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lodash trim vs native string trim
(version: 0)
Comparing performance of:
lodash trim vs native trim
Created:
one year ago
by:
Guest
Jump to the latest result
HTML Preparation code:
<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash-fp/0.10.4/lodash-fp.js'></script>
Script Preparation code:
var test = ' tom hanks '
Tests:
lodash trim
_.trim(test, ' ,')
native trim
test.trim()
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
lodash trim
native trim
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
3 months ago
)
User agent:
Mozilla/5.0 (X11; Linux x86_64; rv:140.0) Gecko/20100101 Firefox/140.0
Browser/OS:
Firefox 140 on Linux
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Embed Benchmark Result
Test name
Executions per second
lodash trim
3012491.8 Ops/sec
native trim
816177344.0 Ops/sec
Autogenerated LLM Summary
(model
gpt-4o-mini
, generated one year ago):
The benchmark provided compares two different methods of trimming whitespace from a string in JavaScript: one using the native string method `String.prototype.trim()` and the other using the `_.trim()` function from the Lodash library. ### Options Compared 1. **Lodash `trim`**: - Syntax: `_.trim(test, ' ,')` - Uses the Lodash library to remove whitespace (and specified characters) from both ends of the string. - The second parameter allows customization of characters to trim, making it flexible for different use cases. 2. **Native `trim`**: - Syntax: `test.trim()` - Utilizes JavaScript’s built-in string method to remove whitespace from both ends of a string. - Simplicity and general efficiency as it does not require an external library for functionality. ### Pros and Cons **Lodash Trim Pros**: - **Flexibility**: Allows developers to specify custom characters to trim, which can be useful for certain applications. - **Consistency**: Using a library can ensure that similar functions are presented uniformly across projects, particularly in large codebases with various utility functions. **Lodash Trim Cons**: - **Performance**: As evidenced by the benchmark results, it is significantly slower than the native trim. The native trim can execute around 13 million operations per second, while Lodash trim executes just over 3 million operations per second. - **Dependency**: Requires the inclusion of the Lodash library, which adds to the bundle size and can increase load times if not managed properly. **Native Trim Pros**: - **Performance**: Excellent performance for basic trimming operations, taking advantage of optimizations in modern JavaScript engines. - **No Dependencies**: It is part of standard JavaScript, meaning no additional libraries or dependencies are required. **Native Trim Cons**: - **Limited Functionality**: Only removes whitespace and does not support custom trimming, which could be an issue in more specific use cases where trimming other characters is necessary. ### Additional Considerations When considering which method to employ, it’s important to factor in the context of use. If your application relies on Lodash for other utility functions, using `_.trim` might maintain consistency. However, if performance is critical and only standard whitespace trimming is required, the native method should be preferred. ### Alternatives Other alternatives for trimming strings include: - **Regular Expressions**: For more complex trimming requirements that require selective trimming of characters, regular expressions can be employed. For example, `string.replace(/^\s+|\s+$/g, '')` will trim whitespace using a regex. - **Polyfill for Older Environments**: If backward compatibility is a concern and you need to support environments where `trim()` is not available, you could implement a simple version of `trim` by defining it as a prototype method using regex. Each approach has its use cases, and understanding the strengths and weaknesses helps in choosing the right tool for the job based on specific requirements. Thus, selecting between Lodash trim and native trim boils down to the specific needs of your project in terms of flexibility and performance.
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