GraphSCC VS text-metrics

Compare GraphSCC vs text-metrics and see what are their differences.

GraphSCC

Tarjan's algorithm for computing strongly connected components (by yav)
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GraphSCC text-metrics
- -
5 42
- -
0.0 5.6
almost 11 years ago about 1 month ago
Haskell Haskell
BSD 3-clause "New" or "Revised" License BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

GraphSCC

Posts with mentions or reviews of GraphSCC. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning GraphSCC yet.
Tracking mentions began in Dec 2020.

text-metrics

Posts with mentions or reviews of text-metrics. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning text-metrics yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing GraphSCC and text-metrics you can also consider the following projects:

graph-generators - A Haskell library for creating random Data.Graph instances using several pop

build - Build Systems à la Carte

spacefill - Space-filling curves

exact-cover

toysolver - My sandbox for experimenting with solver algorithms.

lca - Improves the known complexity of online lowest common ancestor search to O(log h) persistently, and without preprocessing

nonlinear-optimization-ad - Several Haskell packages for numerical optimizations.

sgd - Stochastic gradient descent Haskell library