dc-l2-cairo-invalid-dedup
Map (reference ← swipe → agent)
0:00
cairo_parcels_legacy.geojson is a parcel snapshot stitched together from three legacy provincial systems before unification, and I need to turn it into the foundation for our new central registry. Can you clean it up so we end up with one canonical record per parcel? When duplicates exist, keep the record with the earliest record_seq, and discard any polygon fragments smaller than 1 m².
Please write the result to parcels_canonical.geoparquet including these columns: parcel_id (the join key), parcel_class, district, and area_m2. Every feature must be a MultiPolygon, and there should be no null or empty geometries, no invalid geometries, no duplicate geometries, and no artifact slivers.
0:00
System info
{
"adapter": "openrouter",
"model": "deepseek/deepseek-v4-flash",
"base_url": "https://openrouter.ai/api/v1"
}
0:02
Let me start by reading the input file to understand its structure and content.
0:02
Read
/work/cairo_parcels_legacy.geojson
1 {
2 "type": "FeatureCollection",
3 "name": "cairo_parcels_legacy",
4 "crs": {
5 "type": "name",
6 "properties": {
7 "name": "urn:ogc:def:crs:EPSG::22992"
8 }
9 },
10 "features": [
11 {
12 "type": "Feature",
13 "geometry": {
14 "type": "Polygon",
15 "coordinates": [
16 [
17 [
18 640000.0,
19 815000.0
20 ],
21 [
22 640030.0,
23 815000.0
24 ],
25 [
26 640030.0,
27 815040.0
28 ],
29 [
30 640000.0,
31 815040.0
32 ],
33 [
34 640000.0,
35 815000.0
36 ]
37 ]
38 ]
39 },
40 "properties": {
41 "parcel_id": 1,
42 "record_seq": 1,
43 "parcel_class": "commercial",
44 "district": "Giza-East",
45 "area_m2": 1200.0
46 }
47 },
48 {
49 "type": "Feature",
50 "geometry": {
51 "type": "Polygon",
52 "coordinates": [
53 [
54 [
55 640050.0,
56 815000.0
57 ],
58 [
59 640080.0,
60 815000.0
61 ],
62 [
63 640080.0,
64 815040.0
65 ],
66 [
67 640050.0,
68 815040.0
69 ],
70 [
71 640050.0,
72 815000.0
73 ]
74 ]
75 ]
76 },
77 "properties": {
78 "parcel_id": 2,
79 "record_seq": 2,
80 "parcel_class": "industrial",
<system-reminder>Showed lines 1-80 of 11522. Re-call Read with offset=81 to continue, or raise limit.</system-reminder>
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Let me read more of the file to understand the data structure better.
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Bash
wc -l /work/cairo_parcels_legacy.geojson
11522 /work/cairo_parcels_legacy.geojson
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Bash
python3 -c "
python3 -c "
import geopandas as gpd
gdf = gpd.read_file('/work/cairo_parcels_legacy.geojson')
print('Shape:', gdf.shape)
print('Columns:', gdf.columns.tolist())
print('CRS:', gdf.crs)
print('dtypes:')
print(gdf.dtypes)
print()
print('parcel_id nunique:', gdf['parcel_id'].nunique())
print('record_seq range:', gdf['record_seq'].min(), '-', gdf['record_seq'].max())
print()
print('Geometry types:')
print(gdf.geometry.geom_type.value_counts())
print()
print('Null geometries:', gdf.geometry.isna().sum())
print()
print('Sample of parcel_id duplicates:')
dup_ids = gdf['parcel_id'].value_counts()
dups = dup_ids[dup_ids > 1]
print('Duplicate parcel_ids count:', len(dups))
print(dups.head(10))
"
Shape: (290, 6) Columns: ['parcel_id', 'record_seq', 'parcel_class', 'district', 'area_m2', 'geometry'] CRS: EPSG:22992 dtypes: parcel_id int32 record_seq int32 parcel_class str district str area_m2 float64 geometry geometry dtype: object parcel_id nunique: 290 record_seq range: 1 - 290 Geometry types: Polygon 260 MultiPolygon 30 Name: count, dtype: int64 Null geometries: 0 Sample of parcel_id duplicates: Duplicate parcel_ids count: 0 Series([], Name: count, dtype: int64)
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All 290 parcel_ids are unique. So there are no duplicate parcel_ids where I'd need to pick the earliest record_seq. But the task says "When duplicates exist, keep the record with the earliest record_seq" — since there are no duplicates by parcel_id, that step is a no-op. However, there may be duplicate geometries (same shape for different parcel_ids). Let me check that. Also, I need to: 1. Check for duplicate geometries 2. Remove polygon fragments smaller than 1 m² 3. Discard null/empty geometries 4. Fix invalid geometries 5. Ensure all are MultiPolygon 6. Remove duplicate geometries (same geometry shape) 7. Write to parcels_canonical.geoparquet with columns: parcel_id, parcel_class, district, area_m2 Let me check for invalid geometries and duplicate geometries.
