NAME Acme::CPANModules::OrderedHash - List of modules that provide ordered hash data type VERSION This document describes version 0.001 of Acme::CPANModules::OrderedHash (from Perl distribution Acme-CPANModules-OrderedHash), released on 2023-10-05. SYNOPSIS To run benchmark with default option: % bencher --cpanmodules-module OrderedHash To run module startup overhead benchmark: % bencher --module-startup --cpanmodules-module OrderedHash For more options (dump scenario, list/include/exclude/add participants, list/include/exclude/add datasets, etc), see bencher or run "bencher --help". DESCRIPTION When you ask a Perl's hash for the list of keys, the answer comes back unordered. In fact, Perl explicitly randomizes the order of keys it returns everytime. The random ordering is a (security) feature, not a bug. However, sometimes you want to know the order of insertion. These modules provide you with an ordered hash; most of them implement it by recording the order of insertion of keys in an additional array. Other related modules: Tie::SortHash - will automatically sort keys when you call keys(), values(), each(). But this module does not maintain insertion order. ACME::CPANMODULES ENTRIES Tie::IxHash Author: CHORNY Hash::Ordered Author: DAGOLDEN Tie::Hash::Indexed Author: MHX Provides two interfaces: tied hash and OO. Tie::LLHash Author: XAERXESS Tie::StoredOrderHash Author: TFM Array::OrdHash Author: WOWASURIN Provide something closest to PHP's associative array, where you can refer elements by key or by numeric index, and insertion order is remembered. List::Unique::DeterministicOrder Author: SLAFFAN Provide a list, not hash. BENCHMARKED MODULES Version numbers shown below are the versions used when running the sample benchmark. Tie::IxHash 1.23 Hash::Ordered 0.014 Tie::Hash::Indexed 0.08 Tie::LLHash 1.004 Tie::StoredOrderHash 0.22 Array::OrdHash 1.03 List::Unique::DeterministicOrder 0.004 BENCHMARK PARTICIPANTS * Tie::IxHash (perl_code) Tie::IxHash * Hash::Ordered (perl_code) Hash::Ordered * Tie::Hash::Indexed (perl_code) Tie::Hash::Indexed * Tie::LLHash (perl_code) Tie::LLHash * Tie::StoredOrderHash (perl_code) Tie::StoredOrderHash * Array::OrdHash (perl_code) Array::OrdHash * List::Unique::DeterministicOrder (perl_code) List::Unique::DeterministicOrder BENCHMARK DATASETS * insert 1000 pairs * insert 1000 pairs + delete * insert 1000 pairs + return keys 100 times 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 5.4.0-91-generic*. Benchmark command (default options): % bencher --cpanmodules-module OrderedHash Result formatted as table (split, part 1 of 3): #table1# {dataset=>"insert 1000 pairs"} +----------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+ | participant | rate (/s) | time (ms) | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples | +----------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+ | Tie::LLHash | 200 | 4 | 0.00% | 333.85% | 0.00013 | 20 | | Tie::StoredOrderHash | 350 | 2.9 | 41.84% | 205.88% | 7.5e-06 | 20 | | Array::OrdHash | 540 | 1.8 | 118.76% | 98.32% | 2.1e-06 | 20 | | Hash::Ordered | 600 | 2 | 129.15% | 89.33% | 8.7e-05 | 32 | | Tie::IxHash | 670 | 1.5 | 169.83% | 60.78% | 2.5e-06 | 20 | | Tie::Hash::Indexed | 700 | 1 | 187.24% | 51.04% | 5.7e-05 | 20 | | List::Unique::DeterministicOrder | 1100 | 0.93 | 333.85% | 0.00% | 2.3e-06 | 20 | +----------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+ The above result formatted in Benchmark.pm style: Rate T:L T:S H:O A:O T:I TH:I LU:D T:L 200/s -- -27% -50% -55% -62% -75% -76% T:S 350/s 37% -- -31% -37% -48% -65% -67% H:O 600/s 100% 44% -- -9% -25% -50% -53% A:O 540/s 122% 61% 11% -- -16% -44% -48% T:I 670/s 166% 93% 33% 19% -- -33% -38% TH:I 700/s 300% 190% 100% 80% 50% -- -6% LU:D 1100/s 330% 211% 115% 93% 61% 7% -- Legends: A:O: participant=Array::OrdHash H:O: participant=Hash::Ordered LU:D: participant=List::Unique::DeterministicOrder T:I: participant=Tie::IxHash T:L: participant=Tie::LLHash T:S: participant=Tie::StoredOrderHash TH:I: participant=Tie::Hash::Indexed The above result presented as chart: #IMAGE: share/images/bencher-result-1.png|/tmp/dxS0EuAWVP/bencher-result-1.png Result formatted as table (split, part 2 of 3): #table2# {dataset=>"insert 1000 pairs + delete"} +----------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+ | participant | rate (/s) | time (ms) | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples | +----------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+ | Tie::IxHash | 15 | 67 | 0.00% | 4003.59% | 0.00034 | 20 | | Tie::StoredOrderHash | 200 | 6 | 1082.65% | 246.98% | 8.4e-05 | 21 | | Tie::LLHash | 200 | 5 | 1119.91% | 236.39% | 0.00013 | 20 | | Array::OrdHash | 270 | 3.8 | 1686.96% | 129.64% | 1.5e-05 | 20 | | Hash::Ordered | 300 | 3 | 2008.58% | 94.61% | 3.4e-05 | 22 | | Tie::Hash::Indexed | 500 | 2 | 3188.02% | 24.80% | 6.7e-05 | 20 | | List::Unique::DeterministicOrder | 610 | 1.6 | 4003.59% | 0.00% | 4.3e-06 | 20 | +----------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+ The above result formatted in Benchmark.pm style: Rate T:I T:S T:L A:O H:O TH:I LU:D T:I 15/s -- -91% -92% -94% -95% -97% -97% T:S 200/s 1016% -- -16% -36% -50% -66% -73% T:L 200/s 1240% 19% -- -24% -40% -60% -68% A:O 270/s 1663% 57% 31% -- -21% -47% -57% H:O 300/s 2133% 100% 66% 26% -- -33% -46% TH:I 500/s 3250% 200% 150% 89% 50% -- -19% LU:D 610/s 4087% 275% 212% 137% 87% 25% -- Legends: A:O: participant=Array::OrdHash H:O: participant=Hash::Ordered LU:D: participant=List::Unique::DeterministicOrder T:I: participant=Tie::IxHash T:L: participant=Tie::LLHash T:S: participant=Tie::StoredOrderHash TH:I: participant=Tie::Hash::Indexed The above result presented as chart: #IMAGE: share/images/bencher-result-2.png|/tmp/dxS0EuAWVP/bencher-result-2.png Result formatted as table (split, part 3 of 3): #table3# {dataset=>"insert 1000 pairs + return keys 100 times"} +----------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+ | participant | rate (/s) | time (ms) | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples | +----------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+ | Tie::LLHash | 8 | 100 | 0.00% | 1061.27% | 0.0049 | 20 | | Tie::StoredOrderHash | 8 | 100 | 3.73% | 1019.53% | 0.0019 | 20 | | Array::OrdHash | 13 | 79 | 56.42% | 642.39% | 0.00048 | 21 | | Tie::IxHash | 15 | 69 | 80.98% | 541.64% | 0.00015 | 20 | | Tie::Hash::Indexed | 20 | 50 | 148.79% | 366.76% | 0.00071 | 20 | | Hash::Ordered | 61 | 16 | 662.88% | 52.22% | 0.00011 | 20 | | List::Unique::DeterministicOrder | 94 | 11 | 1061.27% | 0.00% | 9.1e-05 | 20 | +----------------------------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+ The above result formatted in Benchmark.pm style: Rate T:L T:S A:O T:I TH:I H:O LU:D T:L 8/s -- 0% -20% -31% -50% -84% -89% T:S 8/s 0% -- -20% -31% -50% -84% -89% A:O 13/s 26% 26% -- -12% -36% -79% -86% T:I 15/s 44% 44% 14% -- -27% -76% -84% TH:I 20/s 100% 100% 58% 37% -- -68% -78% H:O 61/s 525% 525% 393% 331% 212% -- -31% LU:D 94/s 809% 809% 618% 527% 354% 45% -- Legends: A:O: participant=Array::OrdHash H:O: participant=Hash::Ordered LU:D: participant=List::Unique::DeterministicOrder T:I: participant=Tie::IxHash T:L: participant=Tie::LLHash T:S: participant=Tie::StoredOrderHash TH:I: participant=Tie::Hash::Indexed The above result presented as chart: #IMAGE: share/images/bencher-result-3.png|/tmp/dxS0EuAWVP/bencher-result-3.png Sample benchmark #2 Benchmark command (benchmarking module startup overhead): % bencher --cpanmodules-module OrderedHash --module-startup Result formatted as table: #table4# +----------------------------------+-----------+-------------------+-----------------------+-----------------------+---------+---------+ | participant | time (ms) | mod_overhead_time | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples | +----------------------------------+-----------+-------------------+-----------------------+-----------------------+---------+---------+ | Tie::LLHash | 20 | 10 | 0.00% | 142.41% | 0.00081 | 20 | | Hash::Ordered | 20 | 10 | 19.61% | 102.67% | 0.00039 | 20 | | Tie::Hash::Indexed | 20 | 10 | 21.42% | 99.65% | 0.00044 | 21 | | List::Unique::DeterministicOrder | 19 | 9 | 25.72% | 92.82% | 0.00017 | 21 | | Tie::IxHash | 20 | 10 | 36.08% | 78.13% | 0.00023 | 21 | | Array::OrdHash | 16 | 6 | 46.94% | 64.97% | 0.0001 | 20 | | Tie::StoredOrderHash | 20 | 10 | 52.27% | 59.20% | 0.00075 | 20 | | perl -e1 (baseline) | 10 | 0 | 142.41% | 0.00% | 0.00027 | 20 | +----------------------------------+-----------+-------------------+-----------------------+-----------------------+---------+---------+ The above result formatted in Benchmark.pm style: Rate T:L H:O TH:I T:I T:S LU:D A:O perl -e1 (baseline) T:L 50.0/s -- 0% 0% 0% 0% -5% -19% -50% H:O 50.0/s 0% -- 0% 0% 0% -5% -19% -50% TH:I 50.0/s 0% 0% -- 0% 0% -5% -19% -50% T:I 50.0/s 0% 0% 0% -- 0% -5% -19% -50% T:S 50.0/s 0% 0% 0% 0% -- -5% -19% -50% LU:D 52.6/s 5% 5% 5% 5% 5% -- -15% -47% A:O 62.5/s 25% 25% 25% 25% 25% 18% -- -37% perl -e1 (baseline) 100.0/s 100% 100% 100% 100% 100% 89% 60% -- Legends: A:O: mod_overhead_time=6 participant=Array::OrdHash H:O: mod_overhead_time=10 participant=Hash::Ordered LU:D: mod_overhead_time=9 participant=List::Unique::DeterministicOrder T:I: mod_overhead_time=10 participant=Tie::IxHash T:L: mod_overhead_time=10 participant=Tie::LLHash T:S: mod_overhead_time=10 participant=Tie::StoredOrderHash TH:I: mod_overhead_time=10 participant=Tie::Hash::Indexed perl -e1 (baseline): mod_overhead_time=0 participant=perl -e1 (baseline) The above result presented as chart: #IMAGE: share/images/bencher-result-4.png|/tmp/dxS0EuAWVP/bencher-result-4.png 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 OrderedHash Alternatively you can use the cpanmodules CLI (from App::cpanmodules distribution): % cpanmodules ls-entries OrderedHash | cpanm -n or Acme::CM::Get: % perl -MAcme::CM::Get=OrderedHash -E'say $_->{module} for @{ $LIST->{entries} }' | cpanm -n or directly: % perl -MAcme::CPANModules::OrderedHash -E'say $_->{module} for @{ $Acme::CPANModules::OrderedHash::LIST->{entries} }' | cpanm -n This Acme::CPANModules module contains benchmark instructions. You can run a benchmark for some/all the modules listed in this Acme::CPANModules module using the bencher CLI (from Bencher distribution): % bencher --cpanmodules-module OrderedHash This Acme::CPANModules module also helps lcpan produce a more meaningful result for "lcpan related-mods" command when it comes to finding related modules for the modules listed in this Acme::CPANModules module. See App::lcpan::Cmd::related_mods for more details on how "related modules" are found. HOMEPAGE Please visit the project's homepage at . SOURCE Source repository is at . SEE ALSO Acme::CPANModules::HashUtilities Acme::CPANModules - about the Acme::CPANModules namespace cpanmodules - CLI tool to let you browse/view the lists AUTHOR perlancar CONTRIBUTING To contribute, you can send patches by email/via RT, or send pull requests on GitHub. Most of the time, you don't need to build the distribution yourself. You can simply modify the code, then test via: % prove -l If you want to build the distribution (e.g. to try to install it locally on your system), you can install Dist::Zilla, Dist::Zilla::PluginBundle::Author::PERLANCAR, Pod::Weaver::PluginBundle::Author::PERLANCAR, and sometimes one or two other Dist::Zilla- and/or Pod::Weaver plugins. Any additional steps required beyond that are considered a bug and can be reported to me. COPYRIGHT AND LICENSE This software is copyright (c) 2023 by perlancar . This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself. BUGS Please report any bugs or feature requests on the bugtracker website 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.