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# Binaries for programs and plugins
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*.exe
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*.exe~
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*.dll
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*.so
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*.dylib
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# Output of the go coverage tool, specifically when used with LiteIDE
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*.out
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# Go workspace file
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go.work
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go.work.sum
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# Dependency directories
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vendor/
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# Go build artifacts
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bin/
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build/
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dist/
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# Configuration files for editors and tools
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.vscode/
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.idea/
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*.swp
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*.swo
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# Logs
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*.log
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# Temporary files
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*.tmp
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*.temp
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*.bak
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# Test binary, coverage, and results
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*.test
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*.cover
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*.cov
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*.profile
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*.prof
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# OS-specific files
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.DS_Store
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Thumbs.db
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@ -0,0 +1,23 @@
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DO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE
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Version 2, December 2004
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Copyright (C) 2004 Sam Hocevar <sam@hocevar.net>
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Everyone is permitted to copy and distribute verbatim or modified copies of
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this license document, and changing it is allowed as long as the name is changed.
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DO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE
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TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
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0. You just DO WHAT THE FUCK YOU WANT TO.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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# TimingBench
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`TimingBench` is a Go module for benchmarking the execution time of a
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function. It runs the function a specified number of times and returns the
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minimum, maximum, mean, and median execution times, along with other
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relevant statistics. It also supports context for cancellation.
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## Features
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- Measure min, max, mean, and median execution times of a function.
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- Support for context-based cancellation.
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- Provides detailed timing statistics.
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## Installation
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To install the `timingbench` package, use the following command:
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```sh
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go get git.eeqj.de/sneak/timingbench
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```
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## Usage
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Here's a simple example of how to use the `timingbench` module:
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```go
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package main
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import (
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"context"
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"fmt"
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"math/rand"
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"time"
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"git.eeqj.de/sneak/timingbench"
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)
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// Example function to benchmark
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func sampleFunction() error {
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time.Sleep(time.Duration(rand.Intn(100)) * time.Millisecond)
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return nil
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}
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func main() {
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// Seed the random number generator.
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rand.Seed(time.Now().UnixNano())
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// Define the number of iterations.
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iterations := 10
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// Create a context with a timeout for cancellation.
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ctx, cancel := context.WithTimeout(context.Background(), 2*time.Second)
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defer cancel()
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// Measure the execution times of the sample function.
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result, err := timingbench.TimeFunction(ctx, sampleFunction, iterations)
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if err != nil {
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fmt.Printf("Error measuring function: %v\n", err)
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return
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}
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// Print the timing results.
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fmt.Println(result.String())
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}
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```
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## TimingResult
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The `TimingResult` struct holds the timing statistics for the function executions:
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```go
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type TimingResult struct {
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Min time.Duration // Minimum execution time
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Max time.Duration // Maximum execution time
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Mean time.Duration // Mean execution time
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Median time.Duration // Median execution time
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StartTime time.Time // Start time of the benchmarking
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EndTime time.Time // End time of the benchmarking
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Duration time.Duration // Total duration of the benchmarking
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Iterations int // Number of iterations
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}
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```
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## License
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This project is licensed under the WTFPL License. See the
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[LICENSE](./LICENSE) file for details.
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## Contributing
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Contributions are welcome! Please send patches via email.
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## Author
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`timingbench` was written by [sneak](mailto:sneak@sneak.berlin) ([website](https://sneak.berlin)).
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@ -0,0 +1,77 @@
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package timingbench
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import (
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"context"
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"errors"
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"fmt"
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"sort"
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"time"
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"gonum.org/v1/gonum/stat"
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)
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// TimingResult holds the timing results for a function execution.
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type TimingResult struct {
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Min time.Duration
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Max time.Duration
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Mean time.Duration
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Median time.Duration
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StartTime time.Time
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EndTime time.Time
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Duration time.Duration
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Iterations int
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}
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// String returns a formatted string representation of the TimingResult.
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func (r TimingResult) String() string {
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return fmt.Sprintf(
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"Start Time: %v, End Time: %v, Duration: %v, Iterations: %d, Min: %v, Max: %v, Mean: %v, Median: %v",
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r.StartTime, r.EndTime, r.Duration, r.Iterations, r.Min, r.Max, r.Mean, r.Median,
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)
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}
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// TimeFunction runs the given function fn a specified number of times and returns the timing results.
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// It supports context for cancellation.
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func TimeFunction(ctx context.Context, fn func() error, iterations int) (TimingResult, error) {
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if iterations <= 0 {
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return TimingResult{}, errors.New("iterations must be greater than 0")
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}
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times := make([]float64, 0, iterations)
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startTime := time.Now().UTC()
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for i := 0; i < iterations; i++ {
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select {
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case <-ctx.Done():
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return TimingResult{}, ctx.Err()
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default:
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iterStart := time.Now().UTC()
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if err := fn(); err != nil {
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return TimingResult{}, err
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}
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elapsed := time.Since(iterStart)
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times = append(times, float64(elapsed))
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}
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}
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endTime := time.Now().UTC()
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totalDuration := endTime.Sub(startTime)
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sort.Float64s(times)
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min := time.Duration(times[0])
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max := time.Duration(times[len(times)-1])
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mean := time.Duration(stat.Mean(times, nil))
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median := time.Duration(stat.Quantile(0.5, stat.Empirical, times, nil))
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return TimingResult{
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Min: min,
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Max: max,
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Mean: mean,
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Median: median,
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StartTime: startTime,
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EndTime: endTime,
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Duration: totalDuration,
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Iterations: iterations,
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}, nil
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}
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package timingbench
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import (
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"context"
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"math/rand"
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"testing"
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"time"
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)
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// isPrime checks if a number is a prime number.
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func isPrime(n int) bool {
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if n <= 1 {
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return false
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}
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for i := 2; i*i <= n; i++ {
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if n%i == 0 {
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return false
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}
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}
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return true
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}
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// randomSleep introduces a random delay between 1 and 20 milliseconds.
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func randomSleep() {
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time.Sleep(time.Duration(rand.Intn(20)+1) * time.Millisecond)
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}
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// generatePrimes generates prime numbers up to a given limit.
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func generatePrimes(limit int) []int {
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primes := []int{}
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for i := 2; i <= limit; i++ {
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if isPrime(i) {
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primes = append(primes, i)
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}
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}
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return primes
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}
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// sortRandomSlice generates a slice with random integers and sorts it.
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func sortRandomSlice(size int) {
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slice := make([]int, size)
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for i := range slice {
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slice[i] = rand.Intn(10000)
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}
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quickSort(slice)
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}
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// quickSort sorts a slice of integers using the quicksort algorithm.
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func quickSort(arr []int) {
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if len(arr) < 2 {
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return
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}
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left, right := 0, len(arr)-1
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pivotIndex := rand.Int() % len(arr)
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arr[pivotIndex], arr[right] = arr[right], arr[pivotIndex]
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for i := range arr {
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if arr[i] < arr[right] {
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arr[i], arr[left] = arr[left], arr[i]
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left++
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}
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}
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arr[left], arr[right] = arr[right], arr[left]
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quickSort(arr[:left])
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quickSort(arr[left+1:])
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}
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// multiplyMatrices performs matrix multiplication of two randomly generated matrices.
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func multiplyMatrices(size int) {
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matrixA := make([][]int, size)
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matrixB := make([][]int, size)
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result := make([][]int, size)
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for i := 0; i < size; i++ {
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matrixA[i] = make([]int, size)
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matrixB[i] = make([]int, size)
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result[i] = make([]int, size)
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for j := 0; j < size; j++ {
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matrixA[i][j] = rand.Intn(100)
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matrixB[i][j] = rand.Intn(100)
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}
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}
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for i := 0; i < size; i++ {
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for j := 0; j < size; j++ {
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sum := 0
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for k := 0; k < size; k++ {
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sum += matrixA[i][k] * matrixB[k][j]
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}
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result[i][j] = sum
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}
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}
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}
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// sampleFunction performs a mix of different operations to introduce variability in runtime.
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func sampleFunction() error {
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randomSleep()
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generatePrimes(500 + rand.Intn(1500))
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sortRandomSlice(500 + rand.Intn(1500))
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multiplyMatrices(20 + rand.Intn(10))
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return nil
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}
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func TestTimeFunction(t *testing.T) {
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// Seed the random number generator.
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rand.Seed(time.Now().UnixNano())
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// Define the number of iterations.
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iterations := 1000
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// Create a context with a timeout for cancellation.
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ctx, cancel := context.WithTimeout(context.Background(), 20*time.Second)
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defer cancel()
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// Measure the execution times of the sample function.
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result, err := TimeFunction(ctx, sampleFunction, iterations)
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if err != nil {
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t.Fatalf("Error measuring function: %v", err)
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}
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// Print the timing results.
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t.Logf(result.String())
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}
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@ -0,0 +1,5 @@
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module git.eeqj.de/sneak/timingbench
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go 1.22.2
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require gonum.org/v1/gonum v0.15.0 // indirect
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