1
Copying data is wasteful, mutating data is dangerous
Copying data wastes memory, and modifying/mutating data can lead to bugs. Learn how to implement a compromise between the two in Python: hidden mutability.
Itamar Turner-Trauring
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2
How many CPU cores can you use in parallel?
Figuring out how much parallelism your program can use is surprisingly tricky.
3
Loading NumPy arrays from disk: mmap() vs. Zarr/HDF5
Learn how to load larger-than-memory NumPy arrays from disk using either mmap() (using numpy.memmap), or the very similar Zarr and HDF5 file formats.
4
Measuring memory usage in Python: it’s tricky
Measuring your Python program’s memory usage is not as straightforward as you might think. Learn two techniques, and the tradeoffs between them.
5
Faster floating point math with Rust's new API
Compilers have a hard time optimizing floating point math. Rust has a new API to fix this.