do-me

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)

do-me

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",

do-me

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(

do-me

pmtiles extract https://build.protomaps.com/20250303.pmtiles OUTPUT.pmtiles --region=your_subset.geojson

do-me

#!/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"

do-me

huggingface-cli login # logs in with a suitable HF token 
huggingface-cli upload do-me/Eurovoc_English . files # all files must be in cwd

do-me

find . -maxdepth 1 -type f -name "*.webp" 2>/dev/null | sort | awk '{print NR, $0}' | while read num old_name; do new_name=$(printf "%04d.webp" "$num"); mv "$old_name" "$new_name"; done

do-me

import pandas as pd
import json
import gzip

# Load data
df = pd.read_json("your_file.json.gz")

# Round embeddings to 4 decimal places
df["embeddings"] = df["embeddings"].apply(lambda emb: [round(e, 4) for e in emb])

do-me

import requests
import xml.etree.ElementTree as ET
import geopandas as gpd
from io import StringIO
import pandas as pd
from shapely import wkt
import os

def get_feature_types(wfs_url):
    """Extracts feature type names from a WFS GetCapabilities response."""

do-me

import time
import duckdb

def run_duckdb_query():
    # Connect to DuckDB (using an in-memory database as an example)
    conn = duckdb.connect(database=':memory:')

    # Load the spatial extension
    conn.execute("LOAD spatial")