ffi.py

# Problem:

# This topic demonstrates how to use C extensions and FFI to speed up a long-running data processing task in Python. It involves generating a large number of random integers using the `jot` command and performing computations on those integers.

# The exercise is divided into four steps:

# 1. Implementing the data processing task in Python using the `subprocess` module to execute the `jot` command and perform the computation.
# 2. Implementing the same data processing task in C, compiling it into a shared library.
# 3. Creating a Python extension using C extensions and FFI to integrate the C implementation with Python.
# 4. Comparing the performance of the Python implementation and the Python extension.

# The example usage provides code snippets for each step, demonstrating how to generate random integers using `jot`, perform the computation in Python and C, and use `cffi` to define the interface between Python and the C code.

# The expected output shows the execution times of both the Python implementation and the C extension, highlighting the performance improvement achieved by using C extensions and FFI.

# This exercise aims to showcase the potential of using C extensions and FFI to optimize performance-critical parts of a Python program, particularly when dealing with long-running data processing tasks. It emphasizes the importance of leveraging the speed of C code while still utilizing the flexibility and ease of use of Python.