dd-l1-vienna-gpkg-manifest

Status: done
Score: 100
Duration: 1:04
Cost: 0.11¢
Model: google/gemma-4-26b-a4b-it

Map (reference ← swipe → agent)

0:00
Inherited a GPKG (vienna_planning) from a colleague who retired last week. Before I commit to scripting against it I need a one-page manifest so I can see what's in there and decide which layers actually feed next month's councillor briefing. Catalog the contents and give me one record per layer. Output manifest.json — a JSON list of these records. Each record in the list must be a JSON object with exactly five keys: `layer_name` as a string, `crs` as a string in `EPSG:NNNN` form, `geometry_type` as a string matching the layer's native type (e.g. `Point`, `LineString`, `Polygon`, `MultiPolygon`), `feature_count` as an integer, and `bbox` as a list of four numbers `[xmin, ymin, xmax, ymax]` in the layer's native CRS.
0:00
System info 
{
  "adapter": "openrouter",
  "model": "google/gemma-4-26b-a4b-it",
  "base_url": "https://openrouter.ai/api/v1"
}
0:01
Bash ls -F 
vienna_planning.gpkg
0:28
Write /work/solve.py
content · 58 lines · py 
import geopandas as gpd
import json
import fiona

def get_layer_info(gpkg_path):
    layers = fiona.listlayers(gpkg_path)
    manifest = []

    for layer_name in layers:
        # Load the layer
        gdf = gpd.read_file(gpkg_path, layer=layer_name)
        
        # Get CRS
        crs = gdf.crs.to_string()
        # If it's not in EPSG:NNNN format, we might need to handle it, 
        # but standard geopandas/pyproj usually provides it.
        # Let's refine the CRS string to match the requirement.
        if crs.startswith("EPSG:"):
            epsg_code = crs
        else:
            # Try to get the EPSG code from the CRS object
            epsg_code = f"EPSG:{gdf.crs.to_epsg()}" if gdf.crs.to_epsg() else crs

        # Get geometry type
        # gdf.geometry.type returns a single type if all are the same, 
        # or a collection. We want the native type.
        # In GeoPandas, gdf.geom_type is the type of the geometry column.
        geom_type = gdf.geom_type.iloc[0] if not gdf.empty else "None"
        
        # Get feature count
        feature_count = len(gdf)
        
        # Get bbox
        # bbox is (minx, miny, maxx, maxy)
        if not gdf.empty:
            bbox = list(gdf.total_bounds)
        else:
            bbox = [0.0, 0.0, 0.0, 0.0]

        manifest.append({
            "layer_name": layer_name,
            "crs": epsg_code,
            "geometry_type": geom_type,
            "feature_count": feature_count,
            "bbox": bbox
        })
    
    return manifest

if __name__ == "__main__":
    gpkg_path = "vienna_planning.gpkg"
    manifest_data = get_layer_info(gpkg_path)
    
    with open("manifest.json", "w") as f:
        json.dump(manifest_data, f, indent=4)

    print("Successfully created manifest.json")

Wrote /work/solve.py (1786 chars).
0:29
Bash python solve.py 
Successfully created manifest.json
0:31
Read manifest.json 
     1	[
     2	    {
     3	        "layer_name": "districts",
     4	        "crs": "EPSG:31287",
     5	        "geometry_type": "Polygon",
     6	        "feature_count": 22,
     7	        "bbox": [
     8	            623867.3888224852,
     9	            481236.5836125494,
    10	            626371.3079994549,
    11	            484403.7315526943
    12	        ]
    13	    },
    14	    {
    15	        "layer_name": "parks",
    16	        "crs": "EPSG:31287",
    17	        "geometry_type": "MultiPolygon",
    18	        "feature_count": 119,
    19	        "bbox": [
    20	            623851.990195953,
    21	            481200.6674012489,
    22	            626620.9438865517,
    23	            485539.3479671855
    24	        ]
    25	    },
    26	    {
    27	        "layer_name": "waterbodies",
    28	        "crs": "EPSG:31287",
    29	        "geometry_type": "Polygon",
    30	        "feature_count": 33,
    31	        "bbox": [
    32	            624288.8521056126,
    33	            481236.66320640914,
    34	            626747.8611584986,
    35	            484132.0212685799
    36	        ]
    37	    },
    38	    {
    39	        "layer_name": "schools",
    40	        "crs": "EPSG:31287",
    41	        "geometry_type": "Point",
    42	        "feature_count": 40,
    43	        "bbox": [
    44	            624000.002417057,
    45	            481214.73871311604,
    46	            626259.5421406503,
    47	            484178.87865010765
    48	        ]
    49	    },
    50	    {
    51	        "layer_name": "cafes",
    52	        "crs": "EPSG:31287",
    53	        "geometry_type": "Point",
    54	        "feature_count": 392,
    55	        "bbox": [
    56	            623796.529863561,
    57	            481107.2540129812,
    58	            626399.5618121764,
    59	            484498.9209005649
    60	        ]
    61	    },
    62	    {
    63	        "layer_name": "supermarkets",
    64	        "crs": "EPSG:31287",
    65	        "geometry_type": "Point",
    66	        "feature_count": 87,
    67	        "bbox": [
    68	            623794.0549950565,
    69	            481148.38703723426,
    70	            626392.6164786755,
    71	            484489.91954147833
    72	        ]
    73	    },
    74	    {
    75	        "layer_name": "cycleway_segments",
    76	        "crs": "EPSG:31287",
    77	        "geometry_type": "LineString",
    78	        "feature_count": 271,
    79	        "bbox": [
    80	            623787.4932131292,
    81	            481134.9325878215,
    82	            626619.1631922598,
    83	            485245.6624853243
    84	        ]
    85	    }
    86	]
1:02