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Bash
python3 -c "
python3 -c "
import geopandas as gpd
gdf = gpd.read_file('/work/cairo_parcels_legacy.geojson')
# Check for invalid geometries
invalid = ~gdf.geometry.is_valid
print('Invalid geometries:', invalid.sum())
if invalid.any():
print(gdf[invalid][['parcel_id', 'record_seq', 'parcel_class', 'district']].to_string())
# Check for empty geometries
from shapely.geometry import shape
empty = gdf.geometry.is_empty
print('Empty geometries:', empty.sum())
# Check for duplicate geometries
import pandas as pd
geoms_wkt = gdf.geometry.apply(lambda g: g.wkt)
dup_geoms = geoms_wkt[geoms_wkt.duplicated(keep=False)]
print('Duplicate geometry count:', len(dup_geoms))
if len(dup_geoms) > 0:
dup_indices = geoms_wkt[geoms_wkt.duplicated()].index
print('Rows with duplicated geometries:', dup_indices.tolist())
for idx in dup_indices:
print(f' Row {idx}: parcel_id={gdf.iloc[idx][\"parcel_id\"]}, record_seq={gdf.iloc[idx][\"record_seq\"]}, area={gdf.iloc[idx][\"area_m2\"]}')
# Find the first occurrence
first_idx = geoms_wkt[geoms_wkt == gdf.iloc[idx].geometry.wkt].index[0]
print(f' First at row {first_idx}: parcel_id={gdf.iloc[first_idx][\"parcel_id\"]}, record_seq={gdf.iloc[first_idx][\"record_seq\"]}')
# Check area - any < 1 m²?
areas = gdf.geometry.area
small = areas[areas < 1.0]
print('Features with area < 1 m²:', len(small))
if len(small) > 0:
print(small)
"
Invalid geometries: 20
parcel_id record_seq parcel_class district
6 7 7 agricultural Giza-East
16 17 17 commercial Qalyubia-South
22 23 23 agricultural Qalyubia-South
34 35 35 agricultural Qalyubia-South
40 41 41 commercial Qalyubia-South
52 53 53 commercial Qalyubia-South
57 58 58 industrial Giza-East
70 71 71 agricultural Qalyubia-South
75 76 76 residential Giza-East
88 89 89 commercial Qalyubia-South
93 94 94 industrial Giza-East
106 107 107 agricultural Qalyubia-South
111 112 112 residential Giza-East
124 125 125 commercial Qalyubia-South
129 130 130 industrial Giza-East
142 143 143 agricultural Qalyubia-South
147 148 148 residential Giza-East
160 161 161 commercial Qalyubia-South
165 166 166 industrial Giza-East
178 179 179 agricultural Qalyubia-South
Empty geometries: 0
Duplicate geometry count: 100
Rows with duplicated geometries: [210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259]
Row 210: parcel_id=900001, record_seq=211, area=1200.0
First at row 0: parcel_id=1, record_seq=1
Row 211: parcel_id=900002, record_seq=212, area=1200.0
First at row 1: parcel_id=2, record_seq=2
Row 212: parcel_id=900003, record_seq=213, area=1200.0
First at row 2: parcel_id=3, record_seq=3
Row 213: parcel_id=900004, record_seq=214, area=1200.0
First at row 3: parcel_id=4, record_seq=4
Row 214: parcel_id=900005, record_seq=215, area=1200.0
First at row 4: parcel_id=5, record_seq=5
Row 215: parcel_id=900006, record_seq=216, area=1200.0
First at row 5: parcel_id=6, record_seq=6
Row 216: parcel_id=900007, record_seq=217, area=1200.0
First at row 7: parcel_id=8, record_seq=8
Row 217: parcel_id=900008, record_seq=218, area=1200.0
First at row 8: parcel_id=9, record_seq=9
Row 218: parcel_id=900009, record_seq=219, area=1200.0
First at row 9: parcel_id=10, record_seq=10
Row 219: parcel_id=900010, record_seq=220, area=1200.0
First at row 11: parcel_id=12, record_seq=12
Row 220: parcel_id=900011, record_seq=221, area=1200.0
First at row 12: parcel_id=13, record_seq=13
Row 221: parcel_id=900012, record_seq=222, area=1200.0
First at row 14: parcel_id=15, record_seq=15
Row 222: parcel_id=900013, record_seq=223, area=1200.0
First at row 15: parcel_id=16, record_seq=16
Row 223: parcel_id=900014, record_seq=224, area=1200.0
First at row 17: parcel_id=18, record_seq=18
Row 224: parcel_id=900015, record_seq=225, area=1200.0
First at row 19: parcel_id=20, record_seq=20
Row 225: parcel_id=900016, record_seq=226, area=1200.0
First at row 20: parcel_id=21, record_seq=21
Row 226: parcel_id=900017, record_seq=227, area=1200.0
First at row 21: parcel_id=22, record_seq=22
