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NAME
       perlothrtut - old tutorial on threads in Perl

DESCRIPTION
       WARNING: This tutorial describes the old-style thread
       model that was introduced in release 5.005. This model is
       deprecated, and has been removed for version 5.10. The
       interfaces described here were considered experimental,
       and are likely to be buggy.

       For information about the new interpreter threads
       ("ithreads") model, see the perlthrtut tutorial, and the
       threads and threads::shared modules.

       You are strongly encouraged to migrate any existing
       threads code to the new model as soon as possible.

What Is A Thread Anyway?
       A thread is a flow of control through a program with a
       single execution point.

       Sounds an awful lot like a process, doesn't it? Well, it
       should.  Threads are one of the pieces of a process.
       Every process has at least one thread and, up until now,
       every process running Perl had only one thread.  With
       5.005, though, you can create extra threads.  We're going
       to show you how, when, and why.

Threaded Program Models
       There are three basic ways that you can structure a
       threaded program.  Which model you choose depends on what
       you need your program to do.  For many non-trivial
       threaded programs you'll need to choose different models
       for different pieces of your program.

   Boss/Worker
       The boss/worker model usually has one `boss' thread and
       one or more `worker' threads.  The boss thread gathers or
       generates tasks that need to be done, then parcels those
       tasks out to the appropriate worker thread.

       This model is common in GUI and server programs, where a
       main thread waits for some event and then passes that
       event to the appropriate worker threads for processing.
       Once the event has been passed on, the boss thread goes
       back to waiting for another event.

       The boss thread does relatively little work.  While tasks
       aren't necessarily performed faster than with any other
       method, it tends to have the best user-response times.

   Work Crew
       In the work crew model, several threads are created that
       do essentially the same thing to different pieces of data.



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       It closely mirrors classical parallel processing and
       vector processors, where a large array of processors do
       the exact same thing to many pieces of data.

       This model is particularly useful if the system running
       the program will distribute multiple threads across
       different processors.  It can also be useful in ray
       tracing or rendering engines, where the individual threads
       can pass on interim results to give the user visual
       feedback.

   Pipeline
       The pipeline model divides up a task into a series of
       steps, and passes the results of one step on to the thread
       processing the next.  Each thread does one thing to each
       piece of data and passes the results to the next thread in
       line.

       This model makes the most sense if you have multiple
       processors so two or more threads will be executing in
       parallel, though it can often make sense in other contexts
       as well.  It tends to keep the individual tasks small and
       simple, as well as allowing some parts of the pipeline to
       block (on I/O or system calls, for example) while other
       parts keep going.  If you're running different parts of
       the pipeline on different processors you may also take
       advantage of the caches on each processor.

       This model is also handy for a form of recursive
       programming where, rather than having a subroutine call
       itself, it instead creates another thread.  Prime and
       Fibonacci generators both map well to this form of the
       pipeline model. (A version of a prime number generator is
       presented later on.)

Native threads
       There are several different ways to implement threads on a
       system.  How threads are implemented depends both on the
       vendor and, in some cases, the version of the operating
       system.  Often the first implementation will be relatively
       simple, but later versions of the OS will be more
       sophisticated.

       While the information in this section is useful, it's not
       necessary, so you can skip it if you don't feel up to it.

       There are three basic categories of threads-user-mode
       threads, kernel threads, and multiprocessor kernel
       threads.

       User-mode threads are threads that live entirely within a
       program and its libraries.  In this model, the OS knows
       nothing about threads.  As far as it's concerned, your
       process is just a process.



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       This is the easiest way to implement threads, and the way
       most OSes start.  The big disadvantage is that, since the
       OS knows nothing about threads, if one thread blocks they
       all do.  Typical blocking activities include most system
       calls, most I/O, and things like sleep().

       Kernel threads are the next step in thread evolution.  The
       OS knows about kernel threads, and makes allowances for
       them.  The main difference between a kernel thread and a
       user-mode thread is blocking.  With kernel threads, things
       that block a single thread don't block other threads.
       This is not the case with user-mode threads, where the
       kernel blocks at the process level and not the thread
       level.

       This is a big step forward, and can give a threaded
       program quite a performance boost over non-threaded
       programs.  Threads that block performing I/O, for example,
       won't block threads that are doing other things.  Each
       process still has only one thread running at once, though,
       regardless of how many CPUs a system might have.

       Since kernel threading can interrupt a thread at any time,
       they will uncover some of the implicit locking assumptions
       you may make in your program.  For example, something as
       simple as "$a = $a + 2" can behave unpredictably with
       kernel threads if $a is visible to other threads, as
       another thread may have changed $a between the time it was
       fetched on the right hand side and the time the new value
       is stored.

