Add glide.yaml and vendor deps

vendor/golang.org/x/net/trace/histogram.go

@@ -0,0 +1,356 @@
+// Copyright 2015 The Go Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style
+// license that can be found in the LICENSE file.
+
+package trace
+
+// This file implements histogramming for RPC statistics collection.
+
+import (
+	"bytes"
+	"fmt"
+	"html/template"
+	"log"
+	"math"
+
+	"golang.org/x/net/internal/timeseries"
+)
+
+const (
+	bucketCount = 38
+)
+
+// histogram keeps counts of values in buckets that are spaced
+// out in powers of 2: 0-1, 2-3, 4-7...
+// histogram implements timeseries.Observable
+type histogram struct {
+	sum          int64   // running total of measurements
+	sumOfSquares float64 // square of running total
+	buckets      []int64 // bucketed values for histogram
+	value        int     // holds a single value as an optimization
+	valueCount   int64   // number of values recorded for single value
+}
+
+// AddMeasurement records a value measurement observation to the histogram.
+func (h *histogram) addMeasurement(value int64) {
+	// TODO: assert invariant
+	h.sum += value
+	h.sumOfSquares += float64(value) * float64(value)
+
+	bucketIndex := getBucket(value)
+
+	if h.valueCount == 0 || (h.valueCount > 0 && h.value == bucketIndex) {
+		h.value = bucketIndex
+		h.valueCount++
+	} else {
+		h.allocateBuckets()
+		h.buckets[bucketIndex]++
+	}
+}
+
+func (h *histogram) allocateBuckets() {
+	if h.buckets == nil {
+		h.buckets = make([]int64, bucketCount)
+		h.buckets[h.value] = h.valueCount
+		h.value = 0
+		h.valueCount = -1
+	}
+}
+
+func log2(i int64) int {
+	n := 0
+	for ; i >= 0x100; i >>= 8 {
+		n += 8
+	}
+	for ; i > 0; i >>= 1 {
+		n += 1
+	}
+	return n
+}
+
+func getBucket(i int64) (index int) {
+	index = log2(i) - 1
+	if index < 0 {
+		index = 0
+	}
+	if index >= bucketCount {
+		index = bucketCount - 1
+	}
+	return
+}
+
+// Total returns the number of recorded observations.
+func (h *histogram) total() (total int64) {
+	if h.valueCount >= 0 {
+		total = h.valueCount
+	}
+	for _, val := range h.buckets {
+		total += int64(val)
+	}
+	return
+}
+
+// Average returns the average value of recorded observations.
+func (h *histogram) average() float64 {
+	t := h.total()
+	if t == 0 {
+		return 0
+	}
+	return float64(h.sum) / float64(t)
+}
+
+// Variance returns the variance of recorded observations.
+func (h *histogram) variance() float64 {
+	t := float64(h.total())
+	if t == 0 {
+		return 0
+	}
+	s := float64(h.sum) / t
+	return h.sumOfSquares/t - s*s
+}
+
+// StandardDeviation returns the standard deviation of recorded observations.
+func (h *histogram) standardDeviation() float64 {
+	return math.Sqrt(h.variance())
+}
+
+// PercentileBoundary estimates the value that the given fraction of recorded
+// observations are less than.
+func (h *histogram) percentileBoundary(percentile float64) int64 {
+	total := h.total()
+
+	// Corner cases (make sure result is strictly less than Total())
+	if total == 0 {
+		return 0
+	} else if total == 1 {
+		return int64(h.average())
+	}
+
+	percentOfTotal := round(float64(total) * percentile)
+	var runningTotal int64
+
+	for i := range h.buckets {
+		value := h.buckets[i]
+		runningTotal += value
+		if runningTotal == percentOfTotal {
+			// We hit an exact bucket boundary. If the next bucket has data, it is a
+			// good estimate of the value. If the bucket is empty, we interpolate the
+			// midpoint between the next bucket's boundary and the next non-zero
+			// bucket. If the remaining buckets are all empty, then we use the
+			// boundary for the next bucket as the estimate.
