dd-l1-vienna-gpkg-manifest

Status: done

Score: 1.000

Duration: 1:56

Cost: 0.77¢

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"
}

0:04

Bash ls -F

vienna_planning.gpkg

0:22

Write /work/solve.py

content · 67 lines · py

import geopandas as gpd
import json

def main():
    gpkg_path = 'vienna_planning.gpkg'
    
    try:
        import fiona
    except ImportError:
        print("fiona not installed")
        return

    layers = fiona.listlayers(gpkg_path)
    manifest = []

    for layer in layers:
        gdf = gpd.read_file(gpkg_path, layer=layer)
        
        # layer_name
        layer_name = layer
        
        # crs
        # We want EPSG:NNNN format. 
        # gdf.crs might be a string, a dict, or a pyproj object.
        crs_str = str(gdf.crs)
        # Try to extract EPSG code if it's a complex CRS
        if "EPSG" not in crs_str:
            try:
                epsg_code = gdf.crs.to_epsg()
                if epsg_code:
                    crs_str = f"EPSG:{epsg_code}"
            except Exception:
                pass
        
        # geometry_type
        # gdf.geometry.type returns a single type if all are same, 
        # or a collection type. We want the native type.
        # Let's check the first geometry or use fiona metadata
        layer_info = fiona.info(gpkg_path, layer=layer)
        geom_type = layer_info['geometry']
        # fiona might return 'Polygon' or 'MultiPolygon'.
        # The prompt examples: 'Point', 'LineString', 'Polygon', 'MultiPolygon'
        # Usually fiona types match these closely.
        
        # feature_count
        feature_count = len(gdf)
        
        # bbox
        # bbox is [xmin, ymin, xmax, ymax]
        bbox = list(gdf.total_bounds)
        
        manifest.append({
            "layer_name": layer_name,
            "crs": crs_str,
            "geometry_type": geom_type,
            "feature_count": feature_count,
            "bbox": bbox
        })

    with open('manifest.json', 'w') as f:
        json.dump(manifest, f, indent=4)
    
    print(f"Manifest created with {len(manifest)} layers.")

if __name__ == "__main__":
    main()

Wrote /work/solve.py (1924 chars).

0:24

Bash python solve.py

Traceback (most recent call last):
  File "/work/solve.py", line 66, in <module>
    main()
    ~~~~^^
  File "/work/solve.py", line 39, in main
    layer_info = fiona.info(gpkg_path, layer=layer)
                 ^^^^^^^^^^
AttributeError: module 'fiona' has no attribute 'info'

0:40

Write /work/solve.py

content · 65 lines · py

import geopandas as gpd
import json
import fiona

def get_crs_string(gdf):
    """Ensures CRS is in EPSG:NNNN format."""
    if gdf.crs is None:
        return "Unknown"
    
    try:
        epsg = gdf.crs.to_epsg()
        if epsg:
            return f"EPSG:{epsg}"
        else:
            # Fallback to string representation if EPSG cannot be determined
            return str(gdf.crs)
    except Exception:
        return str(gdf.crs)

def main():
    gpkg_path = 'vienna_planning.gpkg'
    
    layers = fiona.listlayers(gpkg_path)
    manifest = []

    for layer in layers:
        # Use fiona to get metadata without loading the whole dataset if possible,
        # but for bbox and feature count we need to inspect it.
        # Reading with geopandas is fine for this task.
        gdf = gpd.read_file(gpkg_path, layer=layer)
        
        # layer_name
        layer_name = layer
        
        # crs
        crs_str = get_crs_string(gdf)
        
        # geometry_type
        # The prompt asks for the 'native type' and gives examples: 'Point', 'LineString', 'Polygon', 'MultiPolygon'
        # gdf.geometry.type returns the type of the geometry series (e.g. 'Polygon')
        geom_type = gdf.geometry.type
        
        # feature_count
        feature_count = len(gdf)
        
        # bbox
        # bbox is [xmin, ymin, xmax, ymax]
        bbox = list(gdf.total_bounds)
        
        manifest.append({
            "layer_name": layer_name,
            "crs": crs_str,
            "geometry_type": geom_type,
            "feature_count": feature_count,
            "bbox": bbox
        })

    with open('manifest.json', 'w') as f:
        json.dump(manifest, f, indent=4)
    
    print(f"Manifest created with {len(manifest)} layers.")

if __name__ == "__main__":
    main()

Wrote /work/solve.py (1809 chars).

