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Access current conditions, hourly forecasts, 14-day outlooks, historical weather, and astronomy data for any location worldwide. A reliable alternative to OpenWeatherMap for building weather-enriched data pipelines, IoT data ingestion workflows, and climate feature engineering in Python machine learning projects.
WeatherAPI has no official Python SDK, so engineers use `requests` with their API key to query current, forecast, and historical endpoints. Responses are clean JSON that map directly into pandas for time-series correlation with other business data.
WeatherAPI data enriches AI models with real-world environmental context. Retail demand forecasting models use weather as a feature, while RAG systems can retrieve live weather to answer questions like 'Should I bring an umbrella in Tokyo this week?' with accurate, location-specific data.
# pip install requests
import requests
resp = requests.get(
"https://api.weatherapi.com/v1/current.json",
params={"key": "YOUR_API_KEY", "q": "New York"}
)
data = resp.json()
print(data["current"]["temp_c"], "°C", data["current"]["condition"]["text"])Official dataset source
More datasets used by Python data engineers.
Access current weather conditions, hourly and 16-day forecasts, historical weather data, and air pollution metrics for any location on Earth. Widely used in Python data engineering pipelines for enriching datasets with weather context, building weather dashboards, and integrating climate signals into machine learning features via the pyowm library.
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