window.foo = {'cat': 'cat', 'dog': 'dog', 'bird': 'bird'};
window.foo = {'cat': 'cat', 'dog': 'dog', 'bird': 'bird'};
_.isEqual(window.foo, window.bar)
JSON.stringify(window.foo) === JSON.stringify(window.bar);
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
isEqual | |
stringify |
Test name | Executions per second |
---|---|
isEqual | 841503.9 Ops/sec |
stringify | 680160.9 Ops/sec |
Let's break down the provided Benchmark Definition json and explain what is tested, compared options, pros/cons, library usage, special JS features, and other considerations.
Benchmark Overview
The benchmark measures the performance of two JavaScript operations:
isEqual
(using Lodash's _.isEqual
function)stringify
(by comparing the stringified output of two objects using JSON.stringify
)Options Compared
The benchmark compares two options for each test case:
isEqual
: Uses the popular Lodash library to compare two objects.Pros and Cons of Each Approach
Lodash-based isEqual
:
Pros:
Cons:
Built-in comparison:
Pros:
Cons:
Other Considerations
window.foo
and window.bar
objects to compare, which are defined in the Html Preparation Code
.JSON.stringify
method is used to serialize the objects before comparison. This can affect performance if the resulting stringified output is large.Library Usage
The Lodash library is used in the Benchmark Definition
json for the isEqual
test case. Lodash provides a robust and accurate way to compare objects, handling deeper structures and circular references.
Special JS Features
None are explicitly mentioned in this benchmark.
Alternatives
For alternative approaches, you could consider using:
JSON.stringify
comparison: Instead of relying on the Lodash library for equality checks, use a built-in JavaScript function like JSON.stringify
to compare objects.fast-equal
or deep-equal
, that could be used in place of Lodash.[a, b] === [c, d]
). However, these may not work across all platforms and browsers.Keep in mind that the choice of approach ultimately depends on your specific requirements, performance constraints, and personal preference.