An ongoing fun challenge where I'll try to post one Python benchmark per day.
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An ongoing project for benchmarking different Python approaches - ideally one per day!
I would be happy to hear your comments and suggestions.
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Day 1 - Reversing strings [html] [IPython nbviewer] [raw]
Day 2 - Calculating sample means [html] [IPython nbviewer] [raw]
Day 3 - 6 different ways to count elements using a dict [html] [IPython nbviewer] [raw]
Day 4 - Python vs. Cython vs. Numba [html] [IPython nbviewer] [raw]
Day 4.2 - (C)Python compilers - Cython vs. Numba vs. Parakeet [html] [IPython nbviewer] [raw]
Day 5 - Comparing 9 ways for flattening lists of sublists [html] [IPython nbviewer] [raw]
Day 6 - Determining if a string is a number [html] [IPython nbviewer] [raw]
Day 7 - Speeding up NumPy array expressions with Numexpr [html] [IPython nbviewer] [raw]
Day 7.2 - Just-in-time compilers for NumPy array expressions [html] [IPython nbviewer] [raw]
Day 8 - Calculating square roots and exponents [html] [IPython nbviewer] [raw]
Day 9 - The most Pythonic way to check if a string ends with a particular substring [html] [IPython nbviewer] [raw]
Day 10 - Cython - Bridging the gap between Python and Fortran [html] [IPython nbviewer] [raw]
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Day 11 - The
deque
container data type [html] [IPython nbviewer] [raw] -
Day 12 - Lightning fast insertion into sorted lists via the
bisect
module [html] [IPython nbviewer] [raw] Day 13 - Parallel processing via the multiprocessing module [html] [IPython nbviewer] [raw]
Day 14 - Python's and NumPy's in-place operator functions [html] [IPython nbviewer] [raw]
Day 15 - Array indexing in NumPy: Extracting rows and columns [html] [IPython nbviewer] [raw]
Day 16 - Vectorizing a classic for-loop in NumPy [html] [IPython nbviewer] [raw]
Day 17 - Stacking NumPy arrays [html] [IPython nbviewer] [raw]
Day 18 - The scikit-learn preprocessing module for feature scaling [html] [IPython nbviewer] [raw]
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Day 19 - Python 2.7.x's
izip
andxrange
[html] [IPython nbviewer] [raw] Day 20 - Calculating the difference between successive elements in a Python list [html] [IPython nbviewer] [raw]