memoize(3)

NAME

Memoize - Make functions faster by trading space for time

SYNOPSIS

# This is the documentation for Memoize 1.01
use Memoize;
memoize('slow_function');
slow_function(arguments);    # Is faster  than  it
was before
This is normally all you need to know.  However, many
options are available:
memoize(function, options...);
Options include:
NORMALIZER => function
INSTALL => new_name
SCALAR_CACHE => 'MEMORY'
SCALAR_CACHE => ['HASH', cache_hash ]
SCALAR_CACHE => 'FAULT'
SCALAR_CACHE => 'MERGE'
LIST_CACHE => 'MEMORY'
LIST_CACHE => ['HASH', cache_hash ]
LIST_CACHE => 'FAULT'
LIST_CACHE => 'MERGE'

DESCRIPTION

`Memoizing' a function makes it faster by trading space
for time. It does this by caching the return values of
the function in a table. If you call the function again
with the same arguments, "memoize" jumps in and gives you
the value out of the table, instead of letting the func
tion compute the value all over again.

Here is an extreme example. Consider the Fibonacci
sequence, defined by the following function:
# Compute Fibonacci numbers
sub fib {
my $n = shift;
return $n if $n < 2;
fib($n-1) + fib($n-2);
}
This function is very slow. Why? To compute fib(14), it
first wants to compute fib(13) and fib(12), and add the
results. But to compute fib(13), it first has to compute
fib(12) and fib(11), and then it comes back and computes
fib(12) all over again even though the answer is the same.
And both of the times that it wants to compute fib(12), it
has to compute fib(11) from scratch, and then it has to do
it again each time it wants to compute fib(13). This
function does so much recomputing of old results that it
takes a really long time to run---fib(14) makes 1,200
extra recursive calls to itself, to compute and recompute
things that it already computed.
This function is a good candidate for memoization. If you
memoize the `fib' function above, it will compute fib(14)
exactly once, the first time it needs to, and then save
the result in a table. Then if you ask for fib(14) again,
it gives you the result out of the table. While computing
fib(14), instead of computing fib(12) twice, it does it
once; the second time it needs the value it gets it from
the table. It doesn't compute fib(11) four times; it com
putes it once, getting it from the table the next three
times. Instead of making 1,200 recursive calls to `fib',
it makes 15. This makes the function about 150 times
faster.
You could do the memoization yourself, by rewriting the
function, like this:

# Compute Fibonacci numbers, memoized version
{ my @fib;
sub fib {
my $n = shift;
return $fib[$n] if defined $fib[$n];
return $fib[$n] = $n if $n < 2;
$fib[$n] = fib($n-1) + fib($n-2);
}
}
Or you could use this module, like this:

use Memoize;
memoize('fib');
# Rest of the fib function just like the original
version.
This makes it easy to turn memoizing on and off.
Here's an even simpler example: I wrote a simple ray
tracer; the program would look in a certain direction,
figure out what it was looking at, and then convert the
`color' value (typically a string like `red') of that
object to a red, green, and blue pixel value, like this:

for ($direction = 0; $direction < 300; $direction++) {
# Figure out which object is in direction $direction
$color = $object->{color};
($r, $g, $b) = @{&ColorToRGB($color)};
...
}
Since there are relatively few objects in a picture, there
are only a few colors, which get looked up over and over
again. Memoizing "ColorToRGB" sped up the program by sev
eral percent.

DETAILS

This module exports exactly one function, "memoize". The
rest of the functions in this package are None of Your
Business.

You should say
memoize(function)
where "function" is the name of the function you want to
memoize, or a reference to it. "memoize" returns a refer
ence to the new, memoized version of the function, or
"undef" on a non-fatal error. At present, there are no
non-fatal errors, but there might be some in the future.
If "function" was the name of a function, then "memoize"
hides the old version and installs the new memoized ver
sion under the old name, so that "&function(...)" actually
invokes the memoized version.