Row 227: parcel_id=900018, record_seq=228, area=1200.0
First at row 23: parcel_id=24, record_seq=24
Row 228: parcel_id=900019, record_seq=229, area=1200.0
First at row 24: parcel_id=25, record_seq=25
Row 229: parcel_id=900020, record_seq=230, area=1200.0
First at row 25: parcel_id=26, record_seq=26
Row 230: parcel_id=900021, record_seq=231, area=1200.0
First at row 26: parcel_id=27, record_seq=27
Row 231: parcel_id=900022, record_seq=232, area=1200.0
First at row 27: parcel_id=28, record_seq=28
Row 232: parcel_id=900023, record_seq=233, area=1200.0
First at row 29: parcel_id=30, record_seq=30
Row 233: parcel_id=900024, record_seq=234, area=1200.0
First at row 30: parcel_id=31, record_seq=31
Row 234: parcel_id=900025, record_seq=235, area=1200.0
First at row 32: parcel_id=33, record_seq=33
Row 235: parcel_id=900026, record_seq=236, area=1200.0
First at row 33: parcel_id=34, record_seq=34
Row 236: parcel_id=900027, record_seq=237, area=1200.0
First at row 35: parcel_id=36, record_seq=36
Row 237: parcel_id=900028, record_seq=238, area=1200.0
First at row 37: parcel_id=38, record_seq=38
Row 238: parcel_id=900029, record_seq=239, area=1200.0
First at row 38: parcel_id=39, record_seq=39
Row 239: parcel_id=900030, record_seq=240, area=1200.0
First at row 39: parcel_id=40, record_seq=40
Row 240: parcel_id=900031, record_seq=241, area=1200.0
First at row 41: parcel_id=42, record_seq=42
Row 241: parcel_id=900032, record_seq=242, area=1200.0
First at row 42: parcel_id=43, record_seq=43
Row 242: parcel_id=900033, record_seq=243, area=1200.0
First at row 43: parcel_id=44, record_seq=44
Row 243: parcel_id=900034, record_seq=244, area=1200.0
First at row 44: parcel_id=45, record_seq=45
Row 244: parcel_id=900035, record_seq=245, area=1200.0
First at row 45: parcel_id=46, record_seq=46
Row 245: parcel_id=900036, record_seq=246, area=1200.0
First at row 47: parcel_id=48, record_seq=48
Row 246: parcel_id=900037, record_seq=247, area=1200.0
First at row 48: parcel_id=49, record_seq=49
Row 247: parcel_id=900038, record_seq=248, area=1200.0
First at row 50: parcel_id=51, record_seq=51
Row 248: parcel_id=900039, record_seq=249, area=1200.0
First at row 51: parcel_id=52, record_seq=52
Row 249: parcel_id=900040, record_seq=250, area=1200.0
First at row 53: parcel_id=54, record_seq=54
Row 250: parcel_id=900041, record_seq=251, area=1200.0
First at row 55: parcel_id=56, record_seq=56
Row 251: parcel_id=900042, record_seq=252, area=1200.0
First at row 56: parcel_id=57, record_seq=57
Row 252: parcel_id=900043, record_seq=253, area=1200.0
First at row 58: parcel_id=59, record_seq=59
Row 253: parcel_id=900044, record_seq=254, area=1200.0
First at row 59: parcel_id=60, record_seq=60
Row 254: parcel_id=900045, record_seq=255, area=1200.0
First at row 60: parcel_id=61, record_seq=61
Row 255: parcel_id=900046, record_seq=256, area=1200.0
First at row 61: parcel_id=62, record_seq=62
Row 256: parcel_id=900047, record_seq=257, area=1200.0
First at row 62: parcel_id=63, record_seq=63
Row 257: parcel_id=900048, record_seq=258, area=1200.0
First at row 63: parcel_id=64, record_seq=64
Row 258: parcel_id=900049, record_seq=259, area=1200.0
First at row 65: parcel_id=66, record_seq=66
Row 259: parcel_id=900050, record_seq=260, area=1200.0
First at row 66: parcel_id=67, record_seq=67
Features with area < 1 m²: 50
6 0.00
16 0.00
22 0.00
34 0.00
40 0.00
52 0.00
57 0.00
70 0.00
75 0.00
88 0.00
93 0.00
106 0.00
111 0.00
124 0.00
129 0.00
142 0.00
147 0.00
160 0.00
165 0.00
178 0.00
260 0.49
261 0.49
262 0.49
263 0.49
264 0.49
265 0.49
266 0.49
267 0.49
268 0.49
269 0.49
270 0.49
271 0.49
272 0.49
273 0.49
274 0.49
275 0.49
276 0.49
277 0.49
278 0.49
279 0.49
280 0.49
281 0.49
282 0.49
283 0.49
284 0.49
285 0.49
286 0.49
287 0.49
288 0.49
289 0.49
dtype: float64
0:32
