spa-l1-paris-amenity-within
Map (reference ← swipe → agent)
0:00
I'm putting together a neighbourhood demographic crosswalk for the INSEE census team and need each amenity tagged with the Paris arrondissement it falls inside. Can you join `amenities` to `arrondissements` and write the result to `amenity_to_arrondissement.csv` with one row per amenity? The columns are `osm_id`, `amenity_class`, `arrondissement_number` (integer), and `arrondissement_name` (string).
0:00
System info
{
"adapter": "openrouter",
"model": "google/gemma-4-26b-a4b-it",
"base_url": "https://openrouter.ai/api/v1"
}
0:01
Bash
ls -F
paris_amenities.gpkg
0:02
Bash
ogrinfo -al paris_amenities.gpkg
INFO: Open of `paris_amenities.gpkg'
using driver `GPKG' successful.
Layer name: amenities
Geometry: Point
Feature Count: 85
Extent: (645944.178293, 6857854.038066) - (660329.761503, 6866790.507853)
Layer SRS WKT:
PROJCRS["RGF93 v1 / Lambert-93",
BASEGEOGCRS["RGF93 v1",
DATUM["Reseau Geodesique Francais 1993 v1",
ELLIPSOID["GRS 1980",6378137,298.257222101,
LENGTHUNIT["metre",1]]],
PRIMEM["Greenwich",0,
ANGLEUNIT["degree",0.0174532925199433]],
ID["EPSG",4171]],
CONVERSION["Lambert-93",
METHOD["Lambert Conic Conformal (2SP)",
ID["EPSG",9802]],
PARAMETER["Latitude of false origin",46.5,
ANGLEUNIT["degree",0.0174532925199433],
ID["EPSG",8821]],
PARAMETER["Longitude of false origin",3,
ANGLEUNIT["degree",0.0174532925199433],
ID["EPSG",8822]],
PARAMETER["Latitude of 1st standard parallel",49,
ANGLEUNIT["degree",0.0174532925199433],
ID["EPSG",8823]],
PARAMETER["Latitude of 2nd standard parallel",44,
ANGLEUNIT["degree",0.0174532925199433],
ID["EPSG",8824]],
PARAMETER["Easting at false origin",700000,
LENGTHUNIT["metre",1],
ID["EPSG",8826]],
PARAMETER["Northing at false origin",6600000,
LENGTHUNIT["metre",1],
ID["EPSG",8827]]],
CS[Cartesian,2],
AXIS["easting (X)",east,
ORDER[1],
LENGTHUNIT["metre",1]],
AXIS["northing (Y)",north,
ORDER[2],
LENGTHUNIT["metre",1]],
USAGE[
SCOPE["Engineering survey, topographic mapping."],
AREA["France - onshore and offshore, mainland and Corsica (France métropolitaine including Corsica)."],
BBOX[41.15,-9.86,51.56,10.38]],
ID["EPSG",2154]]
Data axis to CRS axis mapping: 1,2
FID Column = fid
Geometry Column = geom
osm_id: Integer64 (0.0)
amenity_class: String (0.0)
name: String (0.0)
OGRFeature(amenities):1
osm_id (Integer64) = 9000000000
amenity_class (String) = restaurant
name (String) = Le Grand Amour Restaurant
POINT (652773.528294589 6864033.34691788)
OGRFeature(amenities):2
osm_id (Integer64) = 9000000001
amenity_class (String) = restaurant
name (String) = Talego
POINT (652322.909837805 6861774.14234469)
OGRFeature(amenities):3
osm_id (Integer64) = 9000000002
amenity_class (String) = bakery
name (String) = Mamiche
POINT (653028.103219332 6863582.05094524)
OGRFeature(amenities):4
osm_id (Integer64) = 9000000003
amenity_class (String) = bakery
name (String) = MyuMyu
POINT (653087.577427508 6858190.65544962)
OGRFeature(amenities):5
osm_id (Integer64) = 9000000004
amenity_class (String) = restaurant
name (String) = Rivages
POINT (650836.830616247 6863603.60953177)
OGRFeature(amenities):6
osm_id (Integer64) = 9000000005
amenity_class (String) = restaurant
name (String) = Seto
POINT (648136.131245244 6860668.26386403)
OGRFeature(amenities):7
osm_id (Integer64) = 9000000006
amenity_class (String) = restaurant
name (String) = Les Petits Campagnards
POINT (655325.130636362 6863817.18247694)
OGRFeature(amenities):8
osm_id (Integer64) = 9000000007
amenity_class (String) = cafe
name (String) = Maison Christine Champault
POINT (651260.332239006 6861602.4052535)
OGRFeature(amenities):9
osm_id (Integer64) = 9000000008
amenity_class (String) = restaurant
