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sympact

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XO Code Style used AVA Test Runner used Istanbul Test Coverage used NI Scaffolding System used NP Release System used
Latest version on npm Project license

๐Ÿ”ฅ An easy way to calculate the 'impact' of running a task in Node.JS
Coded with โค๏ธ by Simone Primarosa.

Synopsis

Sympact runs a script and profiles its execution time, CPU usage, and memory usage. Sympact then returns an execution report containing the averages of the results.

Do you believe that this is useful? Has it saved you time? Or maybe you simply like it?
If so, show your appreciation with a Star โญ๏ธ.

How it works

sympact spawns a separate process and runs your script in an isolated node process and then collects statistics about the system's resource used by your script.

The data are collected using pidusage in combination with pidtree.
The main difference between other projects is that sympact will also "profile" processes spawned by your script or by any of its children.

Finally a report of the samples taken is computed and returned to you.

Install

npm install --save sympact

Usage

const impact = require('sympact');

const report = await impact(`
  let r = 2;
  let c = 10e7;
  while (c--) r = Math.pow(r, r);
  return r;
`, {interval: 125}); // 125 ms of sampling rate

console.log(report.times.execution.end - report.times.execution.start);
// => 2700 ms
console.log(report.stats.cpu.mean);
// => 90.45 % on my machine
console.log(report.stats.memory.mean);
// => 27903317.33 bytes on my machine

CLI

sympact CLI

To make it more usable, a CLI is bundled with the package allowing for an aesthetically pleasing report.

  npx sympact "console.log('Hello World')"

You can even require other files.

  npx sympact "
    const {spawn} = require('child_process');
    let childno = 10;
    let childs = [];
    for (let i = 0; i < childno; i++) {
      childs.push(spawn('node', ['-e', 'setInterval(()=>{let c=10e3;while(c--);},10)']));
    }
    let c = 10e6;
    let m = {};
    while (c--)  m[c] = c;
    for (let i = 0; i < childno; i++) {
      childs[i].kill();
    }
  "



Report object

The object returned by the promise will look like this.

{
  "times": {
    "sampling": {
      "start": 1521666020917,          // ms since epoch
      "end": 1521666036041             // ms since epoch
    },
    "execution": {
      "start": 1521666020958,          // ms since epoch
      "end": 1521666036006             // ms since epoch
    }
  },
  "stats": {
    "cpu": {                           // CPU usage statistics (percentage)
      "mean": 74.17368421052636,
      "median": 75.1,
      "stdev": 11.820700343128212,
      "max": 94.7,
      "min": 0.7
    },
    "memory": {                        // RAM usage statistics (bytes)
      "mean": 1080202186.1052632,
      "median": 1327509504,
      "stdev": 416083837.44653314,
      "max": 1327513600,
      "min": 23441408
    }
  },
  "samples": {                         // List of all the samples taken
    "period": 125,                     // Sampling period
    "count": 114,                      // Number of samples taken
    "list": {
      "39": {                          // Taken after 39ms after the start of the watch command
        "cpu": 0.7,                    // Sum of the usages of all the processes
        "memory": 23441408,            // Sum of the memory of all the processes
        "processes": [{                // List of processes profiled in this timeframe
          "cpu": 0.7,
          "memory": 23441408,
          "ppid": 837,
          "pid": 839,
          "ctime": 6000,
          "elapsed": 1000,
          "timestamp": 1521666020955   // ms since epoch
        }]
      },
      "205": {
        "cpu": 14.8,
        "memory": 55685120,
        "processes": [{
          "cpu": 14.8,
          "memory": 55685120,
          "ppid": 837,
          "pid": 839,
          "ctime": 15000,
          "elapsed": 2000,
          "timestamp": 1521666021122
        }]
      },

      [...]

      "15124": {
        "cpu": 81.2,
        "memory": 878133248,
        "processes": [{
          "cpu": 81.2,
          "memory": 878133248,
          "ppid": 837,
          "pid": 839,
          "ctime": 47600,
          "elapsed": 17000,
          "timestamp": 1521666036041
        }]
      }
    }
  }
}

API

sympact(code, [options]) โ‡’ Promise.<Object>

Measures the impact of running a certain script on your system. Monitors the cpu and memory usage of the whole tree of processes generated by the script provided.

Kind: global function
Returns: Promise.<Object> - An object containing the results.
Access: public

Param Type Default Description
code string The source code to test.
[options] Object Optional configurations.
[options.interval] number 125 Sampling interval in milliseconds.
[options.cwd] string "caller path" CWD for the script.

Contributing

Contributions are REALLY welcome and if you find a security flaw in this code, PLEASE report it.
Please check the contributing guidelines for more details. Thanks!

Authors

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the license file for details.

sympact's People

Contributors

danielruf avatar simonepri avatar xjohn600 avatar

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sympact's Issues

Timestamps in nanoseconds

I'm submitting a

  • feature request

Checklist

  • Searched both open and closed issues for duplicates of this issue
  • Title adequately and concisely reflects the feature or the bug

Information

[email protected]

The Problem

Timestamps are in ms (milliseconds). So, under certain circumstances, the difference between end and start is always zero ms. E.g: when profiling code that do not require long times to execute

Suggested solution

I would like to suggest timestamps in ns (nanoseconds). That could be achieved by replacing Date.now() for process.hrtime() in ./lib/profile.js. That would also require parsing the hrtime format with a function like this one:

function parseTime(hrtime) {
  return (hrtime[0] * 1e9) + hrtime[1]
}

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