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perlthrtut ()
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         perlthrtut - tutorial on threads in Perl


             WARNING: Threading is an experimental feature.  Both the interface
             and implementation are subject to change drastically.  In fact, this
             documentation describes the flavor of threads that was in version
             5.005.  Perl 5.6.0 and later have the beginnings of support for
             interpreter threads, which (when finished) is expected to be
             significantly different from what is described here.  The information
             contained here may therefore soon be obsolete.  Use at your own risk!
         One of the most prominent new features of Perl 5.005 is the
         inclusion of threads.  Threads make a number of things a lot
         easier, and are a very useful addition to your bag of
         programming tricks.

    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.
         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 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.
         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
         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

    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
         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.
         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.
         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

    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
         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 create
         a threaded program.   After that, we'll go over some of the
         features of the Thread module that make threaded programming
         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 need
         to create basic threads.
         The simplest, straightforward way to create a thread is with
             use Thread;
             $thr = new Thread \&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 = new Thread \&sub1, "Param 1", "Param 2", $Param3;
             $thr = new Thread \&sub1, @ParamList;
             $thr = new Thread \&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
         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 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
         Perl's threading package provides the yield() function that
         does this. yield() is pretty straightforward, and works like
             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 = new Thread \&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 = new Thread \&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 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
             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
         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
             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
         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
         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;
             $b = "foo";
             async {
                 sleep 20;
                 lock ($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
         straightforward, and look like this:
             use Thread qw(async);
             use Thread::Queue;
             my $DataQueue = new Thread::Queue;
             $thr = async {
                 while ($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
                 use Thread qw(yield);
                 use Thread::Semaphore;
                 my $semaphore = new Thread::Semaphore;
                 $GlobalVariable = 0;
                 $thr1 = new Thread \&sample_sub, 1;
                 $thr2 = new Thread \&sample_sub, 2;
                 $thr3 = new Thread \&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 $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 to
         serialize calls to a particular subroutine than to have a
         set of locks and sempahores.
         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);
             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 $bar = new Foo;
                 foreach (1..10) {
                     print "$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 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
         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
         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
         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)) {
         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 = new Thread::Queue;
             10 my $kid    = new Thread(\&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 = new Thread::Queue;
             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 = new Thread(\&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).
         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 documention
         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 Jrgen Christoffel:
         Introductory Texts
         Birrell, Andrew D. An Introduction to Programming with
         Threads. Digital Equipment Corporation, 1989, DEC-SRC
         Research Report #35 online as
         (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
         Tanenbaum, Andrew S. Distributed Operating Systems. Prentice
         Hall, 1995, ISBN 0-13-143934-0 (great textbook).
         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).


         Thanks (in no particular order) to Chaim Frenkel, Steve
         Fink, Gurusamy Sarathy, Ilya Zakharevich, Benjamin Sugars,
         Jrgen 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 <>


         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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