What is the correct way to implement a Peak Meter like those in Logic Pro with the Web Audio API AnalyserNode?
I know AnalyserNode.getFloatFrequencyData() returns decibel values, but how do you combine those values to get the one to be displayed in the meter? Do you just take the maximum value like in the following code sample (where analyserData comes from getFloatFrequencyData():
let peak = -Infinity;
for (let i = 0; i < analyserData.length; i++) {
const x = analyserData[i];
if (x > peak) {
peak = x;
}
}
Inspecting some output from just taking the max makes it look like this is not the correct approach. Am I wrong?
Alternatively, would it be a better idea to use a ScriptProcessorNode instead? How would that approach differ?
If you take the maximum of getFloatFrequencyData()'s results in one frame, then what you are measuring is the audio power at a single frequency (whichever one has the most power). What you actually want to measure is the peak at any frequency — in other words, you want to not use the frequency data, but the unprocessed samples not separated into frequency bins.
The catch is that you'll have to compute the decibels power yourself. This is fairly simple arithmetic: you take some number of samples (one or more), square them, and average them. Note that even a “peak” meter may be doing averaging — just on a much shorter time scale.
Here's a complete example. (Warning: produces sound.)
document.getElementById('start').addEventListener('click', () => {
const context = new(window.AudioContext || window.webkitAudioContext)();
const oscillator = context.createOscillator();
oscillator.type = 'square';
oscillator.frequency.value = 440;
oscillator.start();
const gain1 = context.createGain();
const analyser = context.createAnalyser();
// Reduce output level to not hurt your ears.
const gain2 = context.createGain();
gain2.gain.value = 0.01;
oscillator.connect(gain1);
gain1.connect(analyser);
analyser.connect(gain2);
gain2.connect(context.destination);
function displayNumber(id, value) {
const meter = document.getElementById(id + '-level');
const text = document.getElementById(id + '-level-text');
text.textContent = value.toFixed(2);
meter.value = isFinite(value) ? value : meter.min;
}
// Time domain samples are always provided with the count of
// fftSize even though there is no FFT involved.
// (Note that fftSize can only have particular values, not an
// arbitrary integer.)
analyser.fftSize = 2048;
const sampleBuffer = new Float32Array(analyser.fftSize);
function loop() {
// Vary power of input to analyser. Linear in amplitude, so
// nonlinear in dB power.
gain1.gain.value = 0.5 * (1 + Math.sin(Date.now() / 4e2));
analyser.getFloatTimeDomainData(sampleBuffer);
// Compute average power over the interval.
let sumOfSquares = 0;
for (let i = 0; i < sampleBuffer.length; i++) {
sumOfSquares += sampleBuffer[i] ** 2;
}
const avgPowerDecibels = 10 * Math.log10(sumOfSquares / sampleBuffer.length);
// Compute peak instantaneous power over the interval.
let peakInstantaneousPower = 0;
for (let i = 0; i < sampleBuffer.length; i++) {
const power = sampleBuffer[i] ** 2;
peakInstantaneousPower = Math.max(power, peakInstantaneousPower);
}
const peakInstantaneousPowerDecibels = 10 * Math.log10(peakInstantaneousPower);
// Note that you should then add or subtract as appropriate to
// get the _reference level_ suitable for your application.
// Display value.
displayNumber('avg', avgPowerDecibels);
displayNumber('inst', peakInstantaneousPowerDecibels);
requestAnimationFrame(loop);
}
loop();
});
<button id="start">Start</button>
<p>
Short average
<meter id="avg-level" min="-100" max="10" value="-100"></meter>
<span id="avg-level-text">—</span> dB
</p>
<p>
Instantaneous
<meter id="inst-level" min="-100" max="10" value="-100"></meter>
<span id="inst-level-text">—</span> dB
</p>
Do you just take the maximum value
For a peak meter, yes. For a VU meter, there's all sorts of considerations in measuring the power, as well as the ballistics of an analog meter. There's also RMS power metering.
In digital land, you'll find a peak meter to be most useful for many tasks, and by far the easiest to compute.
A peak for any given set of samples is the highest absolute value in the set. First though, you need that set of samples. If you call getFloatFrequencyData(), you're not getting sample values, you're getting the spectrum. What you want instead is getFloatTimeDomainData(). This data is a low resolution representation of the samples. That is, you might have 4096 samples in your window, but your analyser might be configured with 256 buckets... so those 4096 samples will be resampled down to 256 samples. This is generally acceptable for a metering task.