name (String) = Proibido
POINT (651294.337950766 6865384.58776667)
OGRFeature(amenities):10
osm_id (Integer64) = 9000000009
amenity_class (String) = cafe
name (String) = Café Zed
POINT (652311.707509484 6860216.57514999)
OGRFeature(amenities):11
osm_id (Integer64) = 9000000010
amenity_class (String) = restaurant
name (String) = Bedford Epinettes
POINT (650378.591001625 6866408.53238701)
OGRFeature(amenities):12
osm_id (Integer64) = 9000000011
amenity_class (String) = restaurant
name (String) = Bennath
POINT (650322.425261414 6861049.86089619)
OGRFeature(amenities):13
osm_id (Integer64) = 9000000012
amenity_class (String) = restaurant
name (String) = San Régis
POINT (649275.086029316 6863156.73129305)
OGRFeature(amenities):14
osm_id (Integer64) = 9000000013
amenity_class (String) = restaurant
name (String) = Chez Katy
POINT (651621.835552618 6862706.2418534)
OGRFeature(amenities):15
osm_id (Integer64) = 9000000014
amenity_class (String) = restaurant
name (String) = Le Trattoria
POINT (652173.628465493 6863673.43564047)
OGRFeature(amenities):16
osm_id (Integer64) = 9000000015
amenity_class (String) = cafe
name (String) = Le 360 Cafe
POINT (650177.985794601 6860526.60952141)
OGRFeature(amenities):17
osm_id (Integer64) = 9000000016
amenity_class (String) = cafe
name (String) = Rosa Bonheur a l'Est
POINT (660329.761503407 6859982.11822279)
OGRFeature(amenities):18
osm_id (Integer64) = 9000000017
amenity_class (String) = bakery
name (String) = Pâtisserie La Romainville
POINT (649012.559458438 6860590.06564835)
OGRFeature(amenities):19
osm_id (Integer64) = 9000000018
amenity_class (String) = cafe
name (String) = Yumtcha
POINT (652775.410374421 6862777.76524597)
OGRFeature(amenities):20
osm_id (Integer64) = 9000000019
amenity_class (String) = bakery
name (String) = Pastel Bakery
POINT (650846.608424843 6864300.060598)
OGRFeature(amenities):21
osm_id (Integer64) = 9000000020
amenity_class (String) = restaurant
name (String) = Au Relais des Sportifs
POINT (655365.147800597 6866790.50785302)
OGRFeature(amenities):22
osm_id (Integer64) = 9000000021
amenity_class (String) = cafe
name (String) = Café Pigalle
POINT (651400.918892585 6864818.2960926)
OGRFeature(amenities):23
osm_id (Integer64) = 9000000022
amenity_class (String) = restaurant
name (String) = Flam's
POINT (650120.773520746 6860498.95307651)
OGRFeature(amenities):24
osm_id (Integer64) = 9000000023
amenity_class (String) = bakery
name (String) = Pierre Hermé
POINT (650484.549219444 6861793.89851404)
OGRFeature(amenities):25
osm_id (Integer64) = 9000000024
amenity_class (String) = pharmacy
name (String) = Grande Pharmacie de la Place Blanche
POINT (651028.783228002 6865038.04411733)
OGRFeature(amenities):26
osm_id (Integer64) = 9000000025
amenity_class (String) = library
name (String) = Médiathèque Françoise Sagan
POINT (652602.786708231 6864157.56127286)
OGRFeature(amenities):27
osm_id (Integer64) = 9000000026
amenity_class (String) = bakery
name (String) = Maison Marie
POINT (653164.982943908 6863616.54542779)
OGRFeature(amenities):28
osm_id (Integer64) = 9000000027
amenity_class (String) = restaurant
name (String) = Gypsi Motel
POINT (648890.462191529 6863785.19371308)
OGRFeature(amenities):29
osm_id (Integer64) = 9000000028
amenity_class (String) = bakery
name (String) = Le Pain en Fête
POINT (652287.522817416 6865823.46188395)
OGRFeature(amenities):30
osm_id (Integer64) = 9000000029
amenity_class (String) = restaurant
name (String) = Bus restaurant, Les Carrosses de Paris
POINT (650164.45273545 6860516.15266298)
OGRFeature(amenities):31
osm_id (Integer64) = 9000000030
amenity_class (String) = restaurant
name (String) = Canons
POINT (654388.046853858 6863488.63818158)
