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Test immutables data for map operation with Object.values()
(version: 0)
Test immutables data for map operation with Object.values()
Comparing performance of:
Native map vs Immutable
Created:
7 years ago
by:
Guest
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HTML Preparation code:
<script type='text/javascript' src='https://cdnjs.cloudflare.com/ajax/libs/immutable/3.8.2/immutable.min.js'></script>
Script Preparation code:
var output = [ { 'key': 1 }, { 'key': 1 } ]
Tests:
Native map
var result = output.map(v => Object.values(v))
Immutable
var immutableData = Immutable.Seq(output) var result = immutableData.map(v => Object.values(v))
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Native map
Immutable
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 provided benchmark and its test cases. **Benchmark Definition** The benchmark is designed to measure the performance of two approaches: native map operation using JavaScript's built-in `Object.values()` method, and immutable data structure approach using the Immutable.js library. The benchmark definition json contains two scripts: 1. **Native Map**: The first script defines a variable `output` as an array of objects with a single property `key` set to 1. It then uses the native `map()` function to apply the transformation `v => Object.values(v)` to each element in the array. 2. **Immutable**: The second script imports the Immutable.js library and creates an immutable data structure from the original `output` array using `Immutable.Seq()`. It then applies the same transformation as the native map operation, but using the Immutable.js `map()` function. **Options Compared** The benchmark is comparing two approaches: * **Native Map**: Using JavaScript's built-in `Object.values()` method to transform the data. * **Immutable**: Using the Immutable.js library to create an immutable data structure and apply transformations to it. **Pros and Cons of Each Approach** **Native Map:** Pros: * Lighter weight and easier to implement, as it only requires a single function call. * May be more familiar to developers who are used to working with native JavaScript data structures. Cons: * May not provide the same level of immutability and thread-safety guarantees as an immutable library like Immutable.js. * Can lead to unexpected side effects if not implemented carefully, as it modifies the original array in place. **Immutable:** Pros: * Provides a higher level of immutability and thread-safety guarantees, which can improve the overall reliability and stability of the code. * Can help avoid common issues related to mutable state and side effects. Cons: * Heavier weight and more complex implementation, as it requires an additional library and setup. * May require more boilerplate code and setup to achieve the same results as a native map operation. **Library: Immutable.js** The Immutable.js library is used to create immutable data structures and provide a way to apply transformations to them in a thread-safe manner. The `Immutable.Seq()` function is used to create an immutable sequence from the original array, and the `map()` function is used to apply the transformation to each element. **Special JS Feature/ Syntax** None mentioned explicitly in this benchmark. **Other Considerations** When considering performance-critical code or applications where immutability is crucial, it's essential to weigh the trade-offs between lightweight native solutions and more robust immutable libraries like Immutable.js. In general: * If you need light weight and ease of implementation, a native map operation may be sufficient. * However, if you require higher levels of immutability, thread-safety guarantees, and reliability, an immutable library like Immutable.js is likely a better choice. **Alternatives** Some alternative approaches to consider when working with arrays and data transformations in JavaScript include: * Using `Array.prototype.reduce()` instead of `map()` * Implementing custom iteration mechanisms using callbacks or promises * Leveraging libraries like Lodash or Ramda for functional programming utilities * Using Web Workers or worker threads for parallel processing
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