adiyogi-weather 1.0.0

A comprehensive Python SDK for Adiyogi Weather API - High-precision weather, climate, and environmental data

Adiyogi Weather SDK (Python)

A comprehensive Python SDK for accessing high-precision weather, climate, and environmental data with async/await support and full type hints.

📦 Installation

pip install adiyogi-weather

🚀 Quick Start

from adiyogi_weather import Adiyogi
import asyncio

async def main():
    async with Adiyogi() as client:
        # Get current weather
        weather = await client.weather.get_current(
            lat=40.7128,
            lon=-74.0060
        )
        
        print(f"Temperature: {weather.temperature}°C")
        print(f"Condition: {weather.condition}")

if __name__ == "__main__":
    asyncio.run(main())

🌟 Features

• ✅ Fully Typed - Complete type hints with Pydantic models
• ✅ Async/Await - Built on asyncio and httpx
• ✅ Type Safe - Pydantic validation for all responses
• ✅ Zero Config - Works out of the box
• ✅ Error Handling - Comprehensive exception types
• ✅ Python 3.8+ - Modern Python support

📚 Services

Weather Forecast

async with Adiyogi() as client:
    # Get 7-day forecast
    forecast = await client.weather.get_forecast(
        lat=52.52,
        lon=13.41,
        days=7
    )
    
    for day in forecast.daily:
        print(f"{day.date}: {day.temperature.max}°C")

Historical Data

from datetime import datetime, timedelta

async with Adiyogi() as client:
    # Get historical weather
    end_date = datetime.now()
    start_date = end_date - timedelta(days=7)
    
    historical = await client.historical.get_range(
        lat=52.52,
        lon=13.41,
        start_date=start_date,
        end_date=end_date
    )
    
    print(f"Average temp: {historical.avg_temperature}°C")

Air Quality

async with Adiyogi() as client:
    # Get current air quality
    air_quality = await client.air_quality.get_current(
        lat=28.61,
        lon=77.20
    )
    
    print(f"AQI: {air_quality.aqi}")
    print(f"PM2.5: {air_quality.pm25}")

Marine Data

async with Adiyogi() as client:
    # Get marine forecast
    marine = await client.marine.get_forecast(
        lat=35.6762,
        lon=139.6503,
        days=3
    )
    
    print(f"Wave height: {marine.wave_height}m")

Elevation

async with Adiyogi() as client:
    # Get elevation
    elevation = await client.elevation.get_elevation(
        lat=47.5162,
        lon=14.5501
    )
    
    print(f"Elevation: {elevation.altitude}m")

Geocoding

async with Adiyogi() as client:
    # Search for locations
    results = await client.geocoding.search(query="London")
    
    for location in results:
        print(f"{location.name}, {location.country}")

🔧 Advanced Configuration

from adiyogi_weather import Adiyogi, AdiyogiConfig

config = AdiyogiConfig(
    api_key="your-api-key",
    base_url="https://api.adiyogi.com",
    timeout=10.0,
    max_retries=3,
    cache_enabled=True
)

async with Adiyogi(config=config) as client:
    weather = await client.weather.get_current(lat=40.7, lon=-74)

📖 API Reference

Client Methods

• client.weather.get_current(lat, lon) - Current weather
• client.weather.get_forecast(lat, lon, days) - Weather forecast
• client.historical.get_range(lat, lon, start_date, end_date) - Historical data
• client.air_quality.get_current(lat, lon) - Air quality
• client.marine.get_forecast(lat, lon, days) - Marine forecast
• client.elevation.get_elevation(lat, lon) - Elevation data
• client.geocoding.search(query) - Location search
• client.climate.get_projections(lat, lon) - Climate projections
• client.solar.get_radiation(lat, lon) - Solar radiation

Pydantic Models

from adiyogi_weather.models import (
    WeatherResponse,
    ForecastResponse,
    HistoricalResponse,
    AirQualityResponse
)

# All responses are validated Pydantic models
weather: WeatherResponse = await client.weather.get_current(lat=40.7, lon=-74)

⚠️ Error Handling

from adiyogi_weather.exceptions import (
    NetworkError,
    ValidationError,
    APIError
)

try:
    async with Adiyogi() as client:
        weather = await client.weather.get_current(lat=40.7, lon=-74)
except NetworkError as e:
    print(f"Network issue: {e}")
except ValidationError as e:
    print(f"Invalid parameters: {e}")
except APIError as e:
    print(f"API error: {e}")

🔄 Synchronous Usage

For non-async environments:

from adiyogi_weather import AdiyogiSync

client = AdiyogiSync()
weather = client.weather.get_current(lat=40.7128, lon=-74.0060)
print(f"Temperature: {weather.temperature}°C")

🧪 Testing

# Run tests
pytest

# Run with coverage
pytest --cov=adiyogi_weather

📝 Type Checking

# Run mypy
mypy adiyogi_weather

📄 License

MIT License - see LICENSE for details

🤝 Contributing

Contributions are welcome! Please read CONTRIBUTING.md for details.

🔗 Links

• Documentation
• GitHub
• PyPI
• Issues

📞 Support

For support, email [e-mail] or open an issue on GitHub.

🌍 Examples

Weather Dashboard

import asyncio
from adiyogi_weather import Adiyogi

async def weather_dashboard(cities):
    async with Adiyogi() as client:
        tasks = [
            client.weather.get_current(lat=lat, lon=lon)
            for lat, lon in cities
        ]
        results = await asyncio.gather(*tasks)
        
        for city, weather in zip(cities, results):
            print(f"{city}: {weather.temperature}°C - {weather.condition}")

cities = [(40.7128, -74.0060), (51.5074, -0.1278), (35.6762, 139.6503)]
asyncio.run(weather_dashboard(cities))

Historical Analysis

from adiyogi_weather import Adiyogi
from datetime import datetime, timedelta
import pandas as pd

async def analyze_temperature_trend():
    async with Adiyogi() as client:
        end_date = datetime.now()
        start_date = end_date - timedelta(days=365)
        
        data = await client.historical.get_range(
            lat=40.7128,
            lon=-74.0060,
            start_date=start_date,
            end_date=end_date
        )
        
        # Convert to pandas DataFrame
        df = pd.DataFrame(data.daily)
        print(f"Average temperature: {df['temperature'].mean():.1f}°C")
        print(f"Max temperature: {df['temperature'].max():.1f}°C")
        print(f"Min temperature: {df['temperature'].min():.1f}°C")

asyncio.run(analyze_temperature_trend())