OGRFeature(amenities):32
osm_id (Integer64) = 9000000031
amenity_class (String) = bakery
name (String) = Paris' Bakery
POINT (647860.500727435 6859699.70233437)
OGRFeature(amenities):33
osm_id (Integer64) = 9000000032
amenity_class (String) = bakery
name (String) = Aux Délices de Rosa Parks
POINT (654091.903650154 6866416.67124904)
OGRFeature(amenities):34
osm_id (Integer64) = 9000000033
amenity_class (String) = pharmacy
name (String) = Pharmacie Jaïs
POINT (650788.555928847 6860360.46285907)
OGRFeature(amenities):35
osm_id (Integer64) = 9000000034
amenity_class (String) = pharmacy
name (String) = Grande Pharmacie Hahnemann
POINT (648349.744848971 6859904.05930838)
OGRFeature(amenities):36
osm_id (Integer64) = 9000000035
amenity_class (String) = cafe
name (String) = La Coupe d'Or
POINT (650903.526683949 6863054.6604047)
OGRFeature(amenities):37
osm_id (Integer64) = 9000000036
amenity_class (String) = restaurant
name (String) = 91 Gouvion Saint Cyr
POINT (647539.953760233 6864555.90227963)
OGRFeature(amenities):38
osm_id (Integer64) = 9000000037
amenity_class (String) = cafe
name (String) = Le Dis Vin Gaulois
POINT (649187.116880711 6859957.02969198)
OGRFeature(amenities):39
osm_id (Integer64) = 9000000038
amenity_class (String) = library
name (String) = Bibliothèque de l’IDC - Université Paris-Panthéon-Assas
POINT (650715.09558239 6861799.49764804)
OGRFeature(amenities):40
osm_id (Integer64) = 9000000039
amenity_class (String) = bakery
name (String) = Boulangerie Jaabar
POINT (647818.475955772 6859716.72285273)
OGRFeature(amenities):41
osm_id (Integer64) = 9000000040
amenity_class (String) = bakery
name (String) = Boulangerie Mozart
POINT (647096.195040448 6859902.48589219)
OGRFeature(amenities):42
osm_id (Integer64) = 9000000041
amenity_class (String) = library
name (String) = Bibliothèque Sigmund Freud
POINT (651899.898811036 6858855.6410015)
OGRFeature(amenities):43
osm_id (Integer64) = 9000000042
amenity_class (String) = pharmacy
name (String) = Pharmacie Bui-Nguyen
POINT (655818.462858864 6864123.45052437)
OGRFeature(amenities):44
osm_id (Integer64) = 9000000043
amenity_class (String) = cafe
name (String) = Coffee Parisien
POINT (651158.155550115 6861593.74892046)
OGRFeature(amenities):45
osm_id (Integer64) = 9000000044
amenity_class (String) = bakery
name (String) = Boulangerie Clouet
POINT (653146.142543665 6857854.03806592)
OGRFeature(amenities):46
osm_id (Integer64) = 9000000045
amenity_class (String) = library
name (String) = Bibliothequepolar
POINT (652620.377451195 6859097.2960284)
OGRFeature(amenities):47
osm_id (Integer64) = 9000000046
amenity_class (String) = cafe
name (String) = Chez ta Sœur
POINT (651847.662729488 6865807.54006877)
OGRFeature(amenities):48
osm_id (Integer64) = 9000000047
amenity_class (String) = cafe
name (String) = La Coopérative
POINT (651709.149443704 6862466.82971344)
OGRFeature(amenities):49
osm_id (Integer64) = 9000000048
amenity_class (String) = pharmacy
name (String) = Pharmacie Volontaires
POINT (649181.206556948 6860376.83238451)
OGRFeature(amenities):50
osm_id (Integer64) = 9000000049
amenity_class (String) = bakery
name (String) = L'Atelier des Pains
POINT (649736.664496875 6864381.35178851)
OGRFeature(amenities):51
osm_id (Integer64) = 9000000050
amenity_class (String) = bakery
name (String) = Odette Paris
POINT (652048.267104437 6861535.6497115)
OGRFeature(amenities):52
osm_id (Integer64) = 9000000051
amenity_class (String) = pharmacy
name (String) = Grande Pharmacie de la Bourse
POINT (651536.455056417 6863414.08880619)
OGRFeature(amenities):53
osm_id (Integer64) = 9000000052
amenity_class (String) = bakery
name (String) = Les Pains d'Alexis
