bottleneck
Fast NumPy array functions written in C (by pydata)
numpy-stl
Simple library to make working with STL files (and 3D objects in general) fast and easy. (by wolph)
bottleneck | numpy-stl | |
---|---|---|
1 | 1 | |
1,006 | 595 | |
1.4% | - | |
3.5 | 6.6 | |
4 days ago | 6 months ago | |
Python | Python | |
BSD 2-clause "Simplified" 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.
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.
bottleneck
Posts with mentions or reviews of bottleneck.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-10-29.
-
Update on my Python, C++ and Rust Library
Fast Array Manipulation in Python: Since Numpy is the de facto standard for storing multi-dimensional data, any performance gain you see using librapid math kernels will need to be realized on data which probably started its life as a numpy array, and needs to be passed to another tool as a numpy array. Hopefully there will be (or already is?) a way to build a librapid array out of a numpy array without copying the data and vice versa. In fact I might suggest that librapid focus on the fast math operations and simply become an accelerator for numpy arrays. For instance, look at CuPy which provides GPU-implemented operations within a numpy-compatible API, and Bottleneck which simply provides fast C-based implementations of some otherwise slow parts of Numpy. Also note that numpy *can* be multi-threaded depending on the operation and some environment variables. Single-threaded to Single-threaded I think you will be hard-pressed to beat Numpy on general math operations, but that doesn't mean there aren't specific "kernels" that are more specialized that can be greatly improved with a C++ back-end.
numpy-stl
Posts with mentions or reviews of numpy-stl.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Question about 3D model assessment
So far I found https://github.com/WoLpH/numpy-stl which is nice but only covers the first question easily.
What are some alternatives?
When comparing bottleneck and numpy-stl you can also consider the following projects:
cupy - NumPy & SciPy for GPU
python-binance - Binance Exchange API python implementation for automated trading
NumPy - The fundamental package for scientific computing with Python.
cadquery - A python parametric CAD scripting framework based on OCCT
pyxirr - Rust-powered collection of financial functions.
dpnp - Data Parallel Extension for NumPy