Medo VS NumPy

To me the most impressive recent example is a video editor developed for Haiku OS [0]. It fits on a 1.44MB floppy disk.

[0] https://github.com/smallstepforman/Medo

> does anybody know of an editor capable of cutting between inter frames?

https://github.com/smallstepforman/Medo

I’ve created a 4k UHD video editor for Haiku OS (https://github.com/smallstepforman/Medo), it’s a C++17 native app, with over 30 OpenGL GLSL effect plugins and addons, multi threaded Actor model, over 10 user languages, and the entire package file fits on a 1.44Mb floppy disk with space to spare. If I was really concerned about space, I could probably replace all .png resources with WebP and save another 200kb.

How is it so small? No external dependancies (uses stock Haiku packages), uses the standard C++ system API, and written by a developer that learned their trade on restrained systems from the 80’s. Look at the old Amiga stuff from that era.

At its core, Linux offers variety, while Haiku strives to be a unified system. There is only one official UI, one sound API, one filesystem, one preference system, etc. making Haiku easier to administer. The system kits are designed to work together.

For instance, I created a from scratch video editor for Haiku which does 4K UHD videos with OpenGL based plugins, with over 30 effects, and 10 languages. The installer package with no dependancies is 1.3Mb (fits on a floppy disk). https://github.com/smallstepforman/Medo Under Linux, I would require many more dependancies since I have so no guarantee what libraries or API the users have installed.

My favourite - BeOS/Haiku Interface Kit (Link to my project with screenshot https://github.com/smallstepforman/Medo).

You can always use both ... example from my project: https://github.com/smallstepforman/Medo

Wait until you try Haiku on the same hardware. I’ve got a 4K video editor with no HW acceleration yet is smoother to edit videos than both OSX and Win10.

https://github.com/smallstepforman/Medo/raw/main/Docs/Medo.j...

https://github.com/smallstepforman/Medo It is for a opensource Media Operating System called Haiku Os, and it is less than 1.44 Mb open source very lightweight:

In NumPy with @, dot() or matmul():

In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.

Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:

numpy: A library for scientific computing in Python

Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.

I was looking at all the big projects like numpy, pytorch, flask, etc.

I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]