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Multi attributes
(version: 0)
Comparing performance of:
def vs each
Created:
6 years ago
by:
Guest
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HTML Preparation code:
<script src="https://d3js.org/d3.v5.min.js"></script>
Tests:
def
const data = d3.range(50).map(() => ({ x: Math.random() * 300, y: Math.random() * 150 })); const svg = d3.select("body") .append("svg"); svg.selectAll(null) .data(data) .enter() .append("circle") .attr("cx", d => d.x) .attr("cy", d => d.y) .attr("r", 2) .style("fill", "teal")
each
const data = d3.range(50).map(() => ({ cx: Math.random() * 300, cy: Math.random() * 150 })); const svg = d3.select("body") .append("svg"); svg.selectAll(null) .data(data) .enter() .append("circle") .each((d, i, n) => { for (let key in d) { n[i].setAttribute(key, d[key]) } }) .attr("r", 2) .style("fill", "teal")
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
def
each
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
**Overview of the Benchmark** The provided JSON represents a JavaScript benchmark test case, specifically designed to measure the performance of two different approaches: `d3.select()` with an object literal (`"def"`), and `d3.select()` with the `.each()` method (`"each"`). The test is designed to create 50 SVG circles with random x and y coordinates using D3.js (Data-Driven Documents). **Options Compared** The two options compared in this benchmark are: 1. **`d3.select()` with an object literal**: This approach uses the `.attr()` method directly on the `circle` elements, passing the attributes as properties of the object literal. For example: `svg.selectAll(null).enter().append("circle").attr("cx", d => d.x).attr("cy", d => d.y).attr("r", 2).style("fill", "teal")`. 2. **`d3.select()` with the `.each()` method**: This approach uses the `.each()` method to iterate over the data array and set the attributes on each element individually, using a `for...in` loop: `svg.selectAll(null).enter().append("circle").each((d, i, n) => { for (let key in d) { n[i].setAttribute(key, d[key]) } })`.attr("r", 2).style("fill", "teal")`. **Pros and Cons of Each Approach** **`d3.select()` with an object literal** Pros: * Simplifies the code and reduces the number of iterations. * Directly sets attributes on elements without the need for a loop. Cons: * May not work as expected if the data structure changes or if there are duplicate keys in the object literal. * May lead to slower performance if the dataset is large, as D3.js needs to iterate over all elements and apply the transformations. **`d3.select()` with the `.each()` method** Pros: * Allows for more flexibility and customization of the attribute setting process. * Can handle cases where there are duplicate keys in the data object by iterating over the `for...in` loop and setting attributes accordingly. Cons: * Requires an additional iteration over the data array, which may lead to slower performance for large datasets. * May result in slightly more complex code due to the use of a loop. **Other Considerations** The test also uses D3.js versions 5.x, which provides some improvements in performance and functionality compared to older versions. The use of `d3.range()` creates an array of numbers with random values, making it easier to generate large datasets for testing. **Library: d3.js** D3.js (Data-Driven Documents) is a popular JavaScript library used for data visualization. It provides a wide range of tools and methods for manipulating and displaying data in web applications. In this benchmark, D3.js is used for creating the SVG elements, setting attributes, and updating the DOM. **Special JS Feature or Syntax** There are no special JS features or syntax mentioned in the code that would require specific knowledge to understand. **Alternatives** If you're interested in running this benchmark or similar ones on MeasureThat.net, here are some alternatives: 1. **Benchmarking libraries**: There are several other benchmarking libraries available for JavaScript, such as BenchmarkJS, js-benchmark, and micro-benchmark. 2. **Web performance testing tools**: Tools like WebPageTest, Lighthouse, and Google's PageSpeed Insights can also be used to test web application performance. 3. **Custom benchmarking scripts**: You can write your own custom benchmarking script using Node.js or other JavaScript environments. Keep in mind that these alternatives may have different features, APIs, and requirements for writing benchmarks.
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