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SBcoyote 1.5.2

SBcoyote: An Extensible Python-Based Reaction Editor and Viewer.
Introduction
SBcoyote, initially called PyRKViewer or Coyote, is a cross-platform visualization tool for drawing reaction networks written with the
wxPython framework. It can draw reactants, products, reactions, and compartments, and its features include but are not limited to:

Support for floating and boundary species.
Reactions can be displayed using Bezier curves and straight lines.
Plugin support, with some plugin examples: arrow designer, random network, auto layout, etc.

Note that please make sure to save a copy of your SBML file before importing into SBcoyote.
Citing
If you are using any of the code, please cite the article (https://doi.org/10.1016/j.biosystems.2023.105001).
Installing SBcoyote

Install Python 3.8, 3.9 or 3.10 if not already in the system.
Go to the command line and type pip install SBcoyote.
If wxPython doesn't get installed automatically, please try to install wxPython 4.1.1 or 4.2.0 manually referring to https://wxpython.org/pages/downloads/index.html. Note wxPython 4.1.1 does not work with Python 3.10.
To run the application, simply type in the command line SBcoyote.

Documentation
The full documentation can be found at: https://sys-bio.github.io/SBcoyote/
Visualization Example
Here is a visualization example by SBcoyote for the large-scale Escherichia coli core
metabolism network (King et al., 2015; Orth et al., 2010).

Installation Options for Developers
Installing with Poetry

If you do not have poetry installed on your computer, follow the quick steps shown here.
Once you have poetry installed, you will download SBcoyote. Click the green button at the top of this page that says “Code” and choose “Download ZIP”, then unzip the folder to your desired directory. Make a note of the directory location as you will need it for the next step.
Open your terminal and navigate to the directory containing SBcoyote.
Once inside the main folder of the application you can install the dependencies. To install the base dependencies simply run poetry install. To install the optional ones as well, run poetry install -E simulation. Note that this step may take a while. To learn more about which set of dependencies is right for you, refer to the Dependencies section below.
Finally, you will run the application with the command poetry run SBcoyote.

After you have completed all of these steps, you will not have to repeat them every time you want to run the application. Once the setup is done you will only need to open the terminal, navigate into the folder that contains your SBcoyote application, and run the command poetry run SBcoyote.
Installing without Poetry
We strongly advise following the steps above as it makes the set-up process much faster and simpler. However, to install SBcoyote without Poetry, here is the process you will follow:

First, download SBcoyote. Click the green button at the top of this page that says “Code” and choose “Download ZIP”, then unzip the folder to your desired directory. Make a note of the directory location as you will need it for the next step.
Open your terminal and navigate to the directory containing SBcoyote.
To install the base set of dependencies, you will run pip install -r requirements.txt. Then if you want to install the optional dependencies as well, run pip install -r requirements-simulation.txt. To learn more about which set of dependencies is right for you, refer to the Dependencies section below.
Finally, you will run the application with the command python -m rkviewer.main.
After you have completed all of these steps, you will not have to repeat them every time you want to run the application. Once the setup is done you will only need to open the terminal, navigate into the folder that contains your SBcoyote application, and run the command python -m rkviewer.main.

Running

If you have poetry, simply run poetry run SBcoyote.
Otherwise, in your virtual environment, run python -m rkviewer.main.
Then, check out the documentation.

Development Setup
Dependencies
We are using poetry for dependency management. If you are just looking
to build and run, though, you can work solely with pip as well.
There are currently three dependency groups: "base", "development", and "simulation".

"base" is the bare minimum requirements to run the application without any plugins.
"development" includes the additional requirements for development, such as for documentation
and testing.
"simulation" includes a large set of dependencies required for running simulation related plugins. (This is in addition to the base requirements).

The dependency groups are specified in pyproject.toml for poetry. There are additionally
requirement.txt files generated by poetry, including requirements.txt, requirements-dev.txt,
and requirements-simulation.txt. If you do not have poetry, you can opt for those as well. If you are
using linux, extra work would need to be done on installing wxPython. Please refer to the
"Linux Notes" section below.
Installing Dependencies
poetry is recommended for installing dependencies. Simply poetry install for the base
dependencies and poetry install -E simulation to install the optional ones as well.
If you don't have poetry, you can simply run pip install -r <> for any of the aforementioned
requirements.txt files.
Running locally

If you have poetry, simply poetry run SBcoyote.
Otherwise, in your virtual environment, run python -m rkviewer.main.

