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8ab6a5f 19b4563 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 | import re
import pandas as pd
from tasks.base_task import BaseTask
class CityRevenueShareTask(BaseTask):
"""Medium task: identify the city with the highest revenue and its percentage share.
The agent must group by city, compute total revenue per city,
find the top city, and calculate what percentage of overall revenue it represents.
"""
@property
def task_id(self) -> int:
return 2
@property
def difficulty(self) -> str:
return "medium"
@property
def description(self) -> str:
return (
"Which city generates the most revenue? What percentage of total revenue "
"does it represent? Round to 2 decimal places. "
"Submit your answer in the format: 'City: <name>, Percentage: <X.XX>%'"
)
def expected_answer(self) -> str:
"""Compute the top city and its revenue share.
Returns:
Formatted string like 'City: London, Percentage: 10.81%'.
"""
city_rev = self.df.groupby("city")["total_price"].sum()
top_city = city_rev.idxmax()
pct = round(city_rev[top_city] / city_rev.sum() * 100, 2)
return f"City: {top_city}, Percentage: {pct}%"
def grade(self, answer: str) -> float:
"""Grade the answer with partial credit for city and percentage.
Scoring:
- 0.5 for correct city name (case-insensitive)
- 0.5 for percentage within ±0.1 of expected
Args:
answer: The agent's submitted answer string.
Returns:
A score between 0.0 and 1.0.
"""
score = 0.0
city_rev = self.df.groupby("city")["total_price"].sum()
expected_city = city_rev.idxmax()
expected_pct = round(city_rev[expected_city] / city_rev.sum() * 100, 2)
# Check city
city_match = re.search(r"City:\s*([^,]+)", answer, re.IGNORECASE)
if city_match:
submitted_city = city_match.group(1).strip()
if submitted_city.lower() == expected_city.lower():
score += 0.5
# Check percentage
pct_match = re.search(r"Percentage:\s*([\d.]+)%?", answer, re.IGNORECASE)
if pct_match:
try:
submitted_pct = float(pct_match.group(1))
if abs(submitted_pct - expected_pct) <= 0.1:
score += 0.5
except ValueError:
pass
return max(0.05, min(0.95, score))
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