NAME

Bencher::Backend - Backend for Bencher

VERSION

This document describes version 1.046 of Bencher::Backend (from Perl distribution Bencher-Backend), released on 2019-12-02.

FUNCTIONS

bencher

Usage:

 bencher(%args) -> [status, msg, payload, meta]

A benchmark framework.

Bencher is a benchmark framework. You specify a scenario (either in a Bencher::Scenario::* Perl module, or a Perl script, or over the command-line) containing list of participants and datasets. Participants are codes or commands to run, and datasets are arguments for the codes/commands. Bencher will permute the participants and datasets into benchmark items, ready to run.

You can choose to include only some participants, datasets, or items. And there are options to view your scenario's participants/datasets/items/mentioned modules, run benchmark against multiple perls and module versions, and so on. Bencher comes as a CLI script as well as Perl module. See the Bencher::Backend documentation for more information.

This function is not exported by default, but exportable.

Arguments ('*' denotes required arguments):

  • action => str (default: "bench")

  • capture_stderr => bool

    Trap output to stderr.

  • capture_stdout => bool

    Trap output to stdout.

  • code_startup => bool

    Benchmark code startup overhead instead of normal benchmark.

  • cpanmodules_module => perl::modname

    Load a scenario from an Acme::CPANModules:: Perl module.

    An Acme::CPANModules module can also contain benchmarking information, e.g. Acme::CPANModules::TextTable.

  • datasets => array[hash]

    Add datasets.

  • detail => bool

  • env_hashes => array[hash]

    Add environment hashes.

  • exclude_dataset_names => array[str]

    Exclude datasets whose name matches this.

  • exclude_dataset_pattern => re

    Exclude datasets matching this regex pattern.

  • exclude_dataset_seqs => array[int]

    Exclude datasets whose sequence number matches this.

  • exclude_dataset_tags => array[str]

    Exclude datasets whose tag matches this.

    You can specify A & B to exclude datasets that have both tags A and B.

  • exclude_datasets => array[str]

    Exclude datasets whose seq/name matches this.

  • exclude_function_pattern => re

    Exclude function(s) matching this regex pattern.

  • exclude_functions => array[str]

    Exclude functions specified in this list.

  • exclude_item_names => array[str]

    Exclude items whose name matches this.

  • exclude_item_pattern => re

    Exclude items matching this regex pattern.

  • exclude_item_seqs => array[int]

    Exclude items whose sequence number matches this.

  • exclude_items => array[str]

    Exclude items whose seq/name matches this.

  • exclude_module_pattern => re

    Exclude module(s) matching this regex pattern.

  • exclude_modules => array[str]

    Exclude modules specified in this list.

  • exclude_participant_names => array[str]

    Exclude participants whose name matches this.

  • exclude_participant_pattern => re

    Exclude participants matching this regex pattern.

  • exclude_participant_seqs => array[int]

    Exclude participants whose sequence number matches this.

  • exclude_participant_tags => array[str]

    Exclude participants whose tag matches this.

    You can specify A & B to exclude participants that have both tags A and B.

  • exclude_participants => array[str]

    Exclude participants whose seq/name matches this.

  • exclude_perls => array[str]

    Exclude some perls.

  • exclude_pp_modules => bool

    Exclude PP (pure-Perl) modules.

  • exclude_xs_modules => bool

    Exclude XS modules.

  • include_dataset_names => array[str]

    Only include datasets whose name matches this.

  • include_dataset_pattern => re

    Only include datasets matching this regex pattern.

  • include_dataset_seqs => array[int]

    Only include datasets whose sequence number matches this.

  • include_dataset_tags => array[str]

    Only include datasets whose tag matches this.

    You can specify A & B to include datasets that have both tags A and B.

  • include_datasets => array[str]

    Only include datasets whose seq/name matches this.

  • include_function_pattern => re

    Only include functions matching this regex pattern.

  • include_functions => array[str]

    Only include functions specified in this list.

  • include_item_names => array[str]

    Only include items whose name matches this.

  • include_item_pattern => re

    Only include items matching this regex pattern.

  • include_item_seqs => array[int]

    Only include items whose sequence number matches this.

  • include_items => array[str]

    Only include items whose seq/name matches this.

  • include_module_pattern => re

    Only include modules matching this regex pattern.

  • include_modules => array[str]

    Only include modules specified in this list.

  • include_participant_names => array[str]

    Only include participants whose name matches this.

  • include_participant_pattern => re

    Only include participants matching this regex pattern.

  • include_participant_seqs => array[int]

    Only include participants whose sequence number matches this.

  • include_participant_tags => array[str]

    Only include participants whose tag matches this.

    You can specify A & B to include participants that have both tags A and B.

  • include_participants => array[str]

    Only include participants whose seq/name matches this.

  • include_path => array[str]

    Additional module search paths.

    Used when searching for scenario module, or when in multimodver mode.

  • include_perls => array[str]

    Only include some perls.

