Understanding Computation (34 page)

Read Understanding Computation Online

Authors: Tom Stuart

Tags: #COMPUTERS / Programming / General

Beautiful.

Advanced Programming Techniques

Constructing programs entirely out of procs takes a lot of effort,
but we’ve seen that it’s possible to get real work done as long as we
don’t mind applying a bit of ingenuity. Let’s take a quick look at a
couple of other techniques for writing code in this minimal
environment.

Infinite streams

Using code to
represent data has some interesting advantages. Our proc-based lists don’t
have to be static: a list is just code that does the right thing when we pass it to
FIRST
and
REST
, so
we can easily implement lists that calculate their contents on the fly, also
known as
streams
. In fact, there’s no reason why
streams even need to be finite, because the calculation only has to generate the list
contents as they’re consumed, so it can keep producing new values indefinitely.

For example, here’s how to implement an infinite stream of
zeros:

ZEROS
=
Z
[->
f
{
UNSHIFT
[
f
][
ZERO
]
}
]
Note

This is the “no cheating” version of
ZEROS =
UNSHIFT[ZEROS][ZERO]
, a data structure defined in terms of itself. As
programmers, we’re generally comfortable with the idea of defining a recursive function
in terms of itself, but defining a data structure in terms of itself might seem weird
and unusual; in this setting, they’re exactly the same thing, and the Z combinator makes
both completely legitimate.

On the console, we can see that
ZEROS
behaves just
like a list, albeit one with no end in sight:

>>
to_integer
(
FIRST
[
ZEROS
]
)
=> 0
>>
to_integer
(
FIRST
[
REST
[
ZEROS
]]
)
=> 0
>>
to_integer
(
FIRST
[
REST
[
REST
[
REST
[
REST
[
REST
[
ZEROS
]]]]]]
)
=> 0

A helper method to turn this stream into a Ruby array would be
convenient, but
to_array
will run
forever unless we explicitly stop the conversion process. An optional
“maximum size” argument does the trick:

def
to_array
(
l
,
count
=
nil
)
array
=
[]
until
to_boolean
(
IS_EMPTY
[
l
]
)
||
count
==
0
array
.
push
(
FIRST
[
l
]
)
l
=
REST
[
l
]
count
=
count
-
1
unless
count
.
nil?
end
array
end

This lets us retrieve any number of elements from the stream and
turn them into an array:

>>
to_array
(
ZEROS
,
5
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [0, 0, 0, 0, 0]
>>
to_array
(
ZEROS
,
10
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
>>
to_array
(
ZEROS
,
20
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

ZEROS
doesn’t calculate a new element each time,
but that’s easy enough to do. Here’s a stream that counts upward from a given
number:

>>
UPWARDS_OF
=
Z
[->
f
{
->
n
{
UNSHIFT
[->
x
{
f
[
INCREMENT
[
n
]][
x
]
}
][
n
]
}
}
]
=> #
>>
to_array
(
UPWARDS_OF
[
ZERO
]
,
5
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [0, 1, 2, 3, 4]
>>
to_array
(
UPWARDS_OF
[
FIFTEEN
]
,
20
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34]

A more elaborate stream contains all the multiples of a given
number:

>>
MULTIPLES_OF
=
->
m
{
Z
[->
f
{
->
n
{
UNSHIFT
[->
x
{
f
[
ADD
[
m
][
n
]][
x
]
}
][
n
]
}
}
][
m
]
}
=> #
>>
to_array
(
MULTIPLES_OF
[
TWO
]
,
10
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [2, 4, 6, 8, 10, 12, 14, 16, 18, 20]
>>
to_array
(
MULTIPLES_OF
[
FIVE
]
,
20
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100]

Remarkably, we can manipulate these infinite streams like any
other list. For example, we can make a new stream by mapping a proc
over an existing one:

