Package: capellambse
A Python 3 headless implementation of the Capella modeling toolIntrocapellambseallows you reading and writing Capella models from Python
without Java or theCapella toolon any (reasonable) platform. We wanted to
“talk” to Capella models from Python, but without any Java on the way. We
thought this project will help individuals and organisations getting through
the MBSE adoption journey with Capella faster and so we made it public and
open-source.Withcapellambseyou can access all (or almost all) Capella model elements,
and render diagrams as SVG and PNG. We made it for automation of Systems
Engineering work, so it integrates nicely into most CI/CD toolchains. We also
found it at the core of our artifact generation pipelines (model to documents,
model to SW interfaces).The library works withPVMTandRequirementsextensions without any
additional efforts.It started as a basic library somewhere mid 2019. Since then it was
re-architected a few times and now has a full read/write capability for most of
the present Capella ontology. We are continuously improving the API
(introducing shortcuts), increasing the meta-model coverage and have more
engineering automations and improvements in the pipeline to share.Related projectscapellambse-context-diagrams— A capellambse extension that visualizes
the context of Capella objects, and exposes it on element attributes like.context_diagram,.tree_view, etc.capella-diff-tools— A set of tools to compare Capella models.Did you make something cool that is using or extending capellambse?Tell us
about it, so we can add it to this list!Documentation and examplesThe library is designed to be easy to use and discover, especially in an
interactive environment such as JupyterLab. Additionally,API documentationis automatically generated and published whenever new features and bug fixes
are added.You are encouraged to explore our test models and demo notebooks. Click on the
button below to launch aJupyter notebook serveron the public myBinder
service, and get started in seconds:Warning:Do not enter confidential information, such as passwords for
non-public models, into a notebook hosted on myBinder. If you want to try outcapellambsewith those models, pleaseinstall and runit in a local,
trusted environment!Thedocs/source/examplesdirectory contains several hands-on example
notebooks that you can immediately run and start experimenting with. Below is a
short summary of each notebook’s goal. If you are in the JupyterLab
environment, you can click the notebook names to directly open them in a new
lab tab. On Github, you will be shown a statically rendered preview of the
notebook.01 Introduction.ipynbprovides a high-level overview of the library
features. It visualizes examples like a Component - Function allocation table
by leveraging Jupyter’s and IPython’s rich display functionality.02 Intro to Physical Architecture.ipynbexplores some more advanced
concepts on the example of the Physical Architecture Layer. It shows how to
derive tabular data, like a Bill of Materials or a Software to Hardware
allocation table, by usingpandasdataframes.03 Data Values.ipynbshows how the API can be used to explore classes,
class instances and other objects related to data modeling.04 Intro to Jinja templating.ipynbdemonstrates how to effectively
combinecapellambsewith the powerfulJinjatemplating engine. This
enables the creation of all sorts of model-derived documents and artifacts,
including interactive web pages, PDF documents and any other textual
representations of your models.05 Introduction to Libraries.ipynbshows how to use Capella Library
Projects within capellambse. In this example you’ll learn how the API can be
used to open a project that is based on a library and find objects in both
models.06 Introduction to Requirement access and management.ipynbshows how the
API can be used to work with requirements objects, introduced by the CapellaRequirements Viewpoint. In this example you’ll see how to find
requirements in the model, see which objects requirements are linked / traced
to and even export requirements to Excel or ReqIF formats.07 Code Generation.ipynbshows how to generate code from class diagrams.
In particular, we focus on Interface Descriptive Languages with concrete
examples forClasstoROS2 IDLand GoogleProtocol Buffers. We
also show how simple Python stubs could be generated given aClassobject.08 Property Values.ipynbshows how to access property values and property
value groups, as well as theProperty Value Management (PVMT)extension.09 Context Diagrams.ipynbshows thecapellambse-context-diagrams extensionthat visualizes
contexts of Capella objects. The extension is external to the capellambse library
and needs to be installed separately.10 Declarative Modeling.ipynbdemonstrates a basic application of the
declarative approach to modeling on a coffee machine example.11 Complexity Assessment.ipynbquickly demonstrates how to use and view the
model complexity badge for a Capella model.We are constantly working on improving everything shown here, as well as adding
even more useful functionality and helpful demos. If you have any new ideas
that were not mentioned yet,don’t hesitate to contribute!InstallationIn order to use private models that are not publicly available, please install
and usecapellambsein a local, trusted environment.You can install the latest released version directly from PyPI.pipinstallcapellambseTo set up a development environment, clone the project and install it into a
virtual environment.gitclonehttps://github.com/DSD-DBS/py-capellambsecdcapellambsepython-mvenv.venvsource.venv/bin/activate.sh# for Linux / Mac.venv\Scripts\activate# for Windowspipinstall-Upippre-commitpipinstall-e'.[docs,test]'pre-commitinstallWe recommend developing within a localJupyter notebook serverenvironment.
In order to install and run it in the same virtual environment, execute the
following additional commands:pipinstalljupytercapellambsecddocs/source/examplesjupyter-notebookIf your browser did not open automatically, follow the instructions in the
terminal to start it manually.Once in the browser, simply click on the01 Introduction.ipynbnotebook to
start!Current limitationsWe are continuously improving coverage of Capella onthology with ourhigh-level API(the current coverage map is availablehere), however it
is still incomplete. It covers most of the commonly used paths but when you
need to get to an ontology element that isnt covered yet you may do so by using
thelow-level API.Also, as we started in mid 2019 and there was no such thing asPython4Capellayet, we are not API compatible with that project. However,
we intend to add API compatibility with Python4Capella in later releases.The generated diagrams are currently not persisted in.airdfiles, and
currently there is no plan to implement this. If there is a genuine usecase for
that we may re-consider it - feel free to create an issue or add comments to an
existing one.ContributingWe’d love to see your bug reports and improvement suggestions! Please take a
look at ourguidelines for contributorsfor details.LicensesThis project is compliant with theREUSE Specification Version 3.0.Copyright DB InfraGO AG, licensed under Apache 2.0 (see full text inLICENSES/Apache-2.0.txt)Dot-files are licensed under CC0-1.0 (see full text inLICENSES/CC0-1.0.txt)To provide the same look and feel across platforms, we distribute our library
bundled with the OpenSans font (capellambse/OpenSans-Regular.ttf). The
OpenSans font is Copyright 2020The Open Sans Project Authors, licensed
under OFL-1.1 (see full text inLICENSES/OFL-1.1.txt).