0:45

Bash python solve.py

Traceback (most recent call last):
  File "/work/solve.py", line 64, in <module>
    main()
    ~~~~^^
  File "/work/solve.py", line 59, in main
    json.dump(manifest, f, indent=4)
    ~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.14/json/__init__.py", line 181, in dump
    for chunk in iterable:
                 ^^^^^^^^
  File "/usr/local/lib/python3.14/json/encoder.py", line 442, in _iterencode
    yield from _iterencode_list(o, _current_indent_level)
  File "/usr/local/lib/python3.14/json/encoder.py", line 326, in _iterencode_list
    yield from chunks
  File "/usr/local/lib/python3.14/json/encoder.py", line 413, in _iterencode_dict
    yield from chunks
  File "/usr/local/lib/python3.14/json/encoder.py", line 451, in _iterencode
    newobj = _default(o)
  File "/usr/local/lib/python3.14/json/encoder.py", line 182, in default
    raise TypeError(f'Object of type {o.__class__.__name__} '
                    f'is not JSON serializable')
TypeError: Object of type Series is not JSON serializable
when serializing dict item 'geometry_type'
when serializing list item 0

1:03

Write /work/solve.py

content · 64 lines · py

import geopandas as gpd
import json
import fiona

def get_crs_string(gdf):
    """Ensures CRS is in EPSG:NNNN format."""
    if gdf.crs is None:
        return "Unknown"
    
    try:
        epsg = gdf.crs.to_epsg()
        if epsg:
            return f"EPSG:{epsg}"
        else:
            # Fallback to string representation if EPSG cannot be determined
            return str(gdf.crs)
    except Exception:
        return str(gdf.crs)

def main():
    gpkg_path = 'vienna_planning.gpkg'
    
    layers = fiona.listlayers(gpkg_path)
    manifest = []

    for layer in layers:
        gdf = gpd.read_file(gpkg_path, layer=layer)
        
        # layer_name
        layer_name = layer
        
        # crs
        crs_str = get_crs_string(gdf)
        
        # geometry_type
        # gdf.geometry.type returns a single type (e.g. 'Polygon') 
        # but it's a pandas Series if not handled correctly.
        # Actually gdf.geometry.type in recent geopandas returns a string or type.
        # Let's be explicit.
        geom_type = str(gdf.geometry.type)
        
        # feature_count
        feature_count = len(gdf)
        
        # bbox
        # bbox is [xmin, ymin, xmax, ymax]
        bbox = list(gdf.total_bounds)
        
        manifest.append({
            "layer_name": layer_name,
            "crs": crs_str,
            "geometry_type": geom_type,
            "feature_count": feature_count,
            "bbox": bbox
        })

    with open('manifest.json', 'w') as f:
        json.dump(manifest, f, indent=4)
    
    print(f"Manifest created with {len(manifest)} layers.")

if __name__ == "__main__":
    main()

Wrote /work/solve.py (1650 chars).

1:06

Bash python solve.py

Manifest created with 7 layers.

