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Resolving conflict in #1710
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@ -218,7 +218,7 @@ void main() {
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// from 1 to 100. Easy!
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// Just pass lambda expressions as template parameters!
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// You can pass any old function you like, but lambdas are convenient here.
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// You can pass any function you like, but lambdas are convenient here.
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auto num = iota(1, 101).filter!(x => x % 2 == 0)
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.map!(y => y ^^ 2)
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.reduce!((a, b) => a + b);
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@ -228,7 +228,7 @@ void main() {
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```
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Notice how we got to build a nice Haskellian pipeline to compute num?
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That's thanks to a D innovation know as Uniform Function Call Syntax.
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That's thanks to a D innovation know as Uniform Function Call Syntax (UFCS).
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With UFCS, we can choose whether to write a function call as a method
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or free function call! Walter wrote a nice article on this
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[here.](http://www.drdobbs.com/cpp/uniform-function-call-syntax/232700394)
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@ -238,21 +238,23 @@ is of some type A on any expression of type A as a method.
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I like parallelism. Anyone else like parallelism? Sure you do. Let's do some!
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```c
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// Let's say we want to populate a large array with the square root of all
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// consecutive integers starting from 1 (up until the size of the array), and we
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// want to do this concurrently taking advantage of as many cores as we have
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// available.
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import std.stdio;
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import std.parallelism : parallel;
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import std.math : sqrt;
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void main() {
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// We want take the square root every number in our array,
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// and take advantage of as many cores as we have available.
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// Create your large array
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auto arr = new double[1_000_000];
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// Use an index, and an array element by reference,
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// and just call parallel on the array!
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// Use an index, access every array element by reference (because we're
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// going to change each element) and just call parallel on the array!
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foreach(i, ref elem; parallel(arr)) {
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ref = sqrt(i + 1.0);
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}
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}
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```
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