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This is a port of the Scala Ostrich and Python python-ostrich libraries. This port is currently a work in progress, so only the stuff covered in the unit tests are considered to be completed.


npm install ostrich

var stats = require('ostrich')

Stats API

There are three kinds of statistics that ostrich captures:

  • counters

    A counter is a value that never decreases. Examples might be "widgets_sold" or "births". You just click the counter each time a countable event happens, and graphing utilities usually graph the deltas over time. To increment a counter, use:

      # or
      stats.incr("widgets_sold", 5)
  • gauges

    A gauge is a value that has a discrete value at any given moment, like "heap_used" or "current_temperature". It's usually a measurement that you only need to take when someone asks. To define a gauge, stick this code somewhere in the server initialization:

      stats.gauge("current_temperature", function() { my_thermometer.get_temperature_in_celcius() })

    Gauge methods should always return a number.

  • timings

    A timing is a stopwatch timer around code, like so:

      # you can time how long until a callback fires
 'file', stats.time('file_opening', function(err, fd) {
        // ...
      # you can also time something by creating a timer
      var timer = stats.time('file_opening')'file', function(err, fd) {
        // ...

    Timings are collected in aggregate, and the aggregation is reported through the "stats" command. The aggregation includes the count (number of timings performed), sum, maximum, minimum, average, standard deviation, and sum of squares (useful for aggregating the standard deviation).

Dump stats as JSON

There is a TimingStat.prototype.toJSON function provided to make dumping the stats to JSON easy. There was an attempt to make this format compatible between Scala, Python and Node.js versions.

# Don't reset

# Do reset