       Multiprocessor Kernel Threads are the final step in thread
       support.  With multiprocessor kernel threads on a machine
       with multiple CPUs, the OS may schedule two or more
       threads to run simultaneously on different CPUs.

       This can give a serious performance boost to your threaded
       program, since more than one thread will be executing at
       the same time.  As a tradeoff, though, any of those
       nagging synchronization issues that might not have shown
       with basic kernel threads will appear with a vengeance.

       In addition to the different levels of OS involvement in
       threads, different OSes (and different thread
       implementations for a particular OS) allocate CPU cycles
       to threads in different ways.

       Cooperative multitasking systems have running threads give
       up control if one of two things happen.  If a thread calls
       a yield function, it gives up control.  It also gives up
       control if the thread does something that would cause it
       to block, such as perform I/O.  In a cooperative
       multitasking implementation, one thread can starve all the
       others for CPU time if it so chooses.



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       Preemptive multitasking systems interrupt threads at
       regular intervals while the system decides which thread
       should run next.  In a preemptive multitasking system, one
       thread usually won't monopolize the CPU.

       On some systems, there can be cooperative and preemptive
       threads running simultaneously. (Threads running with
       realtime priorities often behave cooperatively, for
       example, while threads running at normal priorities behave
       preemptively.)

What kind of threads are perl threads?
       If you have experience with other thread implementations,
       you might find that things aren't quite what you expect.
       It's very important to remember when dealing with Perl
       threads that Perl Threads Are Not X Threads, for all
       values of X.  They aren't POSIX threads, or DecThreads, or
       Java's Green threads, or Win32 threads.  There are
       similarities, and the broad concepts are the same, but if
       you start looking for implementation details you're going
       to be either disappointed or confused.  Possibly both.

       This is not to say that Perl threads are completely
       different from everything that's ever come before--they're
       not.  Perl's threading model owes a lot to other thread
       models, especially POSIX.  Just as Perl is not C, though,
       Perl threads are not POSIX threads.  So if you find
       yourself looking for mutexes, or thread priorities, it's
       time to step back a bit and think about what you want to
       do and how Perl can do it.

Threadsafe Modules
       The addition of threads has changed Perl's internals
       substantially.  There are implications for people who
       write modules--especially modules with XS code or external
       libraries.  While most modules won't encounter any
       problems, modules that aren't explicitly tagged as thread-
       safe should be tested before being used in production
       code.

       Not all modules that you might use are thread-safe, and
       you should always assume a module is unsafe unless the
       documentation says otherwise.  This includes modules that
       are distributed as part of the core.  Threads are a beta
       feature, and even some of the standard modules aren't
       thread-safe.

       If you're using a module that's not thread-safe for some
       reason, you can protect yourself by using semaphores and
       lots of programming discipline to control access to the
       module.  Semaphores are covered later in the article.
       Perl Threads Are Different





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Thread Basics
       The core Thread module provides the basic functions you
       need to write threaded programs.  In the following
       sections we'll cover the basics, showing you what you need
       to do to create a threaded program.   After that, we'll go
       over some of the features of the Thread module that make
       threaded programming easier.

   Basic Thread Support
       Thread support is a Perl compile-time option-it's
       something that's turned on or off when Perl is built at
       your site, rather than when your programs are compiled. If
       your Perl wasn't compiled with thread support enabled,
       then any attempt to use threads will fail.

       Remember that the threading support in 5.005 is in beta
       release, and should be treated as such.   You should
       expect that it may not function entirely properly, and the
       thread interface may well change some before it is a fully
       supported, production release.  The beta version shouldn't
       be used for mission-critical projects.  Having said that,
       threaded Perl is pretty nifty, and worth a look.

       Your programs can use the Config module to check whether
       threads are enabled. If your program can't run without
       them, you can say something like:

         $Config{usethreads} or die "Recompile Perl with threads to run this program.";

       A possibly-threaded program using a possibly-threaded
       module might have code like this:

           use Config;
           use MyMod;

           if ($Config{usethreads}) {
               # We have threads
               require MyMod_threaded;
               import MyMod_threaded;
           } else {
               require MyMod_unthreaded;
               import MyMod_unthreaded;
           }

       Since code that runs both with and without threads is
       usually pretty messy, it's best to isolate the thread-
       specific code in its own module.  In our example above,
       that's what MyMod_threaded is, and it's only imported if
       we're running on a threaded Perl.

   Creating Threads
       The Thread package provides the tools you need to create
       new threads.  Like any other module, you need to tell Perl
       you want to use it; use Thread imports all the pieces you



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       need to create basic threads.

