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Mario Roy
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NAME

MCE::Step - Parallel step model for building creative steps

VERSION

This document describes MCE::Step version 1.805

DESCRIPTION

MCE::Step is similar to MCE::Flow for writing custom apps. The main difference comes from the transparent use of queues between sub-tasks. MCE 1.7 adds mce_enq, mce_enqp, and mce_await methods described under QUEUE-LIKE FEATURES below.

It is trivial to parallelize with mce_stream shown below.

   ## Native map function
   my @a = map { $_ * 4 } map { $_ * 3 } map { $_ * 2 } 1..10000;

   ## Same as with MCE::Stream (processing from right to left)
   @a = mce_stream
        sub { $_ * 4 }, sub { $_ * 3 }, sub { $_ * 2 }, 1..10000;

   ## Pass an array reference to have writes occur simultaneously
   mce_stream \@a,
        sub { $_ * 4 }, sub { $_ * 3 }, sub { $_ * 2 }, 1..10000;

However, let's have MCE::Step compute the same in parallel. Unlike the example in MCE::Flow, the use of MCE::Queue is totally transparent. This calls for preserving output order provided by MCE::Candy.

   use MCE::Step;
   use MCE::Candy;

Next are the 3 sub-tasks. Compare these 3 sub-tasks with the same as described in MCE::Flow. The call to MCE->step simplifies the passing of data to subsequent sub-task.

   sub task_a {
      my @ans; my ($mce, $chunk_ref, $chunk_id) = @_;
      push @ans, map { $_ * 2 } @{ $chunk_ref };
      MCE->step(\@ans, $chunk_id);
   }

   sub task_b {
      my @ans; my ($mce, $chunk_ref, $chunk_id) = @_;
      push @ans, map { $_ * 3 } @{ $chunk_ref };
      MCE->step(\@ans, $chunk_id);
   }

   sub task_c {
      my @ans; my ($mce, $chunk_ref, $chunk_id) = @_;
      push @ans, map { $_ * 4 } @{ $chunk_ref };
      MCE->gather($chunk_id, \@ans);
   }

In summary, MCE::Step builds out a MCE instance behind the scene and starts running. The task_name (shown), max_workers, and use_threads options can take an anonymous array for specifying the values uniquely per each sub-task.

The task_name option is required to use ->enq, ->enqp, and ->await.

   my @a;

   mce_step {
      task_name => [ 'a', 'b', 'c' ],
      gather => MCE::Candy::out_iter_array(\@a)

   }, \&task_a, \&task_b, \&task_c, 1..10000;

   print "@a\n";

STEP DEMO

In the demonstration below, one may call ->gather or ->step any number of times although ->step is not allowed in the last sub-block. Data is gathered to @arr which may likely be out-of-order. Gathering data is optional. All sub-blocks receive $mce as the first argument.

First, defining 3 sub-tasks.

   use MCE::Step;

   sub task_a {
      my ($mce, $chunk_ref, $chunk_id) = @_;

      if ($_ % 2 == 0) {
         MCE->gather($_);
       # MCE->gather($_ * 4);        ## Ok to gather multiple times
      }
      else {
         MCE->print("a step: $_, $_ * $_\n");
         MCE->step($_, $_ * $_);
       # MCE->step($_, $_ * 4 );     ## Ok to step multiple times
      }
   }

   sub task_b {
      my ($mce, $arg1, $arg2) = @_;

      MCE->print("b args: $arg1, $arg2\n");

      if ($_ % 3 == 0) {             ## $_ is the same as $arg1
         MCE->gather($_);
      }
      else {
         MCE->print("b step: $_ * $_\n");
         MCE->step($_ * $_);
      }
   }

   sub task_c {
      my ($mce, $arg1) = @_;

      MCE->print("c: $_\n");
      MCE->gather($_);
   }

Next, pass MCE options, using chunk_size 1, and run all 3 tasks in parallel. Notice how max_workers and use_threads can take an anonymous array, similarly to task_name.

   my @arr = mce_step {
      task_name   => [ 'a', 'b', 'c' ],
      max_workers => [  2,   2,   2  ],
      use_threads => [  0,   0,   0  ],
      chunk_size  => 1

   }, \&task_a, \&task_b, \&task_c, 1..10;

Finally, sort the array and display its contents.

