sortOn

Sort a list by comparing the results of a key function applied to each element. sortOn f is equivalent to sortBy (comparing f), but has the performance advantage of only evaluating f once for each element in the input list. This is called the decorate-sort-undecorate paradigm, or Schwartzian transform. Elements are arranged from lowest to highest, keeping duplicates in the order they appeared in the input. The argument must be finite.

Examples

>>> sortOn fst [(2, "world"), (4, "!"), (1, "Hello")]
[(1,"Hello"),(2,"world"),(4,"!")]

>>> sortOn length ["jim", "creed", "pam", "michael", "dwight", "kevin"]
["jim","pam","creed","kevin","dwight","michael"]

Performance notes

This function minimises the projections performed, by materialising the projections in an intermediate list. For trivial projections, you should prefer using sortBy with comparing, for example:

>>> sortBy (comparing fst) [(3, 1), (2, 2), (1, 3)]
[(1,3),(2,2),(3,1)]

Or, for the exact same API as sortOn, you can use `sortBy . comparing`:

>>> (sortBy . comparing) fst [(3, 1), (2, 2), (1, 3)]
[(1,3),(2,2),(3,1)]

Sort a NonEmpty on a user-supplied projection of its elements. See sortOn for more detailed information.

Examples

>>> sortOn fst $ (2, "world") :| [(4, "!"), (1, "Hello")]
(1,"Hello") :| [(2,"world"),(4,"!")]

>>> sortOn List.length ("jim" :| ["creed", "pam", "michael", "dwight", "kevin"])
"jim" :| ["pam","creed","kevin","dwight","michael"]

Performance notes

This function minimises the projections performed, by materialising the projections in an intermediate list. For trivial projections, you should prefer using sortBy with comparing, for example:

>>> sortBy (comparing fst) $ (3, 1) :| [(2, 2), (1, 3)]
(1,3) :| [(2,2),(3,1)]

Or, for the exact same API as sortOn, you can use `sortBy . comparing`:

>>> (sortBy . comparing) fst $ (3, 1) :| [(2, 2), (1, 3)]
(1,3) :| [(2,2),(3,1)]

sortWith is an alias for `sortBy . comparing`.

sortOn sorts the specified Seq by comparing the results of a key function applied to each element. The sort is stable, meaning the order of equal elements is preserved. sortOn f is equivalent to sortBy (compare `on` f), but has the performance advantage of only evaluating f once for each element in the input Seq. An example of using sortOn might be to sort a Seq of strings according to their length:

sortOn length (fromList ["alligator", "monkey", "zebra"]) == fromList ["zebra", "monkey", "alligator"]

If, instead, sortBy had been used, length would be evaluated on every comparison, giving <math> evaluations, rather than <math>. If f is very cheap (for example a record selector, or fst), sortBy (compare `on` f) will be faster than sortOn f.

Sort by comparing the results of a function applied to each element. The sort is stable, and the function is evaluated only once for each element.

Sort a NonEmpty on a user-supplied projection of its elements. See sortOn for more detailed information.

Examples

>>> sortOn fst $ (2, "world") :| [(4, "!"), (1, "Hello")]
(1,"Hello") :| [(2,"world"),(4,"!")]

>>> sortOn length $ "jim" :| ["creed", "pam", "michael", "dwight", "kevin"]
"jim" :| ["pam","creed","kevin","dwight","michael"]

Performance notes

This function minimises the projections performed, by materialising the projections in an intermediate list. For trivial projections, you should prefer using sortBy with comparing, for example:

>>> sortBy (comparing fst) $ (3, 1) :| [(2, 2), (1, 3)]
(1,3) :| [(2,2),(3,1)]

Or, for the exact same API as sortOn, you can use `sortBy . comparing`:

>>> (sortBy . comparing) fst $ (3, 1) :| [(2, 2), (1, 3)]
(1,3) :| [(2,2),(3,1)]

sortWith is an alias for `sortBy . comparing`. Since: 4.20.0.0

Sort a list by comparing the results of a key function applied to each element. sortOn f is equivalent to sortBy (comparing f), but has the performance advantage of only evaluating f once for each element in the input list. This is called the decorate-sort-undecorate paradigm, or Schwartzian transform. Elements are arranged from lowest to highest, keeping duplicates in the order they appeared in the input. The argument must be finite.

Examples

>>> sortOn fst [(2, "world"), (4, "!"), (1, "Hello")]
[(1,"Hello"),(2,"world"),(4,"!")]

>>> sortOn length ["jim", "creed", "pam", "michael", "dwight", "kevin"]
["jim","pam","creed","kevin","dwight","michael"]

Performance notes

This function minimises the projections performed, by materialising the projections in an intermediate list. For trivial projections, you should prefer using sortBy with comparing, for example:

>>> sortBy (comparing fst) [(3, 1), (2, 2), (1, 3)]
[(1,3),(2,2),(3,1)]

Or, for the exact same API as sortOn, you can use `sortBy . comparing`:

>>> (sortBy . comparing) fst [(3, 1), (2, 2), (1, 3)]
[(1,3),(2,2),(3,1)]

@since base-4.8.0.0

Sort a list by comparing the results of a key function applied to each element. sortOn f is equivalent to sortBy (comparing f), but has the performance advantage of only evaluating f once for each element in the input list. This is called the decorate-sort-undecorate paradigm, or Schwartzian transform. Elements are arranged from from lowest to highest, keeping duplicates in the order they appeared in the input.