       The simplest, straightforward way to create a thread is
       with new():

           use Thread;

           $thr = Thread->new( \&sub1 );

           sub sub1 {
               print "In the thread\n";
           }

       The new() method takes a reference to a subroutine and
       creates a new thread, which starts executing in the
       referenced subroutine.  Control then passes both to the
       subroutine and the caller.

       If you need to, your program can pass parameters to the
       subroutine as part of the thread startup.  Just include
       the list of parameters as part of the "Thread::new" call,
       like this:

           use Thread;
           $Param3 = "foo";
           $thr = Thread->new( \&sub1, "Param 1", "Param 2", $Param3 );
           $thr = Thread->new( \&sub1, @ParamList );
           $thr = Thread->new( \&sub1, qw(Param1 Param2 $Param3) );

           sub sub1 {
               my @InboundParameters = @_;
               print "In the thread\n";
               print "got parameters >", join("<>", @InboundParameters), "<\n";
           }

       The subroutine runs like a normal Perl subroutine, and the
       call to new Thread returns whatever the subroutine
       returns.

       The last example illustrates another feature of threads.
       You can spawn off several threads using the same
       subroutine.  Each thread executes the same subroutine, but
       in a separate thread with a separate environment and
       potentially separate arguments.

       The other way to spawn a new thread is with async(), which
       is a way to spin off a chunk of code like eval(), but into
       its own thread:

           use Thread qw(async);

           $LineCount = 0;

           $thr = async {



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               while(<>) {$LineCount++}
               print "Got $LineCount lines\n";
           };

           print "Waiting for the linecount to end\n";
           $thr->join;
           print "All done\n";

       You'll notice we did a use Thread qw(async) in that
       example.  async is not exported by default, so if you want
       it, you'll either need to import it before you use it or
       fully qualify it as Thread::async.  You'll also note that
       there's a semicolon after the closing brace.  That's
       because async() treats the following block as an anonymous
       subroutine, so the semicolon is necessary.

       Like eval(), the code executes in the same context as it
       would if it weren't spun off.  Since both the code inside
       and after the async start executing, you need to be
       careful with any shared resources.  Locking and other
       synchronization techniques are covered later.

   Giving up control
       There are times when you may find it useful to have a
       thread explicitly give up the CPU to another thread.  Your
       threading package might not support preemptive
       multitasking for threads, for example, or you may be doing
       something compute-intensive and want to make sure that the
       user-interface thread gets called frequently.  Regardless,
       there are times that you might want a thread to give up
       the processor.

       Perl's threading package provides the yield() function
       that does this. yield() is pretty straightforward, and
       works like this:

           use Thread qw(yield async);
           async {
               my $foo = 50;
               while ($foo--) { print "first async\n" }
               yield;
               $foo = 50;
               while ($foo--) { print "first async\n" }
           };
           async {
               my $foo = 50;
               while ($foo--) { print "second async\n" }
               yield;
               $foo = 50;
               while ($foo--) { print "second async\n" }
           };

   Waiting For A Thread To Exit
       Since threads are also subroutines, they can return



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       values.  To wait for a thread to exit and extract any
       scalars it might return, you can use the join() method.

           use Thread;
           $thr = Thread->new( \&sub1 );

           @ReturnData = $thr->join;
           print "Thread returned @ReturnData";

           sub sub1 { return "Fifty-six", "foo", 2; }

       In the example above, the join() method returns as soon as
       the thread ends.  In addition to waiting for a thread to
       finish and gathering up any values that the thread might
       have returned, join() also performs any OS cleanup
       necessary for the thread.  That cleanup might be
       important, especially for long-running programs that spawn
       lots of threads.  If you don't want the return values and
       don't want to wait for the thread to finish, you should
       call the detach() method instead. detach() is covered
       later in the article.

   Errors In Threads
       So what happens when an error occurs in a thread? Any
       errors that could be caught with eval() are postponed
       until the thread is joined.  If your program never joins,
       the errors appear when your program exits.

       Errors deferred until a join() can be caught with eval():

           use Thread qw(async);
           $thr = async {$b = 3/0};   # Divide by zero error
           $foo = eval {$thr->join};
           if ($@) {
               print "died with error $@\n";
           } else {
               print "Hey, why aren't you dead?\n";
           }

       eval() passes any results from the joined thread back
       unmodified, so if you want the return value of the thread,
       this is your only chance to get them.

   Ignoring A Thread
       join() does three things: it waits for a thread to exit,
       cleans up after it, and returns any data the thread may
       have produced.  But what if you're not interested in the
       thread's return values, and you don't really care when the
       thread finishes? All you want is for the thread to get
       cleaned up after when it's done.

