今天就跟大家聊聊有关利用golang怎么实现单元测试，可能很多人都不太了解，为了让大家更加了解，小编给大家总结了以下内容，希望大家根据这篇文章可以有所收获。
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单元测试
单元测试的格式形如:
func TestAbs(t *testing.T) {
got := Abs(-1)
if got != 1 {
t.Errorf("Abs(-1) = %d; want 1", got)
}
}在 util 目录下创建一个文件 util_test.go, 添加一个单元测试:
package util
import "testing"
// 普通的测试
func TestGenShortID(t *testing.T) {
shortID, err := GenShortID()
if shortID == "" || err != nil {
t.Error("GenShortID failed")
}
}然后, 在根目录下运行 go test -v ./util/, 测试结果如下:
root@592402321ce7:/workspace# go test -v ./util/ === RUN TestGenShortID --- PASS: TestGenShortID (0.00s) PASS ok tzh.com/web/util 0.006s
性能测试
性能测试的结果形如:
func BenchmarkHello(b *testing.B) {
for i := 0; i < b.N; i++ {
fmt.Sprintf("hello")
}
}在 util_test.go 添加性能测试:
// 性能测试
func BenchmarkGenShortID(b *testing.B) {
for i := 0; i < b.N; i++ {
GenShortID()
}
}运行结果如下(使用 --run=none 避免运行普通的测试函数, 因为一般不可能有函数名匹配 none):
root@592402321ce7:/workspace# go test -v -bench="BenchmarkGenShortID$" --run=none ./util/ goos: linux goarch: amd64 pkg: tzh.com/web/util BenchmarkGenShortID-2 507237 2352 ns/op PASS ok tzh.com/web/util 1.229s
这说明, 平均每次运行 GenShortID() 需要 2352 纳秒.
性能分析
运行测试的时候, 可以指定一些参数, 生成性能文件 profile.
-blockprofile block.out Write a goroutine blocking profile to the specified file when all tests are complete. Writes test binary as -c would. -blockprofilerate n Control the detail provided in goroutine blocking profiles by calling runtime.SetBlockProfileRate with n. See 'go doc runtime.SetBlockProfileRate'. The profiler aims to sample, on average, one blocking event every n nanoseconds the program spends blocked. By default, if -test.blockprofile is set without this flag, all blocking events are recorded, equivalent to -test.blockprofilerate=1. -coverprofile cover.out Write a coverage profile to the file after all tests have passed. Sets -cover. -cpuprofile cpu.out Write a CPU profile to the specified file before exiting. Writes test binary as -c would. -memprofile mem.out Write an allocation profile to the file after all tests have passed. Writes test binary as -c would. -memprofilerate n Enable more precise (and expensive) memory allocation profiles by setting runtime.MemProfileRate. See 'go doc runtime.MemProfileRate'. To profile all memory allocations, use -test.memprofilerate=1. -mutexprofile mutex.out Write a mutex contention profile to the specified file when all tests are complete. Writes test binary as -c would. -mutexprofilefraction n Sample 1 in n stack traces of goroutines holding a contended mutex.
使用下面的命令, 生成 CPU 的 profile:
go test -v -bench="BenchmarkGenShortID$" --run=none -cpuprofile cpu.out ./util/
当前目录下, 应该会生成 cpu.out 文件和 util.test 文件.
使用下面的命令, 观察耗时操作:
# 进入交互模式 go tool pprof cpu.out top
安装 Graphviz 后可以生成可视化的分析图.
apt install graphviz go tool pprof -http=":" cpu.out
测试覆盖率
root@592402321ce7:/workspace# go test -v -coverprofile=cover.out ./util/ === RUN TestGenShortID --- PASS: TestGenShortID (0.00s) PASS coverage: 9.1% of statements ok tzh.com/web/util 0.005s coverage: 9.1% of statements root@592402321ce7:/workspace# go tool cover -func=cover.out tzh.com/web/util/util.go:12: GenShortID 100.0% tzh.com/web/util/util.go:17: GetReqID 0.0% tzh.com/web/util/util.go:22: TimeToStr 0.0% tzh.com/web/util/util.go:30: GetTag 0.0% total: (statements) 9.1%
使用 -coverprofile=cover.out 选项可以统计测试覆盖率.使用 go tool cover -func=cover.out 可以查看更加详细的测试覆盖率结果,
统计每个函数的测试覆盖率.
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