In this benchmark, test cases measure the performance difference between using the Lodash library for functional programming style and Vanilla JavaScript for similar data manipulations on an array of objects.

Benchmark Overview

1. Name: Lodash Streams vs Vanilla JavaScript v2
2. Purpose: Compare the performance of Lodash against native JavaScript methods for filtering and mapping through an array of objects.

Test Cases

Lodash Implementation:

result = _(arr)
    .filter((value) => value.valueF > 50)
    .map((value) => ({ "value": value.valueM }))
    .value();

console.log(result);

Vanilla JavaScript Implementation:

const result = arr
    .filter(value => value.valueF > 50)
    .map(value => ({ value: value.valueM }));

console.log(result);

Comparison of Options

1. Lodash Library:

• Description: Lodash is a JavaScript library that provides utility functions for common programming tasks, including manipulating and iterating over arrays and objects.
• Features Cons:
  • Pros: Provides a more readable and expressive way to handle array and object transformations, can chain methods seamlessly.
  • Cons: Introduces additional overhead due to the library weight and extra function calls, which can impact performance, especially for simple tasks.

2. Vanilla JavaScript:

• Description: Uses built-in JavaScript array methods (filter and map).
• Features Cons:
  • Pros: Typically more performant for simpler operations since there's no overhead of an external library; direct access to JavaScript's core functionality without any additional loading.
  • Cons: May require more boilerplate or lower-level understanding of JavaScript for complex transformations compared to Lodash, where chaining can simplify the code.

Performance Results

Based on the benchmark results:

• Lodash achieved approximately 1196.34 executions per second.
• Vanilla JavaScript achieved approximately 973.01 executions per second.

This indicates that in this specific case, Lodash was faster, likely due to optimizations in the library for handling larger datasets, despite the common perception that native methods are generally preferable for performance.

Other Considerations

• Browser Environment: Benchmarks were run in Mobile Safari on iOS, and the performance can vary significantly across different environments and platforms.
• Use Case: When choosing between Lodash and Vanilla JavaScript, consider the complexity of the functionality required. For complex data transformations that benefit from chaining, Lodash may provide cleaner and more maintainable code. For simpler or performance-critical applications, plain JavaScript may be the better choice.
• Alternatives: Other libraries like Underscore.js offer similar functionality to Lodash but might have different performance characteristics. Native JavaScript also has evolved over time, with features like arrow functions and the spread operator enhancing its expressiveness. Additionally, adopting modern practices such as using forEach, reduce, and other Array methods can also achieve similar goals efficiently.

In conclusion, engineers need to weigh the trade-offs between using a utility library like Lodash versus raw JavaScript considering readability, maintainability, performance, and context of use when developing their applications.