Giter Club home page Giter Club logo

aas-core-codegen's Introduction

aas-core-codegen

Continuous integration

Test coverage

PyPI - version

PyPI - Python Version

Aas-core-codegen:

  • generates code for different programming environments and schemas
  • to handle asset administration shells
  • based on the meta-model in simplified Python.

Motivation

The meta-model is still at the stage where it changes frequently. However, we need SDKs in different languages (C#, C++, C, Java, Golang, Erlang etc.) as well as different schemas (JSON Schema, XSD, RDF etc.). Keeping up with the changes is hard, time-consuming and error-prone as each SDK and schema needs to be reviewed independently.

To make the whole development cycle of the meta-model, SDKs and schemas more maintainable, we wrote a code and schema generator. We write a meta-model in a subset of Python language, parse it and, based on this meta-model, generate the code for different languages and schemas.

Therefore we can easily scale to many languages and schemas.

Here is a diagram to illustrate the whole process:

image

Installation

Single-File Release

Please download and unzip the latest release from the GitHub release page.

From PyPI

The tool is also available on PyPI.

Create a virtual environment:

python -m venv venv-aas-core-codegen

Activate it (in Windows):

venv-venv-aas-core-codegen\Scripts\activate

or in Linux and OS X:

source venv-aas-core-codegen/bin/activate

Install the tool in the virtual environment:

pip3 install aas-core-codegen

Usage

Write your meta-model somewhere as well as the code snippets for implementation specific classes and functions. For example, take our test meta-model for inspiration how to write the meta-model and the snippets.

Make sure you are within the virtual environment where you installed the generator. Alternatively, if you are using the binary release, make sure the release is on your path.

Call the generator with the appropriate target:

aas-core-codegen \
    --model_path path/to/meta_model.py \
    --snippets_dir path/to/snippets \
    --output_dir path/to/output \
    --target csharp

--help

usage: aas-core-codegen [-h] --model_path MODEL_PATH --snippets_dir
                        SNIPPETS_DIR --output_dir OUTPUT_DIR --target
                        {csharp,cpp,golang,jsonschema,python,typescript,rdf_shacl,xsd,jsonld_context}
                        [--version]

Generate implementations and schemas based on an AAS meta-model.

optional arguments:
  -h, --help            show this help message and exit
  --model_path MODEL_PATH
                        path to the meta-model
  --snippets_dir SNIPPETS_DIR
                        path to the directory containing implementation-
                        specific code snippets
  --output_dir OUTPUT_DIR
                        path to the generated code
  --target {csharp,cpp,golang,jsonschema,python,typescript,rdf_shacl,xsd,jsonld_context}
                        target language or schema
  --version             show the current version and exit

Versioning

We are still not clear about how to version the generator. For the moment, we use a lax incremental versioning with 0.0 prefix (0.0.1, 0.0.2``) etc.

The changelog is available in CHANGELOG.rst.

Contributing

Feature requests or bug reports are always very, very welcome!

Please see quickly if the issue does not already exist in the issue section and, if not, create a new issue.

Contributions in code are also welcome! Please see CONTRIBUTING.rst for developing guidelines.

aas-core-codegen's People

Contributors

empwilli avatar mristin avatar murloc6 avatar s-heppner avatar zrgt avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.