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Difference between Python and Cython

At present, Python is one of the most popular general-purpose programming languages. It is currently used widely by developers for building desktop GUI applications, web applications, and websites. Also, Python is used in scientific computing, big data, natural language processing, artificial intelligence, and machine learning projects.

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Difference between Python and Cython

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  1. Difference between Python and Cython

  2. At present, Python is one of the most popular general-purpose programming languages. It is currently used widely by developers for building desktop GUI applications, web applications, and websites. Also, Python is used in scientific computing, big data, natural language processing, artificial intelligence, and machine learning projects. Unlike other programming language, Python focuses extensively on keeping code readable and maintainable. It simple and expressive syntax further enables programmers to express concepts without writing additional and complex code.

  3. However, Python is an interpreted programming language. A number of studies suggest that Python is much slower than a number of compiled programming languages including C and C++. Many programmers opt for various supersets of Python programming languages to accelerate code execution speed. Cython is a popular superset of Python. As a compiled programming language, Cython helps programmers to boost performance of code with C-like performance. The developers can load and use the extension modules directly in the Python code through the import statement.

  4. Understanding Important Differences between Python and Cython Type of Programming Language Python is an interpreted programming language. Hence, Python programmers need interpreters to convert Python code into machine code. Each time a programmer runs a Python program, the code needs to be parse and interpreted before execution. On the other hand, Cython is a compiled programming language. The Cython programs can be executed directly by the CPU of the underlying computer without using any interpreter.

  5. Design Goal As noted earlier, Python is designed as a general-purpose programming language. It supports a number of commonly used programming paradig?s — o?je?t-oriented, functional, procedural and imperative. It further features a dynamic type system, supports automatic memory management, and emphasizes on code readability. Cython is designed as a superset of Python programming language. In addition to being written in Python, Cython also have the capability to generate standard Python modules. Syntax The programmers have option to choose from two distinct versions of Pytho? — 2.x and 3.x. The syntax rules of the two versions of Python differ. Also, the two versions of the high level programming languages are not compatible with each other. Hence, the developers have to learn and use syntax rules according to their preferred version of Python. Cython uses syntax which is hugely influenced by Python 2.6. It even supports most Python 2.x syntax. But Cython is yet to support all Python 3.x features.

  6. Behaviour Python enables programmers to organize the code through modules. Each Python module contains specific Python code and has its own attributes. These modules make it easier for programmers to keep the code base organized and maintainable. Cython has the capability to generate standard Python modules. But it translates module code written in Python into C. The translation processes improves the code execution speed significantly. But the modules generated by Cython cannot be used without Python interpreter and standard library. Performance and Speed As mentioned earlier, Python is an interpreted programming language, whereas Cython is a compiled programming language. Despite being a superset of Python, Cython is much faster than Python. It improves Python code execution speed significantly by compiling Python code into C code. The compilation further helps developers to run the Python programs smoothly without deploying additional computing resources. Hence, many programmers to opt for Cython to write concise and readable code in Python that perform as faster as C code.

  7. Interoperability In addition to being a superset of Python, Cython is also written in Python. It is designed as a C-extension for Python to compile Python code to C/C++ code. Hence, both Python and Cython programs implement the same algorithms. The developers can further embed the CPython extension modules generated by Cython in Python code through the import statements. They can even add type hints to existing Python programs through Cython. Cython even enables developers to call C or C++ code natively from Python code. The programmers can include Cython seamlessly in existing Python applications, code, and libraries.

  8. Use Cases Python is a general purpose programming language. In addition to being used widely as a scripting language for web development, Python is currently being used in scientific computing, big data, artificial intelligence, machine learning, and Internet of Things (IoT) projects. Also, Python, at present, is being used by large enterprises like Google, NASA, CERN and Wikipedia. On the other hand, Cython is used widely in scientific and numerical computing projects. A number of widely used scientific computing libraries for Pytho? — Pa?das and S?iPy — are also written in Cython. Also, Cython is currently being used by a number of high traffic websites including Quora. On the whole, Python is a general-purpose programming language, whereas Cython is a superset of Python programming language. The Python developers can take advantage of Cython as a C-extension for Python to optimize performance and speed of Python programs. They can even use Cython to compile Python code to C/C++ code. But Cython cannot be used without Python