Subject
3 entries
Numpy
Bookmarks
Getting the Best Performance out of NumPy
Featured recipe from the IPython Cookbook on getting the best performance out of NumPy — covering vectorization, broadcasting, memory layout, and avoiding Python loops. The kind of practical optimization guide that separates slow scientific Python from production-grade numerical code.
100 Numpy Exercises
Nicolas Rougier's 100 exercises for NumPy, ranging from beginner to expert, covering the array operations that make NumPy indispensable. One of the most effective ways to internalize NumPy's vectorization mindset.
Blaze: A Python Compiler for Big Data
Continuum Analytics' announcement of Blaze — a Python compiler and array expression system designed to scale NumPy-style computations beyond in-memory datasets. An early attempt to bring Python's scientific computing ecosystem to big data before Spark/Dask became dominant.