kystdatahuset-python-lib 0.9.3

A python library for accessing and querying data from Kystdatahuset

Kystdatahuset Python Library

kystdatahuset-python-lib — Python SDK companion for the Kystdatahuset API

kystdatahuset-python-lib is the official Python client for accessing the Kystdatahuset API, a unified data and knowledge platform for coastal and maritime spatial analytics.

It provides a clean, Pythonic, and strongly typed interface for querying datasets, managing authentication, and performing efficient data access.

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✨ Features

🚀 Easy Installation

Install directly from PyPI:

pip install kystdatahuset-python-lib

Supports Python 3.9+ on Linux, macOS, and Windows.

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🔐 Simple Authentication

The client offers:

• API key authentication
• Support for headless servers and notebooks

Example:

from kystdatahuset.auth import login
import os

    login_response = login("username", "password")
    jwt = auth_res.data.JWT
    voyages = get_voyages_for_ships_by_mmsi(
        auth_jwt=jwt,
        mmsi_ids=[258090000, 259028000],
        start_date=datetime(2024,1,1),
        end_date=datetime(2024,5,1),
    )

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🌍 Efficient & “Social” Data Access

Instead of fetching massive multi-GB extracts, the library is designed for smart, cooperative usage patterns, where users share infrastructure responsibly:

✅ Time Window Batching

Fetch long time periods in small, safe slices, python/Pandas "periods"

✅ Geographic Slicing

Request only the needed spatial extent by WKT filters

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🧱 Library Structure

+---kystdatahuset
|   |   ais.py
|   |   api_client.py
|   |   auth.py
|   |   const.py
|   |   file_storage.py
|   |   logging.py
|   |   voyage.py
|   |   __init__.py
|   |
|   +---models
|   |   |   AuthData.py
|   |   |   FileListing.py
|   |   |   WebServiceResponse.py
|   |   |   __init__.py
|   |   |
|   |
|   +---types
|   |   |   PandasFrequency.py
|   |   |   UploadFileType.py
|   |   |   __init__.py
|   |   |
|   |
|   +---utils
|   |   |   _date_range.py
|   |   |   __init__.py

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📦 Development & Distribution

kystdatahuset-py uses standard packaging:

• pyproject.toml + PEP 621 metadata
• versioning via Semantic Versioning
• full type hints (mypy-friendly)
• GitHub Actions for automated testing & publishing

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🧠 Typical Use Cases

• Query live AIS vessel data efficiently
• Retrieve spatial datasets in bounded windows
• Build dashboards, decision-support tools, or AI/ML pipelines
• Avoid oversized extracts by using time/space batching helpers

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📄 License

Open source under the MIT License.