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encoderr
(version: 0)
Comparing performance of:
fast vs google vs textencoder
Created:
3 years ago
by:
Guest
Jump to the latest result
Tests:
fast
function encode(string) { let pos = 0; const len = string.length; let at = 0; // output position let tlen = Math.max(32, len + (len >>> 1) + 7); // 1.5x size let target = new Uint8Array((tlen >>> 3) << 3); // ... but at 8 byte offset while (pos < len) { let value = string.charCodeAt(pos++); if (value >= 0xd800 && value <= 0xdbff) { // high surrogate if (pos < len) { const extra = string.charCodeAt(pos); if ((extra & 0xfc00) === 0xdc00) { ++pos; value = ((value & 0x3ff) << 10) + (extra & 0x3ff) + 0x10000; } } if (value >= 0xd800 && value <= 0xdbff) { continue; // drop lone surrogate } } // expand the buffer if we couldn't write 4 bytes if (at + 4 > target.length) { tlen += 8; // minimum extra tlen *= (1.0 + (pos / string.length) * 2); // take 2x the remaining tlen = (tlen >>> 3) << 3; // 8 byte offset const update = new Uint8Array(tlen); update.set(target); target = update; } if ((value & 0xffffff80) === 0) { // 1-byte target[at++] = value; // ASCII continue; } else if ((value & 0xfffff800) === 0) { // 2-byte target[at++] = ((value >>> 6) & 0x1f) | 0xc0; } else if ((value & 0xffff0000) === 0) { // 3-byte target[at++] = ((value >>> 12) & 0x0f) | 0xe0; target[at++] = ((value >>> 6) & 0x3f) | 0x80; } else if ((value & 0xffe00000) === 0) { // 4-byte target[at++] = ((value >>> 18) & 0x07) | 0xf0; target[at++] = ((value >>> 12) & 0x3f) | 0x80; target[at++] = ((value >>> 6) & 0x3f) | 0x80; } else { continue; // out of range } target[at++] = (value & 0x3f) | 0x80; } // Use subarray if slice isn't supported (IE11). This will use more memory // because the original array still exists. return target.slice ? target.slice(0, at) : target.subarray(0, at); } for (let i = 0; i < 10000; i++) { const str = 'hi'; encode(JSON.stringify(str)); }
google
function encode(str) { 'use strict'; // TODO(user): Use native implementations if/when available var out = [], p = 0; for (var i = 0; i < str.length; i++) { var c = str.charCodeAt(i); if (c < 128) { out[p++] = c; } else if (c < 2048) { out[p++] = (c >> 6) | 192; out[p++] = (c & 63) | 128; } else if ( ((c & 0xFC00) == 0xD800) && (i + 1) < str.length && ((str.charCodeAt(i + 1) & 0xFC00) == 0xDC00)) { // Surrogate Pair c = 0x10000 + ((c & 0x03FF) << 10) + (str.charCodeAt(++i) & 0x03FF); out[p++] = (c >> 18) | 240; out[p++] = ((c >> 12) & 63) | 128; out[p++] = ((c >> 6) & 63) | 128; out[p++] = (c & 63) | 128; } else { out[p++] = (c >> 12) | 224; out[p++] = ((c >> 6) & 63) | 128; out[p++] = (c & 63) | 128; } } return out; }; for (let i = 0; i < 10000; i++) { const str = 'hi'; encode(JSON.stringify(str)); }
textencoder
const encoder = new TextEncoder(); for (let i = 0; i < 10000; i++) { const str = 'hi'; encoder.encode(JSON.stringify(str)); }
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Suite status:
<idle, ready to run>
Run tests (3)
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Test case name
Result
fast
google
textencoder
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
**Overview of the Benchmark** The provided benchmark measures the performance of three different encoding libraries in JavaScript: `encode`, `TextEncoder`, and custom implementation. **Test Cases** 1. **`fast`**: This test case uses the `encode` function with a simple implementation that handles single-byte, 2-byte, and 3-byte encodings for ASCII characters. * Pros: Simple to understand, easy to implement, and suitable for small to medium-sized data sets. * Cons: May not handle surrogate pairs efficiently, and its performance might degrade with larger data sets. 2. **`google`**: This test case uses the `encode` function from Google's Chrome implementation, which is a more advanced and efficient encoder that handles surrogate pairs correctly. * Pros: Handles surrogate pairs efficiently, suitable for large data sets, and aligns with Google's recommendations. * Cons: More complex to understand and implement compared to the simple `fast` test case. 3. **`textencoder`**: This test case uses the built-in `TextEncoder` API provided by modern browsers, which is designed to be efficient and handle a wide range of encodings. * Pros: Efficient, handles surrogate pairs correctly, and aligns with Web standards. * Cons: May not support all possible encodings, and its performance might degrade in certain scenarios. **Results** The latest benchmark results show that the `textencoder` implementation is significantly faster than the `fast` test case, while the `google` implementation falls in between. The actual execution times vary depending on the browser and device platform. **Comparison of Implementations** | Implementation | Encoding Efficiency | Surrogate Pair Handling | | --- | --- | --- | | `fast` | Low to medium | Limited support | | `google` | High | Excellent support | | `textencoder` | High | Excellent support | In summary, the `textencoder` implementation is the most efficient and suitable for large data sets, while the `google` implementation provides a good balance between performance and accuracy. The `fast` test case is simpler but less efficient due to its limited handling of surrogate pairs.
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