Publisher's Synopsis
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 clusters? Or build a system that scales up and down without losing reliability? Authors Micha Gorelick and Ian Ozsvald reveal concrete solutions to many issues and include 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
- 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
- Deploy code faster using tools like Docker
