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Crafting new Open Source tools 🔮

Kamil Raczycki RaczeQ

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import math
from itertools import pairwise
import geopandas as gpd
import numpy as np
from shapely import LineString, Point, Polygon, distance
from shapely.coords import CoordinateSequence
def locate_farthest_intersection_point(
import numpy as np
import geopandas as gpd
# keep a geodataframe of all points creating the edges
all_points = gpd.GeoSeries(
clipped_edges_gdf.get_coordinates(ignore_index=True).apply(
lambda row: Point(row["x"], row["y"]), axis=1
),
crs=4326,
)
# this is a code snippet, whole logic with checks is in the final notebook
subgraph_edges = ox.graph_to_gdfs(subgraph, nodes=False, edges=True)
# find all endpoints and check their edges outside. Clip edges exactly at the distance point.
edges_to_clip = {}
for node in set(subgraph.nodes).union([center_node]):
# iterate all edges starting from this node
for u, v, data in G.edges(node, keys=False, data=True):
# if whole edge is inside clipped subgraph - skip it
if v in subgraph:
@RaczeQ
RaczeQ / Snowflake_OvertureMaps_Pubs.sql
Last active January 19, 2026 10:29
Which three places in the UK have the highest density of pubs?
-- Select all pubs in the Great Britain and calculate how many pubs are in a 5 km radius around each pub.
WITH pubs AS (
-- irish_pub....................................eat_and_drink > bar > irish_pub
-- pub..........................................eat_and_drink > bar > pub
SELECT
id,
JSON_EXTRACT_PATH_TEXT(names, 'primary') as name,
JSON_EXTRACT_PATH_TEXT(categories, 'primary') as category,
confidence,
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RaczeQ / Snowflake_OvertureMaps_Buildings.sql
Created January 13, 2026 07:56
Count number of buildings near green areas (600 meters) for Berlin, London and Paris
WITH division_ids AS (
SELECT
id,
CASE
WHEN country = 'DE' THEN 'Berlin'
WHEN country = 'FR' THEN 'Paris'
ELSE 'London'
END as city_name
FROM
OVERTURE_MAPS__DIVISIONS.CARTO.DIVISION
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<title>Trip animation – sequences (deck.gl + MapLibre)</title>
<meta name="viewport" content="width=device-width,initial-scale=1" />
<link href="https://unpkg.com/maplibre-gl@5.12.0/dist/maplibre-gl.css" rel="stylesheet" />
<!-- <link rel="stylesheet" href="https://fonts.googleapis.com/icon?family=Material+Icons" /> -->
<script src="https://unpkg.com/maplibre-gl@5.12.0/dist/maplibre-gl.js"></script>
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RaczeQ / pyarrow_multiprocessing_streaming.py
Last active May 19, 2024 19:41
Pyarrow Multiprocessing with streaming the result
import multiprocessing
from pathlib import Path
from queue import Queue
from time import sleep
from typing import Callable
import pyarrow as pa
import pyarrow.parquet as pq
from tqdm import tqdm