+			j := uint8(i + 1)
+			min := bucketBoundary(j)
+			if runningTotal < total {
+				for h.buckets[j] == 0 {
+					j++
+				}
+			}
+			max := bucketBoundary(j)
+			return min + round(float64(max-min)/2)
+		} else if runningTotal > percentOfTotal {
+			// The value is in this bucket. Interpolate the value.
+			delta := runningTotal - percentOfTotal
+			percentBucket := float64(value-delta) / float64(value)
+			bucketMin := bucketBoundary(uint8(i))
+			nextBucketMin := bucketBoundary(uint8(i + 1))
+			bucketSize := nextBucketMin - bucketMin
+			return bucketMin + round(percentBucket*float64(bucketSize))
+		}
+	}
+	return bucketBoundary(bucketCount - 1)
+}
+
+// Median returns the estimated median of the observed values.
+func (h *histogram) median() int64 {
+	return h.percentileBoundary(0.5)
+}
+
+// Add adds other to h.
+func (h *histogram) Add(other timeseries.Observable) {
+	o := other.(*histogram)
+	if o.valueCount == 0 {
+		// Other histogram is empty
+	} else if h.valueCount >= 0 && o.valueCount > 0 && h.value == o.value {
+		// Both have a single bucketed value, aggregate them
+		h.valueCount += o.valueCount
+	} else {
+		// Two different values necessitate buckets in this histogram
+		h.allocateBuckets()
+		if o.valueCount >= 0 {
+			h.buckets[o.value] += o.valueCount
+		} else {
+			for i := range h.buckets {
+				h.buckets[i] += o.buckets[i]
+			}
+		}
+	}
+	h.sumOfSquares += o.sumOfSquares
+	h.sum += o.sum
+}
+
+// Clear resets the histogram to an empty state, removing all observed values.
+func (h *histogram) Clear() {
+	h.buckets = nil
+	h.value = 0
+	h.valueCount = 0
+	h.sum = 0
+	h.sumOfSquares = 0
+}
+
+// CopyFrom copies from other, which must be a *histogram, into h.
+func (h *histogram) CopyFrom(other timeseries.Observable) {
+	o := other.(*histogram)
+	if o.valueCount == -1 {
+		h.allocateBuckets()
+		copy(h.buckets, o.buckets)
+	}
+	h.sum = o.sum
+	h.sumOfSquares = o.sumOfSquares
+	h.value = o.value
+	h.valueCount = o.valueCount
+}
+
+// Multiply scales the histogram by the specified ratio.
+func (h *histogram) Multiply(ratio float64) {
+	if h.valueCount == -1 {
+		for i := range h.buckets {
+			h.buckets[i] = int64(float64(h.buckets[i]) * ratio)
+		}
+	} else {
+		h.valueCount = int64(float64(h.valueCount) * ratio)
+	}
+	h.sum = int64(float64(h.sum) * ratio)
+	h.sumOfSquares = h.sumOfSquares * ratio
+}
+
+// New creates a new histogram.
+func (h *histogram) New() timeseries.Observable {
+	r := new(histogram)
+	r.Clear()
+	return r
+}
+
+func (h *histogram) String() string {
+	return fmt.Sprintf("%d, %f, %d, %d, %v",
+		h.sum, h.sumOfSquares, h.value, h.valueCount, h.buckets)
+}
+
+// round returns the closest int64 to the argument
+func round(in float64) int64 {
+	return int64(math.Floor(in + 0.5))
+}
+
+// bucketBoundary returns the first value in the bucket.
+func bucketBoundary(bucket uint8) int64 {
+	if bucket == 0 {
+		return 0
+	}
+	return 1 << bucket
+}
+
+// bucketData holds data about a specific bucket for use in distTmpl.
+type bucketData struct {
+	Lower, Upper       int64
+	N                  int64
+	Pct, CumulativePct float64
+	GraphWidth         int
+}
+
+// data holds data about a Distribution for use in distTmpl.
