python-igraph
graphblas-algorithms
| python-igraph | graphblas-algorithms | |
|---|---|---|
| 1 | 3 | |
| 1,419 | 81 | |
| 0.7% | - | |
| 9.0 | 0.0 | |
| 9 days ago | 3 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
python-igraph
- Apple M1arm Vs X86 Amd Lets Put Things Into
I'll check myself in January. I'll get a Macbook Air, and compare it with the 4700U that I also have. I'll compile a graph processing library like python-igraph, feed it a shit ton of data, and launch several processes, to test.
graphblas-algorithms
- What can I contribute to SciPy (or other) with my pure math skill? I’m pen and paper mathematician
And algorithms for the NetworkX backend graphblas-algorithms is here: https://github.com/python-graphblas/graphblas-algorithms
- NetworkX 3.0
GraphBLAS is wrapped by https://github.com/python-graphblas/python-graphblas/ and the algorithms are available at https://github.com/python-graphblas/graphblas-algorithms. NetworkX only dispatches the computation for a subset of algorithms to graphblas-algorithms right now.
If you want the graphblas API in python, https://github.com/python-graphblas/python-graphblas/ is the right place :)
- GraphBLAS
GraphBLAS is underrated and underused IMHO. If you use e.g. scipy.sparse, NetworkX, or similar, you should check out GraphBLAS. It is really fast even compared to scipy.sparse, and more capable in many ways.
They've actually started implementing the NetworkX API
https://github.com/python-graphblas/graphblas-algorithms
with python-graphblas
https://github.com/python-graphblas/python-graphblas
What are some alternatives?
networkit - NetworKit is a growing open-source toolkit for large-scale network analysis.
cugraph - cuGraph - RAPIDS Graph Analytics Library
curvipy - Make math animations in a few lines of code.
devops-schedule - how do you order a tree of work correctly where there are dependencies between works [GET https://api.github.com/repos/samsquire/devops-schedule: 404 - Not Found // See: https://docs.github.com/rest/repos/repos#get-a-repository]
BisPy - BisPy - Python bisimulation library
netSALT - Simulation of lasing networks with quantum graphs and SALT theory.