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Deep copy performance
(version: 5)
Comparing performance of:
jQuery direct extend vs jQuery extend assignment vs Lodash cloneDeep vs JSON parse and stringify
Created:
7 years ago
by:
Registered User
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HTML Preparation code:
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.3.1/jquery.min.js"></script> <script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>
Script Preparation code:
var data = []; var res = []; fetch('https://jsonplaceholder.typicode.com/posts') .then(response => response.json()) .then(json => data = json)
Tests:
jQuery direct extend
res = []; $.extend(true, res, data);
jQuery extend assignment
res = $.extend(true, [], data);
Lodash cloneDeep
res = _.cloneDeep(data);
JSON parse and stringify
res = JSON.parse(JSON.stringify(data));
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (4)
Previous results
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Test case name
Result
jQuery direct extend
jQuery extend assignment
Lodash cloneDeep
JSON parse and stringify
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided JSON benchmark data for the "Deep copy performance" test case. **What is being tested?** The benchmark measures the performance of different approaches to create a deep copy of an object in JavaScript. The object being copied is a JSON response from a remote server, fetched using the `fetch` API and parsed as JSON. **Options compared:** Four options are compared: 1. **jQuery direct extend**: Uses jQuery's `$extend` method to merge the source data into a new array. 2. **jQuery extend assignment**: Uses jQuery's `$extend` method to assign the result of merging the source data to a new array, instead of modifying the original array. 3. **Lodash cloneDeep**: Uses Lodash's `cloneDeep` function to create a deep copy of the source data. 4. **JSON parse and stringify**: Uses JSON's `parse` and `stringify` functions to create a deep copy of the source data by parsing the JSON string and then stringifying it again. **Pros and cons of each approach:** 1. **jQuery direct extend**: * Pros: Simple and straightforward, leverages jQuery's existing functionality. * Cons: May not be optimal for large datasets due to the overhead of jQuery's library. 2. **jQuery extend assignment**: * Pros: Similar to jQuery direct extend but avoids modifying the original array, reducing potential side effects. * Cons: Still relies on jQuery's library and may not be suitable for non-JQuery environments. 3. **Lodash cloneDeep**: * Pros: Robust and efficient deep copying mechanism, suitable for large datasets and complex data structures. * Cons: Requires an additional dependency (Lodash), which may add overhead. 4. **JSON parse and stringify**: * Pros: Lightweight and efficient, as it only involves basic JSON parsing and stringification. * Cons: May not preserve all the nuances of the original data structure, especially for complex objects. **Library usage:** The benchmark uses jQuery (`$.extend`) and Lodash (`cloneDeep`). These libraries provide optimized implementations for common JavaScript tasks, but they also introduce additional dependencies and potential overhead. **Special JS feature or syntax:** None are explicitly mentioned in this benchmark. However, it's worth noting that the use of `fetch`, JSON parsing, and stringification relies on modern JavaScript features and APIs. **Other alternatives:** If you need to create a deep copy of an object without using libraries like jQuery or Lodash, you can implement your own solution using techniques like: * Recursive object iteration * Shallow/deep cloning using JavaScript's built-in `Object.assign` method * Using a library like `lodash-es` (a lightweight alternative to Lodash) For non-JavaScript environments or when performance is critical, other alternatives may include: * Using a dedicated deep copying library like `js-deep-copy` * Implementing a custom cloning mechanism using native JavaScript APIs Keep in mind that each approach has trade-offs in terms of complexity, performance, and memory usage. The choice ultimately depends on your specific requirements and constraints.
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