grand
chinese-whispers
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| grand | chinese-whispers | |
|---|---|---|
| 2 | 1 | |
| 75 | 57 | |
| - | - | |
| 2.8 | 8.1 | |
| 11 days ago | 3 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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grand
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Show HN: In-memory graph "database" with NetworkX and openCypher
Cypher is a super useful language for querying graph structures, but sometimes it's overkill to load a tiny graph into Neo4j or memgraph. We wrote this tool to act as an abstraction layer so you can query in-memory graph data -- or, using [Grand](https://github.com/aplbrain/grand), rewrite Cypher queries to run on SQLite dbs or even other graph databases that don't support Cypher out of the box. Hoping it'll be helpful to those in the network theory, graph ML, and data science communities!
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A minimalistic Python wrapper to AWS DynamoDB
Hey cool! I'm super curious to hear more about this. I _also_ wrote a pseudo-graph-database on DynamoDB (https://github.com/aplbrain/grand) :) It pretends it's a networkx.Graph, generally, but we also have a Cypher implementation on top of it.
Would love to chat more about this sometime if you were interested!
chinese-whispers
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Clustering Algorithms with Python
As this tutorial introduces the spectral clustering method that uses a similarity matrix between objects, I believe graph clustering methods are also worth mentioning. When I was investigating this topic, I released an implementation of a very efficient randomized clustering algorithm for graphs called Chinese Whispers: https://github.com/nlpub/chinese-whispers-python. Since it does not use matrices internally, it allows handling very large NetworkX graphs.
What are some alternatives?
netgraph - Publication-quality network visualisations in python
agentpy - AgentPy is an open-source framework for the development and analysis of agent-based models in Python.
networkx-guide - We here are very big fans of NetworkX as a graph library and its comprehensive set of graph algorithms. For many though, working with NetworkX involves a steep learning curve. This guide is designed as an aid for beginners and experienced users to find specific tips and explore the world of complex networks.
python-threshold-clustering - NetworkX Community detection for weighted and directed graphs
grand-cypher - Implementation of the Cypher language for searching NetworkX graphs
pygraphistry - PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer
YassQueenDB - Graph database library that allows you to store, analyze, and search through your data in a graph format. By using the Universal Sentence Encoder, it provides an efficient and semantic approach to handle text data. 📚🧠🚀
forceatlas2 - Fastest Gephi's ForceAtlas2 graph layout algorithm implemented for Python and NetworkX
PynamoDB - A pythonic interface to Amazon's DynamoDB
karateclub - Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
dotmotif - A performant, powerful query framework to search for network motifs
osmnx - OSMnx is a Python package to easily download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap.