Fast Python

5 Re-implementing critical code with Cython

This chapter covers

• How to re-implement Python code more efficiently
• Understanding Cython from a data processing perspective
• Profiling Cython code
• Using Cython to implement performant NumPy functions
• Releasing the GIL to implement true threaded parallelism

Python is slow. The standard implementation is slow, and the language’s dynamic features pay a performance toll. Many Python libraries are performant precisely because they are partially implemented in lower-level languages, making available efficient data processing algorithms. But sometimes we will need to implement our own high-performance algorithms in something faster than Python. In this chapter, we will consider Cython, a superset of Python ...