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今天就跟大家聊聊有關利用golang怎么實現單元測試,可能很多人都不太了解,為了讓大家更加了解,小編給大家總結了以下內容,希望大家根據這篇文章可以有所收獲。
單元測試
單元測試的格式形如:
func TestAbs(t *testing.T) { got := Abs(-1) if got != 1 { t.Errorf("Abs(-1) = %d; want 1", got) } }
在 util 目錄下創建一個文件 util_test.go, 添加一個單元測試:
package util import "testing" // 普通的測試 func TestGenShortID(t *testing.T) { shortID, err := GenShortID() if shortID == "" || err != nil { t.Error("GenShortID failed") } }
然后, 在根目錄下運行 go test -v ./util/, 測試結果如下:
root@592402321ce7:/workspace# go test -v ./util/ === RUN TestGenShortID --- PASS: TestGenShortID (0.00s) PASS ok tzh.com/web/util 0.006s
性能測試
性能測試的結果形如:
func BenchmarkHello(b *testing.B) { for i := 0; i < b.N; i++ { fmt.Sprintf("hello") } }
在 util_test.go 添加性能測試:
// 性能測試 func BenchmarkGenShortID(b *testing.B) { for i := 0; i < b.N; i++ { GenShortID() } }
運行結果如下(使用 --run=none 避免運行普通的測試函數, 因為一般不可能有函數名匹配 none):
root@592402321ce7:/workspace# go test -v -bench="BenchmarkGenShortID$" --run=none ./util/ goos: linux goarch: amd64 pkg: tzh.com/web/util BenchmarkGenShortID-2 507237 2352 ns/op PASS ok tzh.com/web/util 1.229s
這說明, 平均每次運行 GenShortID() 需要 2352 納秒.
性能分析
運行測試的時候, 可以指定一些參數, 生成性能文件 profile.
-blockprofile block.out Write a goroutine blocking profile to the specified file when all tests are complete. Writes test binary as -c would. -blockprofilerate n Control the detail provided in goroutine blocking profiles by calling runtime.SetBlockProfileRate with n. See 'go doc runtime.SetBlockProfileRate'. The profiler aims to sample, on average, one blocking event every n nanoseconds the program spends blocked. By default, if -test.blockprofile is set without this flag, all blocking events are recorded, equivalent to -test.blockprofilerate=1. -coverprofile cover.out Write a coverage profile to the file after all tests have passed. Sets -cover. -cpuprofile cpu.out Write a CPU profile to the specified file before exiting. Writes test binary as -c would. -memprofile mem.out Write an allocation profile to the file after all tests have passed. Writes test binary as -c would. -memprofilerate n Enable more precise (and expensive) memory allocation profiles by setting runtime.MemProfileRate. See 'go doc runtime.MemProfileRate'. To profile all memory allocations, use -test.memprofilerate=1. -mutexprofile mutex.out Write a mutex contention profile to the specified file when all tests are complete. Writes test binary as -c would. -mutexprofilefraction n Sample 1 in n stack traces of goroutines holding a contended mutex.
使用下面的命令, 生成 CPU 的 profile:
go test -v -bench="BenchmarkGenShortID$" --run=none -cpuprofile cpu.out ./util/
當前目錄下, 應該會生成 cpu.out 文件和 util.test 文件.
使用下面的命令, 觀察耗時操作:
# 進入交互模式 go tool pprof cpu.out top
安裝 Graphviz 后可以生成可視化的分析圖.
apt install graphviz go tool pprof -http=":" cpu.out
測試覆蓋率
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 選項可以統計測試覆蓋率.使用 go tool cover -func=cover.out 可以查看更加詳細的測試覆蓋率結果,
統計每個函數的測試覆蓋率.
看完上述內容,你們對利用golang怎么實現單元測試有進一步的了解嗎?如果還想了解更多知識或者相關內容,請關注億速云行業資訊頻道,感謝大家的支持。
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