       In this case, you use the detach() method.  Once a thread
       is detached, it'll run until it's finished, then Perl will
       clean up after it automatically.



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           use Thread;
           $thr = Thread->new( \&sub1 ); # Spawn the thread

           $thr->detach; # Now we officially don't care any more

           sub sub1 {
               $a = 0;
               while (1) {
                   $a++;
                   print "\$a is $a\n";
                   sleep 1;
               }
           }

       Once a thread is detached, it may not be joined, and any
       output that it might have produced (if it was done and
       waiting for a join) is lost.

Threads And Data
       Now that we've covered the basics of threads, it's time
       for our next topic: data.  Threading introduces a couple
       of complications to data access that non-threaded programs
       never need to worry about.

   Shared And Unshared Data
       The single most important thing to remember when using
       threads is that all threads potentially have access to all
       the data anywhere in your program.  While this is true
       with a nonthreaded Perl program as well, it's especially
       important to remember with a threaded program, since more
       than one thread can be accessing this data at once.

       Perl's scoping rules don't change because you're using
       threads.  If a subroutine (or block, in the case of
       async()) could see a variable if you weren't running with
       threads, it can see it if you are.  This is especially
       important for the subroutines that create, and makes "my"
       variables even more important.  Remember--if your
       variables aren't lexically scoped (declared with "my")
       you're probably sharing them between threads.

   Thread Pitfall: Races
       While threads bring a new set of useful tools, they also
       bring a number of pitfalls.  One pitfall is the race
       condition:

           use Thread;
           $a = 1;
           $thr1 = Thread->new(\&sub1);
           $thr2 = Thread->new(\&sub2);

           sleep 10;
           print "$a\n";




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           sub sub1 { $foo = $a; $a = $foo + 1; }
           sub sub2 { $bar = $a; $a = $bar + 1; }

       What do you think $a will be? The answer, unfortunately,
       is "it depends." Both sub1() and sub2() access the global
       variable $a, once to read and once to write.  Depending on
       factors ranging from your thread implementation's
       scheduling algorithm to the phase of the moon, $a can be 2
       or 3.

       Race conditions are caused by unsynchronized access to
       shared data.  Without explicit synchronization, there's no
       way to be sure that nothing has happened to the shared
       data between the time you access it and the time you
       update it.  Even this simple code fragment has the
       possibility of error:

           use Thread qw(async);
           $a = 2;
           async{ $b = $a; $a = $b + 1; };
           async{ $c = $a; $a = $c + 1; };

       Two threads both access $a.  Each thread can potentially
       be interrupted at any point, or be executed in any order.
       At the end, $a could be 3 or 4, and both $b and $c could
       be 2 or 3.

       Whenever your program accesses data or resources that can
       be accessed by other threads, you must take steps to
       coordinate access or risk data corruption and race
       conditions.

   Controlling access: lock()
       The lock() function takes a variable (or subroutine, but
       we'll get to that later) and puts a lock on it.  No other
       thread may lock the variable until the locking thread
       exits the innermost block containing the lock.  Using
       lock() is straightforward:

           use Thread qw(async);
           $a = 4;
           $thr1 = async {
               $foo = 12;
               {
                   lock ($a); # Block until we get access to $a
                   $b = $a;
                   $a = $b * $foo;
               }
               print "\$foo was $foo\n";
           };
           $thr2 = async {
               $bar = 7;
               {
                   lock ($a); # Block until we can get access to $a



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                   $c = $a;
                   $a = $c * $bar;
               }
               print "\$bar was $bar\n";
           };
           $thr1->join;
           $thr2->join;
           print "\$a is $a\n";

       lock() blocks the thread until the variable being locked
       is available.  When lock() returns, your thread can be
       sure that no other thread can lock that variable until the
       innermost block containing the lock exits.

       It's important to note that locks don't prevent access to
       the variable in question, only lock attempts.  This is in
       keeping with Perl's longstanding tradition of courteous
       programming, and the advisory file locking that flock()
       gives you.  Locked subroutines behave differently,
       however.  We'll cover that later in the article.

       You may lock arrays and hashes as well as scalars.
       Locking an array, though, will not block subsequent locks
       on array elements, just lock attempts on the array itself.

       Finally, locks are recursive, which means it's okay for a
       thread to lock a variable more than once.  The lock will
       last until the outermost lock() on the variable goes out
       of scope.