>>> sortOn fst [(2, "world"), (4, "!"), (1, "Hello")]
[(1,"Hello"),(2,"world"),(4,"!")]

Same as sortBy . comparing. Since 0.7.0

Sort a list by comparing the results of a key function applied to each element. sortOn f is equivalent to sortBy (comparing f), but has the performance advantage of only evaluating f once for each element in the input list. This is called the decorate-sort-undecorate paradigm, or Schwartzian transform. Elements are arranged from lowest to highest, keeping duplicates in the order they appeared in the input.

>>> sortOn fst [(2, "world"), (4, "!"), (1, "Hello")]
[(1,"Hello"),(2,"world"),(4,"!")]

Return a list of the elements of the given Shell, sorted after applying the given function and keeping duplicates:

>>> sortOn id (select [1,4,2,3,3,7])
[1,2,3,3,4,7]

The sortOn function provides the decorate-sort-undecorate idiom, also known as the "Schwartzian transform".

Sort a list by comparing the results of a key function applied to each element. sortOn f is equivalent to sortBy (comparing f), but has the performance advantage of only evaluating f once for each element in the input list. This is called the decorate-sort-undecorate paradigm, or Schwartzian transform. Elements are arranged from lowest to highest, keeping duplicates in the order they appeared in the input.

>>> sortOn fst [(2, "world"), (4, "!"), (1, "Hello")]
[(1,"Hello"),(2,"world"),(4,"!")]

The argument must be finite.

sortOn sorts the specified NESeq by comparing the results of a key function applied to each element. sortOn f is equivalent to sortBy (compare `on` f), but has the performance advantage of only evaluating f once for each element in the input list. This is called the decorate-sort-undecorate paradigm, or Schwartzian transform. An example of using sortOn might be to sort a NESeq of strings according to their length:

sortOn length (fromList ("alligator" :| ["monkey", "zebra"])) == fromList ("zebra" :| ["monkey", "alligator"])

If, instead, sortBy had been used, length would be evaluated on every comparison, giving <math> evaluations, rather than <math>. If f is very cheap (for example a record selector, or fst), sortBy (compare `on` f) will be faster than sortOn f.

Sort a list by comparing the results of a key function applied to each element. sortOn f is equivalent to sortBy (comparing f), but has the performance advantage of only evaluating f once for each element in the input list. This is called the decorate-sort-undecorate paradigm, or Schwartzian transform. Elements are arranged from lowest to highest, keeping duplicates in the order they appeared in the input. The argument must be finite.

Examples

>>> sortOn fst [(2, "world"), (4, "!"), (1, "Hello")]
[(1,"Hello"),(2,"world"),(4,"!")]

>>> sortOn length ["jim", "creed", "pam", "michael", "dwight", "kevin"]
["jim","pam","creed","kevin","dwight","michael"]

Sort a list by comparing the results of a key function applied to each element. sortOn f is equivalent to sortBy (comparing f), but has the performance advantage of only evaluating f once for each element in the input list. This is called the decorate-sort-undecorate paradigm, or Schwartzian transform.

Sort the vector in ascending order by comparing the results of applying the key function to each element. The sort is stable, meaning the order of equal elements is preserved. sortOn f is equivalent to sortBy (comparing f), but only evaluates f once for each element.

O(n log n). Sorts a list by comparing the results of a key function applied to each element. sortOn f is equivalent to sortBy (comparing f), but has the performance advantage of only evaluating f once for each element in the input list. This is called the decorate-sort-undecorate paradigm, or Schwartzian transform. Elements are arranged from lowest to highest, keeping duplicates in the order they appeared in the input.

>>> sortOn fst $ slist [(2, "world"), (4, "!"), (1, "Hello")]
Slist {sList = [(1,"Hello"),(2,"world"),(4,"!")], sSize = Size 3}

Note: this function hangs on infinite slists.

Sort a list by applying a function to each element and comparing the results.

sortOn negate (mk6 1 4 2 8 5 7) === mk6 8 7 5 4 2 1

This variant of sortOn recomputes the sorting key every comparison. This can be better for functions that are cheap to compute. This is definitely better for projections, as the decorate-sort-undecorate saves nothing and adds two traversals of the list and extra memory allocation.

CPP for new functions not in old containers --------------------------------------------- Compatibility layer for sortOn.

unstableSortOn sorts the specified Seq by comparing the results of a key function applied to each element. unstableSortOn f is equivalent to unstableSortBy (compare `on` f), but has the performance advantage of only evaluating f once for each element in the input Seq. An example of using unstableSortOn might be to sort a Seq of strings according to their length:

unstableSortOn length (fromList ["alligator", "monkey", "zebra"]) == fromList ["zebra", "monkey", "alligator"]

If, instead, unstableSortBy had been used, length would be evaluated on every comparison, giving <math> evaluations, rather than <math>. If f is very cheap (for example a record selector, or fst), unstableSortBy (compare `on` f) will be faster than unstableSortOn f.

A combination of group and sort, using a part of the value to compare on.

groupSortOn length ["test","of","sized","item"] == [["of"],["test","item"],["sized"]]