dd-l1-vienna-gpkg-manifest
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": "deepseek/deepseek-v4-flash",
"base_url": "https://openrouter.ai/api/v1"
}
0:03
Let me start by exploring the GPKG file to understand its structure.
0:03
Bash
ls -la /work/vienna_planning* 2>/dev/null || find /work -name "*.gpkg" -type f 2...
-rw-r--r-- 1 agent agent 524288 Jun 18 23:22 /work/vienna_planning.gpkg
0:09
Good, the file exists. Let me explore its contents using Python with geopandas and other tools.
0:09
Bash
python3 -c "
python3 -c "
import geopandas as gpd
layers = gpd.list_layers('/work/vienna_planning.gpkg')
print(layers)
"
name geometry_type 0 districts Polygon 1 parks MultiPolygon 2 waterbodies Polygon 3 schools Point 4 cafes Point 5 supermarkets Point 6 cycleway_segments LineString
0:16
Now I need to get detailed info for each layer: CRS, feature count, and bounding box. Let me write a Python script that iterates over each layer, reading geometry, getting CRS, counting features, computing bounding box.
0:16
Write
/work/manifest.py
content · 43 lines · py
import geopandas as gpd
import json
GPKG = '/work/vienna_planning.gpkg'
layers_info = gpd.list_layers(GPKG) # name, geometry_type
records = []
for _, row in layers_info.iterrows():
layer_name = row['name']
geom_type = row['geometry_type']
gdf = gpd.read_file(GPKG, layer=layer_name)
# CRS as EPSG:NNNN
crs = gdf.crs
if crs is None:
crs_str = 'None'
else:
crs_str = crs.to_authority()
if crs_str:
crs_str = f"{crs_str[0]}:{crs_str[1]}"
else:
crs_str = str(crs)
feature_count = len(gdf)
# Native bbox in the layer's CRS
bbox = gdf.total_bounds.tolist() # [xmin, ymin, xmax, ymax]
records.append({
'layer_name': layer_name,
'crs': crs_str,
'geometry_type': geom_type,
'feature_count': feature_count,
'bbox': bbox
})
with open('/work/manifest.json', 'w') as f:
json.dump(records, f, indent=2)
print(json.dumps(records, indent=2))
Wrote /work/manifest.py (986 chars).
0:19
Let me run the script.
0:19
Bash
cd /work && python manifest.py
[
{
"layer_name": "districts",
"crs": "EPSG:31287",
"geometry_type": "Polygon",
"feature_count": 22,
"bbox": [
623867.3888224852,
481236.5836125494,
626371.3079994549,
484403.7315526943
]
},
{
"layer_name": "parks",
"crs": "EPSG:31287",
"geometry_type": "MultiPolygon",
"feature_count": 119,
"bbox": [
623851.990195953,
481200.6674012489,
626620.9438865517,
485539.3479671855
]
},
{
"layer_name": "waterbodies",
"crs": "EPSG:31287",
"geometry_type": "Polygon",
"feature_count": 33,
"bbox": [
624288.8521056126,
481236.66320640914,
626747.8611584986,
484132.0212685799
]
},
{
"layer_name": "schools",
"crs": "EPSG:31287",
"geometry_type": "Point",
"feature_count": 40,
"bbox": [
624000.002417057,
481214.73871311604,
626259.5421406503,
484178.87865010765
]
},
{
"layer_name": "cafes",
"crs": "EPSG:31287",
"geometry_type": "Point",
"feature_count": 392,
"bbox": [
623796.529863561,
481107.2540129812,
626399.5618121764,
484498.9209005649
]
},
{
"layer_name": "supermarkets",
"crs": "EPSG:31287",
"geometry_type": "Point",
"feature_count": 87,
"bbox": [
623794.0549950565,
481148.38703723426,
626392.6164786755,
484489.91954147833
]
},
{
"layer_name": "cycleway_segments",
"crs": "EPSG:31287",
"geometry_type": "LineString",
"feature_count": 271,
"bbox": [
623787.4932131292,
481134.9325878215,
626619.1631922598,
485245.6624853243
]
}
]
0:21
The script ran successfully and produced the manifest.json file. Let me verify the output file looks good.
0:21
Read
/work/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 ]
0:25
The manifest.json has been created with all 7 layers catalogued with the required fields. Let me verify the output is clean valid JSON.
0:25