Pyodide benchmarks support

MeasureThat.net now supports Python in-browser benchmarks via Pyodide. This new feature allows users to write and execute Python code directly within their web browser, enabling seamless performance testing and benchmarking of Python scripts.

What is Pyodide?

Pyodide is an open-source project that brings the Python runtime to the web browser by compiling the Python interpreter to WebAssembly. This allows Python code to run in the browser with near-native performance. Pyodide includes a comprehensive set of Python packages, such as NumPy, Pandas, and Matplotlib, making it a powerful tool for scientific computing and data analysis in the browser.

How Pyodide Works

Pyodide works by loading the Python interpreter and its packages into the browser's memory. Here’s a high-level overview of how it operates:

1. Loading Pyodide: The Pyodide JavaScript library is loaded into the browser, which initializes the WebAssembly-compiled Python interpreter.
2. Loading Packages: Pyodide can dynamically load additional Python packages as needed. These packages are also compiled to WebAssembly and can be imported and used just like in a regular Python environment.
3. Running Python Code: Users can write Python code in the browser, which Pyodide executes. The results of the execution can be displayed directly in the web page or used for further processing.

Example

Here is a example of how to setup Pyodide benchmark (based on this benchmark.):

// HTML Preparation code
<script src='https://cdn.jsdelivr.net/pyodide/v0.26.3/full/pyodide.js'></script>

// Script preparation code - load Pyodide and initialize it
async function globalMeasureThatScriptPrepareFunction() {
      window.globalPyodide = await loadPyodide();
      console.log(globalPyodide.runPython('import sys; sys.version'));
    await globalPyodide.loadPackage('numpy');
    await globalPyodide.runPython(`
        import numpy as np
        import random

        def bubble_sort(arr):
            n = len(arr)
            for i in range(n):
                for j in range(0, n-i-1):
                    if arr[j] > arr[j+1]:
                        arr[j], arr[j+1] = arr[j+1], arr[j]
            return arr

        def efficient_sort(arr):
            return sorted(arr)

        def generate_random_array(size, lower_bound, upper_bound):
            return [random.randint(lower_bound, upper_bound) for _ in range(size)]

        # Generate a random array
        random_array = generate_random_array(250, 1, 500000)
        print("Original array:", random_array)
    `);    
}

// Test case #1:
window.globalPyodide.runPython(`
    bubble_sort(random_array.copy())
`);

// Test case #2:
window.globalPyodide.runPython(`
    efficient_sort(random_array.copy())
`);