   Thread Pitfall: Deadlocks
       Locks are a handy tool to synchronize access to data.
       Using them properly is the key to safe shared data.
       Unfortunately, locks aren't without their dangers.
       Consider the following code:

           use Thread qw(async yield);
           $a = 4;
           $b = "foo";
           async {
               lock($a);
               yield;
               sleep 20;
               lock ($b);
           };
           async {
               lock($b);
               yield;
               sleep 20;
               lock ($a);
           };

       This program will probably hang until you kill it.  The
       only way it won't hang is if one of the two async()



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       routines acquires both locks first.  A guaranteed-to-hang
       version is more complicated, but the principle is the
       same.

       The first thread spawned by async() will grab a lock on $a
       then, a second or two later, try to grab a lock on $b.
       Meanwhile, the second thread grabs a lock on $b, then
       later tries to grab a lock on $a.  The second lock attempt
       for both threads will block, each waiting for the other to
       release its lock.

       This condition is called a deadlock, and it occurs
       whenever two or more threads are trying to get locks on
       resources that the others own.  Each thread will block,
       waiting for the other to release a lock on a resource.
       That never happens, though, since the thread with the
       resource is itself waiting for a lock to be released.

       There are a number of ways to handle this sort of problem.
       The best way is to always have all threads acquire locks
       in the exact same order.  If, for example, you lock
       variables $a, $b, and $c, always lock $a before $b, and $b
       before $c.  It's also best to hold on to locks for as
       short a period of time to minimize the risks of deadlock.

   Queues: Passing Data Around
       A queue is a special thread-safe object that lets you put
       data in one end and take it out the other without having
       to worry about synchronization issues.  They're pretty
       straightforward, and look like this:

           use Thread qw(async);
           use Thread::Queue;

           my $DataQueue = Thread::Queue->new();
           $thr = async {
               while ($DataElement = $DataQueue->dequeue) {
                   print "Popped $DataElement off the queue\n";
               }
           };

           $DataQueue->enqueue(12);
           $DataQueue->enqueue("A", "B", "C");
           sleep 10;
           $DataQueue->enqueue(undef);

       You create the queue with "Thread::Queue->new".  Then you
       can add lists of scalars onto the end with enqueue(), and
       pop scalars off the front of it with dequeue().  A queue
       has no fixed size, and can grow as needed to hold
       everything pushed on to it.

       If a queue is empty, dequeue() blocks until another thread
       enqueues something.  This makes queues ideal for event



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       loops and other communications between threads.

Threads And Code
       In addition to providing thread-safe access to data via
       locks and queues, threaded Perl also provides general-
       purpose semaphores for coarser synchronization than locks
       provide and thread-safe access to entire subroutines.

   Semaphores: Synchronizing Data Access
       Semaphores are a kind of generic locking mechanism.
       Unlike lock, which gets a lock on a particular scalar,
       Perl doesn't associate any particular thing with a
       semaphore so you can use them to control access to
       anything you like.  In addition, semaphores can allow more
       than one thread to access a resource at once, though by
       default semaphores only allow one thread access at a time.

       Basic semaphores
           Semaphores have two methods, down and up. down
           decrements the resource count, while up increments it.
           down calls will block if the semaphore's current count
           would decrement below zero.  This program gives a
           quick demonstration:

               use Thread qw(yield);
               use Thread::Semaphore;
               my $semaphore = Thread::Semaphore->new();
               $GlobalVariable = 0;

               $thr1 = Thread->new( \&sample_sub, 1 );
               $thr2 = Thread->new( \&sample_sub, 2 );
               $thr3 = Thread->new( \&sample_sub, 3 );

               sub sample_sub {
                   my $SubNumber = shift @_;
                   my $TryCount = 10;
                   my $LocalCopy;
                   sleep 1;
                   while ($TryCount--) {
                       $semaphore->down;
                       $LocalCopy = $GlobalVariable;
                       print "$TryCount tries left for sub $SubNumber (\$GlobalVariable is $GlobalVariable)\n";
                       yield;
                       sleep 2;
                       $LocalCopy++;
                       $GlobalVariable = $LocalCopy;
                       $semaphore->up;
                   }
               }

           The three invocations of the subroutine all operate in
           sync.  The semaphore, though, makes sure that only one
           thread is accessing the global variable at once.




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       Advanced Semaphores
           By default, semaphores behave like locks, letting only
           one thread down() them at a time.  However, there are
           other uses for semaphores.

           Each semaphore has a counter attached to it. down()
           decrements the counter and up() increments the
           counter.  By default, semaphores are created with the
           counter set to one, down() decrements by one, and up()
           increments by one.  If down() attempts to decrement
           the counter below zero, it blocks until the counter is
           large enough.  Note that while a semaphore can be
           created with a starting count of zero, any up() or
           down() always changes the counter by at least one.
           $semaphore->down(0) is the same as
           $semaphore->down(1).

