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regex capture groups test
(version: 0)
Benchmark.js
Comparing performance of:
A vs B
Created:
3 years ago
by:
Guest
Go to the latest result
Tests:
A
'https://spray.widen.net/content/oqnfu4pcak/web/patterns-other-full-cone-group-660x370.jpeg'.match( /(?<width>[0-9]{2,})x[0-9]{2,}.*\.jpe?g/i)
B
'https://spray.widen.net/content/oqnfu4pcak/web/patterns-other-full-cone-group-660x370.jpeg'.match( /(?<width>[0-9]{2,})x[0-9]{2,}.*\.jp(e)?g/i)
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
A
B
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
one year ago
)
User agent:
Mozilla/5.0 (X11; Linux x86_64; rv:128.0) Gecko/20100101 Firefox/128.0
Browser/OS:
Firefox 128 on Linux
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<iframe src="https://measurethat.net/Embed?id=583171" width="100%" height="500px"></iframe>
A
3.4M/s
B
3.3M/s
View exact numbers
Test name
Executions per second
✓
A
3,436,978 Ops/sec
B
3,267,426 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
**What is tested on the provided JSON?** The provided JSON represents a JavaScript microbenchmark test case, specifically designed to measure the performance of regular expression capture groups. The benchmark is testing two different approaches: 1. Approach A: Using `.*` in the regular expression pattern to match any characters (including newline) before capturing the width and height values. 2. Approach B: Using `.jp(e)?g` in the regular expression pattern to match JPEG files, which will likely be more efficient than the first approach. **Options compared** The two approaches differ in their regular expression patterns: * Approach A uses `.*`, which matches any character (including newline) before capturing the width and height values. * Approach B uses `.jp(e)?g`, which is designed to match JPEG files (.jpg or .jpeg). **Pros and Cons of each approach:** 1. **Approach A (`.match(\r\n /(?<width>[0-9]{2,})x[0-9]{2,}.*\.jpe?g/i)`)**: * Pros: + More flexible, as it can match any URL with width and height values. * Cons: + May be slower due to the more general pattern matching `.*`. 2. **Approach B (`.match(\r\n /(?<width>[0-9]{2,})x[0-9]{2,}.*\.jp(e)?g/i)`)**: * Pros: + More efficient, as it specifically targets JPEG files. * Cons: + Less flexible, as it only matches a specific format. **Library usage** None of the provided benchmarks use any external libraries. **Special JS feature or syntax** The benchmark uses: * **Template literals**: The regular expression patterns are defined using template literals (`\r\n /` ... `i)` to create a multi-line string. * **Regular expressions**: The benchmark uses regular expressions to match URLs and extract values. **Other considerations** * **Image processing**: The benchmark is designed to measure the performance of regular expression capture groups on image URLs, which may involve additional overhead due to image processing. * **Browser differences**: The benchmark results are reported for different browsers (Chrome), devices (Desktop, Mac OS X 10.15.7), and operating systems (Mac OS X 10.15.7). **Alternatives** Other alternatives to this benchmark could include: * Testing regular expression performance on strings or arrays of data. * Comparing the performance of different JavaScript engines (e.g., V8, SpiderMonkey). * Measuring the performance of regular expression libraries or frameworks like RegEx.js or regex-lint.
Related benchmarks
Lazy Quantifier and non capturing group vs Greedy Quantifier with capturing group REGEX B@B
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