Let me analyze the data: 1. **290 features total**, all with non-null geometries. 2. **No duplicate parcel_ids** - the parcel_id values are all unique. 3. **Duplicate geometries exist**: rows 210-259 have the same geometries as rows 0-66 (the first occurrences). These are treated as completely duplicated records (same geometry but different parcel_id and record_seq). Since there's no duplicate `parcel_id`, the "duplicates" here are duplicate geometries, not duplicate parcel_ids. Wait, re-reading the task: "When duplicates exist, keep the record with the earliest record_seq". This means when there are multiple records with the same parcel_id? But there are no duplicate parcel_ids. Let me re-read... Actually, the task says "turn it into the foundation for our new central registry" and "one canonical record per parcel". The `parcel_id` is described as "the join key". And there are 50 records (rows 260-289) with area < 1 m² (tiny slivers of 0.49 m²) and the first 20 invalid geometries (rows 6, 16, 22, etc. with area=0.00) plus the duplicate geometries. Wait, the invalid geometries also have area 0.00 - those are likely slivers too, but they're flagged as invalid. Let me think about this more carefully: - **parcel_id** is the join key, and all 290 are unique. So no duplicate parcel_ids. - But rows 210-259 have duplicate geometries (same as rows 0-49 approximately). These are duplicate *records* for different parcel_ids. So we need to handle "duplicate geometries" - when two records have the same geometry, we keep the one with the earliest record_seq. Since rows 0-49 have record_seq 1-50 and rows 210-259 have record_seq 211-260, the earlier ones win. Wait, but the task says "one canonical record per parcel". A parcel is identified by `parcel_id`. Since all parcel_ids are unique, there's already one record per parcel. But the duplicate geometries suggest this is data from three legacy systems stitched together - some parcels from different systems have the same geometry. Hmm, let me re-read: "When duplicates exist, keep the record with the earliest record_seq". So I think this means: when two or more records have the same geometry (i.e., they represent the same physical parcel), keep only the one with the earliest record_seq. The parcel_id from that kept record becomes the canonical one. Let me also check: - Records with area < 1 m²: 50 features (rows 260-289 = 30 features, plus ~20 with area 0.00 from the invalid ones) - Invalid geometries: 20 of them - The invalid ones all have area=0.00 So my plan: 1. Fix invalid geometries (make them valid using `buffer(0)` or similar) 2. Remove geometries with area < 1 m² 3. When duplicate geometries exist, keep only the record with the earliest record_seq 4. Convert all geometries to MultiPolygon 5. Ensure no null/empty geometries, no invalid geometries 6. Keep only columns: parcel_id, parcel_class, district, area_m2 Wait, but the invalid geometries with area 0.00 - if I fix them with buffer(0), they'd still be tiny. Let me think... Those have area 0.00 which is < 1 m², so they'd be discarded anyway. Let me look at what the invalid geometries look like to understand the issue. Actually, let me just write the script to handle all of this carefully. Let me also check the area_m2 column - is it computed or stored? The stored area_m2 values might not match the actual geometry area. For the final output, should I recalculate area_m2 or use the stored value? The task says "area_m2" as an output column. I think I should compute the actual area from the cleaned geometry in the output's CRS (EPSG:22992 which is metric). Let me write the script: 1. Read the GeoJSON 2. Fix invalid geometries (buffer(0)) 3. Remove any geometries with area < 1 m² 4. Remove duplicate geometries keeping the one with earliest record_seq 5. Ensure MultiPolygon type 6. Recalculate area_m2 from geometry 7. Select only required columns 8. Write to GeoParquet
0:32
0:32
Write
/work/solve.py
content · 85 lines · py
import geopandas as gpd
import pandas as pd
import numpy as np
from shapely.geometry import MultiPolygon
from shapely import wkt
# ── 1. Read source data ────────────────────────────────────────────────
gdf = gpd.read_file("/work/cairo_parcels_legacy.geojson")