From there, it's just Math.max(-Math.min(samples), Math.max(samples)) to get the max of the absolute value.
Suppose you wanted a higher resolution peak meter. For that, you need all the raw samples you can get. That's where a ScriptProcessorNode comes in handy. You get access to the actual sample data.
Basically, for this task, AnalyserNode is much faster, but slightly lower resolution. ScriptProcessorNode is much slower, but slightly higher resolution.
Related
I have a small app that accepts incoming audio stream from the internet and I'm trying to find the frequency of a tone or continuous beep. At the time of the tone / beep it is the only thing that would be playing. The rest of the audio is either silence or talking. I'm using the node-pitchfinder npm module to find the tone and when I use a sample audio clip I made of 2,000Hz the app prints out the frequency within one or two Hz. When I pull the audio stream online I keep getting results like 17,000 Hz. My guess is that there is some "noise" in the audio signal and that's what the node-pitchfinder module is picking up.
Is there any way I can filter out that noise in real time to get an accurate frequency?
The streaming audio file is: http://relay.broadcastify.com/fq85hty701gnm4z.mp3
Code below:
const fs = require('fs');
const fsa = require('fs-extra');
const Lame = require('lame');
const Speaker = require('speaker');
const Volume = require('pcm-volume');
const Analyser = require('audio-analyser')
const request = require('request')
const Chunker = require('stream-chunker');
const { YIN } = require('node-pitchfinder')
const detectPitch = YIN({ sampleRate: 44100})
//const BUFSIZE = 64;
const BUFSIZE = 500;
var decoder = new Lame.Decoder();
decoder.on('format', function(format){onFormat(format)});
var chunker = Chunker(BUFSIZE);
chunker.pipe(decoder);
var options = {
url: 'http://relay.broadcastify.com/fq85hty701gnm4z.mp3',
headers: {
"Upgrade-Insecure-Requests": 1,
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/12.0 Safari/605.1.15"
}
}
var audio_stream = request(options);
//var audio_stream = fs.createReadStream('./2000.mp3');
audio_stream.pipe(chunker);
function onFormat(format)
{
//if (volume == "undefined")
volume = 1.0;
vol = new Volume(volume);
speaker = new Speaker(format);
analyser = createAnalyser(format);
analyser.on('data', sample);
console.log(format);
vol.pipe(speaker);
vol.pipe(analyser);
decoder.pipe(vol);
vol.setVolume(volume);
}
function createAnalyser(format)
{
return new Analyser({
fftSize: 8,
bufferSize: BUFSIZE,
'pcm-stream': {
channels: format.channels,
sampleRate: format.sampleRate,
bitDepth: format.bitDepth
}
});
}
var logFile = 'log.txt';
var logOptions = {flag: 'a'};
function sample()
{
if (analyser) {
const frequency = detectPitch(analyser._data)
console.log(frequency)
}
}
My goal is to find the most dominant audio frequency in a chunk of data so I can figure out the tone.
I found some code that supposedly does this with python
def getFreq( pkt ):
#Use FFT to determine the peak frequency of the last chunk
thefreq = 0
if len(pkt) == bufferSize*swidth:
indata = np.array(wave.struct.unpack("%dh"%(len(pkt)/swidth), pkt))*window
# filter out everything outside of our bandpass Hz
bp = np.fft.rfft(indata)
minFilterBin = (bandPass[0]/(sampleRate/bufferSize)) + 1
maxFilterBin = (bandPass[1]/(sampleRate/bufferSize)) - 1
for i in range(len(bp)):
if i < minFilterBin:
bp[i] = 0
if i > maxFilterBin:
bp[i] = 0
# Take the fft and square each value
fftData = abs(bp)**2
# find the maximum
which = fftData[1:].argmax() + 1
# Compute the magnitude of the sample we found
dB = 10*np.log10(1e-20+abs(bp[which]))
#avgdB = 10*np.log10(1e-20+abs(bp[which - 10:which + 10].mean()))
if dB >= minDbLevel:
# use quadratic interpolation around the max
if which != len(fftData)-1:
warnings.simplefilter("error")
try:
y0, y1, y2 = np.log(fftData[which-1:which+2:])
x1 = (y2 - y0) * .5 / (2 * y1 - y2 - y0)
except RuntimeWarning:
return(-1)
# find the frequency and output it
warnings.simplefilter("always")
thefreq = (which + x1) * sampleRate/bufferSize
else:
thefreq = which * sampleRate/bufferSize
else:
thefreq = -1
return(thefreq)
Original answer:
I can not provide you with a solution but (hopefully) give you enough advice to solve the problem.