  • module_startup => bool

    Benchmark module startup overhead instead of normal benchmark.

  • multimodver => str

    Benchmark multiple module versions.

    If set to a module name, will search for all (instead of the first occurrence) of the module in @INC. Then will generate items for each version.

    Currently only one module can be multi version.

  • multiperl => bool (default: 0)

    Benchmark against multiple perls.

    Requires App::perlbrew to be installed. Will use installed perls from the perlbrew installation. Each installed perl must have Bencher::Backend module installed (in addition to having all modules that you want to benchmark, obviously).

    By default, only perls having Bencher::Backend will be included. Use --include-perl and --exclude-perl to include and exclude which perls you want.

    Also note that due to the way this is currently implemented, benchmark code that contains closures (references to variables outside the code) won't work.

  • note => str

    Put additional note in the result.

  • on_failure => str

    What to do when there is a failure.

    For a command participant, failure means non-zero exit code. For a Perl-code participant, failure means Perl code dies or (if expected result is specified) the result is not equal to the expected result.

    The default is "die". When set to "skip", will first run the code of each item before benchmarking and trap command failure/Perl exception and if that happens, will "skip" the item.

  • on_result_failure => str

    What to do when there is a result failure.

    This is like on_failure except that it specifically refer to the failure of item's result not being equal to expected result.

    There is an extra choice of warn for this type of failure, which is to print a warning to STDERR and continue.

  • participants => array[hash]

    Add participants.

  • precision => float

    Precision.

    When benchmarking with the default Benchmark::Dumb runner, will pass the precision to it. The value is a fraction, e.g. 0.5 (for 5% precision), 0.01 (for 1% precision), and so on. Or, it can also be a positive integer to speciify minimum number of iterations, usually need to be at least 6 to avoid the "Number of initial runs is very small (<6)" warning. The default precision is 0, which is to let Benchmark::Dumb determine the precision, which is good enough for most cases.

    When benchmarking with Benchmark runner, will pass this value as the $count argument. Which can be a positive integer to mean the number of iterations to do (e.g. 10, or 100). Or, can also be set to a negative number (e.g. -0.5 or -2) to mean minimum number of CPU seconds. The default is -0.5.

    When benchmarking with Benchmark::Dumb::SimpleTime, this value is a positive integer which means the number of iterations to perform.

    This setting overrides default_precision property in the scenario.

  • precision_limit => float

    Set precision limit.

    Instead of setting precision which forces a single value, you can also set this precision_limit setting. If the precision in the scenario is higher (=number is smaller) than this limit, then this limit is used. For example, if the scenario specifies default_precision 0.001 and precision_limit is set to 0.005 then 0.005 is used.

    This setting is useful on slower computers which might not be able to reach the required precision before hitting maximum number of iterations.

  • raw => bool

    Show "raw" data.

    When action=show-items-result, will print result as-is instead of dumping as Perl.

  • result_dir => str

    Directory to use when saving benchmark result.

    Default is from BENCHER_RESULT_DIR environment variable, or the home directory.

  • result_filename => str

    Filename to use when saving benchmark result.

    Default is:

     <NAME>.<yyyy-dd-dd-"T"HH-MM-SS>.json

    or, when running in module startup mode:

     <NAME>.module_startup.<yyyy-dd-dd-"T"HH-MM-SS>.json

    or, when running in code startup mode:

     <NAME>.code_startup.<yyyy-dd-dd-"T"HH-MM-SS>.json

    where <NAME> is scenario module name, or NO_MODULE if scenario is not from a module. The :: (double colon in the module name will be replaced with - (dash).

  • return_meta => bool

    Whether to return extra metadata.

    When set to true, will return extra metadata such as platform information, CPU information, system load before & after the benchmark, system time, and so on. This is put in result metadata under func.* keys.

    The default is to true (return extra metadata) unless when run as CLI and format is text (where the extra metadata is not shown).

  • runner => str

    Runner module to use.

    The default is Benchmark::Dumb which should be good enough for most cases.

    You can use Benchmark runner (Benchmark.pm) if you are accustomed to it and want to see its output format.

    You can use Benchmark::Dumb::SimpleTime if your participant code runs for at least a few to many seconds and you want to use very few iterations (like 1 or 2) because you don't want to wait for too long.

  • save_result => bool

    Whether to save benchmark result to file.

    Will also be turned on automatically if BENCHER_RESULT_DIR environment variabl is defined.

    When this is turned on, will save a JSON file after benchmark, containing the result along with metadata. The directory of the JSON file will be determined from the results_dir option, while the filename from the results_filename option.

  • scenario => hash

    Load a scenario from data structure.

  • scenario_file => str

    Load a scenario from a Perl file.

    Perl file will be do()'ed and the last expression should be a hash containing the scenario specification.

  • scenario_module => perl::modname

    Load a scenario from a Bencher::Scenario:: Perl module.