print(f"Read {len(gdf)} records")
print(f"CRS: {gdf.crs}")
# ── 2. Fix invalid geometries (buffer(0) standard trick) ───────────────
invalid_mask = ~gdf.geometry.is_valid
print(f"Invalid geometries: {invalid_mask.sum()}")
gdf.loc[invalid_mask, "geometry"] = gdf.loc[invalid_mask, "geometry"].buffer(0)
# Check that they're now valid
still_invalid = ~gdf.geometry.is_valid
if still_invalid.any():
print(f"WARNING: {still_invalid.sum()} geometries still invalid after buffer(0)")
# Drop what we can't fix
gdf = gdf[~still_invalid].copy()
print(f"After fixing invalids: {len(gdf)} records")
# ── 3. Remove empty geometries ─────────────────────────────────────────
empty_mask = gdf.geometry.is_empty | gdf.geometry.isna()
print(f"Empty/null geometries: {empty_mask.sum()}")
gdf = gdf[~empty_mask].copy()
# ── 4. Remove polygon fragments smaller than 1 m² ──────────────────────
# Compute actual geometry area (CRS is EPSG:22992 — metres)
geom_area = gdf.geometry.area
small_mask = geom_area < 1.0
print(f"Geometries with area < 1 m²: {small_mask.sum()}")
gdf = gdf[~small_mask].copy()
print(f"After removing small fragments: {len(gdf)} records")
# ── 5. Handle duplicate geometries: keep record with earliest record_seq ──
# Strategy: group by geometry WKT, keep row with min record_seq
gdf["geom_wkt"] = gdf.geometry.apply(lambda g: g.wkt)
# Identify duplicate geometries
dup_geom_count = gdf["geom_wkt"].duplicated(keep=False).sum()
print(f"Records with duplicated geometries: {dup_geom_count}")
# For each geometry WKT, keep the row with the smallest record_seq
idx_keep = gdf.groupby("geom_wkt")["record_seq"].idxmin()
gdf = gdf.loc[idx_keep].copy()
gdf.drop(columns=["geom_wkt"], inplace=True)
print(f"After deduplicating geometries: {len(gdf)} records")
# ── 6. Convert all geometries to MultiPolygon ───────────────────────────
def ensure_multipolygon(geom):
if geom.geom_type == "Polygon":
return MultiPolygon([geom])
return geom
gdf["geometry"] = gdf.geometry.apply(ensure_multipolygon)
print(f"Geometry types after conversion:\n{gdf.geometry.geom_type.value_counts()}")
# ── 7. Recompute area_m2 from the cleaned geometry ─────────────────────
gdf["area_m2"] = gdf.geometry.area.round(2)
# ── 8. Select only the required columns ────────────────────────────────
gdf = gdf[["parcel_id", "parcel_class", "district", "area_m2", "geometry"]].copy()
# ── 9. Final quality checks ────────────────────────────────────────────
assert gdf.geometry.is_valid.all(), "Invalid geometries remain!"
assert gdf.geometry.notna().all(), "Null geometries remain!"
assert not gdf.geometry.is_empty.any(), "Empty geometries remain!"
assert (gdf.geometry.geom_type == "MultiPolygon").all(), "Not all MultiPolygon!"
assert gdf["area_m2"].between(1.0, None).all(), "Area < 1 m² remains!"
assert gdf["parcel_id"].notna().all(), "Null parcel_id!"
assert gdf["parcel_class"].notna().all(), "Null parcel_class!"
assert gdf["district"].notna().all(), "Null district!"
print(f"\nFinal output: {len(gdf)} records")
print(f"parcel_id range: {gdf['parcel_id'].min()} – {gdf['parcel_id'].max()}")
print(f"area_m2 range: {gdf['area_m2'].min():.2f} – {gdf['area_m2'].max():.2f}")
# ── 10. Write to GeoParquet ────────────────────────────────────────────
gdf.to_parquet("/work/parcels_canonical.geoparquet", index=False)
print("\n✓ Written to /work/parcels_canonical.geoparquet")Wrote /work/solve.py (3655 chars).
0:33
Let me run the script and check the output.
0:33
Bash
cd /work && python3 solve.py
Read 290 records CRS: EPSG:22992 Invalid geometries: 20 After fixing invalids: 290 records Empty/null geometries: 0 Geometries with area < 1 m²: 30 After removing small fragments: 260 records Records with duplicated geometries: 100 After deduplicating geometries: 210 records Geometry types after conversion: MultiPolygon 210 Name: count, dtype: int64
Traceback (most recent call last):
File "/work/solve.py", line 74, in <module>
assert gdf["area_m2"].between(1.0, None).all(), "Area < 1 m² remains!"
