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Asynchronous Python client for the open datasets of Antwerpen (Belgium).

About

A python package with which you can retrieve data from the Open Data Platform of Antwerpen 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 antwerpen

Datasets

You can read the following datasets with this package:


There are a number of parameters you can set to retrieve the data:

  • limit (default: 10) - How many results you want to retrieve.
Click here to get more details

Disabled parking spaces

Variable Type Description
entry_id integer The ID of this location
number integer The number of parking spots on this location
orientation string The orientation of this location
destiny string What is the purpose of the location
window_time string (none) The window time of this location
lined boolean Whether this location is lined
status string The status of this location
gis_id string The GIS ID of this location
created_at datetime The date this location was added to the dataset, not all locations have a value
coordinates list (float) The coordinates of this location

Example

import asyncio

from antwerpen import ODPAntwerpen


async def main() -> None:
    """Show example on using the Parking Antwerpen API client."""
    async with ODPAntwerpen() as client:
        disabled_parkings = await client.disabled_parkings(limit=10)
        print(disabled_parkings)


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

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.

Open in Dev Containers

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) 2022-2026 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.

Complete parking collections

await client.parking_collection(set_filter=None, max_records=10000) returns ParkingCollection(records, total_count, pages_fetched, source_version=None, complete=True). Each ParkingRecord preserves its original GISID as gis_id, full WGS84 geometry (including all rings), and unmodified source_attributes. The existing capped disabled_parkings() inspection API remains compatible.

The client reads the source count, ordered 500-record pages twice, and the final count. Short pages, duplicate/missing GIS IDs or OBJECTIDs, observed source edits, ArcGIS errors and safety-ceiling overflow raise ODPAntwerpenError; no partial collection is returned. Empty selections can be proven complete. Two identical reads are change detection, not a transactional snapshot. GISID continuity is not guaranteed by the publisher; OBJECTID only orders retrieval.

The public layer contains one record without GISID as checked on 2026-10-13. The default full collection rejects it. Consumers explicitly choosing an identified subset can pass set_filter="GISID IS NOT NULL AND GISID <> ''"; this changes coverage and must be disclosed. The identified subset contained 1,847 records (eight page reads); the full layer contained 1,848.

Layer metadata describes polygons from the paid-parking-area inventory (2018), not verified citywide coverage or present availability. All inspected records say toegang=Beperkt, and 25 contain time-window claims despite the layer description saying no time-window regime. Preserve those claims rather than inferring unrestricted or personal access. EBDD and portal modification times are not verified record-update timestamps. Data rights differ from this client's MIT licence: see the city's open-data terms and publisher item.

Metadata

Release files for antwerpen 2.0.0

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