   @arr = sort { $a <=> $b } @arr;

   print "\n@arr\n\n";

   -- Output

   a step: 1, 1 * 1
   a step: 3, 3 * 3
   a step: 5, 5 * 5
   a step: 7, 7 * 7
   a step: 9, 9 * 9
   b args: 1, 1
   b step: 1 * 1
   b args: 3, 9
   b args: 7, 49
   b step: 7 * 7
   b args: 5, 25
   b step: 5 * 5
   b args: 9, 81
   c: 1
   c: 49
   c: 25

   1 2 3 4 6 8 9 10 25 49

SYNOPSIS when CHUNK_SIZE EQUALS 1

Although MCE::Loop may be preferred for running using a single code block, the text below also applies to this module, particularly for the first block.

All models in MCE default to 'auto' for chunk_size. The arguments for the block are the same as writing a user_func block using the Core API.

Beginning with MCE 1.5, the next input item is placed into the input scalar variable $_ when chunk_size equals 1. Otherwise, $_ points to $chunk_ref containing many items. Basically, line 2 below may be omitted from your code when using $_. One can call MCE->chunk_id to obtain the current chunk id.

   line 1:  user_func => sub {
   line 2:     my ($mce, $chunk_ref, $chunk_id) = @_;
   line 3:
   line 4:     $_ points to $chunk_ref->[0]
   line 5:        in MCE 1.5 when chunk_size == 1
   line 6:
   line 7:     $_ points to $chunk_ref
   line 8:        in MCE 1.5 when chunk_size  > 1
   line 9:  }

Follow this synopsis when chunk_size equals one. Looping is not required from inside the first block. Hence, the block is called once per each item.

   ## Exports mce_step, mce_step_f, and mce_step_s
   use MCE::Step;

   MCE::Step::init {
      chunk_size => 1
   };

   ## Array or array_ref
   mce_step sub { do_work($_) }, 1..10000;
   mce_step sub { do_work($_) }, [ 1..10000 ];

   ## File_path, glob_ref, or scalar_ref
   mce_step_f sub { chomp; do_work($_) }, "/path/to/file";
   mce_step_f sub { chomp; do_work($_) }, $file_handle;
   mce_step_f sub { chomp; do_work($_) }, \$scalar;

   ## Sequence of numbers (begin, end [, step, format])
   mce_step_s sub { do_work($_) }, 1, 10000, 5;
   mce_step_s sub { do_work($_) }, [ 1, 10000, 5 ];

   mce_step_s sub { do_work($_) }, {
      begin => 1, end => 10000, step => 5, format => undef
   };

SYNOPSIS when CHUNK_SIZE is GREATER THAN 1

Follow this synopsis when chunk_size equals 'auto' or greater than 1. This means having to loop through the chunk from inside the first block.

   use MCE::Step;

   MCE::Step::init {          ## Chunk_size defaults to 'auto' when
      chunk_size => 'auto'    ## not specified. Therefore, the init
   };                         ## function may be omitted.

   ## Syntax is shown for mce_step for demonstration purposes.
   ## Looping inside the block is the same for mce_step_f and
   ## mce_step_s.

   mce_step sub { do_work($_) for (@{ $_ }) }, 1..10000;

   ## Same as above, resembles code using the Core API.

   mce_step sub {
      my ($mce, $chunk_ref, $chunk_id) = @_;

      for (@{ $chunk_ref }) {
         do_work($_);
      }

   }, 1..10000;

Chunking reduces the number of IPC calls behind the scene. Think in terms of chunks whenever processing a large amount of data. For relatively small data, choosing 1 for chunk_size is fine.

OVERRIDING DEFAULTS

The following list options which may be overridden when loading the module.

   use Sereal qw( encode_sereal decode_sereal );
   use CBOR::XS qw( encode_cbor decode_cbor );
   use JSON::XS qw( encode_json decode_json );

   use MCE::Step
       max_workers => 8,                # Default 'auto'
       chunk_size => 500,               # Default 'auto'
       tmp_dir => "/path/to/app/tmp",   # $MCE::Signal::tmp_dir
       freeze => \&encode_sereal,       # \&Storable::freeze
       thaw => \&decode_sereal,         # \&Storable::thaw
       fast => 1                        # Default 0 (fast dequeue)
   ;

