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0.3.0 • Public • Published

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A modern benchmarking library for Node.js, capable of generating statistically significant results.


npm install --save-dev nodemark


const benchmark = require('nodemark');
const result = benchmark(myFunction, setupFunction);
console.log(result); // => 14,114,886 ops/sec ±0.58% (7906233 samples)
console.log(result.nanoseconds()); // => 71

Statistical Significance

In benchmarking, it's important to generate statistically significant results. Thankfully, nodemark makes this easy:

  • The margin of error is calculated for you.
  • The noise caused by nodemark is factored out of the results.
  • The garbage collector is manipulated to prevent early runs from having an unfair advantage.
  • Executions done before v8 has a chance to optimize things (JIT) are ignored.

The combination of these things makes it a highly accurate measuring device. However, any benchmark done in JavaScript has its limits. If the average time measured by a benchmark is too small to be reliable (< 10ns), the results will be NaN in order to avoid providing misleading information.


benchmark(subject, [setup, [duration]]) -> benchmarkResult

Runs a new benchmark. This measures the performance of the subject function. If a setup function is provided, it will be invoked before every execution of subject.

By default, the benchmark runs for about 3 seconds, but this can be overridden by passing a duration number (in milliseconds). Regardless of the desired duration, the benchmark will not finish until the subject has been run at least 10 times.

Both subject and setup can run asynchronously by declaring a callback argument in their signature. If you do this, you must invoke the callback to indicate that the operation is complete. When running an asyncronous benchmark, this function returns a promise. However, because subject and setup use callbacks rather than promises, synchronous errors will not automatically be caught.

benchmark(callback => fs.readFile('foo.txt', callback))

There is no plan to support promises in subject and setup because it would cause too much overhead and yield inaccurate results.

class BenchmarkResult

Each benchmark returns an immutable object describing the result of that benchmark. It has five properties:

  • mean, the average measured time in nanoseconds
  • error, the margin of error as a ratio of the mean
  • max, the fastest measured time in nanoseconds
  • min, the slowest measured time in nanoseconds
  • count, the number of times the subject was invoked and measured

.nanoseconds([precision]) -> number

Returns this.mean, rounded to the nearest whole number or the number or decimal places specified by precision.

.microseconds([precision]) -> number

Same as .nanoseconds(), but the value is in microseconds.

.milliseconds([precision]) -> number

Same as .nanoseconds(), but the value is in milliseconds.

.seconds([precision]) -> number

Same as .nanoseconds(), but the value is in seconds.

.hz([precision]) -> number

Returns the average number of executions per second, rounded to the nearest whole number or the number of decimal places specified by precision.

.sd([precision]) -> number

Returns the standard deviation in nanoseconds, rounded to the nearest whole number or the number of decimal places specified by precision.

.toString([format]) -> number

Returns a nicely formatted string describing the result of the benchmark. By default, the "hz" format is used, which displays ops/sec, but you can optionally specify "nanoseconds", "microseconds", "milliseconds", or "seconds" to change the displayed information.



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