Benchmark: string/number/symbol speed test 1

Tests:

Symbol
const a = Symbol('asdf'); const b = Symbol('qwer'); a === b
Number
const a = Number.parseInt('1'); const b = Number.parseInt('2'); a === b

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Symbol
Number

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:136.0) Gecko/20100101 Firefox/136.0

Browser/OS: Firefox 136 on Mac OS X 10.15

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Test name	Executions per second
Symbol	21931324.0 Ops/sec
Number	1630336384.0 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one month ago):

LLMs can make mistakes. Check important info.

The benchmark you provided focuses on measuring the performance of specific JavaScript operations related to symbols and number parsing. Each test case is written to execute a simple operation, and the results reflect how many times per second these operations can be performed under the tested environment. Below, I will detail what each test entails, the implications of the results, and alternative approaches.

### Test Cases Overview

1. **Symbol Test**
   - **Test Name:** Symbol
   - **Benchmark Definition:** `const a = Symbol('asdf'); const b = Symbol('qwer'); a === b`
   - **Purpose:** This test checks the performance of creating two unique symbols and comparing them for equality. In JavaScript, `Symbol` is a primitive data type introduced in ES6 (ECMAScript 2015). Symbols are unique and immutable, primarily used to create private object properties.

2. **Number Test**
   - **Test Name:** Number
   - **Benchmark Definition:** `const a = Number.parseInt('1'); const b = Number.parseInt('2'); a === b`
   - **Purpose:** This test measures the performance of the `Number.parseInt()` function, which converts a string to an integer. The focus here is on invoking this function twice and then comparing the results, which should be `false` since the integers produced will be different.

### Performance Results

The results show:
- **Number Test:** 1,630,336,384 executions per second
- **Symbol Test:** 21,931,324 executions per second

### Analysis of Results

#### Pros and Cons of Each Approach

- **Symbol:**
  - **Pros:** 
    - Provides unique identifiers that do not conflict with string keys or other symbols. This is useful for creating properties in objects that can avoid name clashes.
  - **Cons:**
    - The performance penalty is considerable compared to operations on primitive types like numbers, as seen by the significantly lower executions per second.

- **Number:**
  - **Pros:** 
    - The `parseInt` function is widely used for converting strings to numbers and is generally efficient for basic number parsing. The high performance reflects its importance in various applications, especially in data processing.
  - **Cons:**
    - While `parseInt` is effective, it can lead to confusion if not used correctly, as it can yield unexpected results if not provided explicit base arguments. Additionally, it's less suited for converting non-numeric strings as it stops parsing at the first non-numeric character.

### Other Considerations

1. **Performance Impact:** 
   - When deciding between using `Symbol` and other types (like numbers or strings), performance is crucial. Since symbols perform considerably worse in this specific benchmark, their use should be limited to cases requiring unique identifiers.
   
2. **Use Cases for Symbols:**
   - Symbols are invaluable in scenarios like defining APIs where object properties need to be unique to avoid accidental modifications or collisions with other code.

3. **Alternative Methods:**
   - For numbers, `Number()` could be used instead of `parseInt()` to convert string representations more straightforwardly into numbers. The downside might include less control over the base of conversion.
   - If symbols are not necessary, using strings or an alternative object structure may offer improved performance in scenarios where raw speed is a priority.

In summary, while the benchmark demonstrates distinct performance metrics between symbol creation and number parsing, it ultimately reflects varied use cases. Software engineers should consider the unique attributes of `Symbol` against their performance implications when deciding which approach to utilize in their applications.

Related benchmarks:

string/number/symbol speed test 1 (version: 1)

Comparing performance of: Symbol vs Number

Created: one month ago by: Guest

Jump to the latest result

Symbol

Number

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one month ago):