Metadata-Version: 2.4
Name: sgu-client
Version: 0.1.0
Summary: A modern Python client library for accessing Geological Survey of Sweden groundwater data APIs with type safety and pandas integration
Author: Anders Retzner
Author-email: Anders Retzner <anders.retzner@gmail.com>
License-Expression: MIT
Requires-Dist: requests>=2.28.0
Requires-Dist: pydantic>=2.0.0
Requires-Dist: pandas>=1.5.0 ; extra == 'recommended'
Requires-Python: >=3.11
Provides-Extra: recommended
Description-Content-Type: text/markdown

# SGU Client

A modern Python client library for accessing Geological Survey of Sweden (SGU) groundwater data APIs with type safety and pandas integration.

[![Python Version](https://img.shields.io/badge/python-3.11+-blue.svg)](https://python.org)
[![PyPI version](https://badge.fury.io/py/sgu-client.svg)](https://badge.fury.io/py/sgu-client)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Code style: ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)

> This package is not affiliated with or endorsed by SGU.

## Features

- **Type-safe**: Full type hints with Pydantic validation
- **Pandas integration**: Convert data to DataFrames with optional pandas dependency
- **Friendly shortcuts**: Convenience functions to access stations by names, modeled levels by coordinates, and much more.

Get going with your analysis in just a few lines of code:

```python
from sgu_client import SGUClient

with SGUClient() as client:
    measurements = client.levels.observed.get_measurements_by_name(platsbeteckning="95_2")
    df = measurements.to_dataframe()

# ... rest of your awesome workflow
```

## Installation

Using `uv`

```bash
# basic installation
uv add sgu-client

# with pandas support for dataframe conversion
uv add "sgu-client[recommended]"
```

... or using `pip`

```bash
# basic installation
pip install sgu-client

# with pandas support for dataframe conversion
pip install "sgu-client[recommended]"
```

## Usage

### Initializing a client

```python
from sgu_client import SGUClient

client = SGUClient()

# with custom configuration
from sgu_client import SGUConfig
config = SGUConfig(timeout=60, debug=True, max_retries=5)
client = SGUClient(config=config)

# as a context manager
with SGUClient() as client:
    stations = client.levels.observed.get_stations(limit=10)
```

### Observed groundwater levels

Access real-time and historical groundwater monitoring data from SGU's network of observation stations.

```python
from sgu_client import SGUClient
from datetime import UTC, datetime


with SGUClient() as client:
    # basic API endpoint usage
    stations = client.levels.observed.get_stations(limit=50)
    
    # with OGC API filters, like bbox of southern Sweden
    stations = client.levels.observed.get_stations(
        bbox=[12.0, 55.0, 16.0, 58.0],
        limit=100
    )
    
    # convenience function to get station by name 
    station = client.levels.observed.get_station_by_name(
        platsbeteckning="95_2"  # or obsplatsnamn="95_2"
    )
    # or multiple stations by names
    stations = client.levels.observed.get_stations_by_names(
        platsbeteckning=["95_2", "101_1"]  # or obsplatsnamn=["Lagga_2", ...]
    )

    # convenience function to get measurements by station name
    measurements = client.levels.observed.get_measurements_by_name(
        platsbeteckning="95_2",  # or obsplatsnamn="95_2"
        limit=100
    )
    # or multiple stations by names
    measurements = client.levels.observed.get_measurements_by_names(
        platsbeteckning=["95_2", "101_1"],  # or obsplatsnamn=["Lagga_2", ...]
        limit=100
    )

    # filter by datetime for faster responses
    tmin = datetime(2020, 1, 1, tzinfo=UTC)
    tmax = datetime(2021, 1, 1, tzinfo=UTC)
    measurements = client.levels.observed.get_measurements_by_names(
        platsbeteckning=["95_2"], tmin=tmin, tmax=tmax, limit=10
    )
    
    # responses that create lists of features can be converted to pandas DataFrames
    measurements = client.levels.observed.get_measurements_by_names(
        platsbeteckning=["95_2", "101_1"],  # or obsplatsnamn=["Lagga_2", ...]
        limit=100
    )
    df = measurements.to_dataframe()  # requires pandas
```

