Benchmark: Lodash filter + map vs forEach

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

var contacts = {
  'a1@a.com': {id: 1},
  'a2@a.com': {id: 2},
  'a3@a.com': {id: 3},
  'a4@a.com': {id: 4},
  'a5@a.com': {id: 5},
  'a6@a.com': {id: 6},
  'a7@a.com': {id: 7},
  'a8@a.com': {id: 8},
  'a9@a.com': {id: 9},
  'a10@a.com': {id: 10},
}

var selectedItems = [1,3,7];

Tests:

Lodash filter + map
selectedItems = _Object.values(contacts).filter(contact => selectedItems.indexOf(contact.id) === -1).map(contact => contact.id)
forEach
Object.values(contacts).forEach((contact) => { if (selectedItems.indexOf(contact.id) === -1) { selectedItems.push(contact.id); } });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash filter + map
forEach

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one month ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and individual test cases.

**Benchmark Definition:**
The website `MeasureThat.net` is used to create and run JavaScript microbenchmarks. The provided benchmark measures the performance of two approaches for filtering and mapping an array of objects:

1. Using `filter()` and `map()` from Lodash library.
2. Using a simple `forEach()` loop with conditional logic.

**Options Compared:**
The two options compared are:

* **Lodash filter + map**: This approach uses the `filter()` method to remove elements that don't match the condition, followed by the `map()` method to transform the remaining elements into an array of IDs.
* **forEach**: This approach uses a simple `forEach()` loop with conditional logic to push the ID of each element into the `selectedItems` array if it's not already present.

**Pros and Cons:**
Both approaches have their strengths and weaknesses:

* **Lodash filter + map**:
	+ Pros:
		- More concise and readable code.
		- Takes advantage of optimized Lodash functions.
	+ Cons:
		- Requires an additional library (Lodash) to be included in the test environment.
		- Might have slower startup times due to the import time.
* **forEach**:
	+ Pros:
		- No additional libraries needed, as it's a built-in method.
		- Can be more familiar and comfortable for developers who are used to traditional loops.
	+ Cons:
		- Code might be longer and less readable due to the nested if statement.
		- The loop might not be optimized as much as the Lodash approach.

**Library:**
The Lodash library is a popular utility library that provides various functions for tasks like filtering, mapping, and more. In this case, it's used to simplify the code and take advantage of optimized implementations.

**Special JS Feature or Syntax:**
There isn't any special JavaScript feature or syntax mentioned in the benchmark definition. Both approaches use standard JavaScript methods and syntax.

**Other Alternatives:**
If you want to explore other alternatives for filtering and mapping arrays, here are a few options:

* **Array.prototype.filter()**: A built-in method that can be used without an additional library.
* **Array.prototype.reduce()**: Another built-in method that can be used for both filtering and mapping arrays, although it's often more complex than the simple `forEach()` approach.
* **Underscore.js functions**: Similar to Lodash, but with a slightly different API.

Latest run results:

Run details: (Test run date: 5 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3626.81 Safari/537.36

Browser/OS: Chrome 72 on Linux

View result in a separate tab

Test name	Executions per second
Lodash filter + map	0.0 Ops/sec
forEach	904598.8 Ops/sec

Related benchmarks:

Lodash filter + map vs forEach (version: 0)

Comparing performance of: Lodash filter + map vs forEach

Created: 5 years ago by: Guest

Jump to the latest result

Lodash filter + map

forEach

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one month ago):