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normalize vs simple regex
(version: 0)
Comparing performance of:
normalize vs regex
Created:
3 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
var a = 'éöîù ff yolo'
Tests:
normalize
var b = a b.normalize('NFD').replace(/\p{Diacritic}/gu, '')
regex
var b = a b.replace(/[^a-zA-Z0-9 -]/g, '')
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
normalize
regex
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the benchmark definition and test cases to understand what is being tested. **Benchmark Definition** The benchmark definition specifies two different approaches for normalizing a string: 1. **Normalization**: The `normalize('NFD')` method is used to decompose the string into its base characters and diacritical marks, which are then separated from the base character. 2. **Simple Regex**: A regular expression (`/[^a-zA-Z0-9 -]/g`) is used to remove any non-alphanumeric characters (except spaces) from the string. **Options Compared** The benchmark compares the performance of these two approaches: * **Normalization**: This method can be slower since it involves a more complex algorithm to decompose the characters. * **Simple Regex**: This method uses a simpler approach by removing characters based on a regular expression, which might be faster but may also have accuracy issues. **Pros and Cons** **Normalization** Pros: * Accurate results * No risk of incorrect character removal Cons: * Can be slower due to the complexity of the algorithm * May require additional resources for handling Unicode characters **Simple Regex** Pros: * Faster execution * Easy to implement Cons: * May have accuracy issues if not properly configured * Risk of removing important characters **Other Considerations** * **Unicode Support**: The benchmark script uses Unicode characters, which can affect the performance and accuracy of the normalization process. * **Library Usage**: The `normalize` method is part of the ECMAScript Internationalization API, which provides a standardized way to perform Unicode normalization. **Test Case Analysis** The test cases use the same input string (`a`) but apply different approaches: 1. **Normalize**: This test case uses the `normalize('NFD')` method to decompose the string. 2. **Regex**: This test case uses a regular expression to remove non-alphanumeric characters. Both test cases aim to measure the performance of each approach, but the results may vary depending on the browser and device used. **Benchmark Result Analysis** The latest benchmark result shows: 1. **Normalize**: 271 executions per second 2. **Regex**: 1036661 executions per second The `regex` approach is significantly faster than the normalization approach, which might be due to the simplicity of the regex pattern or the optimization efforts in modern browsers. As a software engineer, understanding these benchmark results can help you: * Choose between different approaches for string processing tasks * Optimize performance-critical code paths * Consider the trade-offs between accuracy and speed in your applications Keep in mind that this is just one example of a benchmark test case. When working with JavaScript benchmarks, it's essential to understand the specific test cases, libraries, and optimizations used to ensure accurate interpretation of the results.
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