I would recommend that you save a part of the stream you want to analyze to a file and then take a look at the file with a spectrum analyzer (e.g. with Audacity). This allows you to determine if the 17kHz signal is present in the audio stream.
If the 17 kHz signal is present in the audio stream then you can filter the audio stream with a low pass filter (e.g. audio-biquad with type lowpass and frequency at somewhere above 2 kHz).
If the 17 kHz signal is not present in the audio then you could try to increase the buffer size BUFSIZE (currently set to 500 in your code). In the example on node-pitchfinder's GitHub page they use a complete audio file for pitch detection. Depending on how the pitch detection algorithm is implemented the result might be different for larger chunks of audio data (i.e. a few seconds) compared to very short chunks (500 samples is around 11 ms at sample rate 44100). Start with a large value for BUFSIZE (e.g. 44100 -> 1 second) and see if it makes a difference.
Explanation of the python code: The code uses FFT (fast fourier transform) to find out which frequencies are present in the audio signal and then searches for the frequency with the highest value. This usually works well for simple signals like a 2 kHz sine wave. You could use dsp.js which provides an FFT implementation if you want to implement it in javascript. However, it is quite a challenge to get this right without some knowledge of digital signal processing theory.
As a side note: the YIN algorithm does not use FFT, it is based on autocorrelation.
Update
The following script uses the fft data of audio-analyser and searches for the maximum frequency. This approach is very basic and only works well for signals where just one frequency is very dominant. The YIN algorithm is much better suited for pitch detection than this example.
const fs = require('fs');
const Lame = require('lame');
const Analyser = require('audio-analyser')
const Chunker = require('stream-chunker');
var analyser;
var fftSize = 4096;
var decoder = new Lame.Decoder();
decoder.on('format', format => {
analyser = createAnalyser(format);
decoder.pipe(analyser);
analyser.on('data', processSamples);
console.log(format);
});
var chunker = Chunker(fftSize);
var audio_stream = fs.createReadStream('./sine.mp3');
audio_stream.pipe(chunker);
chunker.pipe(decoder);
function createAnalyser(format) {
return new Analyser({
fftSize: fftSize,
frequencyBinCount: fftSize / 2,
sampleRate: format.sampleRate,
channels: format.channels,
bitDepth: format.bitDepth
});
}
function processSamples() {
if (analyser) {
var fftData = new Uint8Array(analyser.frequencyBinCount);
analyser.getByteFrequencyData(fftData);
var maxBin = fftData.indexOf(Math.max(...fftData));
var thefreq = maxBin * analyser.sampleRate / analyser.fftSize;
console.log(maxBin + " " + thefreq);
}
}
Given a plain web video of say 30s:
<video src="my-video.mp4"></video>
How could I generate its volume level chart?
volume|
level| ******
| * * **
| * * * **
|** * *** *
| ** * * * *
+---------------*-*-----************------+--- time
0 30s
video is and quiet
loud here here
Note:
Plain JavaScript, please. No libraries.
There are several ways to do this depending on what the usage is.
For accuracy you could measure in conventional volumes and units such as RMS, LUFS/LKFS (K-weighted, loudness), dBFS (full-scale dB) and so forth.
The simple naive approach is to just plot the peaks of the waveform. You would be interested in the positive values only. To just get the peaks you would detect direction between two points and log the first point when the direction changes from upward to downwards (p0 > p1).
For all approaches you can finally apply some form of smoothing such as weighted moving average (example) or a generic smoothing algorithm to remove small peaks and changes, in case of RMS, dB etc. you would use a window size which can be combined with bin-smoothing (an average per segment).
To plot you will obtain the value for the current sample, assume it to be normalized and draw it as line or point to canvas scaled by plot area height.
Mini-discussion as to loading the source data
To address some of the questions in the comments; these are just off the top of my heads to give some pointers -
Since Web Audio API cannot do streaming on its own you have to load the entire file into memory and decode the audio track into a buffer.
