Benchmark: parseInt vs Number(val.toFixed(0))

Script Preparation code:

var arr = [];
var i = 0;

while (i <= 1E7) arr[i] = i++;
console.log(arr);

Tests:

parseInt
arr.map(v => parseInt(v));
Number(val.toFixed)
arr.map(v => Number(v.toFixed(0)));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
parseInt
Number(val.toFixed)

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36

Browser/OS: Chrome 114 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
parseInt	1.4 Ops/sec
Number(val.toFixed)	0.7 Ops/sec

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 and explain what's being tested.

**Benchmark Overview**

The benchmark is comparing two approaches to parse a large array of integers:

1. `parseInt(v)`: using the built-in `parseInt` function to convert each element `v` to an integer.
2. `Number(v.toFixed(0))`: converting each element `v` to a floating-point number by calling the `toFixed` method with a precision of 0.

**Library and Purpose**

The `flatMap` and `filter` methods are part of the Array prototype in JavaScript, which is not explicitly mentioned in the benchmark definition. However, we can infer that these methods are being used as a way to prepare the array for testing.

In this context, `flatMap` and `filter` are likely being used to filter out or transform elements in the array, but their exact purpose is not crucial to understanding the comparison between `parseInt` and `Number`.

**Options Compared**

The two options being compared are:

1. `parseInt(v)`: a built-in function that converts an integer string to an integer.
2. `Number(v.toFixed(0))`: converting an integer string to a floating-point number with a precision of 0.

**Pros and Cons**

**`parseInt(v)`**

Pros:

* Fast execution: `parseInt` is optimized for performance and is usually the fastest way to convert an integer string to an integer.
* Simple syntax: The syntax is straightforward and easy to read.

Cons:

* Limited support: `parseInt` only works with integer strings, and may not work as expected if the input is a floating-point number or a non-numeric value.

**`Number(v.toFixed(0))`**

Pros:

* Flexible: This approach can handle both integer and floating-point numbers.
* Generic syntax: The syntax is more generic and can be used for conversions that require rounding to an integer.

Cons:

* Slower execution: `toFixed` may incur additional overhead compared to `parseInt`.
* More complex syntax: The syntax may be less intuitive for developers familiar with `parseInt`.

**Other Considerations**

When testing performance, it's essential to consider the following factors:

* Input size and distribution
* Browser or runtime environment
* Optimizations enabled (e.g., caching, memoization)
* Other system resources consumed (e.g., memory, CPU)

**Alternatives**

If you wanted to explore alternative approaches, you could consider the following options:

1. `Number(v)`: Without specifying a precision, this approach would convert the input string to a floating-point number without rounding.
2. `Math.round(v) + v.toFixed(0)`: This approach combines rounding with explicit conversion to an integer using `toFixed`.
3. `BigInt(v)`: If available in your target JavaScript environment (e.g., Node.js), you could use `BigInt` to perform high-precision arithmetic.

Keep in mind that these alternatives might have different performance characteristics, syntax, or limitations depending on the specific scenario.

Related benchmarks:

parseInt vs Number(val.toFixed(0)) (version: 0)

flatMap vs filter map

Comparing performance of: parseInt vs Number(val.toFixed)

Created: one year ago by: Guest

Jump to the latest result

parseInt

Number(val.toFixed)

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):