OPTIONS

There are some optional options you can pass to "memoize"
to change the way it behaves a little. To supply options,
invoke "memoize" like this:
memoize(function, NORMALIZER => function,
INSTALL => newname,
SCALAR_CACHE => option,
LIST_CACHE => option
);
Each of these options is optional; you can include some,
all, or none of them.
INSTALL
If you supply a function name with "INSTALL", memoize will
install the new, memoized version of the function under
the name you give. For example,

memoize('fib', INSTALL => 'fastfib')
installs the memoized version of "fib" as "fastfib"; with
out the "INSTALL" option it would have replaced the old
"fib" with the memoized version.
To prevent "memoize" from installing the memoized version
anywhere, use "INSTALL => undef".
NORMALIZER
Suppose your function looks like this:

# Typical call: f('aha!', A => 11, B => 12);
sub f {
my $a = shift;
my %hash = @_;
$hash{B} ||= 2; # B defaults to 2
$hash{C} ||= 7; # C defaults to 7
# Do something with $a, %hash
}
Now, the following calls to your function are all com
pletely equivalent:

f(OUCH);
f(OUCH, B => 2);
f(OUCH, C => 7);
f(OUCH, B => 2, C => 7);
f(OUCH, C => 7, B => 2);
(etc.)
However, unless you tell "Memoize" that these calls are
equivalent, it will not know that, and it will compute the
values for these invocations of your function separately,
and store them separately.
To prevent this, supply a "NORMALIZER" function that turns
the program arguments into a string in a way that equiva
lent arguments turn into the same string. A "NORMALIZER"
function for "f" above might look like this:

sub normalize_f {
my $a = shift;
my %hash = @_;
$hash{B} ||= 2;
$hash{C} ||= 7;
join(',', $a, map ($_ => $hash{$_}) sort keys
%hash);
}
Each of the argument lists above comes out of the "normal
ize_f" function looking exactly the same, like this:

OUCH,B,2,C,7
You would tell "Memoize" to use this normalizer this way:

memoize('f', NORMALIZER => 'normalize_f');
"memoize" knows that if the normalized version of the
arguments is the same for two argument lists, then it can
safely look up the value that it computed for one argument
list and return it as the result of calling the function
with the other argument list, even if the argument lists
look different.
The default normalizer just concatenates the arguments
with character 28 in between. (In ASCII, this is called
FS or control-.) This always works correctly for func
tions with only one string argument, and also when the
arguments never contain character 28. However, it can
confuse certain argument lists:

normalizer("a 34", "b")
normalizer("a", " 34b")
normalizer("a 34 34b")
for example.
Since hash keys are strings, the default normalizer will
not distinguish between "undef" and the empty string. It
also won't work when the function's arguments are refer
ences. For example, consider a function "g" which gets
two arguments: A number, and a reference to an array of
numbers:

g(13, [1,2,3,4,5,6,7]);
The default normalizer will turn this into something like
"13 34ARRAY(0x436c1f)". That would be all right, except
that a subsequent array of numbers might be stored at a
different location even though it contains the same data.
If this happens, "Memoize" will think that the arguments
are different, even though they are equivalent. In this
case, a normalizer like this is appropriate:

sub normalize { join ' ', $_[0], @{$_[1]} }
For the example above, this produces the key "13 1 2 3 4 5
6 7".
Another use for normalizers is when the function depends
on data other than those in its arguments. Suppose you
have a function which returns a value which depends on the
current hour of the day:

sub on_duty {
my ($problem_type) = @_;
my $hour = (localtime)[2];
open my $fh, "$DIR/$problem_type" or die...;
my $line;
while ($hour-- > 0)
$line = <$fh>;
}
return $line;
}
At 10:23, this function generates the 10th line of a data
file; at 3:45 PM it generates the 15th line instead. By
default, "Memoize" will only see the $problem_type argu
ment. To fix this, include the current hour in the nor
malizer:

sub normalize { join ' ', (localtime)[2], @_ }
The calling context of the function (scalar or list con
text) is propagated to the normalizer. This means that if
the memoized function will treat its arguments differently
in list context than it would in scalar context, you can
have the normalizer function select its behavior based on
the results of "wantarray". Even if called in a list con
text, a normalizer should still return a single string.
"SCALAR_CACHE", "LIST_CACHE"
Normally, "Memoize" caches your function's return values
into an ordinary Perl hash variable. However, you might
like to have the values cached on the disk, so that they
persist from one run of your program to the next, or you
might like to associate some other interesting semantics
with the cached values.
There's a slight complication under the hood of "Memoize":
There are actually two caches, one for scalar values and
one for list values. When your function is called in
scalar context, its return value is cached in one hash,
and when your function is called in list context, its
value is cached in the other hash. You can control the
caching behavior of both contexts independently with these
options.
The argument to "LIST_CACHE" or "SCALAR_CACHE" must either
be one of the following four strings:

