fcf-containers VS memory

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

fcf-containers

fcf-containers add tools that can be used with first-class-families (by gspia)

memory

haskell memory (by vincenthz)
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fcf-containers memory
- -
4 47
- -
5.8 0.0
12 months ago 9 months 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.

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.

memory

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

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

What are some alternatives?

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

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.

ramus - 📶 - Elm style FRP library for Haskell

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

first-class-families - First-class type families

hdiff - Hash-based Diffing for AST's

hyperloglogplus - Haskell implementation of HyperLogLog++ & MinHash for efficient cardinality and intersection estimation

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

membrain - 🧠 Type-safe memory units