Skip to content

The main use case of otlmow-model is to provide a class model, allowing instances of OTL compliant classes. The classes have data validation and automatic conversion for attributes and relations between objects.

License

Notifications You must be signed in to change notification settings

l14zj/OTLMOW-Model

 
 

Repository files navigation

OTLMOW-Model

PyPI otlmow-model-downloads Unittests PyPI - Python Version GitHub issues coverage

Summary

The main use case of otlmow-model is to provide a class model, allowing instances of OTL compliant classes. The classes have data validation and automatic conversion for attributes. Helper classes assist you to create relations between objects.

Code examples and usage

See the Readme notebook. This notebook contains examples on how to use the OTL classes and how to create relations between objects.

Project overview

This project aims to implement the Flemish data standard OTL (https://wegenenverkeer.data.vlaanderen.be/) in Python. It is split into different packages to reduce compatibility issues.

The otlmow-model project is a Python implementation model of the OTL standard. This is a collection of OTL compliant classes, which can be used to create instances of OTL objects. When assigning data to the attributes of the classes, the data is validated and converted to the correct type (if incorrect). There is support for conversion from and to Python dictionaries.

A few times during a year a new version of the OTL standard is released. The otlmow-modelbuilder project takes an OTL SQLite as input and generates the classes for the new version of the OTL standard. The otlmow-model project is then updated with the new classes. This way the otlmow-model project is always up to date with the latest version of the OTL standard.

In the otlmow-converter project, the instantiated classes can be converted to and from DAVIE compliant file formats (such as CSV, Excel, ...). There is also support for json-ld files. The objects can also be converted to dotnotation dictionaries or loaded into or from a pandas Dataframe. Because of all these possibilities, the converter has multiple dependencies on other Python packages.

The otlmow-template project produces a CSV or Excel template, based on a subset of the OTL. The created template can then be used to input data and upload into the DAVIE platform of AWV.

The otlmow-postenmapping project implements the mapping artifact and allow the creation or modification of OTL objects.

The otlmow-davie project has a REST client to the DAVIE platform to allow automation of deliveries.

The otlmow-visuals project provides a way to visualize OTL objects and their relations. The result is an interactive HTML file that can be opened in any browser.

The otlmow-gui project is a deployable local application that allows the user to create templates, edit, visualize and export data.

About

The main use case of otlmow-model is to provide a class model, allowing instances of OTL compliant classes. The classes have data validation and automatic conversion for attributes and relations between objects.

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 100.0%