Benchmark: lodash map vs native map (v4.17.21)

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.21/lodash.min.js'></script>

Script Preparation code:

var data = Array(1000000).fill({ a: 'a', b: 1 });

Tests:

lodash
_.map(data, ({a, b}) => `${a}_${b}`)
native
data.map(({a, b}) => `${a}_${b}`)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash
native

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 10 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/137.0.0.0 Safari/537.36

Browser/OS: Chrome 137 on Windows

View result in a separate tab

Test name	Executions per second
lodash	19.3 Ops/sec
native	18.5 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated 10 months ago):

LLMs can make mistakes. Check important info.

The benchmark defined in the provided JSON is designed to compare the performance of two methods for mapping over an array of objects in JavaScript: one using Lodash, a popular utility library, and the other using the native `Array.prototype.map` method.

### Options Compared

1. **Lodash Implementation**: 
   - **Code**: `_.map(data, ({a, b}) => `${a}_${b}`)`
   - **Library**: Lodash (version 4.17.21)
   - **Purpose**: Lodash provides a set of utility functions for common programming tasks, including array manipulation, object manipulation, and more. In this case, `_.map` is used to transform each object in the `data` array into a string formatted as `${a}_${b}`.

2. **Native JavaScript Implementation**: 
   - **Code**: `data.map(({a, b}) => `${a}_${b}`)`
   - **Description**: This uses the built-in `map` function of JavaScript arrays, which is designed to create a new array populated with the results of calling a provided function on every element in the calling array.

### Pros and Cons

#### Lodash (`_.map`)
**Pros**:
- Consistency: Lodash provides a consistent API across different types of data structures (arrays, objects, etc.).
- Utility Functions: It includes many additional helper functions that can be beneficial for complex operations.

**Cons**:
- Performance: Often slightly slower than native methods due to the abstraction and overhead of using a library.
- Overhead: Importing Lodash adds a dependency and additional bundle size, which may be unnecessary for simple operations.

#### Native Map (`Array.prototype.map`)
**Pros**:
- Performance: Generally faster due to optimized execution in modern JavaScript engines, especially for large datasets.
- No Dependencies: This approach does not rely on external libraries, reducing the overall size of the codebase and avoiding potential dependency issues.

**Cons**:
- Limited to Arrays: Only applicable to JavaScript arrays, so if you are operating on objects or other types, you may need different approaches or additional helper functions.

### Other Considerations

- **Execution Speed**: The benchmark results show `ExecutionsPerSecond` values where Lodash performs slightly better (19.31 ops/s) compared to native (18.51 ops/s), but the difference may not be significant for most use cases. It is worth noting that performance can vary based on engine optimizations, dataset size, and use cases.

- **Readability and Maintenance**: The choice between using Lodash and native methods can also depend on code readability and maintainability. Some developers may find Lodash's chaining and utility functions clearer, especially in complex operations.

### Alternatives

- **Manual Iteration**: Developers can also choose to use a traditional `for` loop or the `forEach` method for mapping through data, which can sometimes be more efficient, although less concise.

- **Other Libraries**: Besides Lodash, there are other utility libraries like Ramda or Underscore.js that offer similar functionality, each with their own specific benefits and performance characteristics.

In summary, both Lodash and native `Array.prototype.map` serve the purpose of transforming arrays but come with their own pros and cons. The choice between them should consider not only performance but also factors like readability, maintenance, and specific project requirements.

Related benchmarks:

lodash map vs native map (v4.17.21) (version: 1)

Comparing performance of: lodash vs native

Created: 10 months ago by: Guest

Jump to the latest result

lodash

native

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 10 months ago):