From MCE 1.8 onwards, Sereal 3.008+ is loaded automatically if available. Specify Sereal = 0> to use Storable instead.

   use MCE::Step Sereal => 0;

CUSTOMIZING MCE

MCE::Step->init ( options )
MCE::Step::init { options }

The init function accepts a hash of MCE options. Unlike with MCE::Stream, both gather and bounds_only options may be specified when calling init (not shown below).

   use MCE::Step;

   MCE::Step::init {
      chunk_size => 1, max_workers => 4,

      user_begin => sub {
         print "## ", MCE->wid, " started\n";
      },

      user_end => sub {
         print "## ", MCE->wid, " completed\n";
      }
   };

   my %a = mce_step sub { MCE->gather($_, $_ * $_) }, 1..100;

   print "\n", "@a{1..100}", "\n";

   -- Output

   ## 3 started
   ## 1 started
   ## 4 started
   ## 2 started
   ## 3 completed
   ## 4 completed
   ## 1 completed
   ## 2 completed

   1 4 9 16 25 36 49 64 81 100 121 144 169 196 225 256 289 324 361
   400 441 484 529 576 625 676 729 784 841 900 961 1024 1089 1156
   1225 1296 1369 1444 1521 1600 1681 1764 1849 1936 2025 2116 2209
   2304 2401 2500 2601 2704 2809 2916 3025 3136 3249 3364 3481 3600
   3721 3844 3969 4096 4225 4356 4489 4624 4761 4900 5041 5184 5329
   5476 5625 5776 5929 6084 6241 6400 6561 6724 6889 7056 7225 7396
   7569 7744 7921 8100 8281 8464 8649 8836 9025 9216 9409 9604 9801
   10000

Like with MCE::Step::init above, MCE options may be specified using an anonymous hash for the first argument. Notice how task_name, max_workers, and use_threads can take an anonymous array for setting uniquely per each code block.

Unlike MCE::Stream which processes from right-to-left, MCE::Step begins with the first code block, thus processing from left-to-right.

The following takes 9 seconds to complete. The 9 seconds is from having only 2 workers assigned for the last sub-task and waiting 1 or 2 seconds initially before calling MCE->step.

Removing both calls to MCE->step will cause the script to complete in just 1 second. The reason is due to the 2nd and subsequent sub-tasks awaiting data from an internal queue. Workers terminate upon receiving an undef.

   use threads;
   use MCE::Step;

   my @a = mce_step {
      task_name   => [ 'a', 'b', 'c' ],
      max_workers => [  3,   4,   2, ],
      use_threads => [  1,   0,   0, ],

      user_end => sub {
         my ($mce, $task_id, $task_name) = @_;
         MCE->print("$task_id - $task_name completed\n");
      },

      task_end => sub {
         my ($mce, $task_id, $task_name) = @_;
         MCE->print("$task_id - $task_name ended\n");
      }
   },
   sub { sleep 1; MCE->step(""); },   ## 3 workers, named a
   sub { sleep 2; MCE->step(""); },   ## 4 workers, named b
   sub { sleep 3;                };   ## 2 workers, named c

   -- Output

   0 - a completed
   0 - a completed
   0 - a completed
   0 - a ended
   1 - b completed
   1 - b completed
   1 - b completed
   1 - b completed
   1 - b ended
   2 - c completed
   2 - c completed
   2 - c ended

API DOCUMENTATION

Although input data is optional for MCE::Step, the following assumes chunk_size equals 1 in order to demonstrate all the possibilities of passing input data into the code block.

MCE::Step->run ( { input_data => iterator }, sub { code } )
mce_step { input_data => iterator }, sub { code }

An iterator reference can by specified for input_data. The only other way is to specify input_data via MCE::Step::init. This prevents MCE::Step from configuring the iterator reference as another user task which will not work.

Iterators are described under "SYNTAX for INPUT_DATA" at MCE::Core.

