eindhoven 6.0.0

Asynchronous Python client for the open datasets of Eindhoven (The Netherlands).

About

A python package with which you can retrieve data from the Open Data Platform of Eindhoven via their API. This package was initially created to only retrieve parking data from the API, but the code base is made in such a way that it is easy to extend for other datasets from the same platform.

Installation

pip install eindhoven

Datasets

You can read the following datasets with this package:

• Parking spots / Parkeerplaatsen

Example

import asyncio

from eindhoven import ODPEindhoven, ParkingType


async def main() -> None:
    """Show example on using the Open Data Platform API of Eindhoven."""
    async with ODPEindhoven() as client:
        locations = await client.locations(
            limit=100,
            parking_type=ParkingType.PARKING,
        )
        print(locations)


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

Complete collection contract

Use await client.parking_collection(parking_type=ParkingType.DISABLED_PARKING, max_records=9900) for a complete selection. locations(limit=..., parking_type=...) is a limited convenience API using the same endpoint and record parser. It only fetches the requested prefix and does not assert a full, version-checked collection.

All parking collection clients share this envelope:

Eindhoven returns ParkingSpot with spot_id (original positive integer objectid rendered as a decimal string), source_attributes (all original ODSv2 fields, including null values), data (typed original parking fields), and geometry (typed WGS84 Point). The exact original geometry, including additional source fields, remains in source_attributes["geo_shape"]["geometry"]. Consumer-specific mapping, access decisions, and publication remain outside this package.

The client requests pages of 100 ordered by objectid, validates totals, page lengths and unique IDs, and compares the portal's data_processed token before and after collection. Empty selections return a complete empty collection. The default safety bound is 9900 records and may be lowered; exceeding it raises ODPEindhovenResultsError. The revision comparison is an observation of portal metadata, not a transaction guarantee by the provider.

Migration to ODSv2.1

This release changes the source endpoint and ParkingSpot shape. All requests now use /api/explore/v2.1/catalog/datasets/parkeerplaatsen; the ODSv1 path and response models are removed.

• Replace hashed ODSv1 recordid identities with the original objectid exposed as spot_id. Do not treat these different IDs as equivalent.
• spot.data.parking_type, .street and .number remain available through typed ParkingData. Street and number can be None; a fractional source number is retained as a float without rounding. All raw fields are additionally preserved in spot.source_attributes.
• spot.geometry.latitude, .longitude and .coordinates remain available through typed Geometry; its type is Point. Exact additional geometry fields remain in the raw source_attributes.
• updated_at, BaseResponse and ParkingResponse are removed. ODSv2 does not provide the old per-record portal timestamp; source_version is an observed dataset revision token and must not be substituted for a record modification date.
• locations() retains its limited-list behavior and no-results exception. For a confirmed empty or complete selection, use parking_collection().

Use cases

NIPKaart.nl

A website that provides insight into where disabled parking spaces are, based on data from users and municipalities. Operates mainly in the Netherlands, but also has plans to process data from abroad.

Contributing

This is an active open-source project. We are always open to people who want to use the code or contribute to it.

We've set up a separate document for our contribution guidelines.

Thank you for being involved! 😍

Setting up development environment

The simplest way to begin is by utilizing the Dev Container feature of Visual Studio Code or by opening a CodeSpace directly on GitHub. By clicking the button below you immediately start a Dev Container in Visual Studio Code.

This Python project relies on uv as its dependency manager, providing comprehensive management and control over project dependencies.

You need at least:

• Python 3.12+
• uv

Installation

Install all packages, including all development requirements:

uv sync --locked

uv creates a project virtual environment in .venv and installs the locked dependencies.

Prek

This repository uses the prek framework, all changes are linted and tested with each commit. To setup the prek check, run:

uv run prek install

And to run all checks and tests manually, use the following command:

uv run prek run --all-files

Testing

It uses pytest as the test framework. To run the tests:

uv run pytest

To update the syrupy snapshot tests:

uv run pytest --snapshot-update

License

MIT License

Copyright (c) 2021-2026 Klaas Schoute

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.