+type data struct {
+	Buckets                 []*bucketData
+	Count, Median           int64
+	Mean, StandardDeviation float64
+}
+
+// maxHTMLBarWidth is the maximum width of the HTML bar for visualizing buckets.
+const maxHTMLBarWidth = 350.0
+
+// newData returns data representing h for use in distTmpl.
+func (h *histogram) newData() *data {
+	// Force the allocation of buckets to simplify the rendering implementation
+	h.allocateBuckets()
+	// We scale the bars on the right so that the largest bar is
+	// maxHTMLBarWidth pixels in width.
+	maxBucket := int64(0)
+	for _, n := range h.buckets {
+		if n > maxBucket {
+			maxBucket = n
+		}
+	}
+	total := h.total()
+	barsizeMult := maxHTMLBarWidth / float64(maxBucket)
+	var pctMult float64
+	if total == 0 {
+		pctMult = 1.0
+	} else {
+		pctMult = 100.0 / float64(total)
+	}
+
+	buckets := make([]*bucketData, len(h.buckets))
+	runningTotal := int64(0)
+	for i, n := range h.buckets {
+		if n == 0 {
+			continue
+		}
+		runningTotal += n
+		var upperBound int64
+		if i < bucketCount-1 {
+			upperBound = bucketBoundary(uint8(i + 1))
+		} else {
+			upperBound = math.MaxInt64
+		}
+		buckets[i] = &bucketData{
+			Lower:         bucketBoundary(uint8(i)),
+			Upper:         upperBound,
+			N:             n,
+			Pct:           float64(n) * pctMult,
+			CumulativePct: float64(runningTotal) * pctMult,
+			GraphWidth:    int(float64(n) * barsizeMult),
+		}
+	}
+	return &data{
+		Buckets:           buckets,
+		Count:             total,
+		Median:            h.median(),
+		Mean:              h.average(),
+		StandardDeviation: h.standardDeviation(),
+	}
+}
+
+func (h *histogram) html() template.HTML {
+	buf := new(bytes.Buffer)
+	if err := distTmpl.Execute(buf, h.newData()); err != nil {
+		buf.Reset()
+		log.Printf("net/trace: couldn't execute template: %v", err)
+	}
+	return template.HTML(buf.String())
+}
+
+// Input: data
+var distTmpl = template.Must(template.New("distTmpl").Parse(`
+<table>
+<tr>
+    <td style="padding:0.25em">Count: {{.Count}}</td>
+    <td style="padding:0.25em">Mean: {{printf "%.0f" .Mean}}</td>
+    <td style="padding:0.25em">StdDev: {{printf "%.0f" .StandardDeviation}}</td>
+    <td style="padding:0.25em">Median: {{.Median}}</td>
+</tr>
+</table>
+<hr>
+<table>
+{{range $b := .Buckets}}
+{{if $b}}
+  <tr>
+    <td style="padding:0 0 0 0.25em">[</td>
+    <td style="text-align:right;padding:0 0.25em">{{.Lower}},</td>
+    <td style="text-align:right;padding:0 0.25em">{{.Upper}})</td>
+    <td style="text-align:right;padding:0 0.25em">{{.N}}</td>
+    <td style="text-align:right;padding:0 0.25em">{{printf "%#.3f" .Pct}}%</td>
+    <td style="text-align:right;padding:0 0.25em">{{printf "%#.3f" .CumulativePct}}%</td>
+    <td><div style="background-color: blue; height: 1em; width: {{.GraphWidth}};"></div></td>
+  </tr>
+{{end}}
+{{end}}
+</table>
+`))

vendor/golang.org/x/net/trace/histogram_test.go

@@ -0,0 +1,325 @@
+// Copyright 2015 The Go Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style
+// license that can be found in the LICENSE file.