   MCE::Step::init {
      input_data => iterator
   };

   mce_step sub { $_ };
MCE::Step->run ( sub { code }, list )
mce_step sub { code }, list

Input data can be defined using a list.

   mce_step sub { $_ }, 1..1000;
   mce_step sub { $_ }, [ 1..1000 ];
MCE::Step->run_file ( sub { code }, file )
mce_step_f sub { code }, file

The fastest of these is the /path/to/file. Workers communicate the next offset position among themselves without any interaction from the manager process.

   mce_step_f sub { $_ }, "/path/to/file";
   mce_step_f sub { $_ }, $file_handle;
   mce_step_f sub { $_ }, \$scalar;
MCE::Step->run_seq ( sub { code }, $beg, $end [, $step, $fmt ] )
mce_step_s sub { code }, $beg, $end [, $step, $fmt ]

Sequence can be defined as a list, an array reference, or a hash reference. The functions require both begin and end values to run. Step and format are optional. The format is passed to sprintf (% may be omitted below).

   my ($beg, $end, $step, $fmt) = (10, 20, 0.1, "%4.1f");

   mce_step_s sub { $_ }, $beg, $end, $step, $fmt;
   mce_step_s sub { $_ }, [ $beg, $end, $step, $fmt ];

   mce_step_s sub { $_ }, {
      begin => $beg, end => $end, step => $step, format => $fmt
   };

The sequence engine can compute 'begin' and 'end' items only, for the chunk, and not the items in between (hence boundaries only). This option applies to sequence only and has no effect when chunk_size equals 1.

The time to run is 0.006s below. This becomes 0.827s without the bounds_only option due to computing all items in between, thus creating a very large array. Basically, specify bounds_only => 1 when boundaries is all you need for looping inside the block; e.g. Monte Carlo simulations.

Time was measured using 1 worker to emphasize the difference.

   use MCE::Step;

   MCE::Step::init {
      max_workers => 1, chunk_size => 1_250_000,
      bounds_only => 1
   };

   ## For sequence, the input scalar $_ points to $chunk_ref
   ## when chunk_size > 1, otherwise $chunk_ref->[0].
   ##
   ## mce_step_s sub {
   ##    my $begin = $_->[0]; my $end = $_->[-1];
   ##
   ##    for ($begin .. $end) {
   ##       ...
   ##    }
   ##
   ## }, 1, 10_000_000;

   mce_step_s sub {
      my ($mce, $chunk_ref, $chunk_id) = @_;
      ## $chunk_ref contains 2 items, not 1_250_000

      my $begin = $chunk_ref->[ 0];
      my $end   = $chunk_ref->[-1];   ## or $chunk_ref->[1]

      MCE->printf("%7d .. %8d\n", $begin, $end);

   }, 1, 10_000_000;

   -- Output

         1 ..  1250000
   1250001 ..  2500000
   2500001 ..  3750000
   3750001 ..  5000000
   5000001 ..  6250000
   6250001 ..  7500000
   7500001 ..  8750000
   8750001 .. 10000000

QUEUE-LIKE FEATURES

MCE->step ( item )
MCE->step ( arg1, arg2, argN )

The ->step method is the simplest form for passing elements into the next sub-task.

   use MCE::Step;

   sub provider {
      MCE->step( $_, rand ) for 10 .. 19;
   }

   sub consumer {
      my ( $mce, @args ) = @_;
      MCE->printf( "%d: %d, %03.06f\n", MCE->wid, $args[0], $args[1] );
   }

   MCE::Step::init {
      task_name   => [ 'p', 'c' ],
      max_workers => [  1 ,  4  ]
   };

   mce_step \&provider, \&consumer;

   -- Output

   2: 10, 0.583551
   4: 11, 0.175319
   3: 12, 0.843662
   4: 15, 0.748302
   2: 14, 0.591752
   3: 16, 0.357858
   5: 13, 0.953528
   4: 17, 0.698907
   2: 18, 0.985448
   3: 19, 0.146548
MCE->enq ( task_name, item )
MCE->enq ( task_name, [ arg1, arg2, argN ] )
MCE->enq ( task_name, [ arg1, arg2 ], [ arg1, arg2 ] )
MCE->enqp ( task_name, priority, item )
MCE->enqp ( task_name, priority, [ arg1, arg2, argN ] )
MCE->enqp ( task_name, priority, [ arg1, arg2 ], [ arg1, arg2 ] )

The MCE 1.7 release enables finer control. Unlike ->step, which take multiple arguments, the ->enq and ->enqp methods push items at the end of the array internally. Passing multiple arguments is possible by enclosing the arguments inside an anonymous array.

The direction of flow is forward only. Thus, stepping to itself or backwards will cause an error.

   use MCE::Step;

   sub provider {
      if ( MCE->wid % 2 == 0 ) {
         MCE->enq( 'c', [ $_, rand ] ) for 10 .. 19;
      } else {
         MCE->enq( 'd', [ $_, rand ] ) for 20 .. 29;
      }
   }

   sub consumer_c {
      my ( $mce, $args ) = @_;
      MCE->printf( "C%d: %d, %03.06f\n", MCE->wid, $args->[0], $args->[1] );
   }

   sub consumer_d {
      my ( $mce, $args ) = @_;
      MCE->printf( "D%d: %d, %03.06f\n", MCE->wid, $args->[0], $args->[1] );
   }

   MCE::Step::init {
      task_name   => [ 'p', 'c', 'd' ],
      max_workers => [  2 ,  3 ,  3  ]
   };

   mce_step \&provider, \&consumer_c, \&consumer_d;

   -- Output

   C4: 10, 0.527531
   D6: 20, 0.420108
   C5: 11, 0.839770
   D8: 21, 0.386414
   C3: 12, 0.834645
   C4: 13, 0.191014
   D6: 23, 0.924027
   C5: 14, 0.899357
   D8: 24, 0.706186
   C4: 15, 0.083823
   D7: 22, 0.479708
   D6: 25, 0.073882
   C3: 16, 0.207446
   D8: 26, 0.560755
   C5: 17, 0.198157
   D7: 27, 0.324909
   C4: 18, 0.147505
   C5: 19, 0.318371
   D6: 28, 0.220465
   D8: 29, 0.630111
MCE->await ( task_name, pending_threshold )

Providers may sometime run faster than consumers. Thus, increasing memory consumption. MCE 1.7 adds the ->await method for pausing momentarily until the receiving sub-task reaches the minimum threshold for the number of items pending in its queue.

   use MCE::Step;
   use Time::HiRes 'sleep';

   sub provider {
      for ( 10 .. 29 ) {
         # wait until 10 or less items pending
         MCE->await( 'c', 10 );
         # forward item to a later sub-task ( 'c' comes after 'p' )
         MCE->enq( 'c', [ $_, rand ] );
      }
   }

   sub consumer {
      my ($mce, $args) = @_;
      MCE->printf( "%d: %d, %03.06f\n", MCE->wid, $args->[0], $args->[1] );
      sleep 0.05;
   }

   MCE::Step::init {
      task_name   => [ 'p', 'c' ],
      max_workers => [  1 ,  4  ]
   };

   mce_step \&provider, \&consumer;

   -- Output

   3: 10, 0.527307
   2: 11, 0.036193
   5: 12, 0.987168
   4: 13, 0.998140
   5: 14, 0.219526
   4: 15, 0.061609
   2: 16, 0.557664
   3: 17, 0.658684
   4: 18, 0.240932
   3: 19, 0.241042
   5: 20, 0.884830
   2: 21, 0.902223
   4: 22, 0.699223
   3: 23, 0.208270
   5: 24, 0.438919
   2: 25, 0.268854
   4: 26, 0.596425
   5: 27, 0.979818
   2: 28, 0.918173
   3: 29, 0.358266

GATHERING DATA

Unlike MCE::Map where gather and output order are done for you automatically, the gather method is used to have results sent back to the manager process.

   use MCE::Step chunk_size => 1;

   ## Output order is not guaranteed.
   my @a = mce_step sub { MCE->gather($_ * 2) }, 1..100;
   print "@a\n\n";

   ## Outputs to a hash instead (key, value).
   my %h1 = mce_step sub { MCE->gather($_, $_ * 2) }, 1..100;
   print "@h1{1..100}\n\n";

   ## This does the same thing due to chunk_id starting at one.
   my %h2 = mce_step sub { MCE->gather(MCE->chunk_id, $_ * 2) }, 1..100;
   print "@h2{1..100}\n\n";

The gather method can be called multiple times within the block unlike return which would leave the block. Therefore, think of gather as yielding results immediately to the manager process without actually leaving the block.

   use MCE::Step chunk_size => 1, max_workers => 3;

   my @hosts = qw(
      hosta hostb hostc hostd hoste
   );

   my %h3 = mce_step sub {
      my ($output, $error, $status); my $host = $_;

      ## Do something with $host;
      $output = "Worker ". MCE->wid .": Hello from $host";

      if (MCE->chunk_id % 3 == 0) {
         ## Simulating an error condition
         local $? = 1; $status = $?;
         $error = "Error from $host"
      }
      else {
         $status = 0;
      }

      ## Ensure unique keys (key, value) when gathering to
      ## a hash.
      MCE->gather("$host.out", $output);
      MCE->gather("$host.err", $error) if (defined $error);
      MCE->gather("$host.sta", $status);

   }, @hosts;

   foreach my $host (@hosts) {
      print $h3{"$host.out"}, "\n";
      print $h3{"$host.err"}, "\n" if (exists $h3{"$host.err"});
      print "Exit status: ", $h3{"$host.sta"}, "\n\n";
   }

   -- Output

   Worker 3: Hello from hosta
   Exit status: 0

   Worker 2: Hello from hostb
   Exit status: 0

   Worker 1: Hello from hostc
   Error from hostc
   Exit status: 1

   Worker 3: Hello from hostd
   Exit status: 0

   Worker 2: Hello from hoste
   Exit status: 0

The following uses an anonymous array containing 3 elements when gathering data. Serialization is automatic behind the scene.

   my %h3 = mce_step sub {
      ...

      MCE->gather($host, [$output, $error, $status]);

   }, @hosts;

   foreach my $host (@hosts) {
      print $h3{$host}->[0], "\n";
      print $h3{$host}->[1], "\n" if (defined $h3{$host}->[1]);
      print "Exit status: ", $h3{$host}->[2], "\n\n";
   }

Although MCE::Map comes to mind, one may want additional control when gathering data such as retaining output order.

   use MCE::Step;

   sub preserve_order {
      my %tmp; my $order_id = 1; my $gather_ref = $_[0];

      return sub {
         $tmp{ (shift) } = \@_;

         while (1) {
            last unless exists $tmp{$order_id};
            push @{ $gather_ref }, @{ delete $tmp{$order_id++} };
         }

         return;
      };
   }

   ## Workers persist for the most part after running. Though, not always
   ## the case and depends on Perl. Pass a reference to a subroutine if
   ## workers must persist; e.g. mce_step { ... }, \&foo, 1..100000.

   MCE::Step::init {
      chunk_size => 'auto', max_workers => 'auto'
   };

   for (1..2) {
      my @m2;

      mce_step {
         gather => preserve_order(\@m2)
      },
      sub {
         my @a; my ($mce, $chunk_ref, $chunk_id) = @_;

         ## Compute the entire chunk data at once.
         push @a, map { $_ * 2 } @{ $chunk_ref };

         ## Afterwards, invoke the gather feature, which
         ## will direct the data to the callback function.
         MCE->gather(MCE->chunk_id, @a);

      }, 1..100000;

      print scalar @m2, "\n";
   }

   MCE::Step::finish;

All 6 models support 'auto' for chunk_size unlike the Core API. Think of the models as the basis for providing JIT for MCE. They create the instance, tune max_workers, and tune chunk_size automatically regardless of the hardware.

The following does the same thing using the Core API. Workers persist after running.

   use MCE;

   sub preserve_order {
      ...
   }

   my $mce = MCE->new(
      max_workers => 'auto', chunk_size => 8000,

      user_func => sub {
         my @a; my ($mce, $chunk_ref, $chunk_id) = @_;

         ## Compute the entire chunk data at once.
         push @a, map { $_ * 2 } @{ $chunk_ref };

         ## Afterwards, invoke the gather feature, which
         ## will direct the data to the callback function.
         MCE->gather(MCE->chunk_id, @a);
      }
   );

   for (1..2) {
      my @m2;

      $mce->process({ gather => preserve_order(\@m2) }, [1..100000]);

      print scalar @m2, "\n";
   }

   $mce->shutdown;

MANUAL SHUTDOWN

MCE::Step->finish
MCE::Step::finish

Workers remain persistent as much as possible after running. Shutdown occurs automatically when the script terminates. Call finish when workers are no longer needed.

   use MCE::Step;

   MCE::Step::init {
      chunk_size => 20, max_workers => 'auto'
   };

   mce_step sub { ... }, 1..100;

   MCE::Step::finish;

INDEX

MCE, MCE::Core

AUTHOR

Mario E. Roy, <marioeroy AT gmail DOT com>