Cython is a programming language. It can run on Windows, macOS, and Linux operating systems. It had a version ranging from 2.6 to 3.8. Cython 3.0.0 is under development. In Cython, the Code written in Python is converted to C language. High traffic websites such as Quora use Cython Programming language.
History
Cython is actually derived from the Pyrex language. It is more advanced and has more features and optimizations than the Pyrex language. Cython was separated from the Pyrex development in the year 2007 because its developers envisioned a wider scope of the language than Pyrex. It was a part of a project called Sage. Cython programming language has a .pyx extension. Scientific users of Python use the Cython programming language a lot. It was created by Guido van Rossum and developed by Robert Bradshaw and Stefan Behnel. It was initially released on the 28th of July, 2007. It had its stable release on 24th March 2020.
How to use Cython Programming Language
Cython is aimed at being the superset of the Python programming language. It is so designed that it gives C like performance along with codes mostly written in the Python language allowing extra syntax that is inspired by C. When Cython is compiled it gives CPython extension modules. It provides lesser computational overhead than Python at run-time. C and C++ codes can be wrapped into the Cython modules. The Cython is dependent on the Python interpreter and standard library. Cython employs optimistic optimizations, optional type inference, low control structures overheads, and low function call overhead. Its performance is dependent on the generation and implementation of the C codes. The Cython programming Language is much like Python with very little difference. To understand this, let us take, for example, Python code and its relevant Cython code.
Python code:
Python3
def f(x): return x * * 2 - x def integrate_f(a, b, N): s = 0 dx = (b - a) / N for i in range (N): s + = f(a + i * dx) return s * dx |
Cython code:
Python3
cdef double f(double x): return x * * 2 - x def integrate_f(double a, double b, int N): cdef int i cdef double s, x, dx s = 0 dx = (b - a) / N for i in range (N): s + = f(a + i * dx) return s * dx |
In the two codes, it can be seen that very little has been changed. Only the variables have been explicitly declared and it affects the performance thereby improving its speed.
Advantages of the Cython Programming Language
The Cython programming language is used to speed the written codes. Cython language allows easy working with the C libraries. Cython also supports C++. Cython allows easy interaction with the Python Libraries without Python in the way. Cython Libraries have the same garbage collection as that of Python. It is also possible to manage the C-level Structures using malloc/free. Cython automatically checks for runtime problems that arise in C. The C-code generated by Cython is very safe. If error checks are not required at runtime, they can even be disabled. Cython also uses the Global Interpreter Lock of Python. It is used for countering the problem of resource contention. Cython can be used in Python application and software modules that need extra protection from attacks such as snooping.
Limitations of Cython
When Cython encounters the Python codes its complete conversion to C language is not possible which results in several calls to the Python interpreter. This might give a little speedup (15-20%) or in some cases either have no effect or degradation of performance. Cython code is best in its performance when it is written only in the C language. Cython provides a source code report that illustrates which parts of it are written in Python to avoid performance bottlenecks.
Cython Numpy
Cython has the ability to improve the usage of the third-party number-crunching libraries like NumPy that are based on C. It uses NumPy to counter Python bottleneck problems by taking them outside the loop. Fast access to arrays of Numpy is provided by Cython. The syntax in the Cython written for Numpy is similar to the syntax that is used in Python. For faster bindings of the Cython and Numpy, the custom of Cython is needed. This includes the use of the statement, “cimport”. This statement is used by the Cython programming language to see the C- level constructs at the time of program compilation.