dd-l1-capetown-clinics-bbox
Map (reference ← swipe → agent)
0:00
I'm about to push the `capetown_clinics.csv` export through to our case-management system and I want a quick inventory check first. Can you produce a small JSON file with the total clinic count, the overall bounding box as a bbox array, and the count per subdistrict, so I can confirm every health subdistrict is represented? Please write it to `clinic_inventory.json` with keys `count`, `bbox`, and `count_per_subdistrict`.
0:00
System info
{
"adapter": "openrouter",
"model": "deepseek/deepseek-v4-flash",
"base_url": "https://openrouter.ai/api/v1"
}
0:03
Let me start by reading the CSV file to understand its structure.
0:03
Read
/work/capetown_clinics.csv
1 clinic_id,name,subdistrict,wkt_geom
2 1,Mokoena Western Clinic,Western,POINT(18.478309 -33.888756)
3 2,Ndlovu Western Clinic,Western,POINT(18.421127 -33.924929)
4 3,Pieterse Western Clinic,Western,POINT(18.389237 -33.976099)
5 4,van der Merwe Western Clinic,Western,POINT(18.47354 -33.890933)
6 5,Khumalo Western Clinic,Western,POINT(18.433735 -33.921306)
7 6,Botha Western Clinic,Western,POINT(18.383284 -33.977392)
8 7,Naidoo Western Clinic,Western,POINT(18.465994 -33.893319)
9 8,Adams Western Clinic,Western,POINT(18.446106 -33.917728)
10 9,Hendricks Western Clinic,Western,POINT(18.380309 -33.97843)
11 10,Jansen Western Clinic,Western,POINT(18.456153 -33.895902)
12 11,Mthembu Western Clinic,Western,POINT(18.457449 -33.914217)
13 12,Cloete Western Clinic,Western,POINT(18.380503 -33.97921)
14 13,September Southern Clinic,Southern,POINT(18.421231 -34.033037)
15 14,October Southern Clinic,Southern,POINT(18.467572 -33.996469)
16 15,Williams Southern Clinic,Southern,POINT(18.492329 -34.073855)
17 16,Patel Southern Clinic,Southern,POINT(18.424934 -34.03633)
18 17,Solomons Southern Clinic,Southern,POINT(18.457492 -33.994872)
19 18,du Toit Southern Clinic,Southern,POINT(18.497199 -34.072091)
20 19,Plaatjies Southern Clinic,Southern,POINT(18.430873 -34.039615)
21 20,Mbeki Southern Clinic,Southern,POINT(18.447572 -33.993491)
22 21,Mokoena Southern Clinic,Southern,POINT(18.499696 -34.070128)
23 22,Ndlovu Southern Clinic,Southern,POINT(18.438669 -34.042876)
24 23,Pieterse Southern Clinic,Southern,POINT(18.438445 -33.992331)
25 24,van der Merwe Southern Clinic,Southern,POINT(18.499663 -34.067978)
26 25,Khumalo Tygerberg Clinic,Tygerberg,POINT(18.678466 -33.909762)
27 26,Botha Tygerberg Clinic,Tygerberg,POINT(18.613939 -33.833269)
28 27,Naidoo Tygerberg Clinic,Tygerberg,POINT(18.58094 -33.880193)
29 28,Adams Tygerberg Clinic,Tygerberg,POINT(18.673531 -33.911758)
30 29,Hendricks Tygerberg Clinic,Tygerberg,POINT(18.627788 -33.834612)
31 30,Jansen Tygerberg Clinic,Tygerberg,POINT(18.574099 -33.876911)
32 31,Mthembu Tygerberg Clinic,Tygerberg,POINT(18.665501 -33.913558)
33 32,Cloete Tygerberg Clinic,Tygerberg,POINT(18.641458 -33.836172)
34 33,September Tygerberg Clinic,Tygerberg,POINT(18.570503 -33.873619)
35 34,October Tygerberg Clinic,Tygerberg,POINT(18.654889 -33.915151)
36 35,Williams Tygerberg Clinic,Tygerberg,POINT(18.654079 -33.837939)
37 36,Patel Northern Clinic,Northern,POINT(18.652292 -33.781276)
38 37,Solomons Northern Clinic,Northern,POINT(18.588314 -33.79907)
39 38,du Toit Northern Clinic,Northern,POINT(18.71442 -33.701317)
40 39,Plaatjies Northern Clinic,Northern,POINT(18.671153 -33.777117)
