Metadata-Version: 2.2
Name: meteo_lt-pkg
Version: 0.2.4
Summary: A library to fetch weather data from api.meteo.lt
Author-email: Brunas <brunonas@gmail.com>
Project-URL: Homepage, https://github.com/Brunas/meteo_lt-pkg
Project-URL: Issues, https://github.com/Brunas/meteo_lt-pkg/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: aiohttp
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Requires-Dist: pytest-asyncio; extra == "dev"
Requires-Dist: black; extra == "dev"
Requires-Dist: coverage; extra == "dev"
Requires-Dist: flake8; extra == "dev"
Requires-Dist: pyflakes; extra == "dev"
Requires-Dist: pylint; extra == "dev"
Requires-Dist: build; extra == "dev"

# Meteo.Lt Lithuanian weather forecast package

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MeteoLt-Pkg is a Python library designed to fetch weather data from [`api.meteo.lt`](https://api.meteo.lt/). This library provides convenient methods to interact with the API and obtain weather forecasts and related data. Please visit for more information.

## Installation

You can install the package using pip:

```bash
pip install meteo_lt-pkg
```

## Usage

Initializing the API Client
To start using the library, you need to initialize the `MeteoLtAPI` client:

```python
from meteo_lt import MeteoLtAPI

api_client = MeteoLtAPI()
```

### Fetching Places

To get the list of available places:

```python
import asyncio

async def fetch_places():
    await api_client.fetch_places()
    for place in api_client.places:
        print(place)

asyncio.run(fetch_places())
```

### Getting the Nearest Place

You can find the nearest place using latitude and longitude coordinates:

```python
async def find_nearest_place(latitude, longitude):
    nearest_place = await api_client.get_nearest_place(latitude, longitude)
    print(f"Nearest place: {nearest_place.name}")

 # Example coordinates for Vilnius, Lithuania
asyncio.run(find_nearest_place(54.6872, 25.2797))
```

Also, if no places are retrieved before, that is done automatically in `get_nearest_place` method.

### Fetching Weather Forecast

To get the weather forecast for a specific place, use the get_forecast method with the place code:

```python
async def fetch_forecast(place_code):
    forecast = await api_client.get_forecast(place_code)
    current_conditions = forecast.current_conditions()
    print(f"Current temperature: {current_conditions.temperature}°C")

# Example place code for Vilnius, Lithuania
asyncio.run(fetch_forecast("vilnius"))
```
>**NOTE** `current_conditions` is the current hour record from the `forecast_timestamps` array. Also, `forecast_timestamps` array has past time records filtered out due to `api.meteo.lt` not doing that automatically.

## Data Models

The package includes several data models to represent the API responses:

### Coordinates

Represents geographic coordinates.

```python
from meteo_lt import Coordinates

coords = Coordinates(latitude=54.6872, longitude=25.2797)
print(coords)
```

### Place

Represents a place with associated metadata.

```python
from meteo_lt import Place

place = Place(code="vilnius", name="Vilnius", administrative_division="Vilnius City Municipality", country="LT", coordinates=coords)
print(place.latitude, place.longitude)
```

### ForecastTimestamp

Represents a timestamp within the weather forecast, including various weather parameters.

```python
from meteo_lt import ForecastTimestamp

forecast_timestamp = ForecastTimestamp(
    datetime="2024-07-23T12:00:00+00:00",
    temperature=25.5,
    apparent_temperature=27.0,
    condition_code="clear",
    wind_speed=5.0,
    wind_gust_speed=8.0,
    wind_bearing=180,
    cloud_coverage=20,
    pressure=1012,
    humidity=60,
    precipitation=0
)
print(forecast_timestamp.condition)
```

### Forecast

Represents the weather forecast for a place, containing multiple forecast timestamps.

```python
from meteo_lt import Forecast

forecast = Forecast(
    place=place,
    forecast_created=datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
    forecast_timestamps=[forecast_timestamp]
)
print(forecast.current_conditions().temperature)
```

## Contributing

Contributions are welcome! For major changes please open an issue to discuss or submit a pull request with your changes. If you want to contribute you can use devcontainers in vscode for easiest setup follow [instructions here](.devcontainer/README.md).

***

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[commits]: https://github.com/Brunas/meteo_lt-pkg/commits/main
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[releases]: https://github.com/Brunas/meteo_lt-pkg/releases