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
AssertionError: Area < 1 m² remains!
0:38
Let me check what areas are being reported. The issue might be that after buffer(0), some geometries changed area, or the area < 1 m² check after deduplication includes some that were already close. Let me look at the areas after the dedup step.
0:38
Bash
python3 -c "
python3 -c "
import geopandas as gpd
import pandas as pd
gdf = gpd.read_file('/work/cairo_parcels_legacy.geojson')
# Fix invalids
invalid_mask = ~gdf.geometry.is_valid
gdf.loc[invalid_mask, 'geometry'] = gdf.loc[invalid_mask, 'geometry'].buffer(0)
# Remove small < 1
geom_area = gdf.geometry.area
small_mask = geom_area < 1.0
gdf = gdf[~small_mask].copy()
# Deduplicate by geometry, keep earliest record_seq
gdf['geom_wkt'] = gdf.geometry.apply(lambda g: g.wkt)
idx_keep = gdf.groupby('geom_wkt')['record_seq'].idxmin()
gdf = gdf.loc[idx_keep].copy()
# Recompute area
gdf['area_m2'] = gdf.geometry.area.round(2)
# Check which are < 1
small_after = gdf[gdf['area_m2'] < 1.0]
print(f'Records with area_m2 < 1.0 after dedup: {len(small_after)}')
print(small_after[['parcel_id', 'record_seq', 'area_m2']].to_string())
print()
print('Min area after dedup:', gdf['area_m2'].min())
print('Max area after dedup:', gdf['area_m2'].max())
print('Sorted small areas:')
print(gdf['area_m2'].sort_values().head(20).to_string())
"
Records with area_m2 < 1.0 after dedup: 0 Empty DataFrame Columns: [parcel_id, record_seq, area_m2] Index: [] Min area after dedup: 300.0 Max area after dedup: 1280.0 Sorted small areas: 165 300.0 16 300.0 106 300.0 75 300.0 142 300.0 124 300.0 34 300.0 93 300.0 6 300.0 111 300.0 52 300.0 22 300.0 129 300.0 40 300.0 160 300.0 70 300.0 178 300.0 147 300.0 57 300.0 88 300.0
0:51
The assertion failed because the area_m2 field in the original data has stale values (the 0.49 ones are the small fragments that were dropped). After fixing, deduplicating, and recomputing area, the minimum is 300. So the assertion should pass now. The issue was that I was recomputing area_m2 but then comparing against the recomputed values. Let me check - actually the assertion at line 74 uses `gdf["area_m2"].between(1.0, None)` which tests if values are >= 1.0. The min is 300, so it should pass. Wait, looking at the error more carefully. The assertion failed. Let me re-examine the script flow. Actually, let me look at the flow: 1. We read 290 records 2. Fix invalids - still 290 3. Remove empty - still 290 4. Remove small < 1m² - removed 30 (the 0.49 slivers), now 260 5. Deduplicate geometries - removed 50 duplicate geometry records (they all had area 1200.0), now 210 6. Convert to MultiPolygon 7. Recompute area_m2 - this recomputes from actual geometries 8. Assert area_m2 >= 1.0 The 20 invalid geometries were the ones with area 0.0 (rows 6, 16, 22, 34, 40, 52, 57, 70, 75, 88, 93, 106, 111, 124, 129, 142, 147, 160, 165, 178). After buffer(0), they had area 300.0 instead of 0.0. So after recomputing, they're 300.0. But wait - 20 invalid + 30 small (including both the 20 zero-area ones from invalids and the 10 remaining 0.49 ones from rows 260-289)? Let me recount: The small_mask showed 30 records with area < 1.0. Those 30 consist of: - 20 with area 0.0 (the invalid ones) - 10 ... wait no, there were 20 zeros (rows 6-178) and 30 of 0.49 (rows 260-289) = 50 total. Wait, let me recheck. The first output showed: ``` Features with area < 1 m²: 50 6 0.00 ... 178 0.00 (20 rows of 0.00) ... 260 0.49 ... 289 0.49 (30 rows of 0.49) ``` So 50 total with area < 1.0. But the script showed "Geometries with area < 1 m²: 30". That's because we first fixed the invalids (buffer(0) on the 20 invalid ones), which changed their area from 0 to 300. So after fixing, only 30 have area < 1.0 (the 30 slivers with 0.49 area). Then we removed those 30 (the 0.49 ones), going from 290 to 260. Then deduplicated geometries (removed 50 duplicate geometry records), going from 260 to 210. Then recompute area_m2. Since the only remaining geometries are the valid ones (now with area 300-1280), the min should be 300. But the assertion failed. Let me check the assertion again: ```python assert gdf["area_m2"].between(1.0, None).all(), "Area < 1 m² remains!" ``` `between(1.0, None)` checks >= 1.0 and <= None (which is no upper bound). So `None` as the upper bound is like no upper bound... actually in pandas `between` with `None` as upper bound means no upper bound, so it's just `>= 1.0`. With min of 300, this should pass... Wait, could it be that `between` with None upper bound doesn't work as expected? Let me check. Actually in pandas, `Series.between(left, right)` — if right is None, it might cause an issue. Actually looking at the error again: ``` AssertionError: Area < 1 m² remains! ``` Hmm, maybe the issue is that `between` with `None` doesn't work properly. Let me just change it to use `>= 1.0`.
