Package: brussel
Asynchronous Python client for the open datasets of Brussel (Belgium).AboutA python package with which you can retrieve data from the Open Data Platform of Brussel viatheir 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.InstallationpipinstallbrusselDatasetsYou can read the following datasets with this package:Parking spaces for disabled / Parkings pour personnes handicapées(877 locations)Public parkings / Parkings publics(24 locations)Click here to get more detailsDisabled parkingsParameters:limit(default: 10) - How many results you want to retrieve.VariableTypeDescriptionspot_idintThe ID of the parking spotnumberintHow many parking spots there are on this locationaddressstrThe address of the parking spotlongitudefloatThe longitude of the parking spotlatitudefloatThe latitude of the parking spotupdated_atdatetimeThe last time the data was updatedGaragesParameters:limit(default: 10) - How many results you want to retrieve.VariableTypeDescriptiongarage_idintThe ID of the garagenamestringThe name of the garagecapacityintThe capacity of the garageproviderstringThe organization that manages this garagelongitudefloatThe longitude of the garagelatitudefloatThe latitude of the garageupdated_atdatetimeThe last time the data was updatedExampleimportasynciofrombrusselimportODPBrusselasyncdefmain()->None:"""Show example on using the Open Data API client."""asyncwithODPBrussel()asclient:garages=awaitclient.garages(limit=10)disabled_parkings=awaitclient.disabled_parkings(limit=10)print(garages)print(disabled_parkings)if__name__=="__main__":asyncio.run(main())Use casesNIPKaart.nlA 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.ContributingThis 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 ourcontribution guidelines.Thank you for being involved! :heart_eyes:Setting up development environmentThe simplest way to begin is by utilizing theDev Containerfeature 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 onPoetryas its dependency manager,
providing comprehensive management and control over project dependencies.You need at least:Python 3.9+PoetryInstall all packages, including all development requirements:poetryinstallPoetry creates by default an virtual environment where it installs all
necessary pip packages, to enter or exit the venv run the following commands:poetryshellexitSetup the pre-commit check, you must run this inside the virtual environment:pre-commitinstallNow you're all set to get started!As this repository uses thepre-commitframework, all changes
are linted and tested with each commit. You can run all checks and tests
manually, using the following command:poetryrunpre-commitrun--all-filesTo run just the Python tests:poetryrunpytestLicenseMIT LicenseCopyright (c) 2022-2023 Klaas SchoutePermission 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,
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