Dominik Weckmüller do-me

Joint Research Centre (JRC) Organizational Table (06/2025)

Open https://op.europa.eu/en/web/who-is-who/organization/-/organization/JRC
Run this code snippet multiple times in the browser console document.querySelectorAll('.op-icon-more').forEach(button => button.click()); (wait between the runs; it clicks all plus icons to expand the underlying info)
Either save the page as pdf or if you're an expert, copy the HTML from the DOM
Use Gemini to extract the following table with this prompt: Create a table from this information with the following columns: Level 1, Level 2, Level 3, Level 4, Role, Name, Contact, Unit Code

You can do the same for any other EU institution or on higher levels, like the EC adapting just the columns (levels of hierarchy).

	rsync -avz --progress your_host:/home/disk_image/to_download/large_file.vdi .

	# host must look like this in config
	Host your_host
	HostName yourserver.de
	User root
	IdentityFile ~/.ssh/[email protected]/ed25519/openssh/id_ed25519

	// https://pen.org/banned-words-list/ on 5/5/2025
	let words = [];
	document.querySelectorAll('td').forEach(cell => {
	const text = cell.textContent.trim();
	if (text) {
	words.push(text);
	}
	});
	words.sort((a, b) => a.toLowerCase().localeCompare(b.toLowerCase()));
	console.log(words.join('\n'));

	<!DOCTYPE html>
	<html>
	<head>
	<meta charset="utf-8" />
	<title>MapLibre Draw Rectangle</title>
	<meta name="viewport" content="initial-scale=1,maximum-scale=1,user-scalable=no" />

	<!-- MapLibre GL JS -->
	<script src='https://unpkg.com/[email protected]/dist/maplibre-gl.js'></script>
	<link href='https://unpkg.com/[email protected]/dist/maplibre-gl.css' rel='stylesheet' />

	import json, gzip

	def load_json(file_path):
	try:
	with gzip.open(file_path, 'rt', encoding='utf-8') as f:
	return json.load(f)
	except OSError: #if the file is not gzipped
	with open(file_path, 'r', encoding='utf-8') as f:
	return json.load(f)

	import pydeck as pdk

	df = pd.read_json("https://raw.githubusercontent.com/visgl/deck.gl-data/master/examples/line/heathrow-flights.json")

	INITIAL_VIEW_STATE = pdk.ViewState(latitude=47.65, longitude=7, zoom=4.5, max_zoom=16, pitch=50, bearing=0)

	line_layer = pdk.Layer(
	"LineLayer",
	df,
	get_source_position="start",

	import pydeck as pdk
	import pandas as pd
	import numpy as np

	### sample data
	import duckdb
	import geopandas
	df = duckdb.sql(f"SELECT * FROM 'geonames_23_03_2025.parquet' WHERE \"1\" = 'London' \
	AND \"8\" = 'GB' ").df()
	gdf = geopandas.GeoDataFrame(

	#!/bin/bash

	# Set the input directory (where your PDFs are)
	INPUT_DIR="." # Current directory, change if needed

	# Set the output file name
	OUTPUT_FILE="llm_ready.txt"

	# Set the temporary directory
	TEMP_DIR="temp_pdf_text"