daily-crypto

Daily crypto market information data visualization art experiments

Fork from: daily-crypto

Large number 3d visualization script

Example of the kind of visualization this can generate. Results are optimized using the GLTF instancing extension.

Fetch Prices

Fetch the current prices of the top 100 cryptocurrencies from Coingecko API: https://madjin.github.io/daily-crypto/data.txt

#!/bin/bash

# Set the API endpoint URL
API_URL="https://api.coingecko.com/api/v3/coins/markets"

# Set the parameters for the API request
PARAMS="?vs_currency=usd&order=market_cap_desc&per_page=100&page=1&sparkline=false"

# Make the API request and save the response to a file
curl -s -o prices.json "${API_URL}${PARAMS}"

# Parse the JSON response and extract the price for each cryptocurrency
for row in $(cat prices.json | jq -r '.[] | @base64'); do
    _jq() {
     echo ${row} | base64 --decode | jq -r ${1}
    }
    name=$(_jq '.name')
    price=$(_jq '.current_price')
    echo "${name}: ${price}"
done

Make it executable with the command chmod +x fetch_prices.sh. Then, you can add it as a daily cronjob by running the command crontab -e and adding the following line:

0 0 * * * /path/to/fetch_prices.sh

This will run the script at midnight every day and output the current prices in USD of the top 100 cryptocurrencies to the console.

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Create Cubes

Blender Python script that

• reads the values from column 2 (separated by :) in data.txt
• creates and resizes a cube in terms of volume based on that value
• centers the origin to each geometry, applies transforms
• exports a glTF of each cube as a separate file
• renames filename same as the node
• saves the files into new timestamped folder based on MM-DD-YYYY

import bpy
import math
import os
from datetime import datetime

# Set the path to the data file
data_file = "/path/to/data.txt"

# Define a function to calculate the size of a cube based on its volume
def get_cube_size(volume):
    size = math.pow(volume, 1/3)
    return size

# Get the current date
today = datetime.today().strftime("%m-%d-%Y")

# Create a new folder for the glTF files
output_folder = os.path.join("/path/to/output/folder", today)
if not os.path.exists(output_folder):
    os.makedirs(output_folder)

# Open the data file and read the values
with open(data_file, "r") as f:
    lines = f.readlines()

# Loop through the lines and create a cube for each value
for line in lines:
    # Parse the value from the line
    parts = line.strip().split(":")
    name = parts[0].strip()
    volume = float(parts[1].strip())
    
    # Calculate the size of the cube based on its volume
    size = get_cube_size(volume)
    
    # Create a new cube
    bpy.ops.mesh.primitive_cube_add(size=size, enter_editmode=False, location=(0, 0, 0))
    cube = bpy.context.active_object
    
    # Rename the cube based on the value
    cube.name = name
    
    # Center the origin to the geometry
    bpy.ops.object.origin_set(type="ORIGIN_GEOMETRY", center="BOUNDS")
    
    # Apply transforms
    bpy.ops.object.transform_apply(location=True, rotation=True, scale=True)
    
    # Export the cube as a glTF file
    filename = name.replace(" ", "_").replace(".", "").replace(",", "").replace("(", "").replace(")", "") + ".gltf"
    filepath = os.path.join(output_folder, filename)
    bpy.ops.export_scene.gltf(filepath=filepath, export_format="GLTF_SEPARATE", export_apply=True)
    
    # Delete the cube
    bpy.ops.object.delete()

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Ideas

Create a daily "blockchain"?

Separate each cube by distance, use gltf-transform to merge into 1 file?

Texture each cube the icon of the coin / create a huge texture atlas for top 100 coins