Pros: works (analysis part), fast analysis when data is eventually ready, works fine for smaller files, if cached the URL can be used without re-downloading
Cons: long initial load time/bad UX, possible memory hog/not good for large files, audio is "detached" from video sync-wise, forces reuse of URL*, if large and/or cache is not in place the file will have to be downloaded again/streamed, currently causes issues in some browsers/versions (see example below).
*: There is always the option of storing the downloaded video as blob in IndexedDB (with its implications) and use an Object-URL with that blob to stream in the video element (may require MSE to work properly, haven't tried myself).
Plotting while streaming:
Pros: Cheap on memory/resources
Cons: the plot cannot be shown in full until the entire file has been played through, the user may skip/jump parts, may not finish
Side-loading a low-quality mono audio-only file:
Pros: audio can be loaded into memory independent of video file, results in good enough approximation for level use
Cons: can delay initial loading of video, may not be ready in time before video starts, will require additional processing in advance
Server-side plotting:
Pros: can be plotted when uploaded, can store raw plot data that is provided as meta-data when video is requested, low bandwidth, data ready when video starts (assuming data is representing averages over time-segments).
Cons: require infrastructure on server that can separate, analyze and produce the plot-data, depending on how the data is stored may require database modification.
I've might left out or missed some points, but it should give the general idea...
Example
This example measures conventional dB of a given window size per sample. The bigger the window size the smoother the result, but will also take more time to calculate.
Note that for simplicity in this example pixel position determines the dB window range. This may produce uneven gaps/overlaps depending on buffer size affecting the current sample value, but should work for the purpose demonstrated here. Also for simplicity I am scaling the dB reading by dividing it by 40, a somewhat arbitrary number here (ABS is just for the plotting and the way my brain worked (?) in the late night/early morning when I made this :) ).
I added bin/segment-smoothing in red on top to better show longer-term audio variations relevant to things such as auto-leveling.
I'm using a audio source here but you can plug in a video source instead as long as it contains an audio track format that can be decoded (aac, mp3, ogg etc.).
Besides from that, the example is just that, an example. It's not production code so take it for what it is worth. Make adjustments as needed.
(for some reason the audio won't play in Firefox v58beta, it will plot though. Audio plays in Chrome, FF58dev).
var ctx = c.getContext("2d"), ref, audio;
var actx = new (AudioContext || webkitAudioContext)();
var url = "//dl.dropboxusercontent.com/s/a6s1qq4lnwj46uj/testaudiobyk3n_lo.mp3";
ctx.font = "20px sans-serif";
ctx.fillText("Loading and processing...", 10, 50);
ctx.fillStyle = "#001730";
// Load audio
fetch(url, {mode: "cors"})
.then(function(resp) {return resp.arrayBuffer()})
.then(actx.decodeAudioData.bind(actx))
.then(function(buffer) {
// Get data from channel 0 (you will want to measure all/avg.)
var channel = buffer.getChannelData(0);
// dB per window + Plot
var points = [0];
ctx.clearRect(0, 0, c.width, c.height);
ctx.moveTo(x, c.height);
for(var x = 1, i, v; x < c.width; x++) {
i = ((x / c.width) * channel.length)|0; // get index in buffer based on x
v = Math.abs(dB(channel, i, 8820)) / 40; // 200ms window, normalize
ctx.lineTo(x, c.height * v);
points.push(v);
}
ctx.fill();
// smooth using bins
var bins = 40; // segments
var range = (c.width / bins)|0;
var sum;
ctx.beginPath();
ctx.moveTo(0,c.height);
for(x = 0, v; x < points.length; x++) {
for(v = 0, i = 0; i < range; i++) {
v += points[x++];
}
sum = v / range;
ctx.lineTo(x - (range>>1), sum * c.height); //-r/2 to compensate visually
}
ctx.lineWidth = 2;
ctx.strokeStyle = "#c00";
ctx.stroke();
// for audio / progressbar only
c.style.backgroundImage = "url(" + c.toDataURL() + ")";
c.width = c.width;
ctx.fillStyle = "#c00";
audio = document.querySelector("audio");
audio.onplay = start;
audio.onended = stop;
audio.style.display = "block";
});
// calculates RMS per window and returns dB
function dB(buffer, pos, winSize) {
for(var rms, sum = 0, v, i = pos - winSize; i <= pos; i++) {
v = i < 0 ? 0 : buffer[i];
sum += v * v;
}
rms = Math.sqrt(sum / winSize); // corrected!
