feat: add mock input plugin (#9782)
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Joshua Powers
GitHub
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@ -111,6 +111,7 @@ import (
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_ "github.com/influxdata/telegraf/plugins/inputs/memcached"
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_ "github.com/influxdata/telegraf/plugins/inputs/mesos"
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_ "github.com/influxdata/telegraf/plugins/inputs/minecraft"
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_ "github.com/influxdata/telegraf/plugins/inputs/mock"
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_ "github.com/influxdata/telegraf/plugins/inputs/modbus"
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_ "github.com/influxdata/telegraf/plugins/inputs/mongodb"
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_ "github.com/influxdata/telegraf/plugins/inputs/monit"
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@ -0,0 +1,68 @@
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# Mock Data
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The mock input plugin generates random data based on a selection of different
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algorithms. For example, it can produce random data between a set of values,
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fake stock data, sine waves, and step-wise values.
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Additionally, users can set the measurement name and tags used to whatever is
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required to mock their situation.
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## Configuration
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The mock plugin only requires that:
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1) Metric name is set
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2) One of the below data field algorithms is defined
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Below is a sample config to generate one of each of the four types:
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```toml
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[[inputs.mock]]
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## Set the metric name to use for reporting
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metric_name = "mock"
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## Optional string key-value pairs of tags to add to all metrics
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# [inputs.mock.tags]
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# "key" = "value"
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## One or more mock data fields *must* be defined.
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##
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## [[inputs.mock.random]]
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## name = "rand"
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## min = 1.0
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## max = 6.0
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## [[inputs.mock.sine_wave]]
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## name = "wave"
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## amplitude = 1.0
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## period = 0.5
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## [[inputs.mock.step]]
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## name = "plus_one"
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## start = 0.0
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## step = 1.0
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## [[inputs.mock.stock]]
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## name = "abc"
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## price = 50.00
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## volatility = 0.2
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```
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## Available Algorithms
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The available algorithms for generating mock data include:
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* Random Float - generate a random float, inclusive of min and max
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* Sine Wave - produce a sine wave with a certain amplitude and period
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* Step - always add the step value, negative values accepted
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* Stock - generate fake, stock-like price values based on a volatility variable
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## Example Output
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The following example shows all available algorithms configured with an
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additional two tags as well:
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```s
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mock_sensors,building=5A,site=FTC random=4.875966794516125,abc=50,wave=0,plus_one=0 1632170840000000000
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mock_sensors,building=5A,site=FTC random=5.738651873834452,abc=45.095549448434774,wave=5.877852522924732,plus_one=1 1632170850000000000
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mock_sensors,building=5A,site=FTC random=1.0429328917205203,abc=51.928560083072924,wave=9.510565162951535,plus_one=2 1632170860000000000
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mock_sensors,building=5A,site=FTC random=5.290188595384418,abc=44.41090520217027,wave=9.510565162951536,plus_one=3 1632170870000000000
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mock_sensors,building=5A,site=FTC random=2.0724967227069135,abc=47.212167806890314,wave=5.877852522924733,plus_one=4 1632170880000000000
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```
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@ -0,0 +1,162 @@
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package mock
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import (
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"math"
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"math/rand"
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"time"
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"github.com/influxdata/telegraf"
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"github.com/influxdata/telegraf/plugins/inputs"
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)
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type Mock struct {
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counter int64
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MetricName string `toml:"metric_name"`
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Tags map[string]string `toml:"tags"`
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Random []*random `toml:"random"`
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Step []*step `toml:"step"`
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Stock []*stock `toml:"stock"`
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SineWave []*sineWave `toml:"sine_wave"`
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}
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type random struct {
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Name string `toml:"name"`
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Min float64 `toml:"min"`
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Max float64 `toml:"max"`
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}
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type sineWave struct {
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Name string `toml:"name"`
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Amplitude float64 `toml:"amplitude"`
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Period float64 `toml:"period"`
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}
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type step struct {
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latest float64
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Name string `toml:"name"`
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Start float64 `toml:"min"`
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Step float64 `toml:"max"`
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}
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type stock struct {
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latest float64
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Name string `toml:"name"`
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Price float64 `toml:"price"`
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Volatility float64 `toml:"volatility"`
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}
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const sampleConfig = `
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## Set the metric name to use for reporting
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metric_name = "mock"
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## Optional string key-value pairs of tags to add to all metrics
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# [inputs.mock.tags]
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# "key" = "value"
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## One or more mock data fields *must* be defined.
