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// You know what's coming...
module hello;

import std.stdio;

// args is optional
void main(string[] args) {
    writeln("Hello, World!");
}

import std.stdio;

void main() {

    // Conditionals and loops work as expected.
    for(int i = 0; i < 10000; i++) {
        writeln(i);
    }

    // 'auto' can be used for inferring types.
    auto n = 1;

    // Numeric literals can use '_' as a digit separator for clarity.
    while(n < 10_000) {
        n += n;
    }

    do {
        n -= (n / 2);
    } while(n > 0);

    // For and while are nice, but in D-land we prefer 'foreach' loops.
    // The '..' creates a continuous range, including the first value
    // but excluding the last.
    foreach(n; 1..1_000_000) {
        if(n % 2 == 0)
            writeln(n);
    }

    // There's also 'foreach_reverse' when you want to loop backwards.
    foreach_reverse(n; 1..int.max) {
        if(n % 2 == 1) {
            writeln(n);
        } else {
            writeln("No!");
        }
    }
}

// Here, 'T' is a type parameter. Think '<T>' from C++/C#/Java.
struct LinkedList(T) {
    T data = null;

    // Use '!' to instantiate a parameterized type. Again, think '<T>'.
    LinkedList!(T)* next;
}

class BinTree(T) {
    T data = null;

    // If there is only one template parameter, we can omit the parentheses.
    BinTree!T left;
    BinTree!T right;
}

enum Day {
    Sunday,
    Monday,
    Tuesday,
    Wednesday,
    Thursday,
    Friday,
    Saturday,
}

// Use alias to create abbreviations for types.
alias IntList = LinkedList!int;
alias NumTree = BinTree!double;

// We can create function templates as well!
T max(T)(T a, T b) {
    if(a < b)
        return b;

    return a;
}

// Use the ref keyword to ensure pass by reference. That is, even if 'a' and 'b'
// are value types, they will always be passed by reference to 'swap()'.
void swap(T)(ref T a, ref T b) {
    auto temp = a;

    a = b;
    b = temp;
}

// With templates, we can also parameterize on values, not just types.
class Matrix(uint m, uint n, T = int) {
    T[m] rows;
    T[n] columns;
}

auto mat = new Matrix!(3, 3); // We've defaulted type 'T' to 'int'.

// Consider a class parameterized on types 'T' & 'U'.
class MyClass(T, U) {
    T _data;
    U _other;
}

// And "getter" and "setter" methods like so:
class MyClass(T, U) {
    T _data;
    U _other;

    // Constructors are always named 'this'.
    this(T t, U u) {
        // This will call the setter methods below.
        data = t;
        other = u;
    }

    // getters
    @property T data() {
        return _data;
    }

    @property U other() {
        return _other;
    }

    // setters
    @property void data(T t) {
        _data = t;
    }

    @property void other(U u) {
        _other = u;
    }
}

// And we use them in this manner:
void main() {
    auto mc = new MyClass!(int, string)(7, "seven");

    // Import the 'stdio' module from the standard library for writing to
    // console (imports can be local to a scope).
    import std.stdio;

    // Call the getters to fetch the values.
    writefln("Earlier: data = %d, str = %s", mc.data, mc.other);

    // Call the setters to assign new values.
    mc.data = 8;
    mc.other = "eight";

    // Call the getters again to fetch the new values.
    writefln("Later: data = %d, str = %s", mc.data, mc.other);
}

import std.algorithm : map, filter, reduce;
import std.range : iota; // builds an end-exclusive range
import std.stdio;

void main() {
    // We want to print the sum of a list of squares of even ints
    // from 1 to 100. Easy!

    // Just pass lambda expressions as template parameters!
    // You can pass any function you like, but lambdas are convenient here.
    auto num = iota(1, 101).filter!(x => x % 2 == 0)
                           .map!(y => y ^^ 2)
                           .reduce!((a, b) => a + b);

    writeln(num);
}

// Let's say we want to populate a large array with the square root of all
// consecutive integers starting from 1 (up until the size of the array), and we
// want to do this concurrently taking advantage of as many cores as we have
// available.

import std.stdio;
import std.parallelism : parallel;
import std.math : sqrt;

void main() {
    // Create your large array
    auto arr = new double[1_000_000];

    // Use an index, access every array element by reference (because we're
    // going to change each element) and just call parallel on the array!
    foreach(i, ref elem; parallel(arr)) {
        elem = sqrt(i + 1.0);
    }
}