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ramda union vs Set for merging array with Object.keys
(version: 0)
123
Comparing performance of:
Set vs R.union
Created:
2 years ago
by:
Guest
Go to the latest result
HTML Preparation code:
<script src='https://cdnjs.cloudflare.com/ajax/libs/ramda/0.26.1/ramda.min.js'></script>
Tests:
Set
const first = ["andrey", "alexey", "vasya", "misha", "petya"]; const obj = { vasya: true, petya: true, kolya: true }; return new Set([...first, ...Object.keys(obj)]);
R.union
const first = ["andrey", "alexey", "vasya", "misha", "petya"]; const obj = { vasya: true, petya: true, kolya: true }; return R.union(first, Object.keys(obj));
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Set
R.union
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
2 years ago
)
User agent:
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.84 Safari/537.36 HBPC/12.1.3.306
Browser/OS:
Chrome 99 on Windows
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Embed Benchmark Result
<iframe src="https://measurethat.net/Embed?id=529520" width="100%" height="500px"></iframe>
Set
2.0M/s
R.union
1.3M/s
View exact numbers
Test name
Executions per second
✓
Set
2,005,945 Ops/sec
R.union
1,325,818 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's dive into the world of JavaScript microbenchmarks. **Benchmark Overview** The provided JSON represents a benchmark test on MeasureThat.net, which compares two approaches for merging an array with `Object.keys`: 1. Using a built-in `Set` data structure 2. Using the Ramda library's `R.union` function **Options Compared** Two options are compared in this benchmark: * **Set**: Using a built-in `Set` data structure to merge the arrays. * **R.union**: Using the Ramda library's `R.union` function to merge the arrays. **Pros and Cons of Each Approach** ### Set Pros: * Built-in, no external dependencies required * Fast and efficient for small datasets * Easy to implement Cons: * Not optimized for large datasets or complex data structures * May not be as efficient as other approaches for certain data types (e.g., strings) ### R.union Pros: * Optimized for performance and efficiency * Supports various data types, including strings * Can handle large datasets and complex data structures Cons: * Requires an external library dependency (Ramda) * May have a slight overhead due to the library's implementation **Library: Ramda** The Ramda library is a popular functional programming library for JavaScript. It provides a wide range of utility functions for data manipulation, filtering, mapping, and more. In this benchmark, `R.union` is used to merge two arrays. **Special JS Feature/Syntax** There doesn't seem to be any special JavaScript feature or syntax that's not part of the standard language. However, the use of a library like Ramda may require some familiarity with functional programming concepts and data manipulation techniques. **Other Alternatives** If you're looking for alternatives to `Set` or `R.union`, here are a few options: * **Array.prototype.concat()**: This method can be used to merge two arrays, but it may not be as efficient as `Set` or `R.union`. * **Array.prototype.push() + Array.prototype.indexOf()**: Another approach is to use `push()` to add elements from the second array to the first, and then use `indexOf()` to check for duplicates. However, this method can be slower and less efficient than using a built-in data structure like `Set` or `R.union`. In summary, the benchmark compares two approaches for merging an array with `Object.keys`: using a built-in `Set` data structure versus the Ramda library's `R.union` function. The pros and cons of each approach are discussed, highlighting the benefits and drawbacks of each method.
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