EdgeGraph is an object-oriented approach to network graphs. It provides classes to inherit from in other applications / modules, and provides out-of-the-box operations for these classes and any subclasses of.
The intent of EdgeGraph is to allow applications to model related data with a method closer to reality, without having to implement a custom graph module. It provides facilities to this end, such as the base classes to allow linking and the functions to perform it.
The base classes are also usable directly, should you wish to test-drive this idea or study abstract graphs.
See the docs for more!
At this time, this project is still rather young. Per semantic versioning, it is in version 0. This means that the API may be changed at any time, without warning.
Planned features include can be viewed at the features list milestone.
These features, as with the API, may be changed or dropped at any time without warning. I do have a day job, after all :)
Sphinx documentation and full Pytest-driven unit testing coverage is expected to match the progress of the code.
Edgegraph can be installed via pip with pip install edgegraph.
A few optional dependencies are available:
pip install edgegraph[foreign]for all the other libraries that edgegraph can interact withpip install edgegraph[full]to install all the above (at the time of writing, only the one. But, this "metapackage" exists for future-proofing)
You can start right out building graphs:
from edgegraph.builder import randgraph
from edgegraph.traversal import breadthfirst
uni = randgraph.randgraph(count=10)
print(breadthfirst.bft(uni, uni.vertices[0]))