Benchmark: Math.random().toString(36).substring(2, 12) vs Date.now()

Tests:

Math.random().toString(36).substring(2, 12)
Math.random().toString(36).substring(2, 12)
Date.now()
Date.now()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.random().toString(36).substring(2, 12)
Date.now()

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested, compared, and their pros and cons.

**Benchmark Overview**

The benchmark compares two approaches for generating a unique key: `Math.random().toString(36).substring(2, 12)` (using Math.random()) versus `Date.now()` (using the Date object).

**What is being tested?**

In this benchmark, we're testing which approach is better suited for generating a unique key. The goal is to find an efficient and reliable way to create unique identifiers.

**Options compared**

There are two options being compared:

1. **`Math.random().toString(36).substring(2, 12)`**: This method uses the `Math.random()` function to generate a random number, converts it to a base-36 string (using the radix 36), and then extracts a substring of length 10 from the resulting string. This approach is often used for generating cryptographically secure pseudo-random numbers.
2. **`Date.now()`**: This method uses the `Date.now()` function, which returns the number of milliseconds since January 1, 1970, 00:00:00 UTC.

**Pros and Cons**

* **`Math.random().toString(36).substring(2, 12)`**:
	+ Pros: Can generate cryptographically secure pseudo-random numbers, has a relatively low entropy (i.e., it can produce duplicate values).
	+ Cons: May be slower than `Date.now()`, requires additional processing to convert the number to a string and extract the desired substring.
* **`Date.now()`**:
	+ Pros: Fast, easy to implement, and provides high entropy (i.e., it's unlikely to produce duplicate values). However, it may not be suitable for cryptographic purposes due to its reliance on the system clock.
	+ Cons: May have a fixed precision, potentially leading to collisions if used with a short ID length.

**Other considerations**

The benchmark assumes that the generated unique keys will be stored and compared in some way. It's essential to consider factors like collision resistance, entropy, and performance when choosing an approach for generating unique identifiers.

**Library usage (optional)**

There is no explicit library usage mentioned in this benchmark.

**Special JS features or syntax (none)**

No special JavaScript features or syntax are used in this benchmark.

**Alternatives**

For generating unique keys, other approaches could include:

1. **UUID (Universally Unique Identifier)**: A 128-bit UUID can provide high entropy and is designed for generating globally unique identifiers.
2. **Cryptographically secure pseudo-random number generators**: Other libraries like `crypto-js` or `secp256k1` offer more advanced cryptographic functions, including those for generating cryptographically secure pseudo-random numbers.

The choice of approach ultimately depends on the specific requirements and constraints of your application, such as performance, entropy, and collision resistance.

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64; rv:127.0) Gecko/20100101 Firefox/127.0

Browser/OS: Firefox 127 on Linux

View result in a separate tab

Test name	Executions per second
Math.random().toString(36).substring(2, 12)	3948344.0 Ops/sec
Date.now()	852788.4 Ops/sec

Related benchmarks:

Math.random().toString(36).substring(2, 12) vs Date.now() (version: 0)

Which is best for generating a unique key?

Comparing performance of: Math.random().toString(36).substring(2, 12) vs Date.now()

Created: 2 years ago by: Guest

Jump to the latest result

Math.random().toString(36).substring(2, 12)

Date.now()

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):