3 ms·
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. At some point it might re
by xrayarx 4y ago
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
At some point it might really start to be more efficient to have tags for the posts
- anigbrowl 4y agoI've updated it based on your suggestion. I originally left off a description because NetworkX is the library for doing graph things in Python and I kind of assumed people would know. While it's not the most performant or cutting edge, it's so well-established that everyone else aims for interface compatibility with it, much like pandas and tabular data. It's pretty neat that they've decided to leverage this by opening up the backend, allowing more performant/application specific offerings like SNAP or CUgraph to do the heavy lifting.
- LoganDark 4y ago> I kind of assumed people would know Not everyone writes Python, and not all Python programmers have heard of this particular library.
- decremental 4y agoNot all people are programmers and not all people have heard of programming. This post is catered to an audience that probably knows what NetworkX is.
- LoganDark 4y agoThis is not the same thing. Hacker News as a website is catered to an audience that is mostly familiar with programming. I would say it's safe to assume for any given visitor that they are probably aware of basic computing and programming terminology, but not that they would know what "NetworkX" means. The new title is fitting (it specifies what it's a Python library now).
- Sosh101 4y agoI've never heard of it.
- jimnotgym 4y agoI have written Python for 10 years on and off and have never come across it, or if I did I had forgotten about it.
- Der_Einzige 4y ago"the library"? Igraph and graph tool might have something to retort to that. Up until this update, they were far far faster too (and still likely are if you ignore the ability in this update to specify different backends)
- lmeyerov 4y agoYep we use cuGraph a ton, and stick to the CPU stuff for < 100k graphs, esp for their more niche algs. Exciting days!
- anigbrowl 4y agoYes. I noted that it's not the most performant, indeed it's famous for being slow. But it's so popular, has such extensive code coverage, and such a simple API that it's gained default status, not unlike how Python is the default language for data science despite its limitations.
- NibLer 4y ago[dead]
- nerdponx 4y agoI always used IGraph because there are both R and Python versions, and I learned R first. I never had any complaints about it for the baby-scale problems I used it for, so I never bothered to try NetworkX.
- xarope 4y agoIt was my go-to package in python, when I had to build graphs and ascertain acyclicity, single source, shortest path. They weren't huge graphs (at most 100s of elements), so networkx certainly did the work fast enough.