Function std.algorithm.sorting.sort

sort returns a std.range.SortedRange over the original range, which functions that can take advantage of sorted data can then use to know that the range is sorted and adjust accordingly. The std.range.SortedRange is a wrapper around the original range, so both it and the original range are sorted, but other functions won't know that the original range has been sorted, whereas they can know that std.range.SortedRange has been sorted.

The predicate is expected to satisfy certain rules in order for sort to behave as expected - otherwise, the program may fail on certain inputs (but not others) when not compiled in release mode, due to the cursory assumeSorted check. Specifically, sort expects less(a,b) && less(b,c) to imply less(a,c) (transitivity), and, conversely, !less(a,b) && !less(b,c) to imply !less(a,c). Note that the default predicate ("a < b") does not always satisfy these conditions for floating point types, because the expression will always be false when either a or b is NaN. Use std.math.cmp instead.

Prototype

SortedRange!(Range,less) sort(alias less, std.algorithm.mutation.SwapStrategy ss, Range)(
  Range r
)
if ((ss == SwapStrategy.unstable && (hasSwappableElements!Range || hasAssignableElements!Range) || ss != SwapStrategy.unstable && hasAssignableElements!Range) && isRandomAccessRange!Range && hasSlicing!Range && hasLength!Range);

Parameters

Returns

The initial range wrapped as a SortedRange with the predicate binaryFun!less.

Algorithms

is used for unstable sorting and Timsort is used for stable sorting. Each algorithm has benefits beyond stability. Introsort is generally faster but Timsort may achieve greater speeds on data with low entropy or if predicate calls are expensive. Introsort performs no allocations whereas Timsort will perform one or more allocations per call. Both algorithms have Ο(n log n) worst-case time complexity.

See Also

std.range.assumeSorted
std.range.SortedRange
std.algorithm.mutation.SwapStrategy
std.functional.binaryFun

Example

int[] array = [ 1, 2, 3, 4 ];
// sort in descending order
sort!("a > b")(array);
assert(array == [ 4, 3, 2, 1 ]);
// sort in ascending order
sort(array);
assert(array == [ 1, 2, 3, 4 ]);
// sort with a delegate
bool myComp(int x, int y) @safe pure nothrow { return x > y; }
sort!(myComp)(array);
assert(array == [ 4, 3, 2, 1 ]);

Example

// Showcase stable sorting
string[] words = [ "aBc", "a", "abc", "b", "ABC", "c" ];
sort!("toUpper(a) < toUpper(b)", SwapStrategy.stable)(words);
assert(words == [ "a", "aBc", "abc", "ABC", "b", "c" ]);

Example

// Sorting floating-point numbers in presence of NaN
double[] numbers = [-0.0, 3.0, -2.0, double.nan, 0.0, -double.nan];

import std.math : cmp, isIdentical;
import std.algorithm.comparison : equal;

sort!((a, b) => cmp(a, b) < 0)(numbers);

double[] sorted = [-double.nan, -2.0, -0.0, 0.0, 3.0, double.nan];
assert(numbers.equal!isIdentical(sorted));