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Full Description
Your Python code may run correctly, but what if you need it to run faster? This practical book shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By explaining the fundamental theory behind design choices, this expanded edition of High Performance Python helps experienced Python programmers gain a deeper understanding of Python's implementation.
How do you take advantage of multicore architectures or compilation? Or build a system that scales up beyond RAM limits or with a GPU? Authors Micha Gorelick and Ian Ozsvald reveal concrete solutions to many issues and include war stories from companies that use high-performance Python for GenAI data extraction, 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
Process DataFrames quickly with Pandas, Dask, and Polars
Speed up your neural networks and GPU 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
