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Memoize(3)	       Perl Programmers Reference Guide		    Memoize(3)

NAME
       Memoize - Make functions faster by trading space for time

SYNOPSIS
	       # This is the documentation for Memoize 1.03
	       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
       function 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 computes 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 several 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 reference 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 version 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"; without 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 completely
       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 equivalent 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 "normalize_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 functions with only one string argument, and
       also when the arguments never contain character 28.  However, it can
       confuse certain argument lists:

	       normalizer("a\034", "b")
	       normalizer("a", "\034b")
	       normalizer("a\034\034b")

       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 references.  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\034ARRAY(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 argument.	To fix this, include the current hour
       in the normalizer:

	       sub normalize { join ' ', (localtime)[2], @_ }

       The calling context of the function (scalar or list context) 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
       context, 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 an array whose first element is one
       of these four strings, such as "[HASH, arguments...]".

       "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 typically 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 persists 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_RDWR|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 populates 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.

	   Another reason to use "HASH" is to provide your own hash variable.
	   You can then inspect or modify the contents of the hash to gain
	   finer control over the cache management.

       "TIE"
	   This option is no longer supported.	It is still documented 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;
		   { tie my %cache, PACKAGE, ARGS...;
		     memoize ... [HASH => \%cache];
		   }

       "FAULT"
	   "FAULT" means that you never expect to call the function in scalar
	   (or list) context, and that if "Memoize" detects such a call, it
	   should abort the program.  The error message is one of

		   `foo' function called in forbidden list context at line ...
		   `foo' function called in forbidden scalar context at line ...

       "MERGE"
	   "MERGE" normally means that the memoized function does not
	   distinguish between list and sclar context, and that return values
	   in both contexts should be stored together.	Both "LIST_CACHE =>
	   MERGE" and "SCALAR_CACHE => MERGE" mean the same thing.

	   Consider this function:

		   sub complicated {
		     # ... time-consuming calculation of $result
		     return $result;
		   }

	   The "complicated" function will return the same numeric $result
	   regardless of whether it is called in list or in scalar context.

	   Normally, the following code will result in two calls to
	   "complicated", even if "complicated" is memoized:

	       $x = complicated(142);
	       ($y) = complicated(142);
	       $z = complicated(142);

	   The first call will cache the result, say 37, in the scalar cache;
	   the second will cach the list "(37)" in the list cache.  The third
	   call doesn't call the real "complicated" function; it gets the
	   value 37 from the scalar cache.

	   Obviously, the second call to "complicated" 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.
	   "complicated" ends up being called only once, and both subsequent
	   calls return 3 from the cache, regardless of the calling context.

       List values in scalar context

       Consider this function:

	   sub iota { return reverse (1..$_[0]) }

       This function normally returns a list.  Suppose you memoize it and
       merge the caches:

	   memoize 'iota', SCALAR_CACHE => 'MERGE';

	   @i7 = iota(7);
	   $i7 = iota(7);

       Here the first call caches the list (1,2,3,4,5,6,7).  The second call
       does not really make sense. "Memoize" cannot guess what behavior "iota"
       should have in scalar context without actually calling it in scalar
       context.	 Normally "Memoize" would call "iota" in scalar context and
       cache the result, but the "SCALAR_CACHE => 'MERGE'" option says not to
       do that, but to use the cache list-context value instead. But it cannot
       return a list of seven elements in a scalar context. In this case $i7
       will receive the first element of the cached list value, namely 7.

       Merged disk caches

       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', $filename, ...;

	       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 arguments ...
		 $hashkey = "$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: Suppose 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
       normally, this will happen anyway, but if someone types control-C or
       something then the program will terminate immediately 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 previously
       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 appropriate.  It returns a reference to the
       unmemoized version of the function.

       If you ask it to unmemoize a function that was never memoized, it
       croaks.

   "flush_cache"
       "flush_cache(function)" will flush out the caches, discarding all the
       cached data.  The argument may be a function name or a reference to a
       function.  For finer control over when data is discarded or expired,
       see the documentation 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 examine 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 "Memoize" is
	   concerned, it always returns the same result.  "Memoize" is wrong,
	   of course, and the memoized version 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.\n";
		   }

	   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 $u\n";
		     }
		   }

		   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 different arrays.

       ·   Do not memoize a very simple function.

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

	       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" function.

	   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_RDWR|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 "Memoize::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 memory,
       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 improvement.

       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, memoized 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-memoize-request@plover.com".

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

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

       The author's book Higher-Order Perl (2005, ISBN 1558607013, published
       by Morgan Kaufmann) discusses memoization (and many other topics) in
       tremendous detail. It is available on-line for free.  For more
       information, visit http://hop.perl.plover.com/ .

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

COPYRIGHT AND LICENSE
       Copyright 1998, 1999, 2000, 2001, 2012  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 Florian Ragwitz for administration and packaging
       assistance, to John Tromp for bug reports, to Jonathan Roy for bug
       reports and suggestions, 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.

POD ERRORS
       Hey! The above document had some coding errors, which are explained
       below:

       Around line 751:
	   You forgot a '=back' before '=head3'

       Around line 800:
	   =back without =over

perl v5.18.1			  2013-08-11			    Memoize(3)
[top]
                             _         _         _ 
                            | |       | |       | |     
                            | |       | |       | |     
                         __ | | __ __ | | __ __ | | __  
                         \ \| |/ / \ \| |/ / \ \| |/ /  
                          \ \ / /   \ \ / /   \ \ / /   
                           \   /     \   /     \   /    
                            \_/       \_/       \_/ 
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