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Array.prototype.map vs Lodash map
(version: 0)
Comparing performance of:
Array.prototype.map vs Lodash map
Created:
7 years ago
by:
Guest
Jump to the latest result
HTML Preparation code:
<script src="lodash.js"></script>
Script Preparation code:
var array = [...Array(100000).keys()];
Tests:
Array.prototype.map
array.map(n => n*2)
Lodash map
_.map(array,n => n*2)
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Array.prototype.map
Lodash map
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
one year ago
)
User agent:
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36
Browser/OS:
Chrome 131 on Windows
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Embed Benchmark Result
Test name
Executions per second
Array.prototype.map
1297.2 Ops/sec
Lodash map
1541.4 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided JSON and understand what is being tested. **Benchmark Overview** The benchmark compares the performance of `Array.prototype.map` ( native JavaScript method) with `_map` from the popular utility library Lodash. The goal is to determine which approach provides better performance for mapping an array of numbers by doubling each value. **Options Compared** Two options are compared: 1. **Native JavaScript: Array.prototype.map**: This uses the built-in `Array.prototype.map()` method, which iterates over an array and applies a specified function to each element. 2. **Lodash: _.map()**: This uses the Lodash library's `_map()` function, which provides a similar functionality to the native JavaScript `map()` method but may optimize it for better performance. **Pros and Cons** **Native JavaScript (Array.prototype.map)** Pros: * Widespread support across modern browsers * Low overhead in terms of code size and complexity * Familiarity for developers already using JavaScript Cons: * May not provide optimal performance due to its native implementation * Can be slower compared to specialized libraries like Lodash **Lodash (.map())** Pros: * Optimized for better performance, especially in larger datasets * Often includes additional features and utility methods * Widespread adoption among developers who use JavaScript extensively Cons: * Requires an external library to include, which can add overhead * May not be suitable for projects with strict code size or complexity constraints **Other Considerations** When deciding between these two approaches, consider the following factors: * Project requirements: If you're working on a project that requires high performance and is targeting large datasets, Lodash might be a better choice. For smaller datasets or projects with low performance requirements, native JavaScript might suffice. * Code complexity and size: If code size and complexity are important factors in your project, native JavaScript might be a more suitable option. **Library Overview** Lodash is a popular utility library for JavaScript that provides various functions to simplify common tasks. The `_map()` function is one of its most widely used features, which allows you to apply a specified function to each element of an array while preserving the original array structure. **JavaScript Features and Syntax** This benchmark doesn't use any special JavaScript features or syntax beyond what's required for basic JavaScript programming (e.g., arrow functions, template literals). If it did utilize advanced features like async/await, generators, or Promises, the explanation would focus on those aspects as well. In this case, that's not the case. **Alternative Benchmarks** If you're interested in exploring other alternatives to benchmark performance differences between `Array.prototype.map` and Lodash `_map()`, consider these options: * Using the native JavaScript `forEach()` method instead of `map()` * Implementing your own custom mapping function * Testing with different input sizes or dataset distributions (e.g., arrays of objects, numbers) * Comparing performance across multiple browsers or versions
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