# Highly connected subgraphs

**URL:** <https://igraph.discourse.group/t/highly-connected-subgraphs/1647>\
**Category:** Usage\
**Tags:** R\
**Created:** [31 August 2023 14:40 UTC](https://igraph.discourse.group/t/highly-connected-subgraphs/1647 "2023-08-31T14:40:32Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![apredeus](https://yyz2.discourse-cdn.com/free1/user_avatar/igraph.discourse.group/apredeus/32/981_2.png) [@apredeus](https://igraph.discourse.group/u/apredeus)\
**Post date:** [31 August 2023 14:40 UTC](https://igraph.discourse.group/t/highly-connected-subgraphs/1647/1 "2023-08-31T14:40:32Z")

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Hi all,

I was wondering if there is an implementation of the “Highly connected subgraphs” community detection algorithm in igraph, and if there is not, what would be the easiest way to get it from some other package and then add to the igraph object? I’m using R version of igraph.

Thank you in advance.

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<div class="post-metadata">

**Author:** ![GroteGnoom](https://yyz2.discourse-cdn.com/free1/user_avatar/igraph.discourse.group/grotegnoom/32/428_2.png) [@GroteGnoom](https://igraph.discourse.group/u/GroteGnoom)\
**Post date:** [2 September 2023 13:50 UTC](https://igraph.discourse.group/t/highly-connected-subgraphs/1647/2 "2023-09-02T13:50:30Z")

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I don’t think igraph has an implementation.

It doesn’t look to hard in python: [https://github.com/53RT/Highly-Connected-Subgraphs-Clustering-HCS/blob/master/hcs.py](https://github.com/53RT/Highly-Connected-Subgraphs-Clustering-HCS/blob/master/hcs.py)  
So maybe writing it in R is also not that much work.

If it’s too slow then someone needs to write something a little optimized in C, which will be a bit harder.