package Bencher::Scenario::StringFunctions::CommonPrefix;

our $DATE = '2021-07-31'; # DATE
our $VERSION = '0.005'; # VERSION

use strict;
use warnings;

our $scenario = {
    summary => "Benchmark calculating common prefix",
    participants => [
        {fcall_template=>'String::CommonPrefix::common_prefix(@{<strings>})'},
    ],
    datasets => [
        {name=>'elems0'          , args=>{strings=>[]}},
        {name=>'elems1'          , args=>{strings=>['x']}},
        {name=>'elems10prefix0'  , args=>{strings=>[map{sprintf "%02d", $_} 1..10]}},
        {name=>'elems10prefix1'  , args=>{strings=>[map{sprintf "%02d", $_} 0..9]}},
        {name=>'elems100prefix0' , args=>{strings=>[map{sprintf "%03d", $_} 1..100]}},
        {name=>'elems100prefix1' , args=>{strings=>[map{sprintf "%03d", $_} 0..99]}},
        {name=>'elems1000prefix0', args=>{strings=>[map{sprintf "%04d", $_} 1..1000]}},
        {name=>'elems1000prefix1', args=>{strings=>[map{sprintf "%04d", $_} 0..999]}},
    ],
};

1;
# ABSTRACT: Benchmark calculating common prefix

__END__

=pod

=encoding UTF-8

=head1 NAME

Bencher::Scenario::StringFunctions::CommonPrefix - Benchmark calculating common prefix

=head1 VERSION

This document describes version 0.005 of Bencher::Scenario::StringFunctions::CommonPrefix (from Perl distribution Bencher-Scenarios-StringFunctions), released on 2021-07-31.

=head1 SYNOPSIS

To run benchmark with default option:

 % bencher -m StringFunctions::CommonPrefix

To run module startup overhead benchmark:

 % bencher --module-startup -m StringFunctions::CommonPrefix

For more options (dump scenario, list/include/exclude/add participants, list/include/exclude/add datasets, etc), see L<bencher> or run C<bencher --help>.

=head1 DESCRIPTION

Packaging a benchmark script as a Bencher scenario makes it convenient to include/exclude/add participants/datasets (either via CLI or Perl code), send the result to a central repository, among others . See L<Bencher> and L<bencher> (CLI) for more details.

=head1 BENCHMARKED MODULES

Version numbers shown below are the versions used when running the sample benchmark.

L<String::CommonPrefix> 0.01

=head1 BENCHMARK PARTICIPANTS

=over

=item * String::CommonPrefix::common_prefix (perl_code)

Function call template:

 String::CommonPrefix::common_prefix(@{<strings>})



=back

=head1 BENCHMARK DATASETS

=over

=item * elems0

=item * elems1

=item * elems10prefix0

=item * elems10prefix1

=item * elems100prefix0

=item * elems100prefix1

=item * elems1000prefix0

=item * elems1000prefix1

=back

=head1 BENCHMARK SAMPLE RESULTS

Run on: perl: I<< v5.34.0 >>, CPU: I<< Intel(R) Core(TM) i7-4770 CPU @ 3.40GHz (4 cores) >>, OS: I<< GNU/Linux LinuxMint version 19 >>, OS kernel: I<< Linux version 5.3.0-68-generic >>.

Benchmark command (default options):

 % bencher -m StringFunctions::CommonPrefix

Result formatted as table (split, part 1 of 8):

 #table1#
 {dataset=>"elems0"}
 +-------------------------------------+---------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | participant                         | dataset | ds_tags | p_tags | perl | rate (/s) | time (ns) | pct_faster_vs_slowest | pct_slower_vs_fastest |  errors | samples |
 +-------------------------------------+---------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | String::CommonPrefix::common_prefix | elems0  |         |        | perl |   8690000 |       115 |                 0.00% |                 0.00% | 5.4e-11 |      21 |
 +-------------------------------------+---------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+

The above result formatted in L<Benchmark.pm|Benchmark> style:

          Rate     
     8690000/s  -- 
 
 Legends:
   : dataset=elems0 ds_tags= p_tags= participant=String::CommonPrefix::common_prefix perl=perl

The above result presented as chart:

=begin html

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" />

=end html


Result formatted as table (split, part 2 of 8):

 #table2#
 {dataset=>"elems1"}
 +-------------------------------------+---------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | participant                         | dataset | ds_tags | p_tags | perl | rate (/s) | time (ns) | pct_faster_vs_slowest | pct_slower_vs_fastest |  errors | samples |
 +-------------------------------------+---------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | String::CommonPrefix::common_prefix | elems1  |         |        | perl |   2470000 |       405 |                 0.00% |                 0.00% | 1.9e-10 |      24 |
 +-------------------------------------+---------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+

The above result formatted in L<Benchmark.pm|Benchmark> style:

          Rate     
     2470000/s  -- 
 
 Legends:
   : dataset=elems1 ds_tags= p_tags= participant=String::CommonPrefix::common_prefix perl=perl

The above result presented as chart:

=begin html

<img 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/>

=end html


Result formatted as table (split, part 3 of 8):

 #table3#
 {dataset=>"elems1000prefix0"}
 +-------------------------------------+------------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | participant                         | dataset          | ds_tags | p_tags | perl | rate (/s) | time (μs) | pct_faster_vs_slowest | pct_slower_vs_fastest |  errors | samples |
 +-------------------------------------+------------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | String::CommonPrefix::common_prefix | elems1000prefix0 |         |        | perl |      5580 |       179 |                 0.00% |                 0.00% | 5.3e-08 |      20 |
 +-------------------------------------+------------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+

The above result formatted in L<Benchmark.pm|Benchmark> style:

       Rate     
     5580/s  -- 
 
 Legends:
   : dataset=elems1000prefix0 ds_tags= p_tags= participant=String::CommonPrefix::common_prefix perl=perl

The above result presented as chart:

=begin html

<img src="data:image/png;base64,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" />

=end html


Result formatted as table (split, part 4 of 8):

 #table4#
 {dataset=>"elems1000prefix1"}
 +-------------------------------------+------------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | participant                         | dataset          | ds_tags | p_tags | perl | rate (/s) | time (μs) | pct_faster_vs_slowest | pct_slower_vs_fastest |  errors | samples |
 +-------------------------------------+------------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | String::CommonPrefix::common_prefix | elems1000prefix1 |         |        | perl |      4800 |       210 |                 0.00% |                 0.00% | 2.1e-07 |      20 |
 +-------------------------------------+------------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+

The above result formatted in L<Benchmark.pm|Benchmark> style:

       Rate     
     4800/s  -- 
 
 Legends:
   : dataset=elems1000prefix1 ds_tags= p_tags= participant=String::CommonPrefix::common_prefix perl=perl

The above result presented as chart:

=begin html

<img 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/>

=end html


Result formatted as table (split, part 5 of 8):

 #table5#
 {dataset=>"elems100prefix0"}
 +-------------------------------------+-----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | participant                         | dataset         | ds_tags | p_tags | perl | rate (/s) | time (μs) | pct_faster_vs_slowest | pct_slower_vs_fastest |  errors | samples |
 +-------------------------------------+-----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | String::CommonPrefix::common_prefix | elems100prefix0 |         |        | perl |     55000 |        18 |                 0.00% |                 0.00% | 2.6e-08 |      21 |
 +-------------------------------------+-----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+

The above result formatted in L<Benchmark.pm|Benchmark> style:

        Rate     
     55000/s  -- 
 
 Legends:
   : dataset=elems100prefix0 ds_tags= p_tags= participant=String::CommonPrefix::common_prefix perl=perl

The above result presented as chart:

=begin html

<img 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/>

=end html


Result formatted as table (split, part 6 of 8):

 #table6#
 {dataset=>"elems100prefix1"}
 +-------------------------------------+-----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | participant                         | dataset         | ds_tags | p_tags | perl | rate (/s) | time (μs) | pct_faster_vs_slowest | pct_slower_vs_fastest |  errors | samples |
 +-------------------------------------+-----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | String::CommonPrefix::common_prefix | elems100prefix1 |         |        | perl |     47200 |      21.2 |                 0.00% |                 0.00% | 5.7e-09 |      27 |
 +-------------------------------------+-----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+

The above result formatted in L<Benchmark.pm|Benchmark> style:

        Rate     
     47200/s  -- 
 
 Legends:
   : dataset=elems100prefix1 ds_tags= p_tags= participant=String::CommonPrefix::common_prefix perl=perl

The above result presented as chart:

=begin html

<img 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/>

=end html


Result formatted as table (split, part 7 of 8):

 #table7#
 {dataset=>"elems10prefix0"}
 +-------------------------------------+----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | participant                         | dataset        | ds_tags | p_tags | perl | rate (/s) | time (μs) | pct_faster_vs_slowest | pct_slower_vs_fastest |  errors | samples |
 +-------------------------------------+----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | String::CommonPrefix::common_prefix | elems10prefix0 |         |        | perl |    460000 |       2.2 |                 0.00% |                 0.00% | 2.5e-09 |      20 |
 +-------------------------------------+----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+

The above result formatted in L<Benchmark.pm|Benchmark> style:

         Rate     
     460000/s  -- 
 
 Legends:
   : dataset=elems10prefix0 ds_tags= p_tags= participant=String::CommonPrefix::common_prefix perl=perl

The above result presented as chart:

=begin html

<img 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/>

=end html


Result formatted as table (split, part 8 of 8):

 #table8#
 {dataset=>"elems10prefix1"}
 +-------------------------------------+----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | participant                         | dataset        | ds_tags | p_tags | perl | rate (/s) | time (μs) | pct_faster_vs_slowest | pct_slower_vs_fastest |  errors | samples |
 +-------------------------------------+----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+
 | String::CommonPrefix::common_prefix | elems10prefix1 |         |        | perl |    396000 |      2.53 |                 0.00% |                 0.00% | 7.3e-10 |      26 |
 +-------------------------------------+----------------+---------+--------+------+-----------+-----------+-----------------------+-----------------------+---------+---------+

The above result formatted in L<Benchmark.pm|Benchmark> style:

         Rate     
     396000/s  -- 
 
 Legends:
   : dataset=elems10prefix1 ds_tags= p_tags= participant=String::CommonPrefix::common_prefix perl=perl

The above result presented as chart:

=begin html

<img 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=end html


Benchmark module startup overhead (C<< bencher -m StringFunctions::CommonPrefix --module-startup >>):

Result formatted as table:

 #table9#
 +----------------------+-----------+-------------------+-----------------------+-----------------------+---------+---------+
 | participant          | time (ms) | mod_overhead_time | pct_faster_vs_slowest | pct_slower_vs_fastest |  errors | samples |
 +----------------------+-----------+-------------------+-----------------------+-----------------------+---------+---------+
 | String::CommonPrefix |         8 |                 4 |                 0.00% |                92.35% | 0.00022 |      20 |
 | perl -e1 (baseline)  |         4 |                 0 |                92.35% |                 0.00% | 0.00013 |      20 |
 +----------------------+-----------+-------------------+-----------------------+-----------------------+---------+---------+


The above result formatted in L<Benchmark.pm|Benchmark> style:

                Rate   S:C  :perl -e1 ( 
  S:C          0.1/s    --         -50% 
  :perl -e1 (  0.2/s  100%           -- 
 
 Legends:
   :perl -e1 (: mod_overhead_time=0 participant=perl -e1 (baseline)
   S:C: mod_overhead_time=4 participant=String::CommonPrefix

The above result presented as chart:

=begin html

<img 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/>

=end html


To display as an interactive HTML table on a browser, you can add option C<--format html+datatables>.

=head1 HOMEPAGE

Please visit the project's homepage at L<https://metacpan.org/release/Bencher-Scenarios-StringFunctions>.

=head1 SOURCE

Source repository is at L<https://github.com/perlancar/perl-Bencher-Scenarios-StringFunctions>.

=head1 BUGS

Please report any bugs or feature requests on the bugtracker website L<https://rt.cpan.org/Public/Dist/Display.html?Name=Bencher-Scenarios-StringFunctions>

When submitting a bug or request, please include a test-file or a
patch to an existing test-file that illustrates the bug or desired
feature.

=head1 AUTHOR

perlancar <perlancar@cpan.org>

=head1 COPYRIGHT AND LICENSE

This software is copyright (c) 2021, 2018 by perlancar@cpan.org.

This is free software; you can redistribute it and/or modify it under
the same terms as the Perl 5 programming language system itself.

=cut