MEMORY
FAULT
MERGE
HASH
or else it must be a reference to a list whose first ele
ment is one of these four strings, such as "[HASH, argu
ments...]".
"MEMORY"
"MEMORY" means that return values from the function
will be cached in an ordinary Perl hash variable. The
hash variable will not persist after the program
exits. This is the default.
"HASH"
"HASH" allows you to specify that a particular hash
that you supply will be used as the cache. You can
tie this hash beforehand to give it any behavior you
want.
A tied hash can have any semantics at all. It is typ
ically tied to an on-disk database, so that cached
values are stored in the database and retrieved from
it again when needed, and the disk file typically per
sists after your program has exited. See "perltie"
for more complete details about "tie".
A typical example is:

use DB_File;
tie my %cache => 'DB_File', $filename, O_RD
WR|O_CREAT, 0666;
memoize 'function', SCALAR_CACHE => [HASH =>
cache];
This has the effect of storing the cache in a
"DB_File" database whose name is in $filename. The
cache will persist after the program has exited. Next
time the program runs, it will find the cache already
populated from the previous run of the program. Or
you can forcibly populate the cache by constructing a
batch program that runs in the background and popu
lates the cache file. Then when you come to run your
real program the memoized function will be fast
because all its results have been precomputed.
"TIE"
This option is no longer supported. It is still docu
mented only to aid in the debugging of old programs
that use it. Old programs should be converted to use
the "HASH" option instead.

memoize ... [TIE, PACKAGE, ARGS...]
is merely a shortcut for

require PACKAGE;
{ my %cache;
tie %cache, PACKAGE, ARGS...;
}
memoize ... [HASH => cache];
"FAULT"
"FAULT" means that you never expect to call the func
tion in scalar (or list) context, and that if "Memo
ize" detects such a call, it should abort the program.
The error message is one of

`foo' function called in forbidden list con
text at line ...
`foo' function called in forbidden scalar con
text at line ...
"MERGE"
"MERGE" normally means the function does not distin
guish between list and sclar context, and that return
values in both contexts should be stored together.
"LIST_CACHE => MERGE" means that list context return
values should be stored in the same hash that is used
for scalar context returns, and "SCALAR_CACHE =>
MERGE" means the same, mutatis mutandis. It is an
error to specify "MERGE" for both, but it probably
does something useful.
Consider this function:

sub pi { 3; }
Normally, the following code will result in two calls
to "pi":

$x = pi();
($y) = pi();
$z = pi();
The first call caches the value 3 in the scalar cache;
the second caches the list "(3)" in the list cache.
The third call doesn't call the real "pi" function; it
gets the value from the scalar cache.
Obviously, the second call to "pi" is a waste of time,
and storing its return value is a waste of space.
Specifying "LIST_CACHE => MERGE" will make "memoize"
use the same cache for scalar and list context return
values, so that the second call uses the scalar cache
that was populated by the first call. "pi" ends up
being called only once, and both subsequent calls
return 3 from the cache, regardless of the calling
context.
Another use for "MERGE" is when you want both kinds of
return values stored in the same disk file; this saves
you from having to deal with two disk files instead of
one. You can use a normalizer function to keep the
two sets of return values separate. For example:

tie my %cache => 'MLDBM', 'DB_File', $file
name, ...;
memoize 'myfunc',
NORMALIZER => 'n',
SCALAR_CACHE => [HASH => cache],
LIST_CACHE => MERGE,
;
sub n {
my $context = wantarray() ? 'L' : 'S';
# ... now compute the hash key from the ar
guments ...
$hashkey = "$context:$hashkey";
}
This normalizer function will store scalar context
return values in the disk file under keys that begin
with "S:", and list context return values under keys
that begin with "L:".

