A library for network visualization and algorithm simulation.
Project description
AlgorithmX Python
AlgorithmX Python is a library for network visualization and algorithm simulation, built on AlgorithmX. It can be used through a HTTP/WebSocket
server, or as a widget in Jupyter Notebooks and JupyterLab.
Resources
Installation
Python 3.7.0 or higher is required. Using pip:
python -m pip install algorithmx
Jupyter Widget
In classic Jupyter notebooks, the widget will typically be enabled by default. To enable it manually, run
jupyter nbextension enable --sys-prefix --py algorithmx
with the appropriate flag. To enable in JupyterLab, run
python -m jupyter labextension install @jupyter-widgets/jupyterlab-manager --no-build
python -m jupyter lab build
Example Usage
If you wish to use the library through a HTTP/WebSocket server, follow the template below:
import algorithmx
server = algorithmx.http_server(port=5050)
canvas = server.canvas()
def start():
canvas.nodes([1, 2]).add()
canvas.edge((1, 2)).add()
canvas.onmessage('start', start)
server.start()
The graphics can be found at http://localhost:5050/
.
If you are using Jupyter, try adding the following code to a cell:
from algorithmx import jupyter_canvas
canvas = jupyter_canvas()
canvas.nodes([1, 2]).add()
canvas.edge((1, 2)).add()
canvas
Development
Manual install
Make sure you have Python 3.7 of higher, then run
# build js
cd js
npm run build
cd ..
# install dependencies
python -m pip install -r dev-requirements.txt
python -m pip install --no-deps --editable ".[jupyter,networkx]"
HTTP Server
Docker: Docker-compose up http-server
Manually: python examples/basic_http_server.py
Then open localhost:5050
in a browser.
Jupyter notebook
Docker: docker-compose up notebook
Manually:
python -m jupyter nbextenion list
python -m jupyter notebook
Then try opening examples/basic_notebook.ipynb
.
Jupyter lab
Docker: docker-compose up jupyter-lab
Manually:
python -m jupyter labextension install @jupyter-widgets/jupyterlab-manager --no-build
python -m jupyter lab build
python -m jupyter labextension list
python -m jupyter lab
Then try opening examples/basic_notebook.ipynb
.
Build and test package
Clean any previous builds with rm -rf build dist
.
Docker: docker-compose up --build build
Manually:
python -m mypy .
python -m pytest tests -vv
python setup.py build sdist bdist_wheel
The bundle can be found in dist/
.
Distribute
- Set up pre-commit hooks:
pre-commit install
- Publish to PyPI:
./scripts/deploy.sh
Project details
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Source Distribution
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