Python vs Cpython
Python is a high-level, interpreted programming language favored for its readability and versatility. It's widely used in web development, data science, machine learning, scripting, and more. However, Cpython is the default and most widely used implementation of the Python language. It's written in C and serves as a reference point for other Python implementations.
In this article, we will go through the major differences between Python and Cpython in depth.
What is Python?
Python is a high-level, interpreted programming language created by Guido van Rossum and first released in 1991. It emphasizes code readability and simplicity, allowing programmers to express concepts in fewer lines of code compared to languages like C++ or Java. Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming.
What is Cpython?
CPython is the reference implementation of Python, written in C. It is the most widely used implementation of Python and serves as the standard against which other implementations are measured. CPython compiles Python code into intermediate bytecode, which is then executed by its virtual machine. This implementation provides the default runtime for Python, including the standard library and built-in functions.
Key Differences between Python and Cpython
Here are some major differences between Python and CPython.
Features | Python | Cpython |
---|---|---|
Scope | Python is a language specification, defining syntax, keywords, and core concepts. | Cpython is an interpreter that executes Python code. |
Implementation | Language-agnostic, meaning it can be implemented in various languages. | Specifically implemented in C, making it efficient but tying it to C's ecosystem. |
Portability | Designed to be portable across different platforms. | Portability depends on C compilers and libraries being available on the target system. |
Performance | Varies depending on implementation | Generally slower due to interpreted nature but can be optimized with C extensions |
Compatibility | Broadly compatible across different platforms and implementations | Specifically tailored to work with C extensions |
Usage | General-purpose programming | Used when performance optimization is required or when integrating with C libraries |
Code Implementation of Pthon and CPython
Now let us see an example for both Python and CPython for a better understanding.
In this example, we have a list for five numbers and we will print the square of those number first in Python and then in CPython.
Python Code
# Python Code Example
numbers = [1, 2, 3, 4, 5]
squared_numbers = []
# Squaring each number using a loop
for num in numbers:
squared_numbers.append(num ** 2)
print(f"Squared Numbers: {squared_numbers}")
Output:
Squared Numbers: [1, 4, 9, 16, 25]
Cpython Code
The below code demonstrates Python's elegant list comprehension feature, working seamlessly in CPython.
#include <Python.h>
int main()
{
// Initialize the Python interpreter
Py_Initialize();
// Create a Python list: numbers = [1, 2, 3, 4, 5]
PyObject* numbers = PyList_New(5);
for (int i = 0; i < 5; i++) {
PyList_SetItem(numbers, i, PyLong_FromLong(i + 1));
}
// Create an empty list: squared_numbers = []
PyObject* squared_numbers = PyList_New(0);
// Squaring each number using a loop
for (int i = 0; i < 5; i++) {
PyObject* num = PyList_GetItem(numbers, i);
PyObject* squared = PyNumber_Power(
num, PyLong_FromLong(2), Py_None);
PyList_Append(squared_numbers, squared);
Py_DECREF(squared);
}
// Convert the result list to a string and print it
PyObject* squared_numbers_str
= PyObject_Str(squared_numbers);
const char* squared_numbers_cstr
= PyUnicode_AsUTF8(squared_numbers_str);
printf("Squared Numbers: %s\n", squared_numbers_cstr);
// Clean up
Py_DECREF(numbers);
Py_DECREF(squared_numbers);
Py_DECREF(squared_numbers_str);
// Finalize the Python interpreter
Py_Finalize();
return 0;
}
Output:
Squared Numbers: [1, 4, 9, 16, 25]
Note:
To compile the Cpython code, we will need to link against the Python library. Use the following command (this example assumes Python 3.12; adjust if necessary):
gcc -o squared_numbers squared_numbers.c -I/usr/include/python312 -lpython312
Then, run the compiled program:
./squared_numbers
Conclusion
In conclusion, think of Python as the blueprint (language definition) and Cpython as a specific factory (implementation) that builds products based on that blueprint. While Cpython is the most common, other implementations like Jython (Java), IronPython (.NET), and PyPy (Python) offer alternatives with varying performance characteristics and language interoperability.