### Modeled groundwater levels

Access modeled groundwater levels from SGU-HYPE.

```python
from sgu_client import SGUClient

with SGUClient() as client:
    # basic API endpoint usage
    areas = client.levels.modeled.get_areas(limit=10)
    
    # with OGC API filters, like bbox of southern Sweden
    areas = client.levels.modeled.get_areas(
        bbox=[12.0, 55.0, 16.0, 58.0],
        limit=20
    )
    
    # get a specific area by ID
    area = client.levels.modeled.get_area("omraden.30125")
    print(f"Area ID: {area.properties.omrade_id}")
    print(f"Geometry: {area.geometry.type}")
    
    # convenience function to get levels for a specific area
    levels = client.levels.modeled.get_levels_by_area(30125, limit=10)
    # or multiple areas by IDs
    levels = client.levels.modeled.get_levels_by_areas(
        area_ids=[30125, 30126],
        limit=50
    )

    # convenience function to get levels by coordinates
    levels = client.levels.modeled.get_levels_by_coords(
        lat=57.7089,
        lon=11.9746,
        limit=10
    )
    
    # responses that create lists of features can be converted to pandas DataFrames
    levels = client.levels.modeled.get_levels_by_areas(
        area_ids=[30125, 30126],
        limit=50
    )
    df = levels.to_dataframe()  # requires pandas
```

### Working with Typed Data

All responses are fully typed with Pydantic models:

```python
from sgu_client import SGUClient

client = SGUClient()

# Get stations with full type safety
stations = client.levels.observed.get_stations(limit=5)

for station in stations.features:
    # All properties are typed and documented
    print(f"Station: {station.properties.obsplatsnamn}")
    print(f"Municipality: {station.properties.kommun}")
    print(f"Coordinates: {station.geometry.coordinates}")

# Get measurements with automatic datetime parsing
measurements = client.levels.observed.get_measurements(limit=5)
for measurement in measurements.features:
    props = measurement.properties
    print(f"Date: {props.observation_date}")  # Parsed datetime object
    print(f"Level: {props.grundvattenniva_m_o_h} m above sea level")
```

## API Reference

### SGUClient

The main client class providing access to all SGU APIs.

- `levels.observed` - Observed groundwater level measurements
- `levels.modeled` - Modeled groundwater levels from SGU-HYPE

### Configuration

```python
from sgu_client import SGUConfig

config = SGUConfig(
    timeout=30,        # Request timeout in seconds
    max_retries=3,     # Maximum retry attempts
    debug=False        # Enable debug logging
)
```

## Development

We recommend using [uv](https://github.com/astral-sh/uv) for development:

```bash
# Clone the repository
git clone https://github.com/officialankan/sgu-client.git
cd sgu-client

# Install dependencies and sync environment
uv sync --all-extras

# Run tests
uv run pytest

# Format and lint code
uv run ruff format
uv run ruff check --fix
```

### Release Process

To release a new version:

1. Create PR with your changes + version bump in `pyproject.toml`
2. PR will be tested and published to TestPyPI for verification
3. Once merged, the new version is automatically published to PyPI

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

## Roadmap

- [x] Initial release with observed and modeled groundwater levels
- [ ] Add example notebooks and tutorials
- [ ] Add support for groundwater quality API
- [ ] Add support for geological data API

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Acknowledgments

- [Sveriges geologiska undersökning (SGU)](https://www.sgu.se/) for providing open access to groundwater data
- Built with [uv](https://github.com/astral-sh/uv), [Pydantic](https://pydantic.dev/), and [requests](https://requests.readthedocs.io/)
