esmf-aspect-model-loader 2.2.1

Load Aspect Models based on the Semantic Aspect Meta Model

The Aspect Model Loader as part of the Python SDK provided by the Eclipse Semantic Modeling Framework.

An Aspect of the Meta Model

The esmf-aspect-model-loader package provides the Python implementation for the SAMM Aspect Meta Model, or SAMM. Each Meta Model element and each Characteristic class is represented by an interface with a corresponding implementation.

Documentation

• Check the developer documentation
• Check the SAMM specification
• Having issues with the ESMF SDK Python Aspect Model Loader? Open a GitHub issue.

Set Up SAMM Aspect Meta Model

Before getting started to use the esmf-aspect-model-loader library you need to apply some set up actions:

Required

• Install poetry
• Install project dependencies
• Download SAMM files

Install poetry

Poetry used as a dependency management for the esmf-aspect-model-loader. Follow the next instruction to install it.

To check the poetry version run:

poetry --version

Install project dependencies

Poetry provides convenient functionality for working with dependencies in the project. To automatically download and install all the necessary libraries, just run one command:

poetry install

It is required to run poetry install once in the esmf-aspect-model-loader module.

Download SAMM files

There are two possibilities to download the SAMM files and extract the Turtle sources for the Meta Model: SAMM release or SAMM branch

Download SAMM release

This script downloads a release JAR-file from GitHub, extracts them for further usage in the Aspect Model Loader:

To run script, execute the next command.

poetry run download-samm-release

The version of the SAMM release is specified in the python script.

Link to all Releases: SAMM Releases

Download SAMM branch

The script uses the GitHub API and downloads the files from the main GitHub branch.

If the script is run in a pipeline, it uses a GitHub token to authorize. If the script is run locally, the API is called without a token. This may cause problems because unauthorized API calls are limited.

Run the next command to download and start working with the Aspect Model Loader.

poetry run download-samm-branch

Link to all branches: SAMM Releases

SAMM Aspect Model Graph usage

SAMM Aspect Model Graph is a class that allows you to load and interact with the Semantic Data Aspect Meta Model graph. Below is an example of how to use SAMM Aspect Model Graph in your Python code:

from esmf_aspect_meta_model_python import SAMMGraph

# Define the path to your Turtle file
model_path = "absolute/path/to/turtle.ttl"

# Create an instance of SAMMGraph
samm_graph = SAMMGraph()

# Parse the Turtle file to load the graph
samm_graph.parse(model_path)

# Load the aspect model from the graph
aspect = samm_graph.load_aspect_model()

The load_model_elements method in the SAMMGraph class creates Python objects to represent all nodes from the Aspect model graph. It retrieves all SAMM elements from the RDF graph and converts them into structured Python objects.

from esmf_aspect_meta_model_python import SAMMGraph

# Define the path to your Turtle file
model_path = "absolute/path/to/turtle.ttl"

# Create an instance of SAMMGraph
samm_graph = SAMMGraph()

# Parse the Turtle file to load the graph
samm_graph.parse(model_path)

# Load all model elements from the graph
model_elements = samm_graph.load_model_elements()

Samm Units

SAMMUnitsGraph is a class contains functions for accessing units of measurement.

from esmf_aspect_meta_model_python.samm_meta_model import units

unit_name = "unit:volt"
units.print_info(units.get_info(unit_name))
# preferredName: volt
# commonCode: VLT
# ...
# symbol: V

# Get unit data as dictionary
volt_info = units.get_info("unit:volt")
# {'preferredName': rdflib.term.Literal('volt', lang='en'), 'commonCode': rdflib.term.Literal('VLT'), ... }

units.print_info(volt_info)
# preferredName: volt
# commonCode: VLT
# ...
# symbol: V

SAMM CLI wrapper class

The SAMM CLI is a command line tool provided number of functions for working with Aspect Models.

More detailed information about SAMM CLI functionality can be found in the SAMM CLI documentation.

Python Aspect Model Loader provide a wrapper class to be able to call SAMM CLI functions from the Python code. For instance, validation of a model can be done with the following code snippet:

from esmf_aspect_meta_model_python.samm_cli_functions import SammCli

samm_cli = SammCli()
model_path = "Paht_to_the_model/Model.ttl"
samm_cli.validate(model_path)
# Input model is valid

List of SAMMCLI functions:

• validate
• to_openapi
• to_schema
• to_json
• to_html
• to_png
• to_svg

Scripts

The Aspect Model Loader provide scripts for downloading some additional code and data. Provided scripts:

• download-samm-release
• download-samm-branch
• download-samm-cli
• download-test-models

All scripts run like a poetry command. The poetry is available from the folder where pyproject.toml is located.

Tests running

tox

tox is used for the tests automation purpose. There are two environments with different purposes and tests can be running with the tox:

• pep8: static code checks (PEP8 style) with MyPy and Black
• py310: unit and integration tests

# run all checks use the next command
poetry run tox

# run only pep8 checks
poetry run tox -e pep8

# run tests
poetry run tox -e py310