OTHER FACILITIES

"unmemoize"

There's an "unmemoize" function that you can import if you
want to. Why would you want to? Here's an example: Sup
pose you have your cache tied to a DBM file, and you want
to make sure that the cache is written out to disk if
someone interrupts the program. If the program exits nor
mally, this will happen anyway, but if someone types con
trol-C or something then the program will terminate imme
diately without synchronizing the database. So what you
can do instead is
$SIG{INT} = sub { unmemoize 'function' };
"unmemoize" accepts a reference to, or the name of a pre
viously memoized function, and undoes whatever it did to
provide the memoized version in the first place, including
making the name refer to the unmemoized version if appro
priate. It returns a reference to the unmemoized version
of the function.
If you ask it to unmemoize a function that was never memo
ized, it croaks.
"flush_cache"
"flush_cache(function)" will flush out the caches, dis
carding all the cached data. The argument may be a func
tion name or a reference to a function. For finer control
over when data is discarded or expired, see the documenta
tion for "Memoize::Expire", included in this package.
Note that if the cache is a tied hash, "flush_cache" will
attempt to invoke the "CLEAR" method on the hash. If
there is no "CLEAR" method, this will cause a run-time
error.
An alternative approach to cache flushing is to use the
"HASH" option (see above) to request that "Memoize" use a
particular hash variable as its cache. Then you can exam
ine or modify the hash at any time in any way you desire.
You may flush the cache by using "%hash = ()".

CAVEATS

Memoization is not a cure-all:

· Do not memoize a function whose behavior depends on
program state other than its own arguments, such as
global variables, the time of day, or file input.
These functions will not produce correct results when
memoized. For a particularly easy example:

sub f {
time;
}
This function takes no arguments, and as far as "Memo
ize" is concerned, it always returns the same result.
"Memoize" is wrong, of course, and the memoized ver
sion of this function will call "time" once to get the
current time, and it will return that same time every
time you call it after that.
· Do not memoize a function with side effects.

sub f {
my ($a, $b) = @_;
my $s = $a + $b;
print "$a + $b = $s.0;
}
This function accepts two arguments, adds them, and
prints their sum. Its return value is the numuber of
characters it printed, but you probably didn't care
about that. But "Memoize" doesn't understand that.
If you memoize this function, you will get the result
you expect the first time you ask it to print the sum
of 2 and 3, but subsequent calls will return 1 (the
return value of "print") without actually printing
anything.
· Do not memoize a function that returns a data
structure that is modified by its caller.
Consider these functions: "getusers" returns a list
of users somehow, and then "main" throws away the
first user on the list and prints the rest:

sub main {
my $userlist = getusers();
shift @$userlist;
foreach $u (@$userlist) {
print "User $u0;
}
}
sub getusers {
my @users;
# Do something to get a list of users;
@users; # Return reference to list.
}
If you memoize "getusers" here, it will work right
exactly once. The reference to the users list will be
stored in the memo table. "main" will discard the
first element from the referenced list. The next time
you invoke "main", "Memoize" will not call "getusers";
it will just return the same reference to the same
list it got last time. But this time the list has
already had its head removed; "main" will erroneously
remove another element from it. The list will get
shorter and shorter every time you call "main".
Similarly, this:

$u1 = getusers();
$u2 = getusers();
pop @$u1;
will modify $u2 as well as $u1, because both variables
are references to the same array. Had "getusers" not
been memoized, $u1 and $u2 would have referred to dif
ferent arrays.
· Do not memoize a very simple function.

Recently someone mentioned to me that the Memoize mod
ule made his program run slower instead of faster. It
turned out that he was memoizing the following func
tion:

sub square {
$_[0] * $_[0];
}
I pointed out that "Memoize" uses a hash, and that
looking up a number in the hash is necessarily going
to take a lot longer than a single multiplication.
There really is no way to speed up the "square" func
tion.
Memoization is not magical.

PERSISTENT CACHE SUPPORT

You can tie the cache tables to any sort of tied hash that
you want to, as long as it supports "TIEHASH", "FETCH",
"STORE", and "EXISTS". For example,
tie my %cache => 'GDBM_File', $filename, O_RD
WR|O_CREAT, 0666;
memoize 'function', SCALAR_CACHE => [HASH =>
cache];
works just fine. For some storage methods, you need a
little glue.
"SDBM_File" doesn't supply an "EXISTS" method, so included
in this package is a glue module called "Memo
ize::SDBM_File" which does provide one. Use this instead
of plain "SDBM_File" to store your cache table on disk in
an "SDBM_File" database:

tie my %cache => 'Memoize::SDBM_File', $filename,
O_RDWR|O_CREAT, 0666;
memoize 'function', SCALAR_CACHE => [HASH =>
cache];
"NDBM_File" has the same problem and the same solution.
(Use "Memoize::NDBM_File instead of plain NDBM_File.")
"Storable" isn't a tied hash class at all. You can use it
to store a hash to disk and retrieve it again, but you
can't modify the hash while it's on the disk. So if you
want to store your cache table in a "Storable" database,
use "Memoize::Storable", which puts a hashlike front-end
onto "Storable". The hash table is actually kept in mem
ory, and is loaded from your "Storable" file at the time
you memoize the function, and stored back at the time you
unmemoize the function (or when your program exits):