+
+package trace
+
+import (
+	"math"
+	"testing"
+)
+
+type sumTest struct {
+	value        int64
+	sum          int64
+	sumOfSquares float64
+	total        int64
+}
+
+var sumTests = []sumTest{
+	{100, 100, 10000, 1},
+	{50, 150, 12500, 2},
+	{50, 200, 15000, 3},
+	{50, 250, 17500, 4},
+}
+
+type bucketingTest struct {
+	in     int64
+	log    int
+	bucket int
+}
+
+var bucketingTests = []bucketingTest{
+	{0, 0, 0},
+	{1, 1, 0},
+	{2, 2, 1},
+	{3, 2, 1},
+	{4, 3, 2},
+	{1000, 10, 9},
+	{1023, 10, 9},
+	{1024, 11, 10},
+	{1000000, 20, 19},
+}
+
+type multiplyTest struct {
+	in                   int64
+	ratio                float64
+	expectedSum          int64
+	expectedTotal        int64
+	expectedSumOfSquares float64
+}
+
+var multiplyTests = []multiplyTest{
+	{15, 2.5, 37, 2, 562.5},
+	{128, 4.6, 758, 13, 77953.9},
+}
+
+type percentileTest struct {
+	fraction float64
+	expected int64
+}
+
+var percentileTests = []percentileTest{
+	{0.25, 48},
+	{0.5, 96},
+	{0.6, 109},
+	{0.75, 128},
+	{0.90, 205},
+	{0.95, 230},
+	{0.99, 256},
+}
+
+func TestSum(t *testing.T) {
+	var h histogram
+
+	for _, test := range sumTests {
+		h.addMeasurement(test.value)
+		sum := h.sum
+		if sum != test.sum {
+			t.Errorf("h.Sum = %v WANT: %v", sum, test.sum)
+		}
+
+		sumOfSquares := h.sumOfSquares
+		if sumOfSquares != test.sumOfSquares {
+			t.Errorf("h.SumOfSquares = %v WANT: %v", sumOfSquares, test.sumOfSquares)
+		}
+
+		total := h.total()
+		if total != test.total {
+			t.Errorf("h.Total = %v WANT: %v", total, test.total)
+		}
+	}
+}
+
+func TestMultiply(t *testing.T) {
+	var h histogram
+	for i, test := range multiplyTests {
+		h.addMeasurement(test.in)
+		h.Multiply(test.ratio)
+		if h.sum != test.expectedSum {
+			t.Errorf("#%v: h.sum = %v WANT: %v", i, h.sum, test.expectedSum)
+		}
+		if h.total() != test.expectedTotal {
+			t.Errorf("#%v: h.total = %v WANT: %v", i, h.total(), test.expectedTotal)
+		}
+		if h.sumOfSquares != test.expectedSumOfSquares {
+			t.Errorf("#%v: h.SumOfSquares = %v WANT: %v", i, test.expectedSumOfSquares, h.sumOfSquares)
+		}
+	}
+}
+
+func TestBucketingFunctions(t *testing.T) {
+	for _, test := range bucketingTests {
+		log := log2(test.in)
+		if log != test.log {
+			t.Errorf("log2 = %v WANT: %v", log, test.log)
+		}
+
+		bucket := getBucket(test.in)
+		if bucket != test.bucket {
+			t.Errorf("getBucket = %v WANT: %v", bucket, test.bucket)
+		}
+	}
+}
+
+func TestAverage(t *testing.T) {
+	a := new(histogram)
+	average := a.average()
+	if average != 0 {
+		t.Errorf("Average of empty histogram was %v WANT: 0", average)
+	}
+
+	a.addMeasurement(1)
+	a.addMeasurement(1)
+	a.addMeasurement(3)
+	const expected = float64(5) / float64(3)
+	average = a.average()
+
+	if !isApproximate(average, expected) {
+		t.Errorf("Average = %g WANT: %v", average, expected)
+	}
+}
+
+func TestStandardDeviation(t *testing.T) {
+	a := new(histogram)
+	add(a, 10, 1<<4)
+	add(a, 10, 1<<5)
+	add(a, 10, 1<<6)
+	stdDev := a.standardDeviation()
+	const expected = 19.95
+
+	if !isApproximate(stdDev, expected) {
+		t.Errorf("StandardDeviation = %v WANT: %v", stdDev, expected)
+	}
+
