crs-l1-nyc-webmercator-cycleways
Map (reference ← swipe → agent)
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The `nyc_cycleways` file came out of our tile-renderer, but our web map client can't read the coordinates as they are. It needs plain lat/lon. Can you convert them over? Please leave the attributes alone, and make sure each geometry stays a plain LineString rather than turning into a MultiLineString. Write the result as GeoParquet to `nyc_cycleways_wgs84.geoparquet`, and use `id` as the key.
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System info
{
"adapter": "openrouter",
"model": "google/gemma-4-26b-a4b-it",
"base_url": "https://openrouter.ai/api/v1"
}
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Bash
ls -F
nyc_cycleways_webmercator.geoparquet
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Bash
duckdb -c "SELECT * FROM 'nyc_cycleways_webmercator.geoparquet' LIMIT 5;"
bash: line 1: duckdb: command not found
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Write
/work/solve.py
content · 56 lines · py
import geopandas as gpd
def convert_geometry(geom):
if geom.geom_type == 'MultiLineString':
# If it's a MultiLineString, we want to explode it into individual LineStrings
# But the prompt says "make sure each geometry stays a plain LineString"
# Usually this implies exploding MultiLineStrings into separate rows.
# However, if the user means "don't let it be converted to MultiLineString during processing"
# we should handle it carefully.
# Actually, a MultiLineString represents a single feature.
# If I explode it, I'll have multiple rows for one original ID.
# Let's see what the data looks like first.
pass
return geom
def main():
input_file = 'nyc_cycleways_webmercator.geoparquet'
output_file = 'nyc_cycleways_wgs84.geoparquet'
print(f"Reading {input_file}...")
gdf = gpd.read_parquet(input_file)
print(f"Original CRS: {gdf.crs}")
print(f"Geometry types: {gdf.geometry.geom_type.value_counts().to_dict()}")
# Convert to WGS84 (EPSG:4326)
print("Converting to WGS84...")
gdf = gdf.to_crs(epsg=4326)
# Ensure geometry is LineString and not MultiLineString.
# If there are MultiLineStrings, we explode them into separate LineStrings.
# This is the standard way to ensure every row is a single LineString.
if any(gdf.geometry.geom_type == 'MultiLineString'):
print("Exploding MultiLineStrings to LineStrings...")
gdf = gdf.explode(index_parts=False)
# The prompt says "use id as the key". In GeoParquet, this usually means
# ensuring 'id' is a column and potentially setting it as the index if needed,
# but GeoParquet doesn't have a "key" in the same way a database does,
# it just preserves columns. I will ensure 'id' exists.
if 'id' not in gdf.columns:
print("Warning: 'id' column not found. Creating one from index if necessary.")
# If 'id' is the index, we need to make it a column.
if gdf.index.name == 'id':
gdf = gdf.reset_index()
else:
gdf['id'] = gdf.index
print(f"Writing to {output_file}...")
gdf.to_parquet(output_file)
print("Done.")
if __name__ == "__main__":
main()
Wrote /work/solve.py (2265 chars).
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Bash
python solve.py
Reading nyc_cycleways_webmercator.geoparquet...
Original CRS: {"$schema": "https://proj.org/schemas/v0.7/projjson.schema.json", "type": "ProjectedCRS", "name": "WGS 84 / Pseudo-Mercator", "base_crs": {"name": "WGS 84", "datum_ensemble": {"name": "World Geodetic System 1984 ensemble", "members": [{"name": "World Geodetic System 1984 (Transit)"}, {"name": "World Geodetic System 1984 (G730)"}, {"name": "World Geodetic System 1984 (G873)"}, {"name": "World Geodetic System 1984 (G1150)"}, {"name": "World Geodetic System 1984 (G1674)"}, {"name": "World Geodetic System 1984 (G1762)"}, {"name": "World Geodetic System 1984 (G2139)"}, {"name": "World Geodetic System 1984 (G2296)"}], "ellipsoid": {"name": "WGS 84", "semi_major_axis": 6378137, "inverse_flattening": 298.257223563}, "accuracy": "2.0", "id": {"authority": "EPSG", "code": 6326}}, "coordinate_system": {"subtype": "ellipsoidal", "axis": [{"name": "Geodetic latitude", "abbreviation": "Lat", "direction": "north", "unit": "degree"}, {"name": "Geodetic longitude", "abbreviation": "Lon", "direction": "east", "unit": "degree"}]}, "id": {"authority": "EPSG", "code": 4326}}, "conversion": {"name": "Popular Visualisation Pseudo-Mercator", "method": {"name": "Popular Visualisation Pseudo Mercator", "id": {"authority": "EPSG", "code": 1024}}, "parameters": [{"name": "Latitude of natural origin", "value": 0, "unit": "degree", "id": {"authority": "EPSG", "code": 8801}}, {"name": "Longitude of natural origin", "value": 0, "unit": "degree", "id": {"authority": "EPSG", "code": 8802}}, {"name": "False easting", "value": 0, "unit": "metre", "id": {"authority": "EPSG", "code": 8806}}, {"name": "False northing", "value": 0, "unit": "metre", "id": {"authority": "EPSG", "code": 8807}}]}, "coordinate_system": {"subtype": "Cartesian", "axis": [{"name": "Easting", "abbreviation": "X", "direction": "east", "unit": "metre"}, {"name": "Northing", "abbreviation": "Y", "direction": "north", "unit": "metre"}]}, "scope": "Web mapping and visualisation.", "area": "World between 85.06\u00b0S and 85.06\u00b0N.", "bbox": {"south_latitude": -85.06, "west_longitude": -180, "north_latitude": 85.06, "east_longitude": 180}, "id": {"authority": "EPSG", "code": 3857}}
Geometry types: {'LineString': 272}
Converting to WGS84...
Writing to nyc_cycleways_wgs84.geoparquet...
Done.
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Bash
python -c "import geopandas as gpd; gdf = gpd.read_parquet('nyc_cycleways_wgs84....
id ... geometry 0 008afca9-4118-4569-86a4-e05d2049e5ff ... LINESTRING (-74.00011 40.70788, -74.00004 40.7... 1 019954ce-599a-4f44-9509-f5df571ec8a6 ... LINESTRING (-74.00694 40.70375, -74.00692 40.7... 2 01e21e38-aa74-4a1b-aea5-0c154bc52559 ... LINESTRING (-74.00004 40.70779, -74.0001 40.70... 3 0241690c-de63-42c3-8049-dd993673823b ... LINESTRING (-74.01595 40.71166, -74.01591 40.7... 4 03118a13-69c4-4dac-8677-6d9932e88536 ... LINESTRING (-73.95846 40.75868, -73.95817 40.7... [5 rows x 5 columns] <ArrowStringArray> ['LineString'] Length: 1, dtype: str Index(['id', 'class', 'subclass', 'name', 'geometry'], dtype='str')
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Bash
ls -F
nyc_cycleways_webmercator.geoparquet nyc_cycleways_wgs84.geoparquet solve.py
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