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. How 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.
Get a better grasp of NumPy Cython and profilers Learn how Python abstracts the underlying
computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write
efficient programs by choosing appropriate data structures Speed up matrix and vector
computations Use tools to compile Python down to machine code Manage multiple I O and
computational operations concurrently Convert multiprocessing code to run on local or remote
clusters Deploy code faster using tools like Docker