return 20 * Math.log10(rms);
}
// for progress bar (audio)
function start() {if (!ref) ref = requestAnimationFrame(progress)}
function stop() {cancelAnimationFrame(ref);ref=null}
function progress() {
var x = audio.currentTime / audio.duration * c.width;
ctx.clearRect(0,0,c.width,c.height);
ctx.fillRect(x-1,0,2,c.height);
ref = requestAnimationFrame(progress)
}
body {background:#536375}
#c {border:1px solid;background:#7b8ca0}
<canvas id=c width=640 height=300></canvas><br>
<audio style="display:none" src="//dl.dropboxusercontent.com/s/a6s1qq4lnwj46uj/testaudiobyk3n_lo.mp3" controls></audio>
I want to use a Web Audio bandpass filter to emphasise the frequencies from 300Hz to 3kHz.
However the bandpass filter in the Web Audio API has only one frequency value (representing the center) and one Q value (representing octaves?).
How to set them correctly to represent my to and from frequeuncy range?
var from = 300;
var to = 30000;
var geometricMean = Math.sqrt(from * to);
var filter = audioContext.createBiquadFilter();
filter.type = 'bandpass';
filter.frequency.value = geometricMean;
filter.Q.value = geometricMean / (to - from);
It seems like the frequency is the geometric mean of the from and to value. With this value as center frequency I am now able to calculate the Q value.
On my webpage, I have an audio file inside of an tag.
<!DOCTYPE html>
<html>
<audio src="myTrack.mp3" controls preload="auto"></audio>
</html>
I want to chop up this file stored in an tag into multiple 10 second audio files that I could then insert into the webpage as their own audio files in seperate <audio> tags.
Is it possible to do this in javascript?
Yes, of course this is possible! :)
Make sure the audio fulfill CORS-requirements so we can load it with AJAX (loading from same origin as the page will of course fulfill this).
Load the file as ArrayBuffer and decode it with AudioContext
Calculate the number of segments and length of each (I use a time based length independent of channels below)
Split the main buffer into smaller buffers
Create a file-wrapper for the new buffer (below I made a simple WAVE wrapper for the demo)
Feed that as Blob via an Object-URL to a new instance of the Audio element
Keep keep track of the object-URLs so you can free them up when not needed anymore (revokeObjectURL()).
One drawback is of course that you would have to load the entire file into memory before processing it.
Example
Hopefully the file I'm using for the demo will be available through the current CDN that is used to allow CORS usage (I own the copyright, feel free to use it for testing, but only testing!! :) ). The loading and decoding can take some time depending on your system and connection, so please be patient...
Ideally you should use an asynchronous approach splitting the buffers, but the demo targets only the needed steps to make the buffer segments available as new file fragments.
Also note that I did not take into consideration the last segment to be shorter than the others (I use floor, you should use ceil for the segment count and cut the last block length short). I'll leave that as an exercise for the reader...
