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JSON.parse vs string.splitds
(version: 0)
Comparing performance of:
JSON.parse vs String.split
Created:
2 years ago
by:
Guest
Go to the latest result
Script Preparation code:
var array = new Array(5).fill('1'); var str = JSON.stringify(array);
Tests:
JSON.parse
JSON.parse(str);
String.split
str.split(',')
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
JSON.parse
String.split
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
6 months ago
)
User agent:
Mozilla/5.0 (X11; Linux x86_64; rv:147.0) Gecko/20100101 Firefox/147.0
Browser/OS:
Firefox 147 on Linux
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Embed Benchmark Result
<iframe src="https://measurethat.net/Embed?id=624743" width="100%" height="500px"></iframe>
String.split
18.3M/s
JSON.parse
12.2M/s
View exact numbers
Test name
Executions per second
✓
String.split
18,276,436 Ops/sec
JSON.parse
12,245,641 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the benchmark and explain what's being tested. **Benchmark Purpose** The benchmark is comparing the performance of two approaches: string splitting using `str.split(',')` and JSON parsing using `JSON.parse(str)`. **String Splitting (`str.split(',')`)** The script preparation code creates an array with 5 elements, all filled with the value '1'. The resulting string is then split into individual elements by commas. This test measures the performance of this simple string manipulation technique. Pros: * Easy to implement and understand * Suitable for small strings or simple data processing tasks * Fast execution due to native string splitting mechanism Cons: * May not be efficient for large datasets or complex string manipulation tasks * Can be affected by factors like string length, delimiter complexity, and performance optimizations **JSON Parsing (`JSON.parse(str)`)** The script preparation code creates an array with 5 elements, all filled with the value '1', which is then converted to a JSON string using `JSON.stringify(array)`. This test measures the performance of parsing this JSON string. Pros: * Wide adoption and good performance in modern browsers * Robust error handling and data validation * Can handle complex data structures like arrays, objects, and nested JSON Cons: * May have slower execution compared to native string splitting due to added overhead * Requires a valid JSON input, which may lead to parsing errors or false positives **Library Usage** In this benchmark, the `JSON` library is used. The `JSON.parse()` function takes a JSON string as input and returns an object representing the parsed data. Pros: * Standardized and widely supported API for working with JSON data * Robust error handling and data validation Cons: None notable in this context. **Special JavaScript Feature** There are no special JavaScript features or syntax mentioned in this benchmark. It's a straightforward test of string manipulation techniques. **Alternatives to String Splitting** If `str.split(',')` is not efficient enough for your use case, consider the following alternatives: 1. **RegEx**: Use regular expressions (RegEx) with the `RegExp.prototype.exec()` method to split strings based on specific patterns. 2. **Array.prototype.reduce()`: Apply a reduce function to an array of string elements to concatenate and split them as needed. 3. **Custom implementation**: Write your own custom function for splitting or concatenating strings using bitwise operations, character iteration, or other efficient techniques. **Alternatives to JSON Parsing** If `JSON.parse(str)` is not the best fit, consider the following alternatives: 1. **DOM parser**: Use a DOM-based approach like `XMLSerializer` or `DOMParser` to parse JSON data. 2. **Custom implementation**: Implement your own parsing logic using bitwise operations, character iteration, or other efficient techniques. 3. **Third-party libraries**: Utilize specialized libraries for parsing specific types of data, such as CSV or XML files. Keep in mind that these alternatives may have different performance characteristics and might not be suitable for all use cases.
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