Gathering detailed insights and metrics for uplot
Gathering detailed insights and metrics for uplot
Gathering detailed insights and metrics for uplot
Gathering detailed insights and metrics for uplot
uplot-react
React wrapper for uPlot that allows you to work with charts declaratively inside your favorite framework
@gravity-ui/yagr
High level wrapper for uPlot
uplot-vue
Vue.js wrapper for uPlot that allows you to work with charts declaratively inside your favorite framework
react-uplot
ReactJS wrapper for the uPlot charting library.
📈 A small, fast chart for time series, lines, areas, ohlc & bars
npm install uplot
Typescript
Module System
Node Version
NPM Version
100
Supply Chain
99.6
Quality
79.4
Maintenance
100
Vulnerability
100
License
Updated on 04 Dec 2024
JavaScript (71.82%)
HTML (27.25%)
CSS (0.93%)
Cumulative downloads
Total Downloads
Last day
21%
Compared to previous day
Last week
-2.4%
Compared to previous week
Last month
10.5%
Compared to previous month
Last year
12.1%
Compared to previous year
2
A small (~45 KB min), fast chart for time series, lines, areas, ohlc & bars (MIT Licensed)
μPlot is a fast, memory-efficient Canvas 2D-based chart for plotting time series, lines, areas, ohlc & bars; from a cold start it can create an interactive chart containing 150,000 data points in 90ms, scaling linearly at ~31,000 pts/ms. In addition to fast initial render, the zooming and cursor performance is by far the best of any similar charting lib; at ~50 KB, it's likely the smallest and fastest time series plotter that doesn't make use of context-limited WebGL shaders or WASM, both of which have much higher startup cost and code size.
However, if you need 60fps performance with massive streaming datasets, uPlot can only get you so far. If you decide to venture into this realm with uPlot, make sure to unclog your rendering pipeline. WebGL should still be the tool of choice for applications like realtime signal or waveform visualizations: See danchitnis/webgl-plot, huww98/TimeChart, epezent/implot, or commercial products like LightningChart®.
In order to stay lean, fast and focused the following features will not be added:
The docs are a perpetual work in progress, it seems. Start with /docs/README.md for a conceptual overview. The full API is further documented via comments in /dist/uPlot.d.ts. Additionally, an ever-expanding collection of runnable /demos covers the vast majority of uPlot's API.
Benchmarks done on this hardware:
Full size: https://leeoniya.github.io/uPlot/demos/multi-bars.html
Raw data: https://github.com/leeoniya/uPlot/blob/master/bench/results.json
| lib | size | done | js,rend,paint,sys | heap peak,final | mousemove (10s) | | ---------------------- | ------- | ------- | ----------------- | --------------- | ------------------- | | uPlot v1.6.24 | 47.9 KB | 34 ms | 51 2 1 34 | 21 MB 3 MB | 218 360 146 196 | | Chart.js v4.2.1 | 254 KB | 38 ms | 90 2 1 40 | 29 MB 10 MB | 1154 46 165 235 | | Flot v3.0.0 | 494 KB | 60 ms | 105 5 1 52 | 41 MB 21 MB | --- | | ECharts v5.4.1 | 1000 KB | 55 ms | 148 3 1 35 | 17 MB 3 MB | 1943 444 203 208 | | dygraphs v2.2.1 | 132 KB | 90 ms | 163 2 1 33 | 88 MB 42 MB | 1438 371 174 268 | | LightningChart® v4.0.2 | 1300 KB | --- ms | 250 2 1 33 | 33 MB 13 MB | 5390 120 128 325 | | CanvasJS v3.7.5 | 489 KB | 130 ms | 266 4 1 35 | 98 MB 69 MB | 1030 445 90 246 | | dvxCharts v5.1.0 | 373 KB | 160 ms | 264 23 1 62 | 100 MB 61 MB | 687 779 206 197 | | Highcharts v10.3.3 | 413 KB | --- ms | 416 7 1 38 | 97 MB 55 MB | 1286 824 205 242 | | Plotly.js v2.18.2 | 3600 KB | 310 ms | 655 14 1 40 | 104 MB 70 MB | 1814 163 25 208 | | ApexCharts v3.37.1 | 503 KB | 685 ms | 694 9 1 33 | 175 MB 46 MB | 1708 421 106 207 | | ZingChart v2.9.10 | 871 KB | 681 ms | 717 7 1 105 | 290 MB 195 MB | 9021 305 41 71 | | amCharts v5.3.7 | 625 KB | --- ms | 1601 3 3 46 | 147 MB 121 MB | 9171 71 460 167 |
size
includes the lib itself plus any dependencies required to render the benchmark, e.g. Moment, jQuery, etc.Some libraries provide their own performance demos:
TODO (all of these use SVG, so performance should be similar to Highcharts):
Your browser's performance is highly dependent on your hardware, operating system, and GPU drivers.
If you're using a Chromium-based browser, there are some hidden settings that can unlock significant performance improvements for Canvas2D rendering. Most of these have to do with where and how the rasterization is performed.
Head over to https://leeoniya.github.io/uPlot/demos/sine-stream.html and open up Chrome's DevTools (F12), then toggle the Performance Monitor.
For me:
If your CPU is close to 100%, it may be rasterizing everything in the same CPU process.
Pop open chrome://gpu
and see what's orange or red.
Then open chrome://flags
and search for "raster" to see what can be force-enabled.
Canvas out-of-process rasterization
resulted in a dramatic framerate improvement.YMMV!
Stable Version
1
8.2/10
Summary
uPlot Prototype Pollution vulnerability
Affected Versions
< 1.6.31
Patched Versions
1.6.31
Reason
10 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
Reason
no binaries found in the repo
Reason
license file detected
Details
Reason
0 existing vulnerabilities detected
Reason
Found 3/30 approved changesets -- score normalized to 1
Reason
no effort to earn an OpenSSF best practices badge detected
Reason
security policy file not detected
Details
Reason
project is not fuzzed
Details
Reason
SAST tool is not run on all commits -- score normalized to 0
Details
Score
Last Scanned on 2024-11-25
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