| // JS version of Python partition function | |
| function partition(s, delimiter) { | |
| const i = s.indexOf(delimiter); | |
| if (i >= 0) return [s.substring(0, i), s[i], s.substring(i + 1)]; | |
| else return [s, "", ""]; | |
| } | |
| // JS version of Python rpartition function | |
| function rpartition(s, delimiter) { | |
| const i = s.lastIndexOf(delimiter); |
This document contains step-by-step notes for how to run Elasticsearch and Kibana in local Docker containers.
This assumes three terminal windows are available: A (control), B (Elasticsearch) and C (Kibana). Note also that the stack version included here may be varied, although it should remain identical across both components.
In terminal A, run:
| from argparse import ArgumentParser | |
| from io import BytesIO | |
| from PIL.Image import open as open_image | |
| def image_to_ansi(data, scale=1): | |
| # TODO: optimise this algorithm - it's pretty brute-force right now | |
| image = open_image(BytesIO(data)) | |
| width, height = image.size |
| #!/usr/bin/env bash | |
| MENU=$1 | |
| OPTION=$2 | |
| MENU_PATH=${HOME}/.alt/${MENU} | |
| cd ${MENU_PATH} | |
| if [ ! -z "$OPTION" ] | |
| then |
| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>Snake Game</title> | |
| <style> | |
| body { | |
| display: flex; | |
| justify-content: center; |
