Benchmark: Deep copy algo vs JSON manipulation - 6k lines of prices

Script Preparation code:

function deepCopy(obj) {
    var copy;

    // Handle the 3 simple types, and null or undefined
    if (null == obj || "object" != typeof obj) return obj;

    // Handle Date
    if (obj instanceof Date) {
        copy = new Date();
        copy.setTime(obj.getTime());
        return copy;
    }

    // Handle Array
    if (obj instanceof Array) {
        copy = [];
        for (var i = 0, len = obj.length; i < len; i++) {
            copy[i] = deepCopy(obj[i]);
        }
        return copy;
    }

    // Handle Object
    if (obj instanceof Object) {
        copy = {};
        for (var attr in obj) {
            if (obj.hasOwnProperty(attr)) copy[attr] = deepCopy(obj[attr]);
        }
        return copy;
    }

    throw new Error("Unable to copy obj! Its type isn't supported.");
};

function generate_data() {
  let data = {
    'prices': [],
    'my object': [
      {'object a': 'object object'},
      {'object b': 'object object'}, 
      {'object c': 'object object', 'objectd': 36}, 
      5
    ]
  };

  // Helper function to generate random product names
  function generateProductName() {
    const products = ['Laptop', 'Phone', 'Tablet', 'Headphone', 'Speaker', 'Monitor', 'Keyboard', 'Mouse', 'Smartwatch', 'Camera'];
    const adjectives = ['Super', 'Ultra', 'Pro', 'Max', 'Plus', 'Lite', 'Mini', 'Advanced', 'Portable', 'Wireless'];
    const randomProduct = products[Math.floor(Math.random() * products.length)];
    const randomAdjective = adjectives[Math.floor(Math.random() * adjectives.length)];
    return `${randomAdjective} ${randomProduct}`;
  }

  // Helper function to generate random prices
  function generatePrice() {
    return (Math.random() * 1000).toFixed(2); // Random price between 0 and 1000 with 2 decimal places
  }

  // Generate 6000 product name and price entries
  for (let i = 0; i < 6000; i++) {
    const product = generateProductName();
    const price = generatePrice();
    data['prices'].push({ 'product': product, 'price': parseFloat(price) });
  }

  return data;
};

var data = generate_data();

Tests:

JSON copy
a = JSON.parse(JSON.stringify(data));
Deep copy
a = deepCopy(data);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
JSON copy
Deep copy

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/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
JSON copy	817.4 Ops/sec
Deep copy	3391.6 Ops/sec

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

LLMs can make mistakes. Check important info.

The benchmark provided compares two different methods for creating a deep copy of an object in JavaScript: **JSON manipulation** and a **custom deep copy function**.

### Test Cases Explained

1. **JSON Copy**
   - **Method**: `a = JSON.parse(JSON.stringify(data));`
   - **Description**: This method leverages JSON serialization and deserialization to create a deep copy of the data. The object is first converted to a JSON string using `JSON.stringify()`, and then back to an object with `JSON.parse()`.
   - **Pros**:
     - Simple and concise implementation.
     - Works well for basic objects without methods, special objects, or circular references.
   - **Cons**:
     - It cannot handle functions, undefined, or non-serializable values (like `Date`, `RegExp`, etc.), which may lead to data loss or unexpected results.
     - Any prototype methods or properties from the original object are lost in the resulting object.

2. **Deep Copy**
   - **Method**: `a = deepCopy(data);`
   - **Description**: This method uses a custom recursive function to create a deep copy of the object. It explicitly checks for several JavaScript types (like Date and Array) and creates clones accordingly.
   - **Pros**:
     - More versatile and robust, as it can handle a variety of data types, including arrays, objects, and dates.
     - Recursively checks properties, maintaining object references and preserving prototypes.
   - **Cons**:
     - More complex and potentially slower for very large or deeply nested objects due to recursion.
     - May not handle circular references, which can lead to stack overflow errors unless specifically programmed to do so.

### Other Considerations
- **Performance**: In the benchmark results, the **JSON copy** method is faster with approximately 795 executions per second, compared to 562 executions per second for the **deep copy** method. This is attributed to the inherent efficiency of native methods in JavaScript engines.
- **Data Validation**: Ensure that the depth and structure of the object being copied do not exceed limits defined by JavaScript's call stack size, especially for recursive functions like `deepCopy`.

### Other Alternatives
- **Lodash's `cloneDeep` method**: This utility library provides a `cloneDeep` method designed to handle a wide variety of JavaScript types and structures, including arrays, objects, dates, and circular references. It is a good alternative if you need a reliable deep copy solution without implementing your own.
- **Structured Cloning**: For environments that support it (like modern browsers with `structuredClone()`), this built-in method can create a deep copy of almost any JavaScript value, including DOM elements, though it also has limitations in terms of what it can clone.

### Summary
Choosing between **JSON manipulation** and **custom deep copy** hinges on the specific needs of the application in question, such as the types of data being manipulated and performance requirements. For simple structures, JSON methods may suffice, while complex, nested, or varied structures may benefit from a more tailored approach like `deepCopy` or using libraries like Lodash.

Related benchmarks:

Deep copy algo vs JSON manipulation - 6k lines of prices (version: 0)

Comparing performance of: JSON copy vs Deep copy

Created: one year ago by: Guest

Jump to the latest result

JSON copy

Deep copy

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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