Exploring Languages
with Interpreters
and Functional Programming
Chapter 18
H. Conrad Cunningham
04 April 2022
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Previous chapters examined first-order and higher-order list
programming. In particular, Chapter
15 explored the standard higher
order functions such as map
, filter
, and
concatMap
and
Chapter 16 explored function
concepts such as function composition.
This chapter examines list comprehensions. This feature does not add
new power to the language; the computations can be expressed with
combinations of features from the previous chapters. But list
comprehensions are often easier to write and to understand than
equivalent compositions of map
, filter
, concatMap
,
etc.
The source file for the code in this chapter is in file MoreLists.hs
.
Haskell provides a compact notation for expressing arithmetic sequences.
An arithmetic sequence (or progression) is a sequence of elements
from an enumerated type (i.e., a member of class Enum
) such
that consecutive elements have a fixed difference. Int
, Integer
, Float
, Double
, and
Char
are
all predefined members of this class.
[m..n]
produces the list of elements from m
up to n
in steps of one if m <= n
. It
produces the nil list otherwise.
Examples:
[1..5]
[1,2,3,4,5]
[5..1]
[]
This feature is implemented with Prelude function enumFromTo
applied as enumFromTo m n
.
[m,m’..n]
produces the list of elements from m
in steps of m’-m
. If m’ > m
then
the list is increasing up to n
.
If m’ < m
,
then it is decreasing.
Examples:
[1,3..9]
[1,3,5,7,9]
[9,8..5]
[9,8,7,6,5]
[9,8..11]
[]
This feature is implemented with Prelude function enumFromThenTo
applied as enumFromThenTo m’ m n
.
[m..]
and
[m,m’..]
produce potentially infinite lists beginning with m
and having steps 1 and m’-m
respectively.
These features are implemented with Prelude functions enumFrom
applied as enumFrom m
and
enumFromThen
applied as enumFromThen m m’
.
Of course, we can provide our own functions for sequences. Consider the following function to generate a geometric sequence.
A geometric sequence (or progression) is a sequence of elements from
an ordered, numeric type (i.e., a member of both classes Ord
and Num
) such that
consecutive elements have a fixed ratio.
geometric :: (Ord a, Num a) => a -> a -> a -> [a]
| m > n = []
geometric r m n | otherwise = m : geometric r (m*r) n
Example: geometric 2 1 10
[1,2,4,8]
The list comprehension is another powerful and compact notation for describing lists. A list comprehension has the form
[
expression|
qualifiers]
where expression is any Haskell expression.
The expression and the qualifiers in a comprehension may contain variables that are local to the comprehension. The values of these variables are bound by the qualifiers.
For each group of values bound by the qualifiers, the comprehension generates an element of the list whose value is the expression with the values substituted for the local variables.
There are three kinds of qualifiers that can be used in Haskell: generators, filters, and local definitions.
A generator is a qualifier of the form
pat
<-
exp
where exp is a list-valued expression. The generator extracts each element of exp that matches the pattern pat in the order that the elements appear in the list; elements that do not match the pattern are skipped.
Example:
[ n*n | n <- [1..5]]
[1,4,9,16,25]
A filter is a Boolean-valued expression used as a
qualifier in a list comprehension. These expressions work like
the filter
function; only values that make the expression True
are used
to form elements of the list comprehension.
Example:
[ n*n | even n ]
(if even n then [n*n] else [])
Above variable n
is global to
this expression, not local to the comprehension.
A local definition is a qualifier of the form
let
pat=
expr
introduces a local definition into the list comprehension.
Example:
[ n*n | let n = 2 ]
[4]
The real power of list comprehensions come from using several
qualifiers separated by commas on the right side of the vertical bar
|
.
Generators appearing later in the list of qualifiers vary more quickly than those that appear earlier. Speaking operationally, the generation “loop” for the later generator is nested within the “loop” for the earlier.
