Serialize command parameters to data output files #131
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Thank you very much for your contribution. Can you please provide a little bit of background / motivation for this change? This would make it easier to review. |
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@sharkdp, thank you for responding, and sorry for the sloppy PR. I have updated the initial comment and the subject. Ultimately this patch is driven by me wanting to directly plot results from JSON output files for parameterized benchmarks (e.g., to inspect scaling behavior and identify breakdown of naive scaling). For that I need direct access to benchmark parameter which currently requires command string parsing or adding values by hand. I also realized that in addition to JSON, CSV output could also benefit from this improvement and updated the patches for that (which actually lead to a simplification). |
src/hyperfine/benchmark.rs
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| @@ -412,5 +412,9 @@ pub fn run_benchmark( | |||
| t_min, | |||
| t_max, | |||
| times_real, | |||
| match cmd.get_parameter() { | |||
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Could this match statement be shortened to something like
cmd.get_parameter().map(|p| p.1)?
src/hyperfine/types.rs
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| @@ -196,6 +201,7 @@ impl BenchmarkResult { | |||
| min, | |||
| max, | |||
| times: Some(times), | |||
| parameter: parameter, | |||
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I think this could just be parameter instead of parameter: parameter.
This patch adds any parameter used to data output files (currently JSON and CSV files). With that users have direct access to both input values (i.e., benchmark parameters) and the resulting timings which should simplify follow-up analyses.
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Thank you for the updates! |
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Released in v1.6.0. |
This patch adds any parameter used to data output files (currently JSON
and CSV files). With that users have direct access to both input values
(i.e., benchmark parameters) and the resulting timings which should
simplify follow-up analyses.