tie my %cache => 'Memoize::Storable', $filename;
memoize 'function', SCALAR_CACHE => [HASH =>
cache];
tie my %cache => 'Memoize::Storable', $filename,
'nstore';
memoize 'function', SCALAR_CACHE => [HASH =>
cache];
Include the `nstore' option to have the "Storable"
database written in `network order'. (See Storable for
more details about this.)
The "flush_cache()" function will raise a run-time error
unless the tied package provides a "CLEAR" method.

EXPIRATION SUPPORT

See Memoize::Expire, which is a plug-in module that adds
expiration functionality to Memoize. If you don't like
the kinds of policies that Memoize::Expire implements, it
is easy to write your own plug-in module to implement
whatever policy you desire. Memoize comes with several
examples. An expiration manager that implements a LRU
policy is available on CPAN as Memoize::ExpireLRU.

BUGS

The test suite is much better, but always needs improve
ment.

There is some problem with the way "goto &f" works under
threaded Perl, perhaps because of the lexical scoping of
@_. This is a bug in Perl, and until it is resolved, mem
oized functions will see a slightly different "caller()"
and will perform a little more slowly on threaded perls
than unthreaded perls.

Some versions of "DB_File" won't let you store data under
a key of length 0. That means that if you have a function
"f" which you memoized and the cache is in a "DB_File"
database, then the value of "f()" ("f" called with no
arguments) will not be memoized. If this is a big
problem, you can supply a normalizer function that
prepends "x" to every key.

MAILING LIST

To join a very low-traffic mailing list for announcements
about "Memoize", send an empty note to "mjd-perl-memo
ize-request@plover.com".

AUTHOR

Mark-Jason Dominus ("mjd-perl-memoize+@plover.com"),
Plover Systems co.

See the "Memoize.pm" Page at
http://www.plover.com/~mjd/perl/Memoize/ for news and
upgrades. Near this page, at
http://www.plover.com/~mjd/perl/MiniMemoize/ there is an
article about memoization and about the internals of Memo
ize that appeared in The Perl Journal, issue #13. (This
article is also included in the Memoize distribution as
`article.html'.)

My upcoming book will discuss memoization (and many other
fascinating topics) in tremendous detail. It will be pub
lished by Morgan Kaufmann in 2002, possibly under the
title Perl Advanced Techniques Handbook. It will also be available on-line for free. For more information, visit
http://perl.plover.com/book/ .

To join a mailing list for announcements about "Memoize",
send an empty message to "mjd-perl-memo
ize-request@plover.com". This mailing list is for
announcements only and has extremely low traffic---about
two messages per year.

COPYRIGHT AND LICENSE

Copyright 1998, 1999, 2000, 2001 by Mark Jason Dominus

This library is free software; you may redistribute it
and/or modify it under the same terms as Perl itself.

THANK YOU

Many thanks to Jonathan Roy for bug reports and sugges
tions, to Michael Schwern for other bug reports and
patches, to Mike Cariaso for helping me to figure out the
Right Thing to Do About Expiration, to Joshua Gerth,
Joshua Chamas, Jonathan Roy (again), Mark D. Anderson, and
Andrew Johnson for more suggestions about expiration, to
Brent Powers for the Memoize::ExpireLRU module, to Ariel
Scolnicov for delightful messages about the Fibonacci
function, to Dion Almaer for thought-provoking suggestions
about the default normalizer, to Walt Mankowski and Kurt
Starsinic for much help investigating problems under
threaded Perl, to Alex Dudkevich for reporting the bug in
prototyped functions and for checking my patch, to Tony
Bass for many helpful suggestions, to Jonathan Roy (again)
for finding a use for "unmemoize()", to Philippe Verdret
for enlightening discussion of "Hook::PrePostCall", to Nat
Torkington for advice I ignored, to Chris Nandor for
portability advice, to Randal Schwartz for suggesting the
'"flush_cache" function, and to Jenda Krynicky for being a
light in the world.

Special thanks to Jarkko Hietaniemi, the 5.8.0 pumpking,
for including this module in the core and for his patient
and helpful guidance during the integration process.
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