Skip to main content

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

Project description

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 PyPI version License: MIT codecov Code style: 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 or Series 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:

from sgu_client import SGUClient

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

# ... rest of your awesome workflow

Installation

Using uv

# basic installation
uv add sgu-client

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

... or using pip

# basic installation
pip install sgu-client

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

Usage

Initializing a client

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.

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(
        station_id="95_2"  # or station_name="95_2"
    )
    # or multiple stations by names
    stations = client.levels.observed.get_stations_by_names(
        station_id=["95_2", "101_1"]  # or station_name=["Lagga_2", ...]
    )

    # convenience function to get measurements by station name
    measurements = client.levels.observed.get_measurements_by_name(
        station_id="95_2",  # or station_name="95_2"
        limit=100
    )
    # or multiple stations by names
    measurements = client.levels.observed.get_measurements_by_names(
        station_id=["95_2", "101_1"],  # or station_name=["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(
        station_id=["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(
        station_id=["95_2", "101_1"],  # or station_name=["Lagga_2", ...]
        limit=100
    )
    df = measurements.to_dataframe()  
    # or series
    series = measurements.to_series()  # defaults to 'water_level_masl_m' (head) column with datetime index

Modeled groundwater levels

Access modeled groundwater levels from SGU-HYPE.

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.area_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()
    # or series
    series = levels.to_series()  # defaults to 'relative_level_small_resources' column with datetime index

Working with Typed Data

All responses are fully typed with Pydantic models:

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.station_name}")
    print(f"Municipality: {station.properties.municipality}")
    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_datetime}")  # Parsed datetime object
    print(f"Level: {props.water_level_masl_m} 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

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 for development:

# 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

  • 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 file for details.

Acknowledgments

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sgu_client-0.3.0.tar.gz (17.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sgu_client-0.3.0-py3-none-any.whl (24.3 kB view details)

Uploaded Python 3

File details

Details for the file sgu_client-0.3.0.tar.gz.

File metadata

  • Download URL: sgu_client-0.3.0.tar.gz
  • Upload date:
  • Size: 17.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for sgu_client-0.3.0.tar.gz
Algorithm Hash digest
SHA256 b7aa17f0fcce9291e98485fd6dd3e7f3106a19f359c8a3b1a6e8d50cfcd70a4d
MD5 2638dcbd70f9010fd854f125c8aa687a
BLAKE2b-256 87ba5a92a63b5dadbfb740c1faeef7fdcb8bc667fb2867ce5894a377330236ab

See more details on using hashes here.

Provenance

The following attestation bundles were made for sgu_client-0.3.0.tar.gz:

Publisher: ci-cd.yml on officialankan/sgu-client

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sgu_client-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: sgu_client-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 24.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for sgu_client-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a242f9937df6857e872ecebdb70ec2241c2f53427884fb48e68b6e3617c9bcdf
MD5 6d29886a13c1e7dae867df981dd71985
BLAKE2b-256 34e5baf328d06d7ab4bcb0b1c4995bff40a1d2ed25528ed7d1b1477933655b30

See more details on using hashes here.

Provenance

The following attestation bundles were made for sgu_client-0.3.0-py3-none-any.whl:

Publisher: ci-cd.yml on officialankan/sgu-client

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page