           The question, of course, is why would you do something
           like this? Why create a semaphore with a starting
           count that's not one, or why decrement/increment it by
           more than one? The answer is resource availability.
           Many resources that you want to manage access for can
           be safely used by more than one thread at once.

           For example, let's take a GUI driven program.  It has
           a semaphore that it uses to synchronize access to the
           display, so only one thread is ever drawing at once.
           Handy, but of course you don't want any thread to
           start drawing until things are properly set up.  In
           this case, you can create a semaphore with a counter
           set to zero, and up it when things are ready for
           drawing.

           Semaphores with counters greater than one are also
           useful for establishing quotas.  Say, for example,
           that you have a number of threads that can do I/O at
           once.  You don't want all the threads reading or
           writing at once though, since that can potentially
           swamp your I/O channels, or deplete your process'
           quota of filehandles.  You can use a semaphore
           initialized to the number of concurrent I/O requests
           (or open files) that you want at any one time, and
           have your threads quietly block and unblock
           themselves.

           Larger increments or decrements are handy in those
           cases where a thread needs to check out or return a
           number of resources at once.

   Attributes: Restricting Access To Subroutines
       In addition to synchronizing access to data or resources,
       you might find it useful to synchronize access to
       subroutines.  You may be accessing a singular machine
       resource (perhaps a vector processor), or find it easier



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       to serialize calls to a particular subroutine than to have
       a set of locks and semaphores.

       One of the additions to Perl 5.005 is subroutine
       attributes.  The Thread package uses these to provide
       several flavors of serialization.  It's important to
       remember that these attributes are used in the compilation
       phase of your program so you can't change a subroutine's
       behavior while your program is actually running.

   Subroutine Locks
       The basic subroutine lock looks like this:

           sub test_sub :locked {
           }

       This ensures that only one thread will be executing this
       subroutine at any one time.  Once a thread calls this
       subroutine, any other thread that calls it will block
       until the thread in the subroutine exits it.  A more
       elaborate example looks like this:

           use Thread qw(yield);

           Thread->new(\&thread_sub, 1);
           Thread->new(\&thread_sub, 2);
           Thread->new(\&thread_sub, 3);
           Thread->new(\&thread_sub, 4);

           sub sync_sub :locked {
               my $CallingThread = shift @_;
               print "In sync_sub for thread $CallingThread\n";
               yield;
               sleep 3;
               print "Leaving sync_sub for thread $CallingThread\n";
           }

           sub thread_sub {
               my $ThreadID = shift @_;
               print "Thread $ThreadID calling sync_sub\n";
               sync_sub($ThreadID);
               print "$ThreadID is done with sync_sub\n";
           }

       The "locked" attribute tells perl to lock sync_sub(), and
       if you run this, you can see that only one thread is in it
       at any one time.

   Methods
       Locking an entire subroutine can sometimes be overkill,
       especially when dealing with Perl objects.  When calling a
       method for an object, for example, you want to serialize
       calls to a method, so that only one thread will be in the
       subroutine for a particular object, but threads calling



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       that subroutine for a different object aren't blocked.
       The method attribute indicates whether the subroutine is
       really a method.

           use Thread;

           sub tester {
               my $thrnum = shift @_;
               my $bar = Foo->new();
               foreach (1..10) {
                   print "$thrnum calling per_object\n";
                   $bar->per_object($thrnum);
                   print "$thrnum out of per_object\n";
                   yield;
                   print "$thrnum calling one_at_a_time\n";
                   $bar->one_at_a_time($thrnum);
                   print "$thrnum out of one_at_a_time\n";
                   yield;
               }
           }

           foreach my $thrnum (1..10) {
               Thread->new(\&tester, $thrnum);
           }

           package Foo;
           sub new {
               my $class = shift @_;
               return bless [@_], $class;
           }

           sub per_object :locked :method {
               my ($class, $thrnum) = @_;
               print "In per_object for thread $thrnum\n";
               yield;
               sleep 2;
               print "Exiting per_object for thread $thrnum\n";
           }

           sub one_at_a_time :locked {
               my ($class, $thrnum) = @_;
               print "In one_at_a_time for thread $thrnum\n";
               yield;
               sleep 2;
               print "Exiting one_at_a_time for thread $thrnum\n";
           }

       As you can see from the output (omitted for brevity; it's
       800 lines) all the threads can be in per_object()
       simultaneously, but only one thread is ever in
       one_at_a_time() at once.

   Locking A Subroutine
       You can lock a subroutine as you would lock a variable.