var actx = new(AudioContext || webkitAudioContext)(),
url = "//dl.dropboxusercontent.com/s/7ttdz6xsoaqbzdl/war_demo.mp3";
// STEP 1: Load audio file using AJAX ----------------------------------
fetch(url).then(function(resp) {return resp.arrayBuffer()}).then(decode);
// STEP 2: Decode the audio file ---------------------------------------
function decode(buffer) {
actx.decodeAudioData(buffer, split);
}
// STEP 3: Split the buffer --------------------------------------------
function split(abuffer) {
// calc number of segments and segment length
var channels = abuffer.numberOfChannels,
duration = abuffer.duration,
rate = abuffer.sampleRate,
segmentLen = 10,
count = Math.floor(duration / segmentLen),
offset = 0,
block = 10 * rate;
while(count--) {
var url = URL.createObjectURL(bufferToWave(abuffer, offset, block));
var audio = new Audio(url);
audio.controls = true;
audio.volume = 0.75;
document.body.appendChild(audio);
offset += block;
}
}
// Convert a audio-buffer segment to a Blob using WAVE representation
function bufferToWave(abuffer, offset, len) {
var numOfChan = abuffer.numberOfChannels,
length = len * numOfChan * 2 + 44,
buffer = new ArrayBuffer(length),
view = new DataView(buffer),
channels = [], i, sample,
pos = 0;
// write WAVE header
setUint32(0x46464952); // "RIFF"
setUint32(length - 8); // file length - 8
setUint32(0x45564157); // "WAVE"
setUint32(0x20746d66); // "fmt " chunk
setUint32(16); // length = 16
setUint16(1); // PCM (uncompressed)
setUint16(numOfChan);
setUint32(abuffer.sampleRate);
setUint32(abuffer.sampleRate * 2 * numOfChan); // avg. bytes/sec
setUint16(numOfChan * 2); // block-align
setUint16(16); // 16-bit (hardcoded in this demo)
setUint32(0x61746164); // "data" - chunk
setUint32(length - pos - 4); // chunk length
// write interleaved data
for(i = 0; i < abuffer.numberOfChannels; i++)
channels.push(abuffer.getChannelData(i));
while(pos < length) {
for(i = 0; i < numOfChan; i++) { // interleave channels
sample = Math.max(-1, Math.min(1, channels[i][offset])); // clamp
sample = (0.5 + sample < 0 ? sample * 32768 : sample * 32767)|0; // scale to 16-bit signed int
view.setInt16(pos, sample, true); // update data chunk
pos += 2;
}
offset++ // next source sample
}
// create Blob
return new Blob([buffer], {type: "audio/wav"});
function setUint16(data) {
view.setUint16(pos, data, true);
pos += 2;
}
function setUint32(data) {
view.setUint32(pos, data, true);
pos += 4;
}
}
audio {display:block;margin-bottom:1px}
Since localStorage (currently) only supports strings as values, and in order to do that the objects need to be stringified (stored as JSON-string) before they can be stored, is there a defined limitation regarding the length of the values.
Does anyone know if there is a definition which applies to all browsers?
Quoting from the Wikipedia article on Web Storage:
Web storage can be viewed simplistically as an improvement on cookies, providing much greater storage capacity (10 MB per origin in Google Chrome(https://plus.google.com/u/0/+FrancoisBeaufort/posts/S5Q9HqDB8bh), Mozilla Firefox, and Opera; 10 MB per storage area in Internet Explorer) and better programmatic interfaces.
And also quoting from a John Resig article [posted January 2007]:
Storage Space
It is implied that, with DOM Storage,
you have considerably more storage
space than the typical user agent
limitations imposed upon Cookies.
However, the amount that is provided
is not defined in the specification,
nor is it meaningfully broadcast by
the user agent.
If you look at the Mozilla source code
we can see that 5120KB is the default
storage size for an entire domain.
This gives you considerably more space
to work with than a typical 2KB
cookie.
However, the size of this storage area
can be customized by the user (so a
5MB storage area is not guaranteed,
nor is it implied) and the user agent
(Opera, for example, may only provide
3MB - but only time will tell.)
Actually Opera doesn't have 5MB limit. It offers to increase limit as applications requires more. User can even choose "Unlimited storage" for a domain.
You can easily test localStorage limits/quota yourself.
Here's a straightforward script for finding out the limit:
if (localStorage && !localStorage.getItem('size')) {
var i = 0;
try {
// Test up to 10 MB
for (i = 250; i <= 10000; i += 250) {
localStorage.setItem('test', new Array((i * 1024) + 1).join('a'));
}
} catch (e) {
localStorage.removeItem('test');
localStorage.setItem('size', i - 250);
}
}
Here's the gist, JSFiddle and blog post.
The script will test setting increasingly larger strings of text until the browser throws and exception. At that point it’ll clear out the test data and set a size key in localStorage storing the size in kilobytes.
Find the maximum length of a single string that can be stored in localStorage
This snippet will find the maximum length of a String that can be stored in localStorage per domain.
