Modelica builder enables programmatic parsing and modification of Modelica files.
Project description
Modelica Builder
The Modelica Builder project aims to make in-place modifications to Modelica language files easier. The principal use case is to load, modify using higher level abstracted methods, and then save the resulting file. The user has access to the entire Abstract Syntax Tree of the entire Modelica grammar.
The Modelica Builder project does not:
- Compile nor check for syntax validity
Install
pip install modelica-builder
Usage
ModBuild provides specific methods for reading and modifying files.
from modelica_builder.model import Model
# parse the model file
source_file = 'DCMotor.mo'
model = Model(source_file)
# do read and modify the model
# refer to modelica_builder.model.Model class methods to see what's available
name = model.get_name()
model.set_name('New' + name)
model.add_connect('some.component.port_a', 'another.component.port_b')
model.insert_component('MyComponentType', 'myInst',
modifications={'arg1': '1234'}, string_comment='my comment',
annotations=['my annotation'], insert_index=0)
# save the result
model.save_as('NewDCMotor.mo')
You can also define your own classes for editing the file
from modelica_builder.edit import Edit
from modelica_builder.selector import Selector
from modelica_builder.transformation import SimpleTransformation
class MySelector(Selector):
# implement class for selecting AST nodes
# define the edit to make to the node's text and combine it with the selector
edit = Edit.make_replace('FOOBAR')
selector = MySelector()
transformation = SimpleTransformation(selector, edit)
model = Model('my_modelica_file.mo')
# add your custom transformation
model.add(transformation)
model.save_as('result.mo')
Transformations specify what nodes to change and how to change them. This is done by combining Selectors and Edits. Selectors specify how to select nodes in the AST, and edits are modifications (insert, replace, delete) to the text of selected nodes.
A Transformer is a collection of Transformations, which can then be applied to a file.
See the tests for more examples and information.
Development
For developers, dependency management is through Poetry. Installation is accomplished by running pip install poetry
.
pip install poetry
# install after cloning repo
poetry install
If you change the source grammar file you need to regenerate the parser and lexer.
With docker installed, run these commands from this the repo's root directory
# build Antlr container
docker build -t antlr4:latest -f antlr/Dockerfile .
# run parser generator for python
docker run -v "$(pwd)/modelica_builder/modelica_parser":/var/antlrResult \
antlr4:latest \
-Dlanguage=Python3 /var/antlrResult/modelica.g4
# commit results along with grammar file
If not using Docker, install antlr4 following these instructions.
# in modelica_building/modelica_parser
antlr4 -Dlanguage=Python3 modelica.g4
# commit results along with grammar file
Managed Tasks
Updating Licenses
To apply the copyright/license to all the files, run the following managed task. To update, then update the script, and then rerun the managed task.
./setup.py update_licenses
Testing
To run the tests, simply run the following:
poetry run pytest
Known Issues
- The transformations occur on strings which are immutable. Need to investigate using byte arrays. This does not cause errors, but can be slow when parsing really large modelica files.
Release Instructions
- Bump version to <NEW_VERSION> in pyproject.toml (use semantic versioning, e.g., 0.5.0, 0.5.1.rc1).
- Run
poetry run pre-commit run --all-files
- In a prep-release branch, push the changes to GitHub and draft a release against the latest branch.
- Run 'auto-generate changelog' and copy the contents to the CHANGELOG.md. Cull any items that are repeated.
- Discard the draft release (you will create an official one off of the main branch later)
- Merge the prep-release branch into develop.
- From command line, merge develop into main with:
git checkout main; git pull; git merge --ff-only origin develop; git push
- In GitHub, tag the release against main. Copy and paste the changelog entry into the notes. Verify the release is posted to PyPI.
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