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       Subroutine locks work the same as specifying a "locked"
       attribute for the subroutine, and block all access to the
       subroutine for other threads until the lock goes out of
       scope.  When the subroutine isn't locked, any number of
       threads can be in it at once, and getting a lock on a
       subroutine doesn't affect threads already in the
       subroutine.  Getting a lock on a subroutine looks like
       this:

           lock(\&sub_to_lock);

       Simple enough.  Unlike the "locked" attribute, which is a
       compile time option, locking and unlocking a subroutine
       can be done at runtime at your discretion.  There is some
       runtime penalty to using lock(\&sub) instead of the
       "locked" attribute, so make sure you're choosing the
       proper method to do the locking.

       You'd choose lock(\&sub) when writing modules and code to
       run on both threaded and unthreaded Perl, especially for
       code that will run on 5.004 or earlier Perls.  In that
       case, it's useful to have subroutines that should be
       serialized lock themselves if they're running threaded,
       like so:

           package Foo;
           use Config;
           $Running_Threaded = 0;

           BEGIN { $Running_Threaded = $Config{'usethreads'} }

           sub sub1 { lock(\&sub1) if $Running_Threaded }

       This way you can ensure single-threadedness regardless of
       which version of Perl you're running.

General Thread Utility Routines
       We've covered the workhorse parts of Perl's threading
       package, and with these tools you should be well on your
       way to writing threaded code and packages.  There are a
       few useful little pieces that didn't really fit in
       anyplace else.

   What Thread Am I In?
       The Thread->self method provides your program with a way
       to get an object representing the thread it's currently
       in.  You can use this object in the same way as the ones
       returned from the thread creation.

   Thread IDs
       tid() is a thread object method that returns the thread ID
       of the thread the object represents.  Thread IDs are
       integers, with the main thread in a program being 0.
       Currently Perl assigns a unique tid to every thread ever



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       created in your program, assigning the first thread to be
       created a tid of 1, and increasing the tid by 1 for each
       new thread that's created.

   Are These Threads The Same?
       The equal() method takes two thread objects and returns
       true if the objects represent the same thread, and false
       if they don't.

   What Threads Are Running?
       Thread->list returns a list of thread objects, one for
       each thread that's currently running.  Handy for a number
       of things, including cleaning up at the end of your
       program:

           # Loop through all the threads
           foreach $thr (Thread->list) {
               # Don't join the main thread or ourselves
               if ($thr->tid && !Thread::equal($thr, Thread->self)) {
                   $thr->join;
               }
           }

       The example above is just for illustration.  It isn't
       strictly necessary to join all the threads you create,
       since Perl detaches all the threads before it exits.

A Complete Example
       Confused yet? It's time for an example program to show
       some of the things we've covered.  This program finds
       prime numbers using threads.

           1  #!/usr/bin/perl -w
           2  # prime-pthread, courtesy of Tom Christiansen
           3
           4  use strict;
           5
           6  use Thread;
           7  use Thread::Queue;
           8
           9  my $stream = Thread::Queue->new();
           10 my $kid    = Thread->new(\&check_num, $stream, 2);
           11
           12 for my $i ( 3 .. 1000 ) {
           13     $stream->enqueue($i);
           14 }
           15
           16 $stream->enqueue(undef);
           17 $kid->join();
           18
           19 sub check_num {
           20     my ($upstream, $cur_prime) = @_;
           21     my $kid;
           22     my $downstream = Thread::Queue->new();



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           23     while (my $num = $upstream->dequeue) {
           24         next unless $num % $cur_prime;
           25         if ($kid) {
           26            $downstream->enqueue($num);
           27                  } else {
           28            print "Found prime $num\n";
           29                $kid = Thread->new(\&check_num, $downstream, $num);
           30         }
           31     }
           32     $downstream->enqueue(undef) if $kid;
           33     $kid->join()         if $kid;
           34 }

       This program uses the pipeline model to generate prime
       numbers.  Each thread in the pipeline has an input queue
       that feeds numbers to be checked, a prime number that it's
       responsible for, and an output queue that it funnels
       numbers that have failed the check into.  If the thread
       has a number that's failed its check and there's no child
       thread, then the thread must have found a new prime
       number.  In that case, a new child thread is created for
       that prime and stuck on the end of the pipeline.

       This probably sounds a bit more confusing than it really
       is, so lets go through this program piece by piece and see
       what it does.  (For those of you who might be trying to
       remember exactly what a prime number is, it's a number
       that's only evenly divisible by itself and 1)

       The bulk of the work is done by the check_num()
       subroutine, which takes a reference to its input queue and
       a prime number that it's responsible for.  After pulling
       in the input queue and the prime that the subroutine's
       checking (line 20), we create a new queue (line 22) and
       reserve a scalar for the thread that we're likely to
       create later (line 21).