0:51
0:51
Edit
/work/solve.py
Edited /work/solve.py.
0:54
Wait, but the assertion was wrong, the area values themselves were fine. Let me re-run the script. Actually, looking at the test output, after dedup and recompute, the min area is 300.0 — so the assertion should pass now. The issue was that `between(1.0, None)` doesn't work in pandas (it doesn't handle None as an upper bound properly). Let me just re-run.
0:54
Bash
cd /work && python3 solve.py
Read 290 records CRS: EPSG:22992 Invalid geometries: 20 After fixing invalids: 290 records Empty/null geometries: 0 Geometries with area < 1 m²: 30 After removing small fragments: 260 records Records with duplicated geometries: 100 After deduplicating geometries: 210 records Geometry types after conversion: MultiPolygon 210 Name: count, dtype: int64 Final output: 210 records parcel_id range: 1 – 210 area_m2 range: 300.00 – 1280.00 ✓ Written to /work/parcels_canonical.geoparquet
0:58
Let me verify the output file exists and run some sanity checks.
0:58
Bash
ls -lh /work/parcels_canonical.geoparquet
-rw-r--r-- 1 agent agent 18K Jun 15 16:33 /work/parcels_canonical.geoparquet
0:58
Bash
python3 -c "
python3 -c "
import geopandas as gpd
gdf = gpd.read_parquet('/work/parcels_canonical.geoparquet')
print('Shape:', gdf.shape)
print('Columns:', gdf.columns.tolist())
print('CRS:', gdf.crs)
print()
print('dtypes:')
print(gdf.dtypes)
print()
print('Geometry types:')
print(gdf.geometry.geom_type.value_counts())
print()
print('Null geometries:', gdf.geometry.isna().sum())
print('Empty geometries:', gdf.geometry.is_empty.sum())
print('Invalid geometries:', (~gdf.geometry.is_valid).sum())
print()
print('parcel_id nunique:', gdf['parcel_id'].nunique())
print('parcel_id range:', gdf['parcel_id'].min(), '-', gdf['parcel_id'].max())
print()
print('area_m2 range:', gdf['area_m2'].min(), '-', gdf['area_m2'].max())
print('area_m2 mean:', gdf['area_m2'].mean())
print()
print('Districts:', gdf['district'].unique().tolist())
print('Parcel classes:', gdf['parcel_class'].unique().tolist())
print()
print('Any duplicate geometries:', gdf.geometry.apply(lambda g: g.wkt).duplicated().any())
print()
print('First 10 rows:')
print(gdf.head(10).to_string())
"
Shape: (210, 5)
Columns: ['parcel_id', 'parcel_class', 'district', 'area_m2', 'geometry']
CRS: {"$schema": "https://proj.org/schemas/v0.7/projjson.schema.json", "type": "ProjectedCRS", "name": "Egypt 1907 / Red Belt", "base_crs": {"name": "Egypt 1907", "datum": {"type": "GeodeticReferenceFrame", "name": "Egypt 1907", "ellipsoid": {"name": "Helmert 1906", "semi_major_axis": 6378200, "inverse_flattening": 298.3}}, "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": 4229}}, "conversion": {"name": "Egypt Red Belt", "method": {"name": "Transverse Mercator", "id": {"authority": "EPSG", "code": 9807}}, "parameters": [{"name": "Latitude of natural origin", "value": 30, "unit": "degree", "id": {"authority": "EPSG", "code": 8801}}, {"name": "Longitude of natural origin", "value": 31, "unit": "degree", "id": {"authority": "EPSG", "code": 8802}}, {"name": "Scale factor at natural origin", "value": 1, "unit": "unity", "id": {"authority": "EPSG", "code": 8805}}, {"name": "False easting", "value": 615000, "unit": "metre", "id": {"authority": "EPSG", "code": 8806}}, {"name": "False northing", "value": 810000, "unit": "metre", "id": {"authority": "EPSG", "code": 8807}}]}, "coordinate_system": {"subtype": "Cartesian", "axis": [{"name": "Easting", "abbreviation": "E", "direction": "east", "unit": "metre"}, {"name": "Northing", "abbreviation": "N", "direction": "north", "unit": "metre"}]}, "scope": "Engineering survey, topographic mapping.", "area": "Egypt - onshore between 29\u00b0E and 33\u00b0E, offshore Mediterranean east of 29\u00b0E and offshore Gulf of Suez.", "bbox": {"south_latitude": 21.99, "west_longitude": 29, "north_latitude": 33.82, "east_longitude": 34.27}, "id": {"authority": "EPSG", "code": 22992}}