//Clear localStorage
for (var item in localStorage) delete localStorage[item];
window.result = window.result || document.getElementById('result');
result.textContent = 'Test running…';
//Start test
//Defer running so DOM can be updated with "test running" message
setTimeout(function () {
//Variables
var low = 0,
high = 2e9,
half;
//Two billion may be a little low as a starting point, so increase if necessary
while (canStore(high)) high *= 2;
//Keep refining until low and high are equal
while (low !== high) {
half = Math.floor((high - low) / 2 + low);
//Check if we can't scale down any further
if (low === half || high === half) {
console.info(low, high, half);
//Set low to the maximum possible amount that can be stored
low = canStore(high) ? high : low;
high = low;
break;
}
//Check if the maximum storage is no higher than half
if (storageMaxBetween(low, half)) {
high = half;
//The only other possibility is that it's higher than half but not higher than "high"
} else {
low = half + 1;
}
}
//Show the result we found!
result.innerHTML = 'The maximum length of a string that can be stored in localStorage is <strong>' + low + '</strong> characters.';
//Functions
function canStore(strLen) {
try {
delete localStorage.foo;
localStorage.foo = Array(strLen + 1).join('A');
return true;
} catch (ex) {
return false;
}
}
function storageMaxBetween(low, high) {
return canStore(low) && !canStore(high);
}
}, 0);
<h1>LocalStorage single value max length test</h1>
<div id='result'>Please enable JavaScript</div>
Note that the length of a string is limited in JavaScript; if you want to view the maximum amount of data that can be stored in localStorage when not limited to a single string, you can use the code in this answer.
Edit: Stack Snippets don't support localStorage, so here is a link to JSFiddle.
Results
Chrome (45.0.2454.101): 5242878 characters
Firefox (40.0.1): 5242883 characters
Internet Explorer (11.0.9600.18036): 16386 122066 122070 characters
I get different results on each run in Internet Explorer.
Don't assume 5MB is available - localStorage capacity varies by browser, with 2.5MB, 5MB and unlimited being the most common values.
Source: http://dev-test.nemikor.com/web-storage/support-test/
I wrote this simple code that is testing localStorage size in bytes.
https://github.com/gkucmierz/Test-of-localStorage-limits-quota
const check = bytes => {
try {
localStorage.clear();
localStorage.setItem('a', '0'.repeat(bytes));
localStorage.clear();
return true;
} catch(e) {
localStorage.clear();
return false;
}
};
Github pages:
https://gkucmierz.github.io/Test-of-localStorage-limits-quota/
I have the same results on desktop Google chrome, opera, firefox, brave and mobile chrome which is ~10Mbytes
And half smaller result in safari ~4Mbytes
You don't want to stringify large objects into a single localStorage entry. That would be very inefficient - the whole thing would have to be parsed and re-encoded every time some slight detail changes. Also, JSON can't handle multiple cross references within an object structure and wipes out a lot of details, e.g. the constructor, non-numerical properties of arrays, what's in a sparse entry, etc.
Instead, you can use Rhaboo. It stores large objects using lots of localStorage entries so you can make small changes quickly. The restored objects are much more accurate copies of the saved ones and the API is incredibly simple. E.g.:
var store = Rhaboo.persistent('Some name');
store.write('count', store.count ? store.count+1 : 1);
store.write('somethingfancy', {
one: ['man', 'went'],
2: 'mow',
went: [ 2, { mow: ['a', 'meadow' ] }, {} ]
});
store.somethingfancy.went[1].mow.write(1, 'lawn');
BTW, I wrote it.
I've condensed a binary test into this function that I use:
function getStorageTotalSize(upperLimit/*in bytes*/) {
var store = localStorage, testkey = "$_test"; // (NOTE: Test key is part of the storage!!! It should also be an even number of characters)
var test = function (_size) { try { store.removeItem(testkey); store.setItem(testkey, new Array(_size + 1).join('0')); } catch (_ex) { return false; } return true; }
var backup = {};
for (var i = 0, n = store.length; i < n; ++i) backup[store.key(i)] = store.getItem(store.key(i));
store.clear(); // (you could iterate over the items and backup first then restore later)
var low = 0, high = 1, _upperLimit = (upperLimit || 1024 * 1024 * 1024) / 2, upperTest = true;
while ((upperTest = test(high)) && high < _upperLimit) { low = high; high *= 2; }
if (!upperTest) {
var half = ~~((high - low + 1) / 2); // (~~ is a faster Math.floor())
high -= half;
while (half > 0) high += (half = ~~(half / 2)) * (test(high) ? 1 : -1);
high = testkey.length + high;
}
if (high > _upperLimit) high = _upperLimit;
store.removeItem(testkey);
for (var p in backup) store.setItem(p, backup[p]);
return high * 2; // (*2 because of Unicode storage)
}
It also backs up the contents before testing, then restores them.