1:08

Bash cat manifest.json

[
    {
        "layer_name": "districts",
        "crs": "EPSG:31287",
        "geometry_type": "0     Polygon\n1     Polygon\n2     Polygon\n3     Polygon\n4     Polygon\n5     Polygon\n6     Polygon\n7     Polygon\n8     Polygon\n9     Polygon\n10    Polygon\n11    Polygon\n12    Polygon\n13    Polygon\n14    Polygon\n15    Polygon\n16    Polygon\n17    Polygon\n18    Polygon\n19    Polygon\n20    Polygon\n21    Polygon\ndtype: str",
        "feature_count": 22,
        "bbox": [
            623867.3888224852,
            481236.5836125494,
            626371.3079994549,
            484403.7315526943
        ]
    },
    {
        "layer_name": "parks",
        "crs": "EPSG:31287",
        "geometry_type": "0      MultiPolygon\n1      MultiPolygon\n2      MultiPolygon\n3      MultiPolygon\n4      MultiPolygon\n           ...     \n114    MultiPolygon\n115    MultiPolygon\n116    MultiPolygon\n117    MultiPolygon\n118    MultiPolygon\nLength: 119, dtype: str",
        "feature_count": 119,
        "bbox": [
            623851.990195953,
            481200.6674012489,
            626620.9438865517,
            485539.3479671855
        ]
    },
    {
        "layer_name": "waterbodies",
        "crs": "EPSG:31287",
        "geometry_type": "0     Polygon\n1     Polygon\n2     Polygon\n3     Polygon\n4     Polygon\n5     Polygon\n6     Polygon\n7     Polygon\n8     Polygon\n9     Polygon\n10    Polygon\n11    Polygon\n12    Polygon\n13    Polygon\n14    Polygon\n15    Polygon\n16    Polygon\n17    Polygon\n18    Polygon\n19    Polygon\n20    Polygon\n21    Polygon\n22    Polygon\n23    Polygon\n24    Polygon\n25    Polygon\n26    Polygon\n27    Polygon\n28    Polygon\n29    Polygon\n30    Polygon\n31    Polygon\n32    Polygon\ndtype: str",
        "feature_count": 33,
        "bbox": [
            624288.8521056126,
            481236.66320640914,
            626747.8611584986,
            484132.0212685799
        ]
    },
    {
        "layer_name": "schools",
        "crs": "EPSG:31287",
        "geometry_type": "0     Point\n1     Point\n2     Point\n3     Point\n4     Point\n5     Point\n6     Point\n7     Point\n8     Point\n9     Point\n10    Point\n11    Point\n12    Point\n13    Point\n14    Point\n15    Point\n16    Point\n17    Point\n18    Point\n19    Point\n20    Point\n21    Point\n22    Point\n23    Point\n24    Point\n25    Point\n26    Point\n27    Point\n28    Point\n29    Point\n30    Point\n31    Point\n32    Point\n33    Point\n34    Point\n35    Point\n36    Point\n37    Point\n38    Point\n39    Point\ndtype: str",
        "feature_count": 40,
        "bbox": [
            624000.002417057,
            481214.73871311604,
            626259.5421406503,
            484178.87865010765
        ]
    },
    {
        "layer_name": "cafes",
        "crs": "EPSG:31287",
        "geometry_type": "0      Point\n1      Point\n2      Point\n3      Point\n4      Point\n       ...  \n387    Point\n388    Point\n389    Point\n390    Point\n391    Point\nLength: 392, dtype: str",
        "feature_count": 392,
        "bbox": [
            623796.529863561,
            481107.2540129812,
            626399.5618121764,
            484498.9209005649
        ]
    },
    {
        "layer_name": "supermarkets",
        "crs": "EPSG:31287",
        "geometry_type": "0     Point\n1     Point\n2     Point\n3     Point\n4     Point\n      ...  \n82    Point\n83    Point\n84    Point\n85    Point\n86    Point\nLength: 87, dtype: str",
        "feature_count": 87,
        "bbox": [
            623794.0549950565,
            481148.38703723426,
            626392.6164786755,
            484489.91954147833
        ]
    },
    {
        "layer_name": "cycleway_segments",
        "crs": "EPSG:31287",
        "geometry_type": "0      LineString\n1      LineString\n2      LineString\n3      LineString\n4      LineString\n          ...    \n266    LineString\n267    LineString\n268    LineString\n269    LineString\n270    LineString\nLength: 271, dtype: str",
        "feature_count": 271,
        "bbox": [
            623787.4932131292,
            481134.9325878215,
            626619.1631922598,
            485245.6624853243
        ]
    }
]

1:22

Write /work/solve.py

content · 64 lines · py

import geopandas as gpd
import json
import fiona

def get_crs_string(gdf):
    """Ensures CRS is in EPSG:NNNN format."""
    if gdf.crs is None:
        return "Unknown"
    
    try:
        epsg = gdf.crs.to_epsg()
        if epsg:
            return f"EPSG:{epsg}"
        else:
            return str(gdf.crs)
    except Exception:
        return str(gdf.crs)

def main():
    gpkg_path = 'vienna_planning.gpkg'
    
    layers = fiona.listlayers(gpkg_path)
    manifest = []

    for layer in layers:
        gdf = gpd.read_file(gpkg_path, layer=layer)
        
        # layer_name
        layer_name = layer
        
        # crs
        crs_str = get_crs_string(gdf)
        
        # geometry_type
        # Use the most frequent type or the first one to get a clean string 
        # instead of the Series representation.
        if not gdf.empty:
            geom_type = gdf.geometry.type.iloc[0]
        else:
            geom_type = "Unknown"
        
        # feature_count
        feature_count = len(gdf)
        
        # bbox
        # bbox is [xmin, ymin, xmax, ymax]
        bbox = list(gdf.total_bounds)
        
        manifest.append({
            "layer_name": layer_name,
            "crs": crs_str,
            "geometry_type": geom_type,
            "feature_count": feature_count,
            "bbox": bbox
        })

    with open('manifest.json', 'w') as f:
        json.dump(manifest, f, indent=4)
    
    print(f"Manifest created with {len(manifest)} layers.")

if __name__ == "__main__":
    main()

Wrote /work/solve.py (1538 chars).

