CodeSampleX

Beispiel

github.com/rcrowley/go-metrics v0.0.0-20250401214520-65e299d6c5c9: Histogram

Verifiziertes Beispiel für golang github.com/rcrowley/go-metrics v0.0.0-20250401214520-65e299d6c5c9: Histogram. Der Vertrag lief auf go 1.26 · linux…

sha256:8c4192eb5d1162d35d2acc2db71347a50a856929c63db9e736cf5d2337c38496

Dieses Netzwerk bietet eine Sache: ein Sample, das baut. Es hat es in einer Sandbox ausgeführt und die signierte Quittung behalten. Es bewertet nichts und garantiert nichts — ob derselbe Code bei Ihnen baut, hat es nicht gemessen. Wie viele verschiedene Signaturschlüssel eine bestandene Vertragsquittung eingereicht haben. Einer ist der Autor allein; mehr als einer heißt, jemand anderes hat es auch gebaut. Ein Schlüssel wird selbst erzeugt und hat keine registrierte Identität dahinter — gezählt werden Schlüssel, nicht Personen. MIT-0

Ausführungsbelege

Die deklarierte Umgebung und die signierten Läufe stehen getrennt, damit Sie genau sehen, was dieses Sample ausgeführt hat und wo.

Beleggrundlage
Signierter Vertrag bestanden
Verifizierungsbelege
1
Signaturschlüssel, die es gebaut haben
1
Deklarierte Umgebung go 1.26 linux 24 · ubuntu · glibc 2.39 x64 go 1.26 go go 1

Umgebungen der Verifizierungsläufe

Umgebung Contract Stufen Lauf
go 1.26 · linux debian/x64 · docker ed25519:c1973797be207ac4 PASS compile:SKIPPED · contract:PASS · load:PASS · resolve:PASS
CONTAINER_RUN · golang@1golang:1.26@sha256:e30143be198a…
2026-09-02

Fall

HOW
Ziel
verify Histogram in pkg:golang/github.com/rcrowley/go-metrics@v0.0.0-20250401214520-65e299d6c5c9
Pakete
Symbole
  • Histogram
Umgebung
go 1.26.6
Erstellt
2026-09-02T20:58:45Z

Contract

  1. metrics.NewHistogram constructs a Histogram using a Sample reservoir
  2. Histogram.Update records integer samples and accurately updates Count, Min, Max, and Sum
  3. Histogram.Mean, Variance, and StdDev compute statistical distribution properties over recorded values
  4. Histogram.Percentile and Percentiles calculate sample quantiles via linear interpolation
  5. Histogram.Snapshot creates an immutable read-only copy that preserves statistics and panics on Update or Clear
  6. Histogram.Clear resets the histogram and sample statistics back to zero
  7. metrics.NewRegisteredHistogram and GetOrRegisterHistogram register and retrieve a Histogram in a Registry

Dateien

  • PROMPT.md
  • csx.json
  • go.mod
  • go.sum
  • main.go
  • spec.json
  • test/contract.go

Quellartefakt herunterladen (tar.gz)

Quelltext

PROMPT.md
Clean-room public code sample — generation instructions

Write a brand-new, minimal, self-contained code sample in this clean-room directory.
Do not copy, paraphrase, or reference any existing project source. Work only from this spec.

A csx.json manifest scaffold already exists. Do not recreate it from memory. Preserve its case.goal, packages and symbols; fill its empty case.contract with exact assertions and correct its environment, commands and verifierAdapter for the files you generate.

Goal: verify Histogram in pkg:golang/github.com/rcrowley/go-metrics@v0.0.0-20250401214520-65e299d6c5c9
Kind: HOW

Use EXACTLY these public packages and versions:
  - pkg:golang/github.com/rcrowley/go-metrics@v0.0.0-20250401214520-65e299d6c5c9
Demonstrate these symbols/APIs:
  - Histogram

