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lodash 4.17.15 map vs Object.keys map
(version: 0)
lodash map vs Object.keys map
Comparing performance of:
lodash.map vs native
Created:
5 years ago
by:
Guest
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HTML Preparation code:
<script src="https://cdn.jsdelivr.net/lodash/4.17.15/lodash.min.js"></script>
Script Preparation code:
var value = {a: 30310, b: 100303, c: 3040494};
Tests:
lodash.map
_.map(value, (v) => v)
native
Object.keys(value).map((v) => v)
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
lodash.map
native
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 is comparing two approaches: 1. Lodash `_.map` function 2. Native JavaScript `Object.keys` method with a `map` callback Both tests are measuring the performance of these two functions on a sample data object, which is defined in the "Script Preparation Code": `var value = {a: 30310, b: 100303, c: 3040494};`. **Lodash _.map** Lodash is a popular JavaScript utility library that provides a variety of functional programming helpers. The `_.map` function applies a given function to each element of an array and returns a new array with the results. In this case, Lodash's `_.map` function takes two arguments: the input data object (`value`) and a callback function `(v) => v`. The callback function is expected to return a value for each property in the input object. Since the callback function simply returns its argument (`v`), it doesn't modify the original values. Pros: * Easy to use: Lodash provides a convenient and expressive way to perform operations on data structures. * Abstraction: It abstracts away the underlying implementation details, making it easier to focus on the logic of your code. Cons: * Overhead: Using an external library like Lodash adds overhead due to the need for function calls, memory allocation, and garbage collection. * Licensing: Depending on the version, Lodash might have licensing restrictions or limitations on commercial use. **Native JavaScript Object.keys** The native `Object.keys` method returns an array of a given object's own enumerable property names. In this case, it is used in conjunction with the `map` method to apply a callback function to each property name. Pros: * Performance: Native methods tend to be faster since they don't involve function calls or library overhead. * Security: Since it's a native method, it doesn't rely on any external libraries or dependencies. Cons: * Complexity: The native implementation can be more complex and harder to understand than the Lodash equivalent. * Verbosity: You need to manually define the callback function and handle errors. **Other Considerations** When choosing between these two approaches, consider the following factors: * Performance-critical code: If you're working on a performance-sensitive component, using native methods might be a better choice. * Code readability and maintainability: Lodash provides an expressive way to perform operations, making it easier to read and understand your code. * Library dependencies: Be aware of the licensing restrictions or limitations associated with using external libraries like Lodash. **Other Alternatives** If you don't want to use Lodash, you can also implement the `_.map` functionality yourself: ```javascript function _map(arr) { const result = []; for (const v of arr) { result.push(v); } return result; } ``` Alternatively, you can use other JavaScript libraries or frameworks that provide similar functionality, such as Ramda. **Test Cases** The test cases measure the performance difference between Lodash's `_.map` and native JavaScript `Object.keys.map`. The results show that: * Native JavaScript `Object.keys.map` outperforms Lodash's `_.map` by a significant margin (around 2x). This suggests that, in this specific case, using native methods provides better performance. However, keep in mind that the results might vary depending on your specific use case and environment.
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