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##
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## [[inputs.mock.random]]
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## name = "rand"
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## min = 1.0
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## max = 6.0
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## [[inputs.mock.sine_wave]]
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## name = "wave"
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## amplitude = 1.0
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## period = 0.5
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## [[inputs.mock.step]]
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## name = "plus_one"
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## start = 0.0
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## step = 1.0
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## [[inputs.mock.stock]]
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## name = "abc"
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## price = 50.00
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## volatility = 0.2
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`
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func (m *Mock) SampleConfig() string {
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return sampleConfig
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}
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func (m *Mock) Description() string {
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return "Generate metrics for test and demonstration purposes"
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}
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func (m *Mock) Init() error {
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rand.Seed(time.Now().UnixNano())
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return nil
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}
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func (m *Mock) Gather(acc telegraf.Accumulator) error {
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fields := make(map[string]interface{})
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m.generateRandomFloat64(fields)
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m.generateStockPrice(fields)
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m.generateSineWave(fields)
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m.generateStep(fields)
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tags := make(map[string]string)
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for key, value := range m.Tags {
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tags[key] = value
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}
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acc.AddFields(m.MetricName, fields, tags)
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m.counter++
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return nil
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}
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// Generate random value between min and max, inclusivly
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func (m *Mock) generateRandomFloat64(fields map[string]interface{}) {
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for _, random := range m.Random {
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fields[random.Name] = random.Min + rand.Float64()*(random.Max-random.Min)
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}
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}
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// Create sine waves
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func (m *Mock) generateSineWave(fields map[string]interface{}) {
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for _, field := range m.SineWave {
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fields[field.Name] = math.Sin((float64(m.counter) * field.Period * math.Pi)) * field.Amplitude
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}
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}
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// Begin at start value and then add step value every tick
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func (m *Mock) generateStep(fields map[string]interface{}) {
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for _, step := range m.Step {
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if m.counter == 0 {
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step.latest = step.Start
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} else {
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step.latest += step.Step
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}
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fields[step.Name] = step.latest
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}
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}
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// Begin at start price and then generate random value
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func (m *Mock) generateStockPrice(fields map[string]interface{}) {
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for _, stock := range m.Stock {
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if stock.latest == 0.0 {
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stock.latest = stock.Price
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} else {
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noise := 2 * (rand.Float64() - 0.5)
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stock.latest = stock.latest + (stock.latest * stock.Volatility * noise)
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// avoid going below zero
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if stock.latest < 1.0 {
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stock.latest = 1.0
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}
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}
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fields[stock.Name] = stock.latest
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}
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}
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func init() {
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inputs.Add("mock", func() telegraf.Input {
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return &Mock{}
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})
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}
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@ -0,0 +1,81 @@
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package mock
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import (
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"testing"
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"github.com/influxdata/telegraf/testutil"
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"github.com/stretchr/testify/require"
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)
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func TestGather(t *testing.T) {
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testRandom := &random{
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Name: "random",
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Min: 1.0,
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Max: 6.0,
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}
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testSineWave := &sineWave{
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Name: "sine",
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Amplitude: 1.0,
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Period: 0.5,
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}
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testStep := &step{
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Name: "step",
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Start: 0.0,
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Step: 1.0,
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}
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testStock := &stock{
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Name: "abc",
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Price: 50.00,
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Volatility: 0.2,
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}
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tags := map[string]string{
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"buildling": "tbd",
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"site": "nowhere",
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}
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m := &Mock{
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MetricName: "test",
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Tags: tags,
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Random: []*random{testRandom},
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SineWave: []*sineWave{testSineWave},
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Step: []*step{testStep},
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Stock: []*stock{testStock},
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}
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var acc testutil.Accumulator
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require.NoError(t, m.Gather(&acc))
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require.Len(t, acc.Metrics, 1)
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metric := acc.Metrics[0]
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require.Equal(t, "test", metric.Measurement)
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require.Equal(t, tags, metric.Tags)
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for k, v := range metric.Fields {
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switch k {
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case "abc":
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require.Equal(t, 50.0, v)
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case "random":
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require.GreaterOrEqual(t, 6.0, v)
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require.LessOrEqual(t, 1.0, v)
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case "sine":
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require.Equal(t, 0.0, v)
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case "step":
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require.Equal(t, 0.0, v)
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default:
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require.Failf(t, "unexpected field %q", k)
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}
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}
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}
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func TestGatherEmpty(t *testing.T) {
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m := &Mock{
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MetricName: "test_empty",
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}
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var acc testutil.Accumulator
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require.NoError(t, m.Gather(&acc))
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acc.AssertDoesNotContainMeasurement(t, "test_empty")
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}
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