1:25

Bash python solve.py && cat manifest.json

Manifest created with 7 layers.
[
    {
        "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
        ]
    }
]

1:28

Bash ls -l manifest.json

-rw-r--r-- 1 agent agent 2063 Jun  7 13:38 manifest.json

1:55

score: 1.000

Gates

✓ format_schema_valid

Subchecks

✓ layers_complete (×4) submitted ['cafes', 'cycleway_segments', 'districts', 'parks', 'schools', 'supermarkets', 'waterbodies'] vs expected ['cafes', 'cycleway_segments', 'districts', 'parks', 'schools', 'supermarkets', 'waterbodies']
✓ cafes_crs_correct submitted 'EPSG:31287' vs expected 'EPSG:31287'
✓ cafes_geom_type_correct submitted 'Point' vs expected 'Point'
✓ cafes_count_correct submitted 392 vs expected 392
✓ cafes_bbox_correct submitted [623796.529863561, 481107.2540129812, 626399.5618121764, 484498.9209005649] vs expected [623796.53, 481107.25, 626399.56, 484498.92] (max |Δ|=0.004, eps=1.0)
✓ cycleway_segments_crs_correct submitted 'EPSG:31287' vs expected 'EPSG:31287'
✓ cycleway_segments_geom_type_correct submitted 'LineString' vs expected 'LineString'
✓ cycleway_segments_count_correct submitted 271 vs expected 271
✓ cycleway_segments_bbox_correct submitted [623787.4932131292, 481134.9325878215, 626619.1631922598, 485245.6624853243] vs expected [623787.49, 481134.93, 626619.16, 485245.66] (max |Δ|=0.003, eps=1.0)
✓ districts_crs_correct submitted 'EPSG:31287' vs expected 'EPSG:31287'
✓ districts_geom_type_correct submitted 'Polygon' vs expected 'Polygon'
✓ districts_count_correct submitted 22 vs expected 22
✓ districts_bbox_correct submitted [623867.3888224852, 481236.5836125494, 626371.3079994549, 484403.7315526943] vs expected [623867.39, 481236.58, 626371.31, 484403.73] (max |Δ|=0.004, eps=1.0)
✓ parks_crs_correct submitted 'EPSG:31287' vs expected 'EPSG:31287'
✓ parks_geom_type_correct submitted 'MultiPolygon' vs expected 'MultiPolygon'
✓ parks_count_correct submitted 119 vs expected 119
✓ parks_bbox_correct submitted [623851.990195953, 481200.6674012489, 626620.9438865517, 485539.3479671855] vs expected [623851.99, 481200.67, 626620.94, 485539.35] (max |Δ|=0.004, eps=1.0)
✓ schools_crs_correct submitted 'EPSG:31287' vs expected 'EPSG:31287'
✓ schools_geom_type_correct submitted 'Point' vs expected 'Point'
✓ schools_count_correct submitted 40 vs expected 40
✓ schools_bbox_correct submitted [624000.002417057, 481214.73871311604, 626259.5421406503, 484178.87865010765] vs expected [624000.0, 481214.74, 626259.54, 484178.88] (max |Δ|=0.002, eps=1.0)
✓ supermarkets_crs_correct submitted 'EPSG:31287' vs expected 'EPSG:31287'
✓ supermarkets_geom_type_correct submitted 'Point' vs expected 'Point'
✓ supermarkets_count_correct submitted 87 vs expected 87
✓ supermarkets_bbox_correct submitted [623794.0549950565, 481148.38703723426, 626392.6164786755, 484489.91954147833] vs expected [623794.05, 481148.39, 626392.62, 484489.92] (max |Δ|=0.005, eps=1.0)
✓ waterbodies_crs_correct submitted 'EPSG:31287' vs expected 'EPSG:31287'
✓ waterbodies_geom_type_correct submitted 'Polygon' vs expected 'Polygon'
✓ waterbodies_count_correct submitted 33 vs expected 33
✓ waterbodies_bbox_correct submitted [624288.8521056126, 481236.66320640914, 626747.8611584986, 484132.0212685799] vs expected [624288.85, 481236.66, 626747.86, 484132.02] (max |Δ|=0.003, eps=1.0)

{
  "created_at": "2026-06-07T13:37:32.211277Z",
  "error": null,
  "files": [
    "manifest.json",
    "solve.py",
    "vienna_planning.gpkg"
  ],
  "last_activity_at": "2026-06-07T13:39:27.800008Z",
  "session_id": "cd96ab934ba34279b4e6e83cbf2f63d7",
  "status": "idle",
  "task_version": 1,
  "usage": {
    "agent_version": "0.3.0",
    "duration_s": 115.3860493490356,
    "estimated_cost_usd": 0.00766742,
    "model": "google/gemma-4-26b-a4b-it"
  }
}

dd-l1-vienna-gpkg-manifest Rerun

Map (reference ← swipe → agent)

Gates

Subchecks

dd-l1-vienna-gpkg-manifest