Top 6 Python graph-analysis Projects

NetworkX

61 14,153 9.6 Python

Network Analysis in Python

Project mention: Routes to LANL from 186 sites on the Internet | news.ycombinator.com | 2024-03-04

Built from this data... https://github.com/networkx/networkx/blob/main/examples/grap...
pykale

2 427 9.4 Python

Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem. ⭐ Star to support our work!
InfluxDB

www.influxdata.com
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Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
pygraphblas

7 338 0.0 Python

GraphBLAS for Python

Project mention: Large Photonic Processor Solves Graph Problems | news.ycombinator.com | 2023-05-10

This is interesting to me because it's advancing the work on the notion of quantum graph problem solving.
I'm sure we've all heard how quantum computers can be used in the future to decrypt information from today. There's a lot of research out there on how QC may be able to efficiently factor large semiprimes and bust our existing cryptographic algorithms, but to me this is the more mundane side of QC.
The exciting side to me is that many graph problems, particularly whole graph problems like connectivity and shortest paths have a potential quantum advantage. This is particularly advantageous for sparse and hypersparse graphs that have billions of nodes but relatively low node degree. Language Models, chemical assay databases, proteomics, causal inference, and fraud detection are just a few problems that involve huge sparse graphs that could get a huge boost from quantum.
And to show my own bias here [1], I think the future of graph algorithms, including quantum, is expressing them in Linear Algebraic form with the GraphBLAS API. Using the GraphBLAS, you can write your algorithm in a mathematical form using the multiplication of adjacency matrices that is then synthesized to some optimal form for a given architecture.
The same code you write can then be run on a variety of backends, currently CPUs and CUDA using SuiteSparse's new JIT, but soon FPGAs and yes, quantum computers. Parallelism will become so broad and conceptually divergent that you won't even be able to conceive of an efficient hand written single function for all possible platforms.
[1] https://github.com/Graphegon/pygraphblas
graphblas-algorithms

3 60 6.2 Python

Graph algorithms written in GraphBLAS
lightning-tools

15 22 0.0 Python

Tools for Lightning Network node operators
social-balance

2 3 0.0 Python

A library-agnostic project for calculating exactly and efficiently social balance, based on the Aref, Mason and Wilson paper (https://arxiv.org/abs/1611.09030)

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2024-03-04.