# What is this Python project?
Ray is a flexible, high-performance distributed execution framework. It achieves parallelism in Python with simple and consistent API.
Ray is particularly suited for machine learning and forms the base of libraries for deep and reinforcement learning, distributing processing of Pandas dataframes, or hyper parameter search.
# What's the difference between this Python project and similar ones?
- Similar to Dask, see a comparison here: https://github.com/ray-project/ray/issues/642
- Allows to efficiently share large numpy arrays (or objects serializable with Arrow) between the processes, without copying the data and with only minimal deserialization
- Achieves lower latency with bottom up scheduling
pyvips is a binding for the libvips image processing library. It's
fast and only needs a little memory. For example, on this benchmark:
https://github.com/jcupitt/libvips/wiki/Speed-and-memory-use
It's 3x faster than ImageMagick and needs 5x less memory.
pyvips works on all python versions on all platforms, is LGPL, can be
simply installed with pip, has complete documentation, has a large test
suite and has no memory leaks.
Added PySimpleGUI to the list of GUI frameworks.
It's a new package that enables creation of custom GUIs in very few lines of clear, easy to read Python code.
None of the other simplified GUI frameworks come close to this kind of design.
