Acme-CPANModules-UUID
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Code template:
UUID::Tiny::create_uuid() for 1..1000; UUID::Tiny::uuid_to_string(UUID::Tiny::create_uuid())
* UUID::Random (perl_code)
Code template:
UUID::Random::generate() for 1..1000; ; UUID::Random::generate()
* UUID::Random::PERLANCAR::generate (perl_code)
Code template:
UUID::Random::PERLANCAR::generate() for 1..1000; UUID::Random::PERLANCAR::generate()
* UUID::Random::PERLANCAR::generate_rfc (perl_code)
Code template:
UUID::Random::PERLANCAR::generate_rfc() for 1..1000; UUID::Random::PERLANCAR::generate_rfc()
* UUID::Random::Secure::generate (perl_code)
Code template:
UUID::Random::Secure::generate() for 1..1000; UUID::Random::Secure::generate()
* UUID::Random::Secure::generate_rfc (perl_code)
Code template:
UUID::Random::Secure::generate_rfc() for 1..1000; UUID::Random::Secure::generate_rfc()
* Crypt::Misc (perl_code)
Code template:
Crypt::Misc::random_v4uuid() for 1..1000; Crypt::Misc::random_v4uuid()
* UUID (perl_code)
Code template:
my $uuid; UUID::generate_random($uuid) for 1..1000; UUID::generate_random($uuid); $uuid
BENCHMARK SAMPLE RESULTS
Sample benchmark #1
Run on: perl: *v5.38.0*, CPU: *Intel(R) Core(TM) i5-7200U CPU @ 2.50GHz
(2 cores)*, OS: *GNU/Linux Ubuntu version 20.04*, OS kernel: *Linux
version 5.4.0-164-generic*.
Benchmark command (default options):
% bencher --cpanmodules-module UUID
Result formatted as table:
#table1#
+---------------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+
| participant | rate (/s) | time (ms) | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples |
+---------------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+
| UUID::Random::Secure::generate | 30 | 30 | 0.00% | 4218.76% | 0.0013 | 22 |
| UUID::Random::Secure::generate_rfc | 40 | 20 | 42.61% | 2928.29% | 0.0003 | 21 |
| UUID::Random | 100 | 9 | 257.90% | 1106.70% | 0.00018 | 20 |
| UUID::Tiny | 100 | 8 | 335.56% | 891.54% | 0.00013 | 20 |
| UUID | 171 | 5.84 | 481.07% | 643.25% | 1.4e-06 | 21 |
| Crypt::Misc | 296 | 3.37 | 906.43% | 329.12% | 2.6e-06 | 20 |
| UUID::Random::PERLANCAR::generate_rfc | 520 | 1.9 | 1682.35% | 142.31% | 7.6e-06 | 20 |
| UUID::Random::PERLANCAR::generate | 900 | 1 | 2809.14% | 48.45% | 2.5e-05 | 23 |
| UUID::FFI | 870 | 1.2 | 2848.45% | 46.48% | 1.8e-06 | 20 |
| Data::UUID | 1000 | 0.8 | 4218.76% | 0.00% | 9.3e-06 | 21 |
+---------------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+
The above result formatted in Benchmark.pm style:
Rate URS:g URS:g_r U:R U:T U C:M URP:g_r U:F URP:g D:U
URS:g 30/s -- -33% -70% -73% -80% -88% -93% -96% -96% -97%
URS:g_r 40/s 50% -- -55% -60% -70% -83% -90% -94% -95% -96%
U:R 100/s 233% 122% -- -11% -35% -62% -78% -86% -88% -91%
U:T 100/s 275% 150% 12% -- -27% -57% -76% -85% -87% -90%
U 171/s 413% 242% 54% 36% -- -42% -67% -79% -82% -86%
C:M 296/s 790% 493% 167% 137% 73% -- -43% -64% -70% -76%
URP:g_r 520/s 1478% 952% 373% 321% 207% 77% -- -36% -47% -57%
U:F 870/s 2400% 1566% 650% 566% 386% 180% 58% -- -16% -33%
URP:g 900/s 2900% 1900% 800% 700% 484% 237% 89% 19% -- -19%
D:U 1000/s 3650% 2400% 1025% 900% 630% 321% 137% 49% 25% --
Legends:
C:M: participant=Crypt::Misc
D:U: participant=Data::UUID
U: participant=UUID
U:F: participant=UUID::FFI
U:R: participant=UUID::Random
U:T: participant=UUID::Tiny
URP:g: participant=UUID::Random::PERLANCAR::generate
URP:g_r: participant=UUID::Random::PERLANCAR::generate_rfc
URS:g: participant=UUID::Random::Secure::generate
URS:g_r: participant=UUID::Random::Secure::generate_rfc
Sample benchmark #2
Benchmark command (benchmarking module startup overhead):
% bencher --cpanmodules-module UUID --module-startup
Result formatted as table:
#table2#
+-------------------------+-----------+-------------------+-----------------------+-----------------------+-----------+---------+
| participant | time (ms) | mod_overhead_time | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples |
+-------------------------+-----------+-------------------+-----------------------+-----------------------+-----------+---------+
| UUID::Random::Secure | 95 | 88.45 | 0.00% | 1352.22% | 0.00022 | 20 |
| UUID::FFI | 53 | 46.45 | 80.85% | 703.01% | 0.00013 | 20 |
| UUID::Tiny | 26.7 | 20.15 | 256.48% | 307.38% | 2.3e-05 | 20 |
| Crypt::Misc | 20.9 | 14.35 | 354.68% | 219.40% | 1.9e-05 | 20 |
| Data::UUID | 20 | 13.45 | 429.95% | 174.03% | 0.00041 | 20 |
| UUID | 11.4 | 4.85 | 734.65% | 73.99% | 5.5e-06 | 20 |
| UUID::Random | 8.9 | 2.35 | 962.94% | 36.62% | 1e-05 | 20 |
| UUID::Random::PERLANCAR | 8.94 | 2.39 | 964.20% | 36.46% | 7.2e-06 | 20 |
| perl -e1 (baseline) | 6.55 | 0 | 1352.22% | 0.00% | 6.3e-06 | 20 |
+-------------------------+-----------+-------------------+-----------------------+-----------------------+-----------+---------+
The above result formatted in Benchmark.pm style:
Rate UR:S U:F U:T C:M D:U U UR:P U:R perl -e1 (baseline)
UR:S 10.5/s -- -44% -71% -78% -78% -88% -90% -90% -93%
U:F 18.9/s 79% -- -49% -60% -62% -78% -83% -83% -87%
U:T 37.5/s 255% 98% -- -21% -25% -57% -66% -66% -75%
C:M 47.8/s 354% 153% 27% -- -4% -45% -57% -57% -68%
D:U 50.0/s 375% 165% 33% 4% -- -42% -55% -55% -67%
U 87.7/s 733% 364% 134% 83% 75% -- -21% -21% -42%
UR:P 111.9/s 962% 492% 198% 133% 123% 27% -- 0% -26%
U:R 112.4/s 967% 495% 200% 134% 124% 28% 0% -- -26%
perl -e1 (baseline) 152.7/s 1350% 709% 307% 219% 205% 74% 36% 35% --
Legends:
C:M: mod_overhead_time=14.35 participant=Crypt::Misc
D:U: mod_overhead_time=13.45 participant=Data::UUID
U: mod_overhead_time=4.85 participant=UUID
U:F: mod_overhead_time=46.45 participant=UUID::FFI
U:R: mod_overhead_time=2.35 participant=UUID::Random
U:T: mod_overhead_time=20.15 participant=UUID::Tiny
UR:P: mod_overhead_time=2.39 participant=UUID::Random::PERLANCAR
UR:S: mod_overhead_time=88.45 participant=UUID::Random::Secure
perl -e1 (baseline): mod_overhead_time=0 participant=perl -e1 (baseline)
To display as an interactive HTML table on a browser, you can add option
"--format html+datatables".
FAQ
What is an Acme::CPANModules::* module?
An Acme::CPANModules::* module, like this module, contains just a list
of module names that share a common characteristics. It is a way to
categorize modules and document CPAN. See Acme::CPANModules for more
details.
What are ways to use this Acme::CPANModules module?
Aside from reading this Acme::CPANModules module's POD documentation,
you can install all the listed modules (entries) using cpanm-cpanmodules
script (from App::cpanm::cpanmodules distribution):
% cpanm-cpanmodules -n UUID
Alternatively you can use the cpanmodules CLI (from App::cpanmodules
distribution):
% cpanmodules ls-entries UUID | cpanm -n
or Acme::CM::Get:
( run in 1.238 second using v1.01-cache-2.11-cpan-39bf76dae61 )