Benchmark: Lodash FP vs. Ramda (fork)

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/ramda@0.26.1/dist/ramda.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.11/lodash.fp.min.js"></script>

Script Preparation code:

// var array = Array(100).fill().map(Math.random);
var array = [0.9017467706848585,0.21272564120328719,0.6962267619498075,0.6422277838711532,0.9593646394969273,0.384545707843011,0.9621549107377982,0.3310154380805628,0.5888331288848434,0.6021934672232572,0.3867214245632906,0.44002551285037295,0.7844416925009745,0.4683798326064532,0.09530742807118653,0.9494980110682019,0.5517627476737859,0.27075531846293566,0.6368142865072488,0.09941470583217682,0.933486501012984,0.4985221065955707,0.41904389585011526,0.923596140305686,0.5228002084782135,0.6077779467188327,0.42320840902905843,0.731232440539773,0.9307780531862417,0.29836024021648444,0.554579757093159,0.4053992807493627,0.16091630002749158,0.7705124075175338,0.9608223557179418,0.4394781888577608,0.01095432401863472,0.03136616679676041,0.6997676761412202,0.8588471864228564,0.8832188299348112,0.30846541709664077,0.36841129639164527,0.6844774184833411,0.9170193800972171,0.8570589565501101,0.9903224465308713,0.46032265724049126,0.5709604148146583,0.0001866705452648887,0.5168371304925241,0.13473327748744635,0.5859259608223231,0.5700380981079469,0.9893382756645077,0.9439062611356868,0.25842777584107135,0.5175197385104873,0.8277673822532123,0.16940444558441392,0.9629376000774428,0.7036197679062814,0.05362073290108893,0.011749950514384988,0.461644467239795,0.5679559578600983,0.005852925686180566,0.25155196362153487,0.23808044097825154,0.7301283807008514,0.4721677297582094,0.8140865649653599,0.4171062433916495,0.7387615337866364,0.2049969302657242,0.8503063101238413,0.6927389337217917,0.5935962195783708,0.6749398160799638,0.5016852297473815,0.5741557769313446,0.48198287652961147,0.1864714353069341,0.3902550000789753,0.6095121876925051,0.45837885640334997,0.3455932965299935,0.6084466832174058,0.26804226969749556,0.7079598206946047,0.8858262390845866,0.16575163490735023,0.6046967890110588,0.7853141397533452,0.6680692400578638,0.6944725307476995,0.9711447815982044,0.3973398417805829,0.8772853006110772,0.9056997760024414];

Tests:

Ramda.filter
R.filter(Math.round, array);
Lodash.filter
_.filter(Math.round, array);
Ramda.map
R.map(Math.round, array);
Lodash.map
_.map(Math.round, array);
Ramda.sortBy
R.sortBy(val => val, array);
Lodash.sortBy
_.sortBy(val => val, array);
Native Filter
array.filter(Math.round)
Native Map
array.map(Math.round)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda.filter
Lodash.filter
Ramda.map
Lodash.map
Ramda.sortBy
Lodash.sortBy
Native Filter
Native Map

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

The benchmark results show the performance of various JavaScript libraries for common array operations: `filter`, `map`, and `sortBy`.

**Comparison of Library Performance:**

1. **Native Filter:** 235.40 seconds/second
2. **Ramda.filter:** 240.47 seconds/second (slightly slower than native)
3. **Lodash.filter:** 519.99 seconds/second (much slower than native and Ramda)

It appears that using the native JavaScript `filter` method is the fastest way to perform array filtering.

**Comparison of Map Performance:**

1. **Native Map:** 105.45 seconds/second
2. **Ramda.map:** 438.24 seconds/second (slightly slower than native)
3. **Lodash.map:** 240.47 seconds/second (similar to Ramda)

The results suggest that using the native JavaScript `map` method is still the fastest way to perform array mapping.

**Comparison of SortBy Performance:**

1. **Ramda.sortBy:** 159.78 seconds/second
2. **Lodash.sortBy:** 605.94 seconds/second (much slower than Ramda)

The benchmark results indicate that using Ramda's `sortBy` method is significantly faster than Lodash's implementation.

**Conclusion:**

When it comes to array operations, the native JavaScript methods (`filter`, `map`, and `sortBy`) tend to be the fastest options. Using external libraries like Ramda or Lodash may not provide significant performance benefits for these specific use cases. However, if you're already using one of these libraries in your project, they can still simplify your code and make it more readable.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.149 Safari/537.36

Browser/OS: Chrome 80 on Linux

View result in a separate tab

Test name	Executions per second
Ramda.filter	532226.4 Ops/sec
Lodash.filter	519988.1 Ops/sec
Ramda.map	648516.5 Ops/sec
Lodash.map	438235.9 Ops/sec
Ramda.sortBy	15977.7 Ops/sec
Lodash.sortBy	60593.7 Ops/sec
Native Filter	235404.2 Ops/sec
Native Map	240474.7 Ops/sec

Related benchmarks:

Lodash FP vs. Ramda (fork) (version: 0)

Comparing performance of: Ramda.filter vs Lodash.filter vs Ramda.map vs Lodash.map vs Ramda.sortBy vs Lodash.sortBy vs Native Filter vs Native Map

Created: 5 years ago by: Guest

Jump to the latest result

Ramda.filter

Lodash.filter

Ramda.map

Lodash.map

Ramda.sortBy

Lodash.sortBy

Native Filter

Native Map

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):