Benchmark: RegEx vs Trim - MeasureThat.net

Script Preparation code:

line = "Date/Time, DynamX_SHKX, DynamX_SHKY, DynamX_SHKZ, DynamX_SHKLAT, DynamX_SHKLATAVG, DynamX_SHKRSK, DynamX_SHK_AXL_TOT, DynamX_SHKTY, DynamX_SHKTZ, DynamX_SHK_LAT_TOT, DynamX_ACCMINLAT, DynamX_SHK_AXL_MAX, DynamX_ACCYMAX, DynamX_ACCZMAX, DynamX_SHK_LAT_MAX, DynamX_ACCXAVG, DynamX_ACCYAVG, DynamX_ACCZAVG, DynamX_ACCLATAVG, DynamX_CRPM_MIN, DynamX_CRPM_MAX, DynamX_CPRM_AVG, DynamX_RPM_RAW, DynamX_STUCKEVT, DynamX_STUCKCNT, DynamX_NEGEVT, DynamX_NEGCNT, DynamX_STKSLP_RM, DynamX_STKSLP_Level, DynamX_STICK_RT,AXIAL_SHKRSK,SHKRSK_2019,Vibe_Axl_Max,Vibe_Lat_Max"

Tests:

regex
line.split(/,\s?/);
trim
line.split(",").map(s=>s.trim());

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
regex
trim

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36 Edg/97.0.1072.62

Browser/OS: Chrome 97 on Windows

View result in a separate tab

Test name	Executions per second
regex	615378.2 Ops/sec
trim	1088277.9 Ops/sec

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

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The benchmark is designed to compare two approaches for splitting a CSV string: using regular expressions (RegEx) versus trimming whitespace from each column.

The script preparation code provides a sample CSV string `line` with 10 columns, each containing a mix of numeric and string values. The description mentions that the test aims to measure which approach is faster.

**Options Compared**

Two options are being compared:

1. **RegEx**: Using the `split()` function with a RegEx pattern to split the CSV columns. This involves creating a regular expression pattern to match commas (`\`) followed by optional whitespace characters (`\\s?`).
2. **Trim**: Using the `trim()` method on each column after splitting the string using `.split()`. This removes leading and trailing whitespace from each column.

**Pros and Cons of Each Approach**

* **RegEx**:
	+ Pros: Can handle more complex CSV structures with quotes or escaped characters.
	+ Cons: May be slower due to the overhead of regular expression compilation and matching.
* **Trim**:
	+ Pros: Generally faster, as it only requires iterating through each column once to remove whitespace.
	+ Cons: May not handle all possible edge cases (e.g., quoted values with multiple consecutive spaces).

**Library Usage**

In this benchmark, there is no specific library being used beyond the built-in JavaScript functions (`split()` and `trim()`). However, it's essential to note that if you were using a third-party CSV parsing library, its implementation would likely affect the results.

**Special JS Feature or Syntax**

There are no special features or syntaxes being tested in this benchmark. The focus is solely on comparing two standard JavaScript approaches for splitting CSV strings.

**Other Alternatives**

If you wanted to explore alternative approaches for handling CSV data, some options might include:

* Using a dedicated CSV parsing library (e.g., Papa.js, csv-parser)
* Implementing your own custom CSV parser using loops and string manipulation
* Utilizing streaming or asynchronous processing techniques to improve performance

Keep in mind that the choice of approach depends on the specific requirements and constraints of your project.

**Benchmark Preparation Code**

The provided script preparation code creates a sample CSV string `line` with 10 columns, which is then used as input for both test cases. The HTML preparation code is null, indicating that no additional setup or rendering is necessary before running the benchmark.

Overall, this benchmark provides a straightforward comparison between two standard JavaScript approaches for splitting CSV strings, allowing users to evaluate their performance and choose the best option for their specific use case.

Related benchmarks:

RegEx vs Trim (version: 2)

Compare splitting CSV columns using regex includes spaces or split and trim

Comparing performance of: regex vs trim

Created: 3 years ago by: Registered User

Jump to the latest result

regex

trim

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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