NetworkX Alternatives
Similar projects and alternatives to NetworkX



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snap
Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library. (by snapstanford)




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biobjectiveastar
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Reviews and mentions

Are there libraries for python that implement (mathematical) graphs?
Take a look at NetworkX.

PostWeek 5 Circle of Suck
This analysis is done using Python's NetworkX package and the simple_cycles function. All data comes from Massey Ratings. I've limited using game data to FBS and FCS. I'll try to keep this analysis going through the weeks, but each week looking for the longest cycle will get harder as more games are played and there are more potential cycles.

A Sankey diagram visualizing the flow of materials in wagons/min through my planned 1kSPM base
I used the excellent Factory Planner Mod to map out the material needs. From there I took the required items/min for each subfactory and created a weighted directed graph with NetworkX in Python. The nodes are the different subfactories (stations) using the Data.raw names. The edges go from source to target station, weighted by the input value. Didn't figure out a better way to represent oil processing (multiple outputs), so I just created nodes for light, heavy and petroleum and set the weight to 1. Got the stack sizes from this Gist. Finally I used plotly to visualize the graph.

How can i make a basic path finding with PHP?
Storing the graph in memory is pretty simple and I'd be surprised if PHP didn't have some kind of library for graph storage. For reference, there is a really good Python library for graphs called NetworkX that I used extensively a few years ago in a project. I would recommend playing around with it, since it has a great API and a lot of useful features and it might help you get a better feel for the problem.

Modified shortest path
See for example packages like [https://igraph.org/python/) or networkx.

Mentor Monday, June 28, 2021: Ask all your bitcoin questions!
What you can do with the data is a bit limited to be honest. The transaction hashes have no natural order, so not very good to visualise directly. The most interesting data is the input>output tree where you take a transaction and trace all the inputs into that transaction, build up a map of the network and try to identify clusters. https://networkx.org/ is a good library for this. If you use mongodb (or some database which stores jsonlike data) it's quite easy to get up and running with python, jupyter notebooks etc.

Pure mathematics and learning python
A fun project might be write code that uses NetworkX to visualize arbitrary Cayley diagrams for simple groups. Again a bit elementary—but there may be more interesting research directions to go there that I lack the knowledge to think of.
 Algorithms and graph search

Are we Complex Network Analysis yet?
I'm a researcher approaching Rust these days. It seems that the Rust ecosystem does not offer a robust complex network analysis library, or at least I cannot find anything related to it. I worked a lot with SNAP (C++) and networkx (Python) but I can't find something similar in Rust. Am I wrong?

Visualizing your LinkedIn Connections using Python
Creating the network  creating a network graph using NetworkX

Is there another way to find all the cliques in a graph (dictionary)?
https://github.com/networkx/networkx/blob/main/networkx/algorithms/clique.py#L105

Looking for guidance on how to frame a problem.
There exist a few libraries to work with graphs, most notably I think is NetworkX. Aside from this there are also several algorithms which are usually mentioned in this context eg. Dijkstra.

ntree data structure?
It sounds like you have a more general directed graph rather than a tree. In that case you could have a look at networkx.

Graph module reccomendations?
Networkx: Easily the easiest library to use. It's written in Python and by far and away the most Pythonic. It's extremely well documented and there's a robust community that uses it. Unfortunately, because it's written in Python (with bells and whistles from Numpy and Scipy) it inherits a lot of Python's limitations: namely that it is slow as all getout. Python is particularly bad when nested loops are involved, which is terrible in graph analysis, since many measures need to be bruteforced by iterating over all nodes, edges, paths, etc. Doesn't work well for large networks (large here being 500+ nodes)

[Topic][Open] Open Discussion Monday — Anybody can post a general visualization question or start a fresh discussion!
If you are comfortable working with or learning basic python  the NetworkX library sounds like it will fit well with what you would like to do. https://networkx.org/
Stats
networkx/networkx is an open source project licensed under BSD 3clause "New" or "Revised" License which is an OSI approved license.
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