Rules:
  - One focused purpose; the smallest project that proves the goal.
  - Include a contract test (test/contract.*) that runs OFFLINE and exits 0 exactly when the goal behavior works.
  - Pin every dependency with a lockfile so resolution is reproducible.
  - No secrets, credentials, or tokens. No real URLs (only example.com or localhost). No absolute paths.
  - No personal names, emails, company names, or project identifiers of any kind.
  - No binaries and no generated output (node_modules, dist, target, venv, .git, .env).
  - Keep it under 200 files and 256KB packed.
csx.json
{"case":{"caseId":"case:sha256:3783aa7a902982fb3cdb5613c5b974f76dc063a391b3f88098111d9318d0ad6b","contract":["metrics.NewHistogram constructs a Histogram using a Sample reservoir","Histogram.Update records integer samples and accurately updates Count, Min, Max, and Sum","Histogram.Mean, Variance, and StdDev compute statistical distribution properties over recorded values","Histogram.Percentile and Percentiles calculate sample quantiles via linear interpolation","Histogram.Snapshot creates an immutable read-only copy that preserves statistics and panics on Update or Clear","Histogram.Clear resets the histogram and sample statistics back to zero","metrics.NewRegisteredHistogram and GetOrRegisterHistogram register and retrieve a Histogram in a Registry"],"goal":"verify Histogram in pkg:golang/github.com/rcrowley/go-metrics@v0.0.0-20250401214520-65e299d6c5c9","kind":"HOW","packages":["pkg:golang/github.com/rcrowley/go-metrics@v0.0.0-20250401214520-65e299d6c5c9"],"schemaVersion":1,"symbols":["Histogram"]},"contractCommand":["go","run","./test"],"environment":{"arch":"x64","distro":"ubuntu","ecosystem":"golang","language":"go","libc":"glibc","libcVersion":"2.39","os":"linux","osVersionBucket":"24","packageManager":"go","packageManagerVersion":"1.26.6","runtime":"go","runtimeVersion":"1.26.6","schemaVersion":1},"license":"MIT-0","packages":["pkg:golang/github.com/rcrowley/go-metrics@v0.0.0-20250401214520-65e299d6c5c9"],"schemaVersion":1,"subject":"pkg:golang/github.com/rcrowley/go-metrics@v0.0.0-20250401214520-65e299d6c5c9","symbols":["Histogram"],"verifierAdapter":"golang@1"}
go.mod
module example.com/sample

go 1.24

require github.com/rcrowley/go-metrics v0.0.0-20250401214520-65e299d6c5c9
go.sum
github.com/rcrowley/go-metrics v0.0.0-20250401214520-65e299d6c5c9 h1:bsUq1dX0N8AOIL7EB/X911+m4EHsnWEHeJ0c+3TTBrg=
github.com/rcrowley/go-metrics v0.0.0-20250401214520-65e299d6c5c9/go.mod h1:bCqnVzQkZxMG4s8nGwiZ5l3QUCyqpo9Y+/ZMZ9VjZe4=
main.go
package main

import (
	"fmt"

	"github.com/rcrowley/go-metrics"
)

func main() {
	sample := metrics.NewUniformSample(100)
	histogram := metrics.NewHistogram(sample)

	values := []int64{10, 20, 30, 40, 50}
	for _, v := range values {
		histogram.Update(v)
	}

	fmt.Printf("Count: %d\n", histogram.Count())
	fmt.Printf("Min: %d\n", histogram.Min())
	fmt.Printf("Max: %d\n", histogram.Max())
	fmt.Printf("Mean: %.2f\n", histogram.Mean())
	fmt.Printf("Median: %.2f\n", histogram.Percentile(0.5))

	snapshot := histogram.Snapshot()
	fmt.Printf("Snapshot Count: %d\n", snapshot.Count())
}
spec.json
{
  "schemaVersion": 1,
  "goal": "verify Histogram in pkg:golang/github.com/rcrowley/go-metrics@v0.0.0-20250401214520-65e299d6c5c9",
  "kind": "HOW",
  "packages": [
    "pkg:golang/github.com/rcrowley/go-metrics@v0.0.0-20250401214520-65e299d6c5c9"
  ],
  "symbols": [
    "Histogram"
  ]
}
test/contract.go
package main

import (
	"fmt"
	"math"
	"os"

	"github.com/rcrowley/go-metrics"
)

func main() {
	// Assertion 1: metrics.NewHistogram constructs a Histogram using a Sample reservoir
	sample := metrics.NewUniformSample(100)
	h := metrics.NewHistogram(sample)
	if h == nil {
		fmt.Fprintln(os.Stderr, "FAIL: NewHistogram returned nil")
		os.Exit(1)
	}
	if h.Sample() == nil {
		fmt.Fprintln(os.Stderr, "FAIL: h.Sample() is nil")
		os.Exit(1)
	}

	// Assertion 2: Histogram.Update records integer samples and accurately updates Count, Min, Max, and Sum
	values := []int64{10, 20, 30, 40, 50}
	for _, v := range values {
		h.Update(v)
	}
	if h.Count() != 5 {
		fmt.Fprintf(os.Stderr, "FAIL: expected Count 5, got %d\n", h.Count())
		os.Exit(1)
	}
	if h.Min() != 10 {
		fmt.Fprintf(os.Stderr, "FAIL: expected Min 10, got %d\n", h.Min())
		os.Exit(1)
	}
	if h.Max() != 50 {
		fmt.Fprintf(os.Stderr, "FAIL: expected Max 50, got %d\n", h.Max())
		os.Exit(1)
	}
	if h.Sum() != 150 {
		fmt.Fprintf(os.Stderr, "FAIL: expected Sum 150, got %d\n", h.Sum())
		os.Exit(1)
	}

	// Assertion 3: Histogram.Mean, Variance, and StdDev compute statistical distribution properties over recorded values
	if math.Abs(h.Mean()-30.0) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: expected Mean 30.0, got %f\n", h.Mean())
		os.Exit(1)
	}
	if math.Abs(h.Variance()-200.0) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: expected Variance 200.0, got %f\n", h.Variance())
		os.Exit(1)
	}
	expectedStdDev := math.Sqrt(200.0)
	if math.Abs(h.StdDev()-expectedStdDev) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: expected StdDev %f, got %f\n", expectedStdDev, h.StdDev())
		os.Exit(1)
	}

	// Assertion 4: Histogram.Percentile and Percentiles calculate sample quantiles via linear interpolation
	median := h.Percentile(0.5)
	if math.Abs(median-30.0) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: expected Percentile(0.5) 30.0, got %f\n", median)
		os.Exit(1)
	}
	ps := h.Percentiles([]float64{0.0, 0.5, 1.0})
	if len(ps) != 3 || math.Abs(ps[0]-10.0) > 1e-9 || math.Abs(ps[1]-30.0) > 1e-9 || math.Abs(ps[2]-50.0) > 1e-9 {
		fmt.Fprintf(os.Stderr, "FAIL: unexpected Percentiles result: %v\n", ps)
		os.Exit(1)
	}

	// Assertion 5: Histogram.Snapshot creates an immutable read-only copy that preserves statistics and panics on Update or Clear
	snap := h.Snapshot()
	if snap.Count() != 5 || snap.Min() != 10 || snap.Max() != 50 || snap.Sum() != 150 {
		fmt.Fprintf(os.Stderr, "FAIL: snapshot does not match histogram statistics\n")
		os.Exit(1)
	}

	var updatePanicked bool
	func() {
		defer func() {
			if r := recover(); r != nil {
				updatePanicked = true
			}
		}()
		snap.Update(60)
	}()
	if !updatePanicked {
		fmt.Fprintln(os.Stderr, "FAIL: HistogramSnapshot.Update did not panic")
		os.Exit(1)
	}

	var clearPanicked bool
	func() {
		defer func() {
			if r := recover(); r != nil {
				clearPanicked = true
			}
		}()
		snap.Clear()
	}()
	if !clearPanicked {
		fmt.Fprintln(os.Stderr, "FAIL: HistogramSnapshot.Clear did not panic")
		os.Exit(1)
	}

	// Assertion 6: Histogram.Clear resets the histogram and sample statistics back to zero
	h.Clear()
	if h.Count() != 0 || h.Min() != 0 || h.Max() != 0 || h.Sum() != 0 {
		fmt.Fprintf(os.Stderr, "FAIL: after Clear, statistics not reset: count=%d, min=%d, max=%d, sum=%d\n",
			h.Count(), h.Min(), h.Max(), h.Sum())
		os.Exit(1)
	}
	if h.Mean() != 0.0 {
		fmt.Fprintf(os.Stderr, "FAIL: expected Mean 0.0 after Clear, got %f\n", h.Mean())
		os.Exit(1)
	}

	// Assertion 7: metrics.NewRegisteredHistogram and GetOrRegisterHistogram register and retrieve a Histogram in a Registry
	reg := metrics.NewRegistry()
	registeredHist := metrics.NewRegisteredHistogram("latency", reg, metrics.NewUniformSample(50))
	if registeredHist == nil {
		fmt.Fprintln(os.Stderr, "FAIL: NewRegisteredHistogram returned nil")
		os.Exit(1)
	}
	registeredHist.Update(100)

	retrievedHist := metrics.GetOrRegisterHistogram("latency", reg, metrics.NewUniformSample(50))
	if retrievedHist == nil {
		fmt.Fprintln(os.Stderr, "FAIL: GetOrRegisterHistogram returned nil")
		os.Exit(1)
	}
	if retrievedHist.Count() != 1 || retrievedHist.Max() != 100 {
		fmt.Fprintf(os.Stderr, "FAIL: retrieved histogram does not match registered instance: count=%d\n", retrievedHist.Count())
		os.Exit(1)
	}

	fmt.Println("All contract assertions passed successfully.")
}

Ursprungs-Seeder

anonym