>>
to_array
(
MULTIPLES_OF
[
THREE
]
,
10
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [3, 6, 9, 12, 15, 18, 21, 24, 27, 30]
>>
to_array
(
MAP
[
MULTIPLES_OF
[
THREE
]][
INCREMENT
]
,
10
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [4, 7, 10, 13, 16, 19, 22, 25, 28, 31]
>>
to_array
(
MAP
[
MULTIPLES_OF
[
THREE
]][
MULTIPLY
[
TWO
]]
,
10
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [6, 12, 18, 24, 30, 36, 42, 48, 54, 60]

We can even write procs that combine two streams to make a
third:

>>
MULTIPLY_STREAMS
=
Z
[->
f
{
->
k
{
->
l
{
UNSHIFT
[->
x
{
f
[
REST
[
k
]][
REST
[
l
]][
x
]
}
][
MULTIPLY
[
FIRST
[
k
]][
FIRST
[
l
]]]
}
}
}
]
=> #
>>
to_array
(
MULTIPLY_STREAMS
[
UPWARDS_OF
[
ONE
]][
MULTIPLES_OF
[
THREE
]]
,
10
)
.
map
{
|
p
|
to_integer
(
p
)
}
=> [3, 12, 27, 48, 75, 108, 147, 192, 243, 300]

Since the contents of a stream can be generated by any
computation, there’s nothing to stop us creating an infinite list of
the Fibonacci series, or the prime numbers, or all possible strings in
alphabetical order, or anything else computable. This abstraction is a
powerful one and doesn’t require any clever features on top of what we
already
have.

Native Ruby Streams

Ruby has
an
Enumerator
class
that can be used to build infinite streams without relying on procs.
Here’s how to implement the “multiples of a given number”
stream:

def
multiples_of
(
n
)
Enumerator
.
new
do
|
yielder
|
value
=
n
loop
do
yielder
.
yield
(
value
)
value
=
value
+
n
end
end
end

This method returns an
Enumerator
that performs one iteration of
the
loop
each time we call
#next
on it, returning the
yielded value each time:

>>
multiples_of_three
=
multiples_of
(
3
)
=> #:each>
>>
multiples_of_three
.
next
=> 3
>>
multiples_of_three
.
next
=> 6
>>
multiples_of_three
.
next
=> 9

The
Enumerator
class
includes
the
Enumerable
module, so we can also call methods like
#first
,
#take
, and
#detect
:

>>
multiples_of
(
3
)
.
first
=> 3
>>
multiples_of
(
3
)
.
take
(
10
)
=> [3, 6, 9, 12, 15, 18, 21, 24, 27, 30]
>>
multiples_of
(
3
)
.
detect
{
|
x
|
x
>
100
}
=> 102

Other
Enumerable
methods like
#map
and
#select
won’t work properly on
this
Enumerator
, because
they’ll try to process every item in the infinite stream. However, Ruby
2.0’s
Enumerator::Lazy
class reimplements some
Enumerable
methods so that they work even when the
underlying
Enumerator
goes on forever. We can get an
Enumerator::Lazy
by calling
#lazy
on an
Enumerator
,
and then we can manipulate these infinite streams just as we could with the proc
versions:

>>
multiples_of
(
3
)
.
lazy
.
map
{
|
x
|
x
*
2
}
.
take
(
10
)
.
force
=> [6, 12, 18, 24, 30, 36, 42, 48, 54, 60]
>>
multiples_of
(
3
)
.
lazy
.
map
{
|
x
|
x
*
2
}
.
select
{
|
x
|
x
>
100
}
.
take
(
10
)
.
force
=> [102, 108, 114, 120, 126, 132, 138, 144, 150, 156]
>>
multiples_of
(
3
)
.
lazy
.
zip
(
multiples_of
(
4
))
.
map
{
|
a
,
b
|
a
*
b
}
.
take
(
10
)
.
force
=> [12, 48, 108, 192, 300, 432, 588, 768, 972, 1200]

This isn’t quite as tidy as proc-based lists—we have to write
special code to work with infinite streams, instead of just treating
them like conventional
Enumerable
s—but it shows that Ruby does
have a built-in way of handling these unusual data
structures.

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