+	// No values
+	a = new(histogram)
+	stdDev = a.standardDeviation()
+
+	if !isApproximate(stdDev, 0) {
+		t.Errorf("StandardDeviation = %v WANT: 0", stdDev)
+	}
+
+	add(a, 1, 1<<4)
+	if !isApproximate(stdDev, 0) {
+		t.Errorf("StandardDeviation = %v WANT: 0", stdDev)
+	}
+
+	add(a, 10, 1<<4)
+	if !isApproximate(stdDev, 0) {
+		t.Errorf("StandardDeviation = %v WANT: 0", stdDev)
+	}
+}
+
+func TestPercentileBoundary(t *testing.T) {
+	a := new(histogram)
+	add(a, 5, 1<<4)
+	add(a, 10, 1<<6)
+	add(a, 5, 1<<7)
+
+	for _, test := range percentileTests {
+		percentile := a.percentileBoundary(test.fraction)
+		if percentile != test.expected {
+			t.Errorf("h.PercentileBoundary (fraction=%v) = %v WANT: %v", test.fraction, percentile, test.expected)
+		}
+	}
+}
+
+func TestCopyFrom(t *testing.T) {
+	a := histogram{5, 25, []int64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
+		19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38}, 4, -1}
+	b := histogram{6, 36, []int64{2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+		20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39}, 5, -1}
+
+	a.CopyFrom(&b)
+
+	if a.String() != b.String() {
+		t.Errorf("a.String = %s WANT: %s", a.String(), b.String())
+	}
+}
+
+func TestClear(t *testing.T) {
+	a := histogram{5, 25, []int64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
+		19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38}, 4, -1}
+
+	a.Clear()
+
+	expected := "0, 0.000000, 0, 0, []"
+	if a.String() != expected {
+		t.Errorf("a.String = %s WANT %s", a.String(), expected)
+	}
+}
+
+func TestNew(t *testing.T) {
+	a := histogram{5, 25, []int64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
+		19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38}, 4, -1}
+	b := a.New()
+
+	expected := "0, 0.000000, 0, 0, []"
+	if b.(*histogram).String() != expected {
+		t.Errorf("b.(*histogram).String = %s WANT: %s", b.(*histogram).String(), expected)
+	}
+}
+
+func TestAdd(t *testing.T) {
+	// The tests here depend on the associativity of addMeasurement and Add.
+	// Add empty observation
+	a := histogram{5, 25, []int64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
+		19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38}, 4, -1}
+	b := a.New()
+
+	expected := a.String()
+	a.Add(b)
+	if a.String() != expected {
+		t.Errorf("a.String = %s WANT: %s", a.String(), expected)
+	}
+
+	// Add same bucketed value, no new buckets
+	c := new(histogram)
+	d := new(histogram)
+	e := new(histogram)
+	c.addMeasurement(12)
+	d.addMeasurement(11)
+	e.addMeasurement(12)
+	e.addMeasurement(11)
+	c.Add(d)
+	if c.String() != e.String() {
+		t.Errorf("c.String = %s WANT: %s", c.String(), e.String())
+	}
+
+	// Add bucketed values
+	f := new(histogram)
+	g := new(histogram)
+	h := new(histogram)
+	f.addMeasurement(4)
+	f.addMeasurement(12)
+	f.addMeasurement(100)
+	g.addMeasurement(18)
+	g.addMeasurement(36)
+	g.addMeasurement(255)
+	h.addMeasurement(4)
+	h.addMeasurement(12)
+	h.addMeasurement(100)
+	h.addMeasurement(18)
+	h.addMeasurement(36)
+	h.addMeasurement(255)
+	f.Add(g)
+	if f.String() != h.String() {