POINT (651977.640281005 6860007.10069004)
OGRFeature(amenities):54
osm_id (Integer64) = 9000000053
amenity_class (String) = cafe
name (String) = Caffè Concerto
POINT (651130.240257343 6862588.27136404)
OGRFeature(amenities):55
osm_id (Integer64) = 9000000054
amenity_class (String) = pharmacy
name (String) = Pharmacie du Drugstore des Champs-Élysées
POINT (648434.306990963 6863854.87493581)
OGRFeature(amenities):56
osm_id (Integer64) = 9000000055
amenity_class (String) = pharmacy
name (String) = Pharmacie Bienvenue
POINT (650226.463287975 6860305.52728172)
OGRFeature(amenities):57
osm_id (Integer64) = 9000000056
amenity_class (String) = cafe
name (String) = Coffee Club
POINT (651213.046424065 6860427.23062987)
OGRFeature(amenities):58
osm_id (Integer64) = 9000000057
amenity_class (String) = cafe
name (String) = Coconut Cafe
POINT (647143.249085489 6863201.75409782)
OGRFeature(amenities):59
osm_id (Integer64) = 9000000058
amenity_class (String) = cafe
name (String) = Café Pasteur
POINT (649586.907897647 6860534.37831715)
OGRFeature(amenities):60
osm_id (Integer64) = 9000000059
amenity_class (String) = cafe
name (String) = Le Boudoir CAFE
POINT (652105.9010669 6864531.35254002)
OGRFeature(amenities):61
osm_id (Integer64) = 9000000060
amenity_class (String) = pharmacy
name (String) = Soins Holistiques - Maria Vittoria Ruffo
POINT (652571.991347368 6862629.44146339)
OGRFeature(amenities):62
osm_id (Integer64) = 9000000061
amenity_class (String) = pharmacy
name (String) = Académie Dien Chan
POINT (645944.178292822 6861065.42669241)
OGRFeature(amenities):63
osm_id (Integer64) = 9000000062
amenity_class (String) = cafe
name (String) = Maca-Rong
POINT (650566.551689986 6865957.88740352)
OGRFeature(amenities):64
osm_id (Integer64) = 9000000063
amenity_class (String) = cafe
name (String) = Café Odilon
POINT (654671.209328297 6865643.7715652)
OGRFeature(amenities):65
osm_id (Integer64) = 9000000064
amenity_class (String) = cafe
name (String) = Café Dose Paris Lamarck
POINT (651507.364693074 6865765.32571854)
OGRFeature(amenities):66
osm_id (Integer64) = 9000000065
amenity_class (String) = cafe
name (String) = Au Métro
POINT (649531.381665764 6860520.15635166)
OGRFeature(amenities):67
osm_id (Integer64) = 9000000066
amenity_class (String) = pharmacy
name (String) = Pharmacie Pharmavance
POINT (647387.799337267 6863606.56726319)
OGRFeature(amenities):68
osm_id (Integer64) = 9000000067
amenity_class (String) = library
name (String) = Library François Villon
POINT (653855.660918546 6864319.26638835)
OGRFeature(amenities):69
osm_id (Integer64) = 9000000068
amenity_class (String) = pharmacy
name (String) = Pharmacie des Orgues de Flandre
POINT (654231.42260792 6865796.10263219)
OGRFeature(amenities):70
osm_id (Integer64) = 9000000069
amenity_class (String) = pharmacy
name (String) = Grande pharmacie du Palais
POINT (652409.000173277 6862140.56593736)
OGRFeature(amenities):71
osm_id (Integer64) = 9000000070
amenity_class (String) = pharmacy
name (String) = Pharmacie F
POINT (654131.927654414 6859280.11008617)
OGRFeature(amenities):72
osm_id (Integer64) = 9000000071
amenity_class (String) = pharmacy
name (String) = Pharmacie D'anvers
POINT (652044.891743009 6864867.00556403)
OGRFeature(amenities):73
osm_id (Integer64) = 9000000072
amenity_class (String) = library
name (String) = Bibliothèque d'histoire de l'art, Fondation Custodia
POINT (650100.841676611 6862585.59324263)
OGRFeature(amenities):74
osm_id (Integer64) = 9000000073
amenity_class (String) = library
name (String) = CDMC
POINT (655561.733498605 6865785.79710841)
OGRFeature(am
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OGRFeature(arrondissements):19
id (String) = ed5166f4-7111-4e42-bcbe-0630271cc71e