41 40,Mbeki Northern Clinic,Northern,POINT(18.581843 -33.802295)
42 41,Mokoena Northern Clinic,Northern,POINT(18.701063 -33.702388)
43 42,Ndlovu Northern Clinic,Northern,POINT(18.688984 -33.772866)
44 43,Pieterse Northern Clinic,Northern,POINT(18.580036 -33.805293)
45 44,van der Merwe Northern Clinic,Northern,POINT(18.684768 -33.703768)
46 45,Khumalo Northern Clinic,Northern,POINT(18.704648 -33.768546)
47 46,Botha Eastern Clinic,Eastern,POINT(18.727635 -33.852256)
48 47,Naidoo Eastern Clinic,Eastern,POINT(18.728035 -33.861878)
49 48,Adams Eastern Clinic,Eastern,POINT(18.819549 -33.939883)
50 49,Hendricks Eastern Clinic,Eastern,POINT(18.741322 -33.855575)
51 50,Jansen Eastern Clinic,Eastern,POINT(18.716335 -33.858291)
52 51,Mthembu Eastern Clinic,Eastern,POINT(18.815812 -33.939998)
53 52,Cloete Eastern Clinic,Eastern,POINT(18.7562 -33.859051)
54 53,September Eastern Clinic,Eastern,POINT(18.707419 -33.854847)
55 54,October Eastern Clinic,Eastern,POINT(18.808516 -33.939819)
56 55,Williams Eastern Clinic,Eastern,POINT(18.771321 -33.862666)
57 56,Patel Klipfontein Clinic,Klipfontein,POINT(18.504291 -33.993739)
58 57,Solomons Klipfontein Clinic,Klipfontein,POINT(18.538871 -33.97474)
59 58,du Toit Klipfontein Clinic,Klipfontein,POINT(18.576669 -33.941723)
60 59,Plaatjies Klipfontein Clinic,Klipfontein,POINT(18.509944 -33.992334)
61 60,Mbeki Klipfontein Clinic,Klipfontein,POINT(18.528892 -33.976893)
62 61,Mokoena Klipfontein Clinic,Klipfontein,POINT(18.579503 -33.941066)
63 62,Ndlovu Klipfontein Clinic,Klipfontein,POINT(18.517513 -33.99081)
64 63,Pieterse Klipfontein Clinic,Klipfontein,POINT(18.51962 -33.97901)
65 64,van der Merwe Klipfontein Clinic,Klipfontein,POINT(18.579818 -33.940564)
66 65,Khumalo Mitchells Plain Clinic,Mitchells Plain,POINT(18.61394 -34.023507)
67 66,Botha Mitchells Plain Clinic,Mitchells Plain,POINT(18.593973 -34.007393)
68 67,Naidoo Mitchells Plain Clinic,Mitchells Plain,POINT(18.676699 -34.058137)
69 68,Adams Mitchells Plain Clinic,Mitchells Plain,POINT(18.626313 -34.025666)
70 69,Hendricks Mitchells Plain Clinic,Mitchells Plain,POINT(18.586437 -34.006012)
71 70,Jansen Mitchells Plain Clinic,Mitchells Plain,POINT(18.670735 -34.057301)
72 71,Mthembu Mitchells Plain Clinic,Mitchells Plain,POINT(18.638921 -34.027849)
73 72,Cloete Mitchells Plain Clinic,Mitchells Plain,POINT(18.581678 -34.004759)
74 73,September Khayelitsha Clinic,Khayelitsha,POINT(18.749114 -34.000231)
75 74,October Khayelitsha Clinic,Khayelitsha,POINT(18.687599 -34.047513)
76 75,Williams Khayelitsha Clinic,Khayelitsha,POINT(18.661432 -34.043001)
77 76,Patel Khayelitsha Clinic,Khayelitsha,POINT(18.7452 -34.000039)
78 77,Solomons Khayelitsha Clinic,Khayelitsha,POINT(18.700128 -34.045685)
79 78,du Toit Khayelitsha Clinic,Khayelitsha,POINT(18.654691 -34.044943)
80 79,Plaatjies Khayelitsha Clinic,Khayelitsha,POINT(18.738404 -34.000007)
81 80,Mbeki Khayelitsha Clinic,Khayelitsha,POINT(18.712648 -34.043773)
0:11
Let me analyze the data: 1. It's a CSV with columns: clinic_id, name, subdistrict, wkt_geom 2. There are 80 clinics (rows 2-81, so lines 2-81) 3. Subdistricts: Western, Southern, Tygerberg, Northern, Eastern, Klipfontein, Mitchells Plain, Khayelitsha 4. I need to compute: - Total count: 80 - Bounding box: [min_lon, min_lat, max_lon, max_lat] from all POINT geometries - Count per subdistrict Let me write a Python script to do this properly.
0:11
Write
/work/solve.py
content · 44 lines · py
import csv
import json
# Read the CSV
rows = []
with open("/work/capetown_clinics.csv") as f:
reader = csv.DictReader(f)
for row in reader:
rows.append(row)
# Total count
total_count = len(rows)
# Parse WKT points and compute bounding box
lons, lats = [], []
for row in rows:
wkt = row["wkt_geom"].strip()
# POINT(lon lat)
inner = wkt.replace("POINT(", "").replace(")", "")
lon_str, lat_str = inner.split()
lon = float(lon_str)
lat = float(lat_str)
lons.append(lon)
lats.append(lat)
bbox = [min(lons), min(lats), max(lons), max(lats)]
# Count per subdistrict
count_per_subdistrict = {}
for row in rows:
sd = row["subdistrict"].strip()
count_per_subdistrict[sd] = count_per_subdistrict.get(sd, 0) + 1
# Build output
result = {
"count": total_count,
"bbox": bbox,
"count_per_subdistrict": count_per_subdistrict
}
with open("/work/clinic_inventory.json", "w") as f:
json.dump(result, f, indent=2)
print(json.dumps(result, indent=2))Wrote /work/solve.py (1009 chars).
0:15
Let me run the script and then verify the output.
0:15
Bash
cd /work && python solve.py
{
"count": 80,
"bbox": [
18.380309,
-34.073855,
18.819549,
-33.701317
],
"count_per_subdistrict": {
"Western": 12,
"Southern": 12,
"Tygerberg": 11,
"Northern": 10,
"Eastern": 10,
"Klipfontein": 9,
"Mitchells Plain": 8,
"Khayelitsha": 8
}
}
0:21
The output looks correct. Let me verify the output file exists and do a quick sanity check on the bbox coordinates. Coordinates are in degrees (WGS84), so we expect lons around ~18.x and lats around ~-33.x to -34.x. That matches: - min lon: 18.380309 - min lat: -34.073855 - max lon: 18.819549 - max lat: -33.701317 That's reasonable for Cape Town. Let me verify the file exists.
0:21
Bash
ls -la /work/clinic_inventory.json
-rw-r--r-- 1 agent agent 297 Jun 18 00:28 /work/clinic_inventory.json
0:25
Everything looks good. Let me verify the output file content.
0:25
Read
/work/clinic_inventory.json
1 {
2 "count": 80,
3 "bbox": [
4 18.380309,
5 -34.073855,
6 18.819549,
7 -33.701317
8 ],
9 "count_per_subdistrict": {
10 "Western": 12,
11 "Southern": 12,
12 "Tygerberg": 11,
13 "Northern": 10,
14 "Eastern": 10,
15 "Klipfontein": 9,
16 "Mitchells Plain": 8,
17 "Khayelitsha": 8
18 }
19 }
0:31
Everything looks good. Let me verify against the requirements: 1. **count**: 80 clinics total ✓ 2. **bbox**: [min_lon, min_lat, max_lon, max_lat] = [18.380309, -34.073855, 18.819549, -33.701317] - these are reasonable degrees for Cape Town ✓ 3. **count_per_subdistrict**: 8 subdistricts all represented: Western (12), Southern (12), Tygerberg (11), Northern (10), Eastern (10), Klipfontein (9), Mitchells Plain (8), Khayelitsha (8) ✓ The output file exists with the correct name and structure. Sanity check on coordinates: longitudes ~18.38–18.82 and latitudes ~-34.07 to -33.70 — these are perfectly valid for Cape Town, South Africa in EPSG:4326 (WGS84 degrees).
0:31