Benchmark: Lodash Sum vs ApSum

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>

Script Preparation code:

function* generate(until) {
  let current = 0
  while(current < until) {
    yield 1 + (5 * current)
    current++
  }
}

function apSum(array) {
  const N = array.length
  const [a] = array
  const L = array[N - 1]
  return (N / 2) * (a + L)
}

function sum(array) {
  return _.sum(array)
}

function naiveSum(array) {
  array.reduce((total, current) => total += current, 0)
}

Tests:

Lodash sum
const data = [...generate(1000 * 1000)] sum(data)
Ap Sum
const data = [...generate(1000 * 1000)] apSum(data)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash sum
Ap Sum

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.1:latest, generated one year ago):

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Let's dive into the details of this benchmark.

**What is being tested?**

The benchmark compares three different approaches to calculate the sum of an array of numbers:

1. **Lodash sum**: This uses the `_.sum` function from the Lodash library, which is a popular JavaScript utility library.
2. **Ap Sum**: This calculates the sum using the arithmetic mean formula: `(n/2) * (a + l)`, where `n` is the array length, `a` is the first element, and `l` is the last element.
3. **Naive Sum** (not actually tested in this benchmark): This uses the built-in `reduce` method to sum up all elements in the array.

**What options are compared?**

The two test cases compare the performance of:

1. **Lodash sum**: Uses the `_.sum` function from Lodash.
2. **Ap Sum**: Calculates the sum using a simple mathematical formula.

**Pros and Cons:**

* **Lodash sum**: Pros:
	+ Using a well-established library with good performance.
	+ Easy to use and understand for developers familiar with Lodash.
* Cons:
	+ Requires an additional dependency (the Lodash library).
	+ May have overhead due to the library's complexity.
* **Ap Sum**: Pros:
	+ Simple and efficient mathematical formula.
	+ No additional dependencies required.
* Cons:
	+ May not be as well-optimized or maintained as a dedicated library like Lodash.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a wide range of functions for tasks such as array manipulation, object transformation, and function composition. In this benchmark, the `_.sum` function is used to calculate the sum of an array.

**JavaScript features or syntax used:**

* **Spread operator (`...`)**: Used to create an array from a generator function.
* **Generator function**: A special type of function that returns a sequence of values instead of a single value.
* **Arrow functions**: Used in the `sum`, `apSum`, and `naiveSum` functions for concise syntax.

**Other alternatives:**

If you're not using Lodash, other ways to calculate the sum of an array include:

1. Using the built-in `reduce` method (not actually tested in this benchmark).
2. Implementing a custom loop or recursive function to sum up all elements.
3. Using a different library like Underscore.js or Ramda.

Keep in mind that these alternatives may have their own trade-offs and performance characteristics, which might not be comparable to the Lodash implementation used in this benchmark.

Related benchmarks:

Lodash Sum vs ApSum (version: 0)

Comparing performance of: Lodash sum vs Ap Sum

Created: 4 years ago by: Guest

Jump to the latest result

Lodash sum

Ap Sum

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.1:latest, generated one year ago):