Example:
[ (m,n) | m<-[1..3], n<-[4,5] ]
[(1,4),(1,5),(2,4),(2,5),(3,4),(3,5)]
Qualifiers appearing later in the list of qualifiers may use values generated by qualifiers appearing earlier, but not vice versa.
Examples:
[ n*n | n<-[1..10], even n ]
[4,16,36,64,100]
[ (m,n) | m<-[1..3], n<-[1..m] ]
[ (1,1), (2,1), (2,2), (3,1), (3,2), (3,3)]
The generated values may or may not be used in the expression.
Examples:
[ 27 | n<-[1..3]]
[27,27,27]
[ x | x<-[1..3], y<-[1..2]]
[1,1,2,2,3,3]
List comprehensions are syntactic sugar. We can translate them into core Haskell features by applying the following identities.
For any expression e
,
| True ] [ e
is equivalent to:
[ e ]
For any expression e
and
qualifier q
,
| q ] [ e
is equivalent to:
| q, True ] [ e
For any expression e
,
boolean b
, and sequence of
qualifiers Q
,
| b, Q ] [ e
is equivalent to:
if b then [ e | Q ] else []
For any expression e
,
pattern p
, list-valued
expression l
, sequence of
qualifiers Q
, and fresh
variable ok
,
| p <- l, Q ] [ e
is equivalent to:
let ok p = [ e | Q ] -- p is a pattern
= []
ok _ in concatMap ok l
For any expression e
,
declaration list D
, and
sequence of qualifiers Q
,
| let D, Q ] [ e
is equivalent to:
let D in [ e | Q ]
Function concatMap
and
boolean value True
are as
defined in the Prelude.
As we saw in a previous chapter, concatMap
applies a list-returning function to each element of an input list and
then concatenates the resulting list of lists into a single list. Both
map
and
filter
can be defined in terms of concatMap
.
Consider the list comprehension:
*n | n<-[1..10], even n ] [ n
Apply identity 4:
let ok n = [ n*n | even n ]
= []
ok _ in concatMap ok [1..10]
Apply identity 2:
let ok n = [ n*n | even n, True ]
= []
ok _ in concatMap ok [1..10]
Apply identity 3:
let ok n = if (even n) then [ n*n | True ]
= []
ok _ in concatMap ok [1..10]
Apply identity 1:
let ok n = if (even n) then [ n*n ]
= []
ok _ in concatMap ok [1..10]
This section gives several examples where list comprehensions can be used to solve problems and express the solutions conveniently.
Consider a function spaces
that takes a number and generates a string with that many spaces.
spaces :: Int -> String
= [ ' ' | i<-[1..n]] spaces n
Note that when n < 1
the result is the empty string.
Consider a Boolean function isPrime
that takes a nonzero natural
number and determines whether the number is prime. (Remember
that a prime number is a natural number whose only natural number
factors are 1 and itself.)
isPrime :: Int -> Bool
| n > 1 = (factors n == [])
isPrime n where factors m = [ x | x<-[2..(m-1)], m `mod` x == 0 ]
= False isPrime _
Consider a function sqPrimes
that takes two natural numbers and returns the list of squares of the
prime numbers in the inclusive range from the first up to the
second.
sqPrimes :: Int -> Int -> [Int]
= [ x*x | x<-[m..n], isPrime x ] sqPrimes m n
Alternatively, this function could be defined using map
and filter
as
follows:
sqPrimes' :: Int -> Int -> [Int]
= map (\x -> x*x) (filter isPrime [m..n]) sqPrimes' m n
We can use a list comprehension to define (our, by now, old and dear
friend) the function doublePos
,
which doubles the positive integers in a list.
doublePos5 :: [Int] -> [Int]
= [ 2*x | x<-xs, 0 < x ] doublePos5 xs
Consider a program superConcat
that takes a list of lists
of lists and concatenates the elements into a single list.
superConcat :: [[[a]]] -> [a]
= [ x | xss<-xsss, xs<-xss, x<-xs ] superConcat xsss
Alternatively, this function could be defined using Prelude functions
concat
and map
and functional composition as follows:
superConcat' :: [[[a]]] -> [a]
= concat . map concat superConcat'
Consider a function position
that takes a list and a value of the same type. If the value occurs in
the list, position
returns the
position of the value’s first occurrence; if the value does not occur in
the list, position
returns
0.
