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Reuven findIndex benchmark
(version: 1)
Comparing performance of:
findIndex vs for loop
Created:
one year ago
by:
Guest
Go to the latest result
HTML Preparation code:
<!--your preparation HTML code goes here-->
Script Preparation code:
var target = {"id": 1337}; var arr = new Array(1000); arr.fill({"id": 1}); arr[999] = target;
Tests:
findIndex
arr.findIndex((itm) => itm.id === target.id);
for loop
for (let i = 0; i < arr.length; i++) { if (arr[i].id === target.id) break; }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
findIndex
for loop
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
one year ago
)
User agent:
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/138.0.0.0 Safari/537.36
Browser/OS:
Chrome 138 on Mac OS X 10.15.7
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Embed Benchmark Result
<iframe src="https://measurethat.net/Embed?id=613163" width="100%" height="500px"></iframe>
findIndex
2.3M/s
for loop
479K/s
View exact numbers
Test name
Executions per second
✓
findIndex
2,303,298 Ops/sec
for loop
479,463 Ops/sec
Autogenerated LLM Summary
(model
gpt-4o-mini
, generated one year ago):
The benchmark provided compares two different methods for searching through an array of objects in JavaScript, specifically targeting the `id` property of objects within the array. The options being compared are: 1. **`findIndex` Method:** - **Code:** `arr.findIndex((itm) => itm.id === target.id);` - **Description:** This method is part of the array prototype in JavaScript and is used to find the index of the first element in the array that satisfies a provided testing function. In this case, it checks if the `id` of each object is equal to `target.id`. - **Performance (Executions Per Second):** 2,303,297.75 - **Pros:** - Concise and readable syntax suitable for functional programming. - Returns the index directly, leading to cleaner code. - **Cons:** - May have overhead associated with the function call for each element, which could impact performance in very large arrays compared to a traditional loop. 2. **For Loop:** - **Code:** ```javascript for (let i = 0; i < arr.length; i++) { if (arr[i].id === target.id) break; } ``` - **Description:** This is a traditional `for` loop, which iterates over the array elements. It checks each object's `id` property and breaks out of the loop once a match is found. - **Performance (Executions Per Second):** 479,462.6875 - **Pros:** - More control over the iteration, allowing for early termination as soon as a match is found. - Typically has lower overhead since it avoids function calls for every iteration. - **Cons:** - More verbose and less readable than methods using built-in array functions. - Increased potential for errors if not handled carefully (e.g., managing loop conditions). ### Other Considerations: - **Readability vs. Performance:** The choice between using a traditional loop and a more modern method like `findIndex` often depends on the context of the code. While `findIndex` is more succinct and easier to read, the performance may degrade in scenarios with large datasets, especially when the overhead of function calls in `findIndex` is significant. - **Browser Compatibility:** Both methods are widely supported in modern browsers, but the performance can vary based on the JavaScript engine's optimizations. ### Alternatives: - Other alternatives for searching elements in an array include using `forEach`, `filter`, or implementing binary search (if the array is sorted). However, each of these comes with trade-offs concerning complexity and performance. - For extremely large datasets, strategies such as using data structures like hash tables or sets for O(1) average lookup times could be employed to improve search performance, though these would require additional memory overhead and data transformations. ### Conclusion: This benchmark clearly illustrates the trade-offs between readability and performance present in JavaScript array manipulation. Engineers must consider these balances based on their project's needs, taking into account factors like array size, execution speed requirements, and maintainability of the code.
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