https://github.com/bastidood/js-generators-vs-array-methods

The repository for all the scripts, notebooks, results, and analyses related to my experiments on JavaScript generators and chained array methods.
https://github.com/bastidood/js-generators-vs-array-methods

bun deno javascript node notebook python

Last synced: about 1 month ago
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The repository for all the scripts, notebooks, results, and analyses related to my experiments on JavaScript generators and chained array methods.

• Host: GitHub
• URL: https://github.com/bastidood/js-generators-vs-array-methods
• Owner: BastiDood
• License: mit
• Created: 2024-09-08T13:49:06.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-09-09T01:18:30.000Z (4 months ago)
• Last Synced: 2024-11-22T23:10:05.181Z (about 1 month ago)
• Topics: bun, deno, javascript, node, notebook, python
• Language: Jupyter Notebook
• Homepage: https://dev.to/somedood/i-was-wrong-about-array-methods-and-generators-2ig9
• Size: 1.01 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# JavaScript Generators vs. Array Methods

The repository for all the scripts, notebooks, results, and analyses related to my experiments on JavaScript generators and chained array methods. See the full article ["I was wrong about array methods and generators..."][article] for more details on the methodology, results, interpretations, and conclusions.

[article]: https://dev.to/somedood/i-was-wrong-about-array-methods-and-generators-2ig9

## Generating Random Bytes

The first step is to generate 32 KiB of random data. There are many ways to do this, but I opted to generate them via the [`Crypto#getRandomValues`] function in JavaScript. A Deno script is already available at [`random/random.js`].

[`Crypto#getRandomValues`]: https://developer.mozilla.org/en-US/docs/Web/API/Crypto/getRandomValues

[`random/random.js`]: random/random.js

```bash

# This will overwrite the already existing `random.bin` file!

deno run random/random.js

```

## Running the Experiments

```bash

# Node.js

function run () { node --experimental-default-type=module benchmark/bench.node.js $1 > notebook/node/$1.csv; }

run raw-for-loop

run for-of-loop

run array-method

run generator

```

```bash

# Deno

function run () { deno --quiet --allow-read --allow-hrtime benchmark/bench.deno.js -- $1 > notebook/deno/$1.csv; }

run raw-for-loop

run for-of-loop

run array-method

run generator

```

```bash

# Bun

function run () { bun --silent benchmark/bench.bun.js $1 > notebook/bun/$1.csv; }

run raw-for-loop

run for-of-loop

run array-method

run generator

```

## Analyzing the Data

The Python notebook containing the data analysis is located at [`notebook/analysis.ipynb`].

[`notebook/analysis.ipynb`]: notebook/analysis.ipynb

```bash

conda env create --file notebook/environment.yml

conda activate js-generators-vs-array-methods

# You may now run the Python notebook.

```