    Will try to load module Bencher::Scenario::<NAME> and expect to find a package variable in the module called $scenario which should be a hashref containing the scenario specification.

  • scientific_notation => bool

  • sorts => array[str] (default: ["-time"])

  • test => bool

    Whether to test participant code once first before benchmarking.

    By default, participant code is run once first for testing (e.g. whether it dies or return the correct result) before benchmarking. If your code runs for many seconds, you might want to skip this test and set this to 0.

  • with_args_size => bool

    Also return memory usage of item's arguments.

    Memory size is measured using Devel::Size.

  • with_process_size => bool

    Also return process size information for each item.

    This is done by dumping each item's code into a temporary file and running the file with a new perl interpreter process and measuring the process size at the end (so it does not need to load Bencher itself or the other items). Currently only works on Linux because process size information is retrieved from /proc/PID/smaps. Not all code can work, e.g. if the code tries to access a closure or outside data or extra modules (modules not specified in the participant or loaded by the code itself). Usually does not make sense to use this on external command participants.

  • with_result_size => bool

    Also return memory usage of each item code's result (return value).

    Memory size is measured using Devel::Size.

Returns an enveloped result (an array).

First element (status) is an integer containing HTTP status code (200 means OK, 4xx caller error, 5xx function error). Second element (msg) is a string containing error message, or 'OK' if status is 200. Third element (payload) is optional, the actual result. Fourth element (meta) is called result metadata and is optional, a hash that contains extra information.

Return value: (any)

chart_result

Usage:

 chart_result(%args) -> [status, msg, payload, meta]

Generate chart from the result.

Will use gnuplot (via Chart::Gnuplot) to generate the chart. Will produce .png files in the specified directory.

Currently only results with one or two permutations of different items will be chartable.

Options to customize the look/style of the chart will be added in the future.

This function is not exported by default, but exportable.

Arguments ('*' denotes required arguments):

  • envres* => array

    Enveloped result from bencher.

  • output_file* => str

  • overwrite => bool

  • title => str

Returns an enveloped result (an array).

First element (status) is an integer containing HTTP status code (200 means OK, 4xx caller error, 5xx function error). Second element (msg) is a string containing error message, or 'OK' if status is 200. Third element (payload) is optional, the actual result. Fourth element (meta) is called result metadata and is optional, a hash that contains extra information.

Return value: (any)

format_result

Usage:

 format_result($envres, $formatters, $options) -> [status, msg, payload, meta]

Format bencher result.

This function is not exported by default, but exportable.

Arguments ('*' denotes required arguments):

  • $envres* => array

    Enveloped result from bencher.

  • $formatters* => array[str|array]

    Formatters specification.

  • $options => hash

Returns an enveloped result (an array).

First element (status) is an integer containing HTTP status code (200 means OK, 4xx caller error, 5xx function error). Second element (msg) is a string containing error message, or 'OK' if status is 200. Third element (payload) is optional, the actual result. Fourth element (meta) is called result metadata and is optional, a hash that contains extra information.

Return value: (any)

parse_scenario

Usage:

 parse_scenario(%args) -> [status, msg, payload, meta]

Parse scenario (fill in default values, etc).

This function is not exported by default, but exportable.

Arguments ('*' denotes required arguments):

  • scenario => hash

    Unparsed scenario.

Returns an enveloped result (an array).

First element (status) is an integer containing HTTP status code (200 means OK, 4xx caller error, 5xx function error). Second element (msg) is a string containing error message, or 'OK' if status is 200. Third element (payload) is optional, the actual result. Fourth element (meta) is called result metadata and is optional, a hash that contains extra information.

Return value: (any)

split_result

Usage:

 split_result($envres, $fields, $options) -> any

Split results based on one or more fields.

This routine splits a table into multiple table based on one or more fields. If you want to split a result, you should do it before format_result() and then format the split results individually.

A common use-case is to produce separate tables for each participant or dataset, to make the benchmark results more readable (this is an alternative to having to perform separate benchmark run per participant or dataset).

Each split result clones all the result metadata (like func.module_version, func.platform_info, table.fields, and so on). But the result items are only a subset of the original result.

Return an array where each element is [\%field_values, $split_result].

This function is not exported by default, but exportable.

Arguments ('*' denotes required arguments):

  • $envres* => array

    Enveloped result from bencher.

  • $fields* => array[str]

    Fields to split the results on.

  • $options => hash

Return value: (any)

ENVIRONMENT

BENCHER_RESULT_DIR => str

Set default for --results-dir.

HOMEPAGE

Please visit the project's homepage at https://metacpan.org/release/Bencher-Backend.

SOURCE

Source repository is at https://github.com/perlancar/perl-Bencher-Backend.

BUGS

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

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.

SEE ALSO

bencher

Bencher

Bencher::Manual::*

AUTHOR

perlancar <perlancar@cpan.org>

COPYRIGHT AND LICENSE

This software is copyright (c) 2019, 2018, 2017, 2016, 2015 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.