https://github.com/winstxnhdw/python-bench

Simple code optimisation benchmark for speed and accuracy.
https://github.com/winstxnhdw/python-bench

benchmark numba numpy python scipy

Last synced: about 13 hours ago
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Simple code optimisation benchmark for speed and accuracy.

• Host: GitHub
• URL: https://github.com/winstxnhdw/python-bench
• Owner: winstxnhdw
• Created: 2021-08-05T12:45:29.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2022-11-08T23:54:52.000Z (about 2 years ago)
• Last Synced: 2024-12-11T02:21:33.028Z (about 2 months ago)
• Topics: benchmark, numba, numpy, python, scipy
• Language: Jupyter Notebook
• Homepage:
• Size: 66.4 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# python-bench

Simple code optimisation benchmark for speed and accuracy. Never will I write slow Python code like a noob again.

## Benchmarks

- Array/List Operations

  - [Appending](src/appending.ipynb)

  - [Prepending](src/prepending.ipynb)

  - [Unpacking](src/unpacking.ipynb)

  - [Homogeneous Arrays](src/homogeneous_arrays.ipynb)

  - [Array Conversion](src/array_conversion.ipynb)

- Mathematical Operations

  - [Exponentiation](src/exponentiation.ipynb)

  - [Dot Product](src/dot_product.ipynb)

  - [L2-Norm](src/l2_norm.ipynb)

- Libraries

  - [NumPy Vectorisation/Broadcasting](src/vectorisation.ipynb)

  - [NumPy hypot](src/numpy_hypot.ipynb)

  - [Numba](src/numba.ipynb)

  - [Math](src/math.ipynb)