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X11R7.4 - man page for perlothrtut (x11r4 section 1)

PERLOTHRTUT(1)			 Perl Programmers Reference Guide		   PERLOTHRTUT(1)

       perlothrtut - old tutorial on threads in Perl

       WARNING: This tutorial describes the old-style thread model that was introduced in release
       5.005. This model is now deprecated, and will be removed, probably in 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 pro-
       grams you'll need to choose different models for different pieces of your program.


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

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


       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 imple-
       mented 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 multi-
       processor 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.

       This is the easiest way to implement threads, and the way most OSes start.  The big disad-
       vantage 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

       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 sim-
       ple 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 dif-
       ferent thread implementations for a particular OS) allocate CPU cycles to threads in dif-
       ferent 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 con-
       trol 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.

       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 similari-
       ties, 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, espe-
       cially 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 implica-
       tions 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 dis-
       tributed 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

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 cre-
       ate 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 pro-
       gram 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 mod-
       ule, you need to tell Perl you want to use it; use Thread imports all the pieces you 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

	   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;

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

	   print "Waiting for the linecount to end\n";
	   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

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

       Waiting For A Thread To Exit

       Since threads are also subroutines, they can return 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.

	   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) {
		   print "\$a is $a\n";
		   sleep 1;

       Once a thread is detached, it may not be joined, and any output that it might have pro-
       duced (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.  Thread-
       ing 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 poten-
       tially 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 lexi-
       cally 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";

	   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 fac-
       tors 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 syn-
       chronization, 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
		   $c = $a;
		   $a = $c * $bar;
	       print "\$bar was $bar\n";
	   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 pro-
       gramming, 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

       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 fol-
       lowing code:

	   use Thread qw(async yield);
	   $a = 4;
	   $b = "foo";
	   async {
	       sleep 20;
	       lock ($b);
	   async {
	       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() 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 straight-
       forward, 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("A", "B", "C");
	   sleep 10;

       You create the queue with new Thread::Queue.  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 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--) {
		       $LocalCopy = $GlobalVariable;
		       print "$TryCount tries left for sub $SubNumber (\$GlobalVariable is $GlobalVariable)\n";
		       sleep 2;
		       $GlobalVariable = $LocalCopy;

	   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.

       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

	   The question, of course, is why would you do something like this? Why create a sema-
	   phore 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 syn-
	   chronize 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 poten-
	   tially 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

	   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 syn-
       chronize access to subroutines.	You may be accessing a singular machine resource (perhaps
       a vector processor), or find it easier 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 subrou-
       tine'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);

	   new Thread \&thread_sub, 1;
	   new Thread \&thread_sub, 2;
	   new Thread \&thread_sub, 3;
	   new Thread \&thread_sub, 4;

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

	   sub thread_sub {
	       my $ThreadID = shift @_;
	       print "Thread $ThreadID calling sync_sub\n";
	       print "$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.


       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 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";
		   print "$thrnum out of per_object\n";
		   print "$thrnum calling one_at_a_time\n";
		   print "$thrnum out of one_at_a_time\n";

	   foreach my $thrnum (1..10) {
	       new Thread \&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";
	       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";
	       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.	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:


       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 choos-
       ing 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

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 repre-
       sents.  Thread IDs are integers, with the main thread in a program being 0.  Currently
       Perl assigns a unique tid to every thread ever 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 run-
       ning.  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)) {

       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
	   4  use strict;
	   6  use Thread;
	   7  use Thread::Queue;
	   9  my $stream = Thread::Queue->new();
	   10 my $kid	 = Thread->new(\&check_num, $stream, 2);
	   12 for my $i ( 3 .. 1000 ) {
	   13	  $stream->enqueue($i);
	   14 }
	   16 $stream->enqueue(undef);
	   17 $kid->join();
	   19 sub check_num {
	   20	  my ($upstream, $cur_prime) = @_;
	   21	  my $kid;
	   22	  my $downstream = Thread::Queue->new();
	   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 pipe-
       line has an input queue that feeds numbers to be checked, a prime number that it's respon-
       sible 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 pro-
       gram piece by piece and see what it does.  (For those of you who might be trying to remem-
       ber 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 cre-
       ated, 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).

       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.

       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 documenta-
       tion 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.

       Here's a short bibliography courtesy of Jurgen Christoffel:

       Introductory Texts

       Birrell, Andrew D. An Introduction to Programming with Threads. Digital Equipment Corpora-
       tion, 1989, DEC-SRC Research Report #35 online as http://www.research.digi-
       tal.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

       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).

       Silberschatz, Abraham, and Peter B. Galvin. Operating System Concepts, 4th ed. Addi-
       son-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 Virtu-
       ally Shared Memory Architectures" in Memory Management: Proc. of the International Work-
       shop IWMM 92, St. Malo, France, September 1992, Yves Bekkers and Jacques Cohen, eds.
       Springer, 1992, ISBN 3540-55940-X (real-life thread applications).

       Thanks (in no particular order) to Chaim Frenkel, Steve Fink, Gurusamy Sarathy, Ilya
       Zakharevich, Benjamin Sugars, Jurgen 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.

       Dan Sugalski <sugalskd@ous.edu>

       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.

perl v5.8.9				    2007-11-17				   PERLOTHRTUT(1)

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