dtypes:
parcel_id int32
parcel_class str
district str
area_m2 float64
geometry geometry
dtype: object
Geometry types:
MultiPolygon 210
Name: count, dtype: int64
Null geometries: 0
Empty geometries: 0
Invalid geometries: 0
parcel_id nunique: 210
parcel_id range: 1 - 210
area_m2 range: 300.0 - 1280.0
area_m2 mean: 1125.7142857142858
Districts: ['Giza-East', 'Qalyubia-South', 'Cairo-Central']
Parcel classes: ['agricultural', 'commercial', 'residential', 'industrial']
Any duplicate geometries: False
First 10 rows:
parcel_id parcel_class district area_m2 geometry
0 91 agricultural Giza-East 1280.0 MULTIPOLYGON (((640000 815360, 640030 815360, 640030 815400, 640000 815400, 640000 815360)), ((640035 815365, 640043 815365, 640043 815375, 640035 815375, 640035 815365)))
1 181 commercial Giza-East 1280.0 MULTIPOLYGON (((640000 815720, 640030 815720, 640030 815760, 640000 815760, 640000 815720)), ((640035 815725, 640043 815725, 640043 815735, 640035 815735, 640035 815725)))
2 32 residential Qalyubia-South 1280.0 MULTIPOLYGON (((640050 815120, 640080 815120, 640080 815160, 640050 815160, 640050 815120)), ((640085 815125, 640093 815125, 640093 815135, 640085 815135, 640085 815125)))
3 47 agricultural Qalyubia-South 1280.0 MULTIPOLYGON (((640050 815180, 640080 815180, 640080 815220, 640050 815220, 640050 815180)), ((640085 815185, 640093 815185, 640093 815195, 640085 815195, 640085 815185)))
4 122 industrial Qalyubia-South 1280.0 MULTIPOLYGON (((640050 815480, 640080 815480, 640080 815520, 640050 815520, 640050 815480)), ((640085 815485, 640093 815485, 640093 815495, 640085 815495, 640085 815485)))
5 137 commercial Qalyubia-South 1280.0 MULTIPOLYGON (((640050 815540, 640080 815540, 640080 815580, 640050 815580, 640050 815540)), ((640085 815545, 640093 815545, 640093 815555, 640085 815555, 640085 815545)))
6 19 agricultural Giza-East 1280.0 MULTIPOLYGON (((640150 815060, 640180 815060, 640180 815100, 640150 815100, 640150 815060)), ((640185 815065, 640193 815065, 640193 815075, 640185 815075, 640185 815065)))
7 109 commercial Giza-East 1280.0 MULTIPOLYGON (((640150 815420, 640180 815420, 640180 815460, 640150 815460, 640150 815420)), ((640185 815425, 640193 815425, 640193 815435, 640185 815435, 640185 815425)))
8 50 industrial Qalyubia-South 1280.0 MULTIPOLYGON (((640200 815180, 640230 815180, 640230 815220, 640200 815220, 640200 815180)), ((640235 815185, 640243 815185, 640243 815195, 640235 815195, 640235 815185)))
9 65 commercial Qalyubia-South 1280.0 MULTIPOLYGON (((640200 815240, 640230 815240, 640230 815280, 640200 815280, 640200 815240)), ((640235 815245, 640243 815245, 640243 815255, 640235 815255, 640235 815245)))
1:03
Everything checks out: 1. **File exists**: `parcels_canonical.geoparquet` (18KB) 2. **Columns**: parcel_id, parcel_class, district, area_m2 — all present 3. **All MultiPolygon**: 210/210 4. **No null/empty geometries**: 0 null, 0 empty 5. **No invalid geometries**: 0 invalid 6. **No duplicate geometries**: False (confirmed) 7. **Area ≥ 1 m²**: min is 300.0, all good 8. **210 records** (290 input → 30 removed as < 1m² fragments → 50 duplicate geometries removed → 210 canonical records) 9. **CRS**: EPSG:22992 preserved correctly 10. **parcel_id** is int, serves as join key All requirements met.
1:03