name (String) = Paris 1er Arrondissement
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OGRFeature(arrondissements):20
id (String) = f22f8b89-a6ec-449f-bc9a-cf3c7644d0e0
name (String) = Paris 15e Arrondissement
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0:18
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/work/solve.py
content · 87 lines · py
import geopandas as gpd
import pandas as pd
def solve():
# Load the data
gdf_amenities = gpd.read_file('paris_amenities.gpkg', layer='amenities')
gdf_arrondissements = gpd.read_file('paris_amenities.gpkg', layer='arrondissements')
# Ensure both use the same CRS
if gdf_amenities.crs != gdf_arrondissements.crs:
gdf_amenities = gdf_amenities.to_crs(gdf_arrondissements.crs)
# Perform spatial join
# amenities (points) inside arrondissements (polygons)
joined = gpd.sjoin(gdf_amenities, gdf_arrondissements, how='left', predicate='within')
# The goal is to have:
# osm_id, amenity_class, arrondissement_number (int), arrondissement_name (str)
# Let's check the column names in arrondissements from the ogrinfo output
# name: String
# id: String
# wait, I don't see 'arrondissement_number' in the ogrinfo output for 'arrondissements'
# Let's re-examine the ogrinfo output for 'arrondissements'
# Looking at the ogrinfo output again:
# Layer name: arrondissements
# name (String) = Paris 1er Arrondissement
# id (String) = ed5166f4-7111-4e42-bcbe-0630271cc71e
# I need to extract the number from 'name'.
# 'Paris 1er Arrondissement' -> 1
# 'Paris 15e Arrondissement' -> 15
import re
def extract_number(name):
if not name:
return None
# Match digits followed by 'er' or 'e' or nothing (though usually 'er' or 'e' in French)
# Example: '1er', '15e'
match = re.search(r'(\d+)(?:er|e)?', name)
if match:
return int(match.group(1))
return None
# Create the new columns
# Note: 'name_left' and 'name_right' might occur due to join if both have 'name'
# Since we did gdf_amenities.sjoin(gdf_arrondissements),
# columns from gdf_arrondissements will be prefixed with 'index_right' or similar?
# No, geopandas adds 'index_right'. If names clash, it's usually name_left, name_right.
# Let's check columns after join
print("Columns after join:", joined.columns.tolist())
# Rename/Extract
# Based on ogrinfo, 'name' in arrondissements is the full string.
# In sjoin, if both have 'name', gdf_arrondissements's name becomes 'name_right' or 'name' depending on version.
# Let's assume 'name_right' or 'name' for arrondissements.
arr_name_col = 'name_right' if 'name_right' in joined.columns else 'name'
# But wait, 'name' is also in amenities.
# Let's be safer.
# Check if 'name' from arrondissements is present.
# If gdf_amenities has 'name' and gdf_arrondissements has 'name',
# the result will have 'name_left' (amenity name) and 'name_right' (arrondissement name).
# Let's look at the result of the print(joined.columns) in the script.
# We'll define the final columns
# osm_id, amenity_class, arrondissement_number, arrondissement_name
# We will use 'name_right' for arrondissement_name
# We will use 'name_left' for amenity name if needed, but we don't need it in output.
# We'll clean up the dataframe
# Note: some amenities might not fall in any arrondissement (though in Paris they should)
# The requirement says "each amenity tagged with the Paris arrondissement it falls inside"
# We should probably drop amenities that didn't join if they are outside,
# but usually 'left' join is safer and then we can check.
# However, the prompt implies every amenity in the list should be there.
# Let's refine the logic in the script after I know the column names.
solve()
Wrote /work/solve.py (3616 chars).
