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Ksar Hellal
City in Monastir, Tunisia
Overview
Ksar Hellal is a lively mid-sized city in the Monastir region, renowned for its textile industry and warm local culture. Its lively streets, welcoming residents, and markets offer an authentic Tunisian experience without the tourist crowds. Proximity to the Mediterranean coast and Monastir adds extra appeal.
Geographic Context
Jurisdiction
Tunisia
Governorate
Monastir
Population
49,376
Time Zone
Africa/Tunis
Coordinates
35.65°, 10.89°
Key Metrics
Safety Score · estimate
65
Female Safety
50
LGBTQ+ Safety
30
Traffic Safety
60
Food Safety
70
Monthly Cost · estimate
$532
Local Cost
$267
Local Income
$220
Cashless
40
English
30
Temperature
19.6°C
Summer Avg
28.0°C
Winter Avg
11.5°C
Record High
46.2°C
Record Low
-1.2°C
Humidity
64%
Precipitation
360 mm
Internet Speed
11 Mbps
Upload
3 Mbps
Latency
57 ms
City Vibrancy
18
Coworking
0
Cafes
17
Nightlife
0
Parks
1
Transport
0
Walk Score
0
Footways
—
Airport
MIR
Distance
17 km
Explore
Data sources
Source-backed data
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-06.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Record updated 2025-12-05.
Estimates and unverified origins
Oyster List climate data - Climate origins are unverified. Available methods include historical APIs and AI estimates; stored rows do not identify the original dataset, reference period, or model for each value. Treat these summaries as estimates until independently verified. Record updated 2026-03-22.
Oyster List city price estimates - Price origins are unverified. Available generation methods include AI estimates; stored records do not identify a survey, observation period, or model for each price. Record updated 2026-01-14.
Oyster List AI-assisted estimates - Safety, lifestyle, income, and practical scores include model-assisted estimates. Stored records do not identify supporting observations for each score. Model-reported confidence: 55/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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