plotlyhs VS fcf-containers

Compare plotlyhs vs fcf-containers and see what are their differences.

plotlyhs

Plotly.js bindings for Haskell (by glutamate)

fcf-containers

fcf-containers add tools that can be used with first-class-families (by gspia)
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plotlyhs fcf-containers
- -
4 4
- -
0.0 5.8
about 7 years ago 12 months ago
Haskell Haskell
MIT 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.

plotlyhs

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

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

fcf-containers

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

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

What are some alternatives?

When comparing plotlyhs and fcf-containers you can also consider the following projects:

chart-unit - Unital Charts

xmonad-utils - A small collection of X utilities useful when running XMonad.

require - 🔌 Scrap your qualified import clutter

xmonad-screenshot - Gtk-based screen capturing utility for XMonad.

tttool - Trying to understand the file format of Tip Toi

xmonad - The core of xmonad, a small but functional ICCCM-compliant tiling window manager

first-class-families - First-class type families

xmonad-contrib - Contributed modules for xmonad

hdiff - Hash-based Diffing for AST's

tensor-safe - A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras.