5 ms·
Igraph and cugraph, and graph tool are far superior for a wide variety of reasons
by Der_Einzige 3y ago
Igraph and cugraph, and graph tool are far superior for a wide variety of reasons
- rdedev 3y agoI've used igraph. While it's much faster, for me at least, modifying the graph once it's constructed is harder compared to network. Haven't worked with cugraph though. As always use the right tool for the job
- gkoller 3y agoI would be interested in one that is properly type annotated. None of the options here (NetworkX, igraph, cugraph) are.
- westurner 3y agohttps://news.ycombinator.com/item?id=36922924 https://news.ycombinator.com/item?id=36922924 : > pytype (Google) [1], PyAnnotate (Dropbox) [2], and MonkeyType (Instagram) [3] all do dynamic / runtime PEP-484 type annotation type inference [4] to generate type annotations. Hypothesis generates tests from type annotations; and icontract and pycontracts do runtime type checking.
- westurner 3y ago/? "networkx" "igraph" "cugraph" site:github.com inurl:awesome https://www.google.com/search?q=%22networkx%22+%22igraph%22+%22cugraph%22+site%3Agithub.com+inurl%3Aawesome https://www.google.com/search?q=%22networkx%22+%22igraph%22+... : - https://github.com/johnhany/awesome-list#graph https://github.com/johnhany/awesome-list#graph lists a few Tensorflow and Pytorch + graphs applications CuGraph docs > List of Supported and Planned Algorithms: https://docs.rapids.ai/api/cugraph/stable/graph_support/algorithms/ https://docs.rapids.ai/api/cugraph/stable/graph_support/algo... https://github.com/rapidsai/cugraph#news https://github.com/rapidsai/cugraph#news : > NEW! nx-cugraph, a NetworkX backend that provides GPU acceleration to NetworkX with zero code change. : pip install nx-cugraph-cu11 --extra-index-url https://pypi.nvidia.com export NETWORKX_AUTOMATIC_BACKENDS=cugraph