x:xs Is actually a special list shorthand that says for list xs, let the value x be the first element and xs be the remainder. Additionally this could be expressed as a:b:c:xs, abc representing the first 3 elements of the list and xs representing the remainder.
[] The left and right square brackets represent a list, so in this case we’re creating a new list filled with 1 character which will be uppercase.
toUpper From the Data.Char library accepts a Char and returns an upper case Char
toLower From the Data.Char library accepts a Char and returns a lower case Char
map Is a built in library function which performs a function on each individual member of a list and returns a resulting list. ie map (\x -> x * 2) [1,2,3] will return a list with the function (x * 2) applied to each of its elements [2,4,6]
++ Concatenates two lists.

So in 1 line of code you could read the above function as taking a list of characters, return the first element as uppercase and the remainder as lowercase.

Vs C#

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public static string ToSentenceCase(this string original)
{
	return String.IsNullOrEmpty(original) 
		? original 
		: string.Format("{0}{1}", Head(original).ToUpper(), Tail(original).ToLower());
}
 
public static string Head(this string original)
{
	return String.IsNullOrEmpty(original) 
		? original 
		: original.First().ToString();
}
 
public static string Tail(this string original)
{
	return String.IsNullOrEmpty(original) 
		? original 
		: original.Substring(1, original.Length - 1);
}

To be fair, c# doesn’t have a Head or Tail method built in. However even using extension classes, the built in pattern matching from Haskell seems to be a far nicer solution language wise than c#.

Is there a way to refactor this c# code futher?

Compiling Resources using Nant

In: C#|NAnt

24 Sep 2010

Including an embedded resource into your Nant script is not difficult at all.

Simply add a resources tag and include the Full Namespace. Note that you will also need to include /Path/To/Resource/File.resx in the include if you don’t have the resource file under the root folder of your library.

Here’s a working example.

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<csc target="library" output="../bin/Domain.dll" doc="../bin/Domain.dll.xml" debug="${debug}" warnaserror="true">
     <sources>
	<include name="**.cs" />
     </sources>
     <references>
          <include name="System.Configuration.dll" />
          <!-- other includes removed for brevity -->
      </references>
      <resources prefix="Domain.Tests.Resource">
        <include name="Tests/Resource/TestFixtureResource.resx" />
      </resources>
</csc>
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justin

Justin is a Senior Software Engineer living in Brisbane. A Polyglot Developer proficient in multiple programming languages including [C#, C/C++, Java, Android, Ruby..]. He's currently taking an active interest in Teaching Kids to Code, Functional Programming, Robotics, 3D Printers, RC Quad-Copters and Augmented Reality.

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