0:53
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/work/solve.py
old_string not found in /work/solve.py
1:05
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/work/solve.py
content · 74 lines · py
import geopandas as gpd
import pandas as pd
import re
def extract_number(name):
if not name or pd.isna(name):
return None
# Match digits
match = re.search(r'(\d+)', str(name))
if match:
return int(match.group(1))
return None
def solve():
# Load the data
gdf_amenities = gpd.read_file('paris_amenities.gpkg', layer='amenities')
gdf_arrondissements = gpd.read_file('paris_amenities.gpkg', layer='arrondissements')
# Ensure both use the same CRS
if gdf_amenities.crs != gdf_arrondissements.crs:
gdf_amenities = gdf_amenities.to_crs(gdf_arrondissements.crs)
# Perform spatial join
# amenities (points) inside arrondissements (polygons)
joined = gpd.sjoin(gdf_amenities, gdf_arrondissements, how='left', predicate='within')
# Inspect columns to be absolutely sure
print("Columns after join:", joined.columns.tolist())
# In geopandas sjoin, if both layers have a 'name' column,
# the result will have 'name_left' and 'name_right'.
# amenity 'name' -> 'name_left'
# arrondissement 'name' -> 'name_right'
result = pd.DataFrame()
result['osm_id'] = joined['osm_id']
result['amenity_class'] = joined['amenity_class']
if 'name_right' in joined.columns:
result['arrondissement_name'] = joined['name_right']
elif 'name' in joined.columns:
# This would happen if only one had 'name' or they didn't collide.
# But given our ogrinfo, they both have it.
# If 'name' is the only one, we have to guess.
# But we'll assume name_right if it exists.
result['arrondissement_name'] = joined['name']
else:
result['arrondissement_name'] = None
# Extract number
result['arrondissement_number'] = result['arrondissement_name'].apply(extract_number)
# Fill NaNs for number if we want integer type (pandas requires float for NaN or using Int64)
# The instruction says arrondissement_number (integer).
# We'll use Int64 which supports NaNs but is an integer type.
result['arrondissement_number'] = result['arrondissement_number'].astype('Int64')
# Ensure arrondissement_name is string
result['arrondissement_name'] = result['arrondissement_name'].astype(str).replace('nan', None).replace('None', None)
# Actually, the requirement says "arrondissement_name (string)".
# Let's just make sure it's string and handle any possible nulls gracefully.
result['arrondissement_name'] = result['arrondissement_name'].astype(str)
# Final columns check
result = result[['osm_id', 'amenity_class', 'arrondissement_number', 'arrondissement_name']]
# Save to CSV
result.to_csv('amenity_to_arrondissement.csv', index=False)
print("Successfully wrote amenity_to_arrondissement.csv")
print(result.head())
if __name__ == "__main__":
solve()
Wrote /work/solve.py (2875 chars).
1:08
Bash
python solve.py
Columns after join: ['osm_id', 'amenity_class', 'name_left', 'geometry', 'index_right', 'id', 'name_right']
Successfully wrote amenity_to_arrondissement.csv
osm_id amenity_class arrondissement_number arrondissement_name
0 9000000000 restaurant 10 Paris 10e Arrondissement
1 9000000001 restaurant 4 Paris 4e Arrondissement
2 9000000002 bakery 10 Paris 10e Arrondissement
3 9000000003 bakery 13 Paris 13e Arrondissement
4 9000000004 restaurant 9 Paris 9e Arrondissement
1:10
Bash
head -n 5 amenity_to_arrondissement.csv
osm_id,amenity_class,arrondissement_number,arrondissement_name 9000000000,restaurant,10,Paris 10e Arrondissement 9000000001,restaurant,4,Paris 4e Arrondissement 9000000002,bakery,10,Paris 10e Arrondissement 9000000003,bakery,13,Paris 13e Arrondissement
1:14
Bash
python -c "import pandas as pd; df = pd.read_csv('amenity_to_arrondissement.csv'...
osm_id int64 amenity_class str arrondissement_number int64 arrondissement_name str dtype: object
1:18
Bash
ls -F
amenity_to_arrondissement.csv paris_amenities.gpkg solve.py
1:30