Python-Code mit C beschleunigen (und ohne zusätzliche Bibliotheken)

NOTE:Originally posted in my Substack: https://open.substack.com/pub/andresalvareziglesias/p/speeding-up-python-code-with-c-and

Python is not the paradigm of speed, we all know this. But we can speed up some critical parts of our apps with the help of our good old friend C.

The Fibonacci sequence in plain Python

The Fibonacci sequence is a classic example used to teach software development. Is a series of numbers that starts with 0 and 1. Each subsequent number is the sum of the previous two. So, the sequence goes like this: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, ...

We can develop Fibonacci in python in this way:

import time # Configure iterations iterations = 30 # Define fibonacci in native python def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2) # Calculate in pure python start_time = time.perf_counter() print(f"Calculating {iterations} iterations of fibonacci...") print(fibonacci(iterations)) end_time = time.perf_counter() execution_time_ms = (end_time - start_time) * 1000 print(f"Execution time: {execution_time_ms:.2f} milliseconds") print()

If we execute this pure Python (in a Google IDX virtual machine) version of Fibonacci we get:

• 10 iterations: 5.77 milliseconds
• 30 iterations: 984.36 milliseconds
• 50 iterations: (I have to cancel the process, too much time)

The Fibonacci sequence in C

We can develop the same sequence in plain C:

#include  int fibonacci(int n) { if (n <= 1) { return n; } else { return fibonacci(n - 1) + fibonacci(n - 2); } }

Compile the library with GCC:

gcc -o fibonacci.so -shared -fPIC -O2 fibonacci.c

Now, we have a native binary library with the fibonacci sequence function inside. We can embed this library inside a Python app with ctypes (the Python C types library, because Python itself is developed in C):

import time from ctypes import c_double, c_int, CDLL # Configure iterations iterations = 30 # Import the C library library = CDLL('./fibonacci.so') fibonacciAsLibrary = library.fibonacci fibonacciAsLibrary.restype = c_int # Calculate as C library start_time = time.perf_counter() print(f"Calculating {iterations} iterations of fibonacci as C library...") print(fibonacciAsLibrary(iterations)) end_time = time.perf_counter() execution_time_ms = (end_time - start_time) * 1000 print(f"Execution time: {execution_time_ms:.2f} milliseconds") print()

Now, if we execute this version on Fibonacci, we get:

• 10 iterations: 0.54 milliseconds
• 30 iterations: 6.92 millisecond
• 50 iterations: 82324.90 milliseconds

Better, isn’t?

Use cases for Python and C integration

We can use this kind of integration in a lot of apps and scenarios, like:

• Speed up serializers and deserializers in our Django app
• Speed up critical parts on a workflow
• Low level interactions with the OS
• Etc.

And you? How will you use this litle trick in your project? I woult love to hear your comments!

About the list

Among the Python and Docker posts, I will also write about other related topics (always tech and programming topics, I promise... with the fingers crossed), like:

• Software architecture
• Programming environments
• Linux operating system
• Etc.

If you found some interesting technology, programming language or whatever, please, let me know! I'm always open to learning something new!

About the author

I'm Andrés, a full-stack software developer based in Palma, on a personal journey to improve my coding skills. I'm also a self-published fantasy writer with four published novels to my name. Feel free to ask me anything!

Das obige ist der detaillierte Inhalt vonPython-Code mit C beschleunigen (und ohne zusätzliche Bibliotheken). Für weitere Informationen folgen Sie bitte anderen verwandten Artikeln auf der PHP chinesischen Website!