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πŸ“‰ gobenchdata

View Action publish@v1 pipeline demo Demo

gobenchdata is a tool for parsing and inspecting go test -bench data, and a GitHub Action for continuous benchmarking. It was inspired by the continuous benchmarks, which aims to display performance improvements and regressions on a continuous basis.


GitHub Action

gobenchdata can be used as GitHub Action for uploading Go benchmark data as JSON to gh-pages and visualizing it with a generated web app or your own web application.


For example, in .github/workflows/push.yml, using the new YAML syntax for workflows, a simple benchmark run and publish workflow would look like:

name: gobenchdata publish
on: push
    runs-on: ubuntu-latest
    - name: checkout
      uses: actions/checkout@v2
    - name: gobenchdata publish
      uses: bobheadxi/gobenchdata@v1
        PRUNE_COUNT: 30
        GO_TEST_FLAGS: -cpu 1,2
        PUBLISH: true
        PUBLISH_BRANCH: gh-pages
        GITHUB_TOKEN: ${{ secrets.ACCESS_TOKEN }}

Learn more about GitHub Actions in the official documentation.



Input variables are configured using jobs.<job_id>.steps.with.

Variable Default Purpose
SUBDIRECTORY . subdirectory of project to run commands from
GO_BENCHMARKS . benchmarks to run (argument for -bench)
GO_TEST_FLAGS additional flags for go test
GO_TEST_PKGS ./... packages to test (argument for go test)

The following inputs enable publishing - this merges and publishes benchmark results to a repository and branch of your choice. This is most useful in conjunction with the gobenchdata web application.

Variable Default Purpose
PUBLISH false if true, publishes results
PUBLISH_REPO an alternative repository to publish to
PUBLISH_BRANCH gh-pages branch to publish to
PRUNE_COUNT 0 number of past runs to keep (0 keeps everything)
GIT_COMMIT_MESSAGE "add new benchmark run" the commit message for the benchmark update
BENCHMARKS_OUT benchmarks.json destination path of benchmark data

The following inputs are for enabling Pull Request Checks, which allow you to watch for performance regressions in your pull requests.

Variable Default Purpose
CHECKS false if true, runs checks and sets JSON results to checks-results
CHECKS_CONFIG gobenchdata-checks.yml path to checks configuration
PUBLISH_REPO repository of benchmark data to check against
PUBLISH_BRANCH gh-pages branch of benchmark data to check against
BENCHMARKS_OUT benchmarks.json path to benchmark data to check against


Environment variables are configured using jobs.<job_id>.steps.env.

Variable Recommended Purpose
GITHUB_TOKEN ${{ secrets.GITHUB_TOKEN }} token to provide access to repository
GITHUB_ACTOR set by GitHub the user to make commits as

Note that for GITHUB_TOKEN, it seems that pushes to gh-pages made by the default secrets.GITHUB_TOKEN might not trigger page builds. This issue can be resolved by using a personal access token instead.

Pull Request Checks

Instead of publishing results, benchmark output can be used to pass and fail pull requests using CHECKS: true. To get started, set up the checks configuration:

go get -u
gobenchdata checks generate

This will generate a file, gobenchdata-checks.yml, where you can configure what checks are executed. The checks are run against any benchmarks that match given package and benchmarks values, which should be provided as regular expressions.

Simple Example

- name: My Check
  description: |-
    Define a check here - in this example, we caculate % difference for NsPerOp in the diff function.
    diff is a function where you receive two parameters, current and base, and in general this function
    should return a negative value for an improvement and a positive value for a regression.
  package: .
  benchmarks: []
  diff: (current.NsPerOp - base.NsPerOp) / base.NsPerOp * 100
    max: 10


The gobenchdata GitHub action eventually generates a JSON file with past benchmarks. You can visualize these continuous benchmarks by creating a web app that reads from the JSON benchmarks file, or by using gobenchdata. An easy way to get started is:

go get -u
gobenchdata web generate --web.config-only .
gobenchdata web serve # opens visualization in browser

You can configure the web application using gobenchdata-web.yml. The configuration allows you to define groups of charts, where each group can be used to compare a set of benchmarks. Benchmarks are selected with regular expressions by package and benchmark names provided in the configuration.

Note that in each set of compared benchmarks, every metric will get its own chart. You can select which metrics to display using the metrics option.


title: gobenchdata web
description: Benchmarks generated using 'gobenchdata'
benchmarksFile: benchmarks.json
  - name: Demo Benchmarks
    description: |
      This is a demo for gobenchdata, a tool and GitHub action for setting up simple continuous
      benchmarks to monitor performance improvements and regressions in your Golang benchmarks!
      - name: specify charts by package
      - name: match on specific benchmarks across packages with glob patterns
        benchmarks: [ 'BenchmarkFib.' ]
  - name: More Demo Benchmarks
    description: Create multiple groups of benchmarks
      - name: match by a combination of package and benchmarks
        benchmarks: [ 'BenchmarkPizzas.', '.FibSlow.' ]

You can output the entire web application (to publish to Github pages, for example) using:

gobenchdata web generate ./app

Command Line Interface

gobenchdata, which the GitHub Action leverages to manage benchmark data, is also available as a CLI:

go get -u
gobenchdata help

The easiest way to use the CLI is by piping the output of go test -bench to it - gobenchdata will consume the output and generate a JSON report for you.

go test -bench . -benchmem ./... | gobenchdata --json bench.json

You can use this report to create your own charts, or just use the built-in web application:

gobenchdata web serve

gobenchdata can also execute checks for you to help you ensure performance regressions don't happen:

gobenchdata checks generate
gobenchdata checks eval ${base benchmarks} ${current benchmarks} --checks.pretty
Example Report

βœ… 5aa9b7f901e770f1364bfc849aaba0cc06066336 abfdd5c29b1aff48cb22e0cbb6f4f7526ad85604 2 0 2
βœ… An example NsPerOp check BenchmarkFib10/Fib() -2.61
βœ… An example NsPerOp check BenchmarkFib10/Fib()-2 -2.85
βœ… An example NsPerOp check BenchmarkFib10/FibSlow() -2.47
βœ… An example NsPerOp check BenchmarkFib10/FibSlow()-2 -2.19
βœ… An example NsPerOp check BenchmarkPizzas/Pizzas() -1.85
βœ… An example NsPerOp check BenchmarkPizzas/Pizzas()-2 -2.45
βœ… An example NsPerOp check BenchmarkPizzas/PizzasSquared() -5.71
βœ… An example NsPerOp check BenchmarkPizzas/PizzasSquared()-2 -3.03
βœ… An example custom metric check BenchmarkPizzas/Pizzas() 8.00
βœ… An example custom metric check BenchmarkPizzas/Pizzas()-2 4.00
βœ… An example custom metric check BenchmarkPizzas/PizzasSquared() 4.00
βœ… An example custom metric check BenchmarkPizzas/PizzasSquared()-2 1.00

For more details on how to use checks, see the pull request checks documentation.


Please report bugs and requests in the repository issues!

See for more detailed development documentation.