OTLMOW-Model
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.
- otlmow_model (you are currently looking at this package)
- otlmow_modelbuilder
- otlmow_converter
- otlmow_template
- otlmow_postenmapping
- otlmow_davie
- otlmow_visuals
- otlmow_gui
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.
Installation
I recommend working with uv. Install this first:
pip install uv
Then install this package by using the uv pip install command:
uv pip install otlmow-model
If you are a developer, use this command to install the dependencies, including those needed to run the test suite.
uv pip install -r pyproject.toml --extra test
1 maintainer
Metadata
1 maintainer
Release files for otlmow-model 2.20.4.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| otlmow_model-2.20.4.2.tar.gz | 1.0 MB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| otlmow_model-2.20.4.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.6 MB
Release files / otlmow_model-2.20.4.2.tar.gz
| Download URL | otlmow_model-2.20.4.2.tar.gz |
|---|---|
| Size | 1.0 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
747b0549b19cac82dab067a3eee2bd0eedae5e1c49acc2ed151e2eac6a4b1914
|
|
BLAKE2b-256 checksum How to use checksums |
3224698fe9de0f2c09ffbd8ed22ec9a52ab364e4deee55cbd6837708e60a6aaa
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 13, 2026.
Transparency logRelease files / otlmow_model-2.20.4.2-py3-none-any.whl
| Download URL | otlmow_model-2.20.4.2-py3-none-any.whl |
|---|---|
| Size | 2.6 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
21735005cd3d8a4b52ea63c7ec92bb83032764a4ad5bf409a59083d46ea8df64
|
|
BLAKE2b-256 checksum How to use checksums |
287511416cad0e40a2340e3b22099a7c79b84308b1bf73cf7749501313ecf8a9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 13, 2026.
Transparency logSecurity for otlmow-model 2.20.4.2
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for otlmow_model-2.20.4.2.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 13, 2026.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