       The while loop from lines 23 to line 31 grabs a scalar off
       the input queue and checks against the prime this thread
       is responsible for.  Line 24 checks to see if there's a
       remainder when we modulo the number to be checked against
       our prime.  If there is one, the number must not be evenly
       divisible by our prime, so we need to either pass it on to
       the next thread if we've created one (line 26) or create a
       new thread if we haven't.

       The new thread creation is line 29.  We pass on to it a
       reference to the queue we've created, and the prime number
       we've found.

       Finally, once the loop terminates (because we got a 0 or
       undef in the queue, which serves as a note to die), we
       pass on the notice to our child and wait for it to exit if
       we've created a child (Lines 32 and 37).



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       Meanwhile, back in the main thread, we create a queue
       (line 9) and the initial child thread (line 10), and pre-
       seed it with the first prime: 2.  Then we queue all the
       numbers from 3 to 1000 for checking (lines 12-14), then
       queue a die notice (line 16) and wait for the first child
       thread to terminate (line 17).  Because a child won't die
       until its child has died, we know that we're done once we
       return from the join.

       That's how it works.  It's pretty simple; as with many
       Perl programs, the explanation is much longer than the
       program.

Conclusion
       A complete thread tutorial could fill a book (and has,
       many times), but this should get you well on your way.
       The final authority on how Perl's threads behave is the
       documentation bundled with the Perl distribution, but with
       what we've covered in this article, you should be well on
       your way to becoming a threaded Perl expert.

Bibliography
       Here's a short bibliography courtesy of JXrgen
       Christoffel:

   Introductory Texts
       Birrell, Andrew D. An Introduction to Programming with
       Threads. Digital Equipment Corporation, 1989, DEC-SRC
       Research Report #35 online as
       http://www.research.digital.com/SRC/staff/birrell/bib.html
       (highly recommended)

       Robbins, Kay. A., and Steven Robbins. Practical Unix
       Programming: A Guide to Concurrency, Communication, and
       Multithreading. Prentice-Hall, 1996.

       Lewis, Bill, and Daniel J. Berg. Multithreaded Programming
       with Pthreads. Prentice Hall, 1997, ISBN 0-13-443698-9 (a
       well-written introduction to threads).

       Nelson, Greg (editor). Systems Programming with Modula-3.
       Prentice Hall, 1991, ISBN 0-13-590464-1.

       Nichols, Bradford, Dick Buttlar, and Jacqueline Proulx
       Farrell.  Pthreads Programming. O'Reilly & Associates,
       1996, ISBN 156592-115-1 (covers POSIX threads).

   OS-Related References
       Boykin, Joseph, David Kirschen, Alan Langerman, and Susan
       LoVerso. Programming under Mach. Addison-Wesley, 1994,
       ISBN 0-201-52739-1.

       Tanenbaum, Andrew S. Distributed Operating Systems.
       Prentice Hall, 1995, ISBN 0-13-219908-4 (great textbook).



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       Silberschatz, Abraham, and Peter B. Galvin. Operating
       System Concepts, 4th ed. Addison-Wesley, 1995, ISBN
       0-201-59292-4

   Other References
       Arnold, Ken and James Gosling. The Java Programming
       Language, 2nd ed. Addison-Wesley, 1998, ISBN
       0-201-31006-6.

       Le Sergent, T. and B. Berthomieu. "Incremental
       MultiThreaded Garbage Collection on Virtually Shared
       Memory Architectures" in Memory Management: Proc. of the
       International Workshop IWMM 92, St. Malo, France,
       September 1992, Yves Bekkers and Jacques Cohen, eds.
       Springer, 1992, ISBN 3540-55940-X (real-life thread
       applications).

Acknowledgements
       Thanks (in no particular order) to Chaim Frenkel, Steve
       Fink, Gurusamy Sarathy, Ilya Zakharevich, Benjamin Sugars,
       JXrgen Christoffel, Joshua Pritikin, and Alan Burlison,
       for their help in reality-checking and polishing this
       article.  Big thanks to Tom Christiansen for his rewrite
       of the prime number generator.

AUTHOR
       Dan Sugalski <sugalskd@ous.edu>

Copyrights
       This article originally appeared in The Perl Journal #10,
       and is copyright 1998 The Perl Journal. It appears
       courtesy of Jon Orwant and The Perl Journal.  This
       document may be distributed under the same terms as Perl
       itself.























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