In this problem, we generalize the problem to finding all occurrences of a value in a list. This more general problem is actually easier to solve.
positions :: Eq a => [a] -> a -> [Int]
= [ i | (i,y)<-zip [1..length xs] xs, x == y] positions xs x
Function zip
is useful
in pairing an element of the list with its position within the list. The
subsequent filter removes those pairs not involving the value x
. The “zipper” functions can be very
useful within list comprehensions.
Now that we have the positions of all the occurrences, we can use
head
to
get the first occurrence. Of course, we need to be careful that we
return 0 when there are no occurrences of x
in xs
.
position :: Eq a => [a] -> a -> Int
= head ( positions xs x ++ [0] ) position xs x
Because of lazy evaluation, this implementation of position
is not as inefficient as it
first appears. The function positions
will, in actuality, only
generate the head element of its output list.
Also because of lazy evaluation, the upper bound length xs
can
be left off the generator in positions
. In fact, the function is
more efficient to do so.
This chapter (18) examined list comprehensions. Although they do not add new power to the language, programs involving comprehensions are often easier to write and to understand than equivalent compositions of other functions.
Chapters 19 and 20 discuss problem solving techniques. Chapter 19 discusses systematic generalization of functions. Chapter 20 surveys various problem-solving techniques uses in this textbook and other sources.
The source file for the code in this chapter is in file MoreLists.hs
.
Show the list (or string) yielded by each of the following
Haskell list expressions. Display it using fully specified list bracket
notation, e.g., expression [1..5]
yields [1,2,3,4,5]
.
[7..11]
[11..7]
[3,6..12]
[12,9..2]
[ n*n | n <- [1..10], even n ]
[ 7 | n <- [1..4] ]
[ x | (x:xs) <- [Did, you, study?] ]
[ (x,y) | x <- [1..3], y <- [4,7] ]
[ (m,n) | m <- [1..3], n <- [1..m] ]
take 3 [ [1..n] | n <- [1..] ]
Translate the following expressions into expressions that use
list comprehensions. For example, map (*2) xs
could be translated to [ x*2 | x <- xs ]
.
map (\x -> 2*x-1) xs
filter p xs
map (^2) (filter even [1..5])
foldr (++) [] xss
map snd (filter (p . fst) (zip xs [1..]))
In 2016 and 2017, I adapted and revised my previous notes to form Chapter 7, More List Processing and Problem Solving, in the 2017 version of this textbook. In particular, I drew the information on More List Processing from:
In Summer 2018, I divided the 2017 More List Processing and Problem Solving chapter back into two chapters in the 2018 version of the textbook, now titled Exploring Languages with Interpreters and Functional Programming. Previous sections 7.2-7.3 (essentially chapter 7 of [1]) became the basis for new Chapter 18, More List Processing (this chapter), and the Problem Solving discussion became the basis for new Chapter 20, Problem Solving.
I retired from the full-time faculty in May 2019. As one of my post-retirement projects, I am continuing work on this textbook. In January 2022, I began refining the existing content, integrating additional separately developed materials, reformatting the document (e.g., using CSS), constructing a bibliography (e.g., using citeproc), and improving the build workflow and use of Pandoc.
I maintain this chapter as text in Pandoc’s dialect of Markdown using embedded LaTeX markup for the mathematical formulas and then translate the document to HTML, PDF, and other forms as needed.
Sequence (arithmetic, geometric), list comprehension (generator, filter, local definition, multiple generators and filters), syntactic sugar, translating list comprehensions to function calls, prime numbers, solve a harder problem first.