Development Distributing

Use poetry build and poetry publish. Refer to poetry docs
for more detail.
To re-generate the requirements*.txt, run scripts/gen_requirements.py.

Bundling an Executable with PyInstaller
NOTE: This section is obsolete for now, as we are currently distributing with pip.

Always run pyinstaller rkviewer.spec when rkviewer.spec is present.
If somehow rkviewer.spec went missing or you want to regenerate the build specs, run pyinstaller -F --windowed --add-data ext/Iodine.dll;. main.py on Windows or pyinstaller -F -- windowed --add-data ext/Iodine.dll:. main.py on Linux/Mac to generate a file named main.spec. Note that if a main.spec file is already present it will be overwritten.

Development for Different Platforms
The python version for development was 3.7.7.
Mac Notes

Note that on MacOS, if you wish to use SBcoyote in a virtual environment, use venv instead of
virtualenv, due to the latter's issues with wxPython.
pyinstaller and wxPython require a python built with enable-framework on. Therefore, one should do env PYTHON_CONFIGURE_OPTS="--enable-framework" pyenv install 3.7.7 and
use that Python installation for building.
If the text is blurry in the app bundled by pyinstaller, one needs to add an entry in the pyinstaller settings as described here.

Linux Notes

To install wxPython on linux, see https://wxpython.org/blog/2017-08-17-builds-for-linux-with-pip/index.html. requirements-dev.txt and requirements.txt assume the user is on Ubuntu 18.04 for readthedocs. If you have a different distro and have trouble using requirements.txt, just install wxPython manually using the previous link.
Related to the last note, if readthedocs start having trouble building wxPython, understand that it might be because readthedocs updated its distro from Ubuntu 18.04. Go to requirements-dev.txt and change the line above wxPython to look in the appropriate link.
i.e. -f https://extras.wxpython.org/wxPython4/extras/linux/gtk3/ubuntu-18.04/ \n wxPython==4.1.1

Future Development
Testing and Profiling

To run all tests, go to project root and run python -m unittest discover.
To run a specific test suite, run e.g. python -m unittest test.api.test_node.
Or even more specific: python -m unittest test.api.test_node.TestNode.test_add_nodes.
To profile the application, run python -m cProfile -o rkviewer.stat main.py.
To visualize the profile result, run tuna rkviewer.stat.

Building Local Docs

Run sphinx-apidoc -f -o docs/source/rkviewer rkviewer rkviewer/plugin rkviewer/resources to regenerate the full reference doc source
code if new files were added to the package rkviewer.
Run sphinx-build -b html docs\source docs\build.

Note on Style
Usually snake_case is used for function names. However, to retain some degree of backwards
compatibility for wxPython, subclasses of wxPython classes use PascalCase for their methods, e.g. Canvas::RegisterAllChildren.
TODOs

ENHANCEMENT: Add support for multiple net IDs. Currently all net IDs are set to 0 by default.

Shapes TODOs

Events (NodeModified)

Roadmap for Shape Engine
A shape "engine" allows the user to specify custom composite shapes for nodes and compartments.
Composite shapes are constructed out of primitives such as circles, (rounded) rectangles, polygons,
etc.
RKViewer provides a default list of (composite) shapes, but the user may also create their own
shapes out of primitives. A (composite) shape is formed out of one or many primitives, each
scaled, rotated, and translated by certain amounts. User-created shapes will be
associated with each model in the exported .json files.
A shape-creation plugin may be created in the future to facilitate the process of designing
complex shapes.
Here is the roadmap for the shape engine:

Create preliminary list of primitives and a default list of shapes. Allow model loader/saver to
reference that list.
Modify renderer to be able to render these default shapes.
Modify inspector to allow the user to change the properties of the primitives in the shape, such
as colors, border thickness, etc.
Modify model loader/saver to allow users to create custom shape lists manually.
Write shape-creation plugin?