Add downsample_country_borders.py script here instead.

scripts/downsample_country_borders.py

@@ -0,0 +1,118 @@
+#!/usr/bin/env python3
+"""
+A script I generated with AI to downsample the world country borders reference image we were provided to a suitable geojson size for frontend use.
+
+I think as data updates do come to the other types of data (e.g. NUTS) which exist and are defined here on the backend, this makes sense to live here,
+but the exported image then gets used and saved on the frontent.
+
+Downsample GeoJSON-like boundary files to a target max size.
+Usage example:
+python _scripts/downsample_geojson.py "World Bank Official Boundaries - Admin 0(1).png" --output "/
+  downsample.geojson" --max-mb 6
+
+
+Example output:
+step=1 size=80140386
+step=2 size=41256344
+step=3 size=28353567
+step=4 size=21702896
+step=5 size=17520696
+step=6 size=14747263
+step=8 size=11331385
+step=10 size=9310428
+step=12 size=7977292
+step=15 size=6655828
+step=20 size=5353581
+
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+
+def is_point(item: object) -> bool:
+    return (
+            isinstance(item, list)
+            and len(item) >= 2
+            and isinstance(item[0], (int, float))
+            and isinstance(item[1], (int, float))
+    )
+
+
+def simplify_line(line: list, step: int) -> list:
+    if not line:
+        return line
+    points = line[::step] if step > 1 else line[:]
+    if points[0] != line[0]:
+        points.insert(0, line[0])
+    if points[-1] != line[-1]:
+        points.append(line[-1])
+    return [[round(p[0], 5), round(p[1], 5)] + p[2:] for p in points]
+
+
+def simplify_coords(coords: object, step: int) -> object:
+    if not isinstance(coords, list):
+        return coords
+    if coords and is_point(coords[0]):
+        return simplify_line(coords, step)
+    return [simplify_coords(item, step) for item in coords]
+
+
+def simplify_geom(geom: dict, step: int) -> dict:
+    out = dict(geom)
+    if "coordinates" in out:
+        out["coordinates"] = simplify_coords(out["coordinates"], step)
+    if "geometries" in out and isinstance(out["geometries"], list):
+        out["geometries"] = [simplify_geom(item, step) for item in out["geometries"]]
+    return out
+
+
+def downsample_geojson(data: dict, step: int) -> dict:
+    out = dict(data)
+    features = out.get("features")
+    if isinstance(features, list):
+        next_features = []
+        for feature in features:
+            updated = dict(feature)
+            if isinstance(feature.get("geometry"), dict):
+                updated["geometry"] = simplify_geom(feature["geometry"], step)
+            next_features.append(updated)
+        out["features"] = next_features
+    return out
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Downsample boundary GeoJSON to target size.")
+    parser.add_argument("input", type=Path, help="Input file path (GeoJSON text)")
+    parser.add_argument("--output", type=Path, help="Output file path")
+    parser.add_argument("--max-mb", type=float, default=6.0, help="Target max size in MB")
+    args = parser.parse_args()
+
+    input_path = args.input
+    output_path = args.output or input_path.with_name(f"{input_path.stem} - downsampled.geojson")
+    max_bytes = int(args.max_mb * 1024 * 1024)
+
+    with input_path.open("r", encoding="utf-8") as f:
+        data = json.load(f)
+
+    steps = [1, 2, 3, 4, 5, 6, 8, 10, 12, 15, 20, 25, 30, 40, 50, 75, 100]
+    for step in steps:
+        output_data = downsample_geojson(data, step)
+        text = json.dumps(output_data, separators=(",", ":"))
+
+        output_path.write_text(text, encoding="utf-8")
+        size = output_path.stat().st_size
+        print(f"step={step} size={size}")
+        if size < max_bytes:
+            print(f"output={output_path}")
+            print(f"final_size_bytes={size}")
+            return
+
+    raise SystemExit(f"Could not reduce file below {args.max_mb} MB")
+
+
+if __name__ == "__main__":
+    main()