How it works: It doubles the size until the limit is reached or the test fails. It then stores half the distance between low and high and subtracts/adds a half of the half each time (subtract on failure and add on success); honing into the proper value.
upperLimit is 1GB by default, and just limits how far upwards to scan exponentially before starting the binary search. I doubt this will even need to be changed, but I'm always thinking ahead. ;)
On Chrome:
> getStorageTotalSize();
> 10485762
> 10485762/2
> 5242881
> localStorage.setItem("a", new Array(5242880).join("0")) // works
> localStorage.setItem("a", new Array(5242881).join("0")) // fails ('a' takes one spot [2 bytes])
IE11, Edge, and FireFox also report the same max size (10485762 bytes).
You can use the following code in modern browsers to efficiently check the storage quota (total & used) in real-time:
if ('storage' in navigator && 'estimate' in navigator.storage) {
navigator.storage.estimate()
.then(estimate => {
console.log("Usage (in Bytes): ", estimate.usage,
", Total Quota (in Bytes): ", estimate.quota);
});
}
I'm doing the following:
getLocalStorageSizeLimit = function () {
var maxLength = Math.pow(2,24);
var preLength = 0;
var hugeString = "0";
var testString;
var keyName = "testingLengthKey";
//2^24 = 16777216 should be enough to all browsers
testString = (new Array(Math.pow(2, 24))).join("X");
while (maxLength !== preLength) {
try {
localStorage.setItem(keyName, testString);
preLength = testString.length;
maxLength = Math.ceil(preLength + ((hugeString.length - preLength) / 2));
testString = hugeString.substr(0, maxLength);
} catch (e) {
hugeString = testString;
maxLength = Math.floor(testString.length - (testString.length - preLength) / 2);
testString = hugeString.substr(0, maxLength);
}
}
localStorage.removeItem(keyName);
// Original used this.storageObject in place of localStorage. I can only guess the goal is to check the size of the localStorage with everything but the testString given that maxLength is then added.
maxLength = JSON.stringify(localStorage).length + maxLength + keyName.length - 2;
return maxLength;
};
I really like cdmckay's answer, but it does not really look good to check the size in a real time: it is just too slow (2 seconds for me). This is the improved version, which is way faster and more exact, also with an option to choose how big the error can be (default 250,000, the smaller error is - the longer the calculation is):
function getLocalStorageMaxSize(error) {
if (localStorage) {
var max = 10 * 1024 * 1024,
i = 64,
string1024 = '',
string = '',
// generate a random key
testKey = 'size-test-' + Math.random().toString(),
minimalFound = 0,
error = error || 25e4;
// fill a string with 1024 symbols / bytes
while (i--) string1024 += 1e16;
i = max / 1024;
// fill a string with 'max' amount of symbols / bytes
while (i--) string += string1024;
i = max;
// binary search implementation
while (i > 1) {
try {
localStorage.setItem(testKey, string.substr(0, i));
localStorage.removeItem(testKey);
if (minimalFound < i - error) {
minimalFound = i;
i = i * 1.5;
}
else break;
} catch (e) {
localStorage.removeItem(testKey);
i = minimalFound + (i - minimalFound) / 2;
}
}
return minimalFound;
}
}
To test:
console.log(getLocalStorageMaxSize()); // takes .3s
console.log(getLocalStorageMaxSize(.1)); // takes 2s, but way more exact
This works dramatically faster for the standard error; also it can be much more exact when necessary.
Once I developed Chrome (desktop browser) extension and tested Local Storage real max size for this reason.
My results:
Ubuntu 18.04.1 LTS (64-bit)
Chrome 71.0.3578.98 (Official Build) (64-bit)
Local Storage content size 10240 KB (10 MB)
More than 10240 KB usage returned me the error:
Uncaught DOMException: Failed to execute 'setItem' on 'Storage': Setting the value of 'notes' exceeded the quota.
Edit on Oct 23, 2020
For a Chrome extensions available chrome.storage API. If you declare the "storage" permission in manifest.js:
{
"name": "My extension",
...
"permissions": ["storage"],
...
}
You can access it like this:
chrome.storage.local.QUOTA_BYTES // 5242880 (in bytes)