Why “numpy.any” has no short-circuit mechanism?
I don’t understand why a so basic optimization has not yet be done:
performance
Performance with global variables vs local
I am still new to Python, and I have been trying to improve the performance of my Python script, so I tested it with and without global variables. I timed it, and to my surprise, it ran faster with global variables declared rather than passing local vars to functions. What’s going on? I thought execution speed was faster with local variables? (I know globals are not safe, I am still curious.)
Vectorizing Haversine distance calculation in Python
I am trying to calculate a distance matrix for a long list of locations identified by Latitude & Longitude using the Haversine formula that takes two tuples of coordinate pairs to produce the distance:
Python OpenCV streaming from camera – multithreading, timestamps
I ran simple python script on Raspberry Pi 3. This script is responsible to open video device and stream data (800×600) to HTTP endpoint using MJPEG. When I receive this stream one of my Raspberry Pi cores works on 100%. It possible to run OpenCV with multi threading?
Pandas pd.Series.isin performance with set versus array
In Python generally, membership of a hashable collection is best tested via set. We know this because the use of hashing gives us O(1) lookup complexity versus O(n) for list or np.ndarray.
Are NumPy’s math functions faster than Python’s?
I have a function defined by a combination of basic math functions (abs, cosh, sinh, exp, …).
Why is numpy.array so slow?
I am baffled by this
Creating an empty list in Python
What is the best way to create a new empty list in Python?
multiprocessing.Pool() slower than just using ordinary functions
(This question is about how to make multiprocessing.Pool() run code faster. I finally solved it, and the final solution can be found at the bottom of the post.)
Python Requests vs PyCurl Performance
How does the Requests library compare with the PyCurl performance wise?