+		t.Errorf("f.String = %q WANT: %q", f.String(), h.String())
+	}
+
+	// add buckets to no buckets
+	i := new(histogram)
+	j := new(histogram)
+	k := new(histogram)
+	j.addMeasurement(18)
+	j.addMeasurement(36)
+	j.addMeasurement(255)
+	k.addMeasurement(18)
+	k.addMeasurement(36)
+	k.addMeasurement(255)
+	i.Add(j)
+	if i.String() != k.String() {
+		t.Errorf("i.String = %q WANT: %q", i.String(), k.String())
+	}
+
+	// add buckets to single value (no overlap)
+	l := new(histogram)
+	m := new(histogram)
+	n := new(histogram)
+	l.addMeasurement(0)
+	m.addMeasurement(18)
+	m.addMeasurement(36)
+	m.addMeasurement(255)
+	n.addMeasurement(0)
+	n.addMeasurement(18)
+	n.addMeasurement(36)
+	n.addMeasurement(255)
+	l.Add(m)
+	if l.String() != n.String() {
+		t.Errorf("l.String = %q WANT: %q", l.String(), n.String())
+	}
+
+	// mixed order
+	o := new(histogram)
+	p := new(histogram)
+	o.addMeasurement(0)
+	o.addMeasurement(2)
+	o.addMeasurement(0)
+	p.addMeasurement(0)
+	p.addMeasurement(0)
+	p.addMeasurement(2)
+	if o.String() != p.String() {
+		t.Errorf("o.String = %q WANT: %q", o.String(), p.String())
+	}
+}
+
+func add(h *histogram, times int, val int64) {
+	for i := 0; i < times; i++ {
+		h.addMeasurement(val)
+	}
+}
+
+func isApproximate(x, y float64) bool {
+	return math.Abs(x-y) < 1e-2
+}

vendor/golang.org/x/net/trace/trace_test.go

@@ -0,0 +1,71 @@
+// Copyright 2015 The Go Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style
+// license that can be found in the LICENSE file.
+
+package trace
+
+import (
+	"net/http"
+	"reflect"
+	"testing"
+)
+
+type s struct{}
+
+func (s) String() string { return "lazy string" }
+
+// TestReset checks whether all the fields are zeroed after reset.
+func TestReset(t *testing.T) {
+	tr := New("foo", "bar")
+	tr.LazyLog(s{}, false)
+	tr.LazyPrintf("%d", 1)
+	tr.SetRecycler(func(_ interface{}) {})
+	tr.SetTraceInfo(3, 4)
+	tr.SetMaxEvents(100)
+	tr.SetError()
+	tr.Finish()
+
+	tr.(*trace).reset()
+
+	if !reflect.DeepEqual(tr, new(trace)) {
+		t.Errorf("reset didn't clear all fields: %+v", tr)
+	}
+}
+
+// TestResetLog checks whether all the fields are zeroed after reset.
+func TestResetLog(t *testing.T) {
+	el := NewEventLog("foo", "bar")
+	el.Printf("message")
+	el.Errorf("error")
+	el.Finish()
+
+	el.(*eventLog).reset()
+
+	if !reflect.DeepEqual(el, new(eventLog)) {
+		t.Errorf("reset didn't clear all fields: %+v", el)
+	}
+}
+
+func TestAuthRequest(t *testing.T) {
+	testCases := []struct {
+		host string
+		want bool
+	}{
+		{host: "192.168.23.1", want: false},
+		{host: "192.168.23.1:8080", want: false},
+		{host: "malformed remote addr", want: false},
+		{host: "localhost", want: true},
+		{host: "localhost:8080", want: true},
+		{host: "127.0.0.1", want: true},
+		{host: "127.0.0.1:8080", want: true},
+		{host: "::1", want: true},
+		{host: "[::1]:8080", want: true},
+	}
+	for _, tt := range testCases {
+		req := &http.Request{RemoteAddr: tt.host}
+		any, sensitive := AuthRequest(req)
+		if any != tt.want || sensitive != tt.want {
+			t.Errorf("AuthRequest(%q) = %t, %t; want %t, %t", tt.host, any, sensitive, tt.want, tt.want)
+		}
+	}
+}