Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python's implementation.\n\nHow do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more.\n\n\n\nGet a better grasp of NumPy, Cython, and profilers\nLearn how Python abstracts the underlying computer architecture\nUse profiling to find bottlenecks in CPU time and memory usage\nWrite efficient programs by choosing appropriate data structures\nSpeed up matrix and vector computations\nUse tools to compile Python down to machine code\nManage multiple I/O and computational operations concurrently\nConvert multiprocessing code to run on local or remote clusters\nDeploy code faster using tools like Docker
