Benchmark: imperative-prop-selector4

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.26.1/ramda.min.js"></script>

Script Preparation code:

var mock = {
  name: 'José Manuel',
  surname: 'Lucas',
  organization: {
    id: 11,
    selfcare: {
      id: 12355,
      customization: {
        colors: {
          foreground: '#fff',
          background: {
            primary: '#ff0000',
          }
        }
      }
    }
  },
};

const getName = ({ name }) => name;

const getOrganization = obj => obj && obj.organization;

const getSelfcare = (obj) => {
  const a = getOrganization(obj);
  return a && a.selfcare;
};

const getCustomization = (obj) => {
  const a = getSelfcare(obj);
  return a && a.customization;
};

const getColors = (obj) => {
  const a = getCustomization(obj);
  return a && a.colors;
};

var imperativePath = (obj) => {
  const a = getColors(obj);
  return a && a.foreground;
};

const { pipe, prop, defaultTo } = R;

const organizationSelector = prop('organization');
const selfcareSelector = pipe(
  organizationSelector,
  prop('selfcare'),
);
 
const customizationSelector = pipe(
  selfcareSelector,
  prop('customization'),
);
  
const colorsSelector = pipe(
  customizationSelector,
  prop('colors'),
);

var ramdaPath = pipe(
  colorsSelector,
  prop('foreground'),
);

// Ensuring that all functions work properly
if (ramdaPath(mock) !== '#fff') {
  throw new Error('Invalid ramda path');
}

if (imperativePath(mock) !== '#fff') {
  throw new Error('Invalid imperative path');
}

Tests:

Imperative path
imperativePath(mock);
Ramda path
ramdaPath(mock);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Imperative path
Ramda path

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark and explain what is being tested.

**Benchmark Overview**

The benchmark is designed to compare two approaches to select a specific value from an object: imperative (using a simple chain of functions) and Ramda's `pipe` function.

**Imperative Path**

The imperative path uses a series of individual functions to navigate the object:

1. `getOrganization(obj)` returns the organization object.
2. `getSelfcare(a)` returns the selfcare object if `a` is not null or undefined.
3. `getCustomization(b)` returns the customization object if `b` is not null or undefined.
4. `getColors(c)` returns the colors object if `c` is not null or undefined.
5. `imperativePath(obj)` returns the foreground color if `obj` has a colors object and the foreground property exists.

The entire chain of functions is executed using the `imperativePath(mock)` call.

**Ramda Path**

The Ramda path uses the `pipe` function to compose multiple functions together:

1. `organizationSelector(prop('organization'))`: returns the organization object.
2. `selfcareSelector(organizationSelector)`: returns the selfcare object if it exists in the organization.
3. `customizationSelector(selfcareSelector)`: returns the customization object if it exists in the selfcare.
4. `colorsSelector(customizationSelector)`: returns the colors object if it exists in the customization.
5. `prop('foreground')`: returns the foreground color.

The entire chain of functions is executed using the `ramdaPath(mock)` call.

**Comparison**

The benchmark measures the execution time of both approaches to retrieve the foreground color from the mock object.

**Pros and Cons**

* **Imperative Path**: Pros:
	+ Easy to understand for those familiar with imperative programming.
	+ May be more efficient for small objects.
Cons:
	+ Can lead to deep function calls, which can be slower due to overhead.
	+ Requires explicit error handling (e.g., `getSelfcare(a)` returns null).
* **Ramda Path**: Pros:
	+ Composes functions in a declarative way, making the code more concise and easier to read.
	+ Reduces overhead by executing multiple functions in a single call.
Cons:
	+ May be less intuitive for those unfamiliar with functional programming.
	+ Requires additional dependencies (e.g., Ramda library).

**Other Considerations**

* **Memory Usage**: Both approaches have similar memory usage, as they both access the same properties of the object.

**Library and Special JS Feature**

The benchmark uses the Ramda library, which provides a set of functional programming utilities. The `pipe` function is used to compose multiple functions together in a declarative way.

Note that there are no special JavaScript features or syntaxes used in this benchmark.

Related benchmarks:

imperative-prop-selector4 (version: 0)

Comparing performance of: Imperative path vs Ramda path

Created: 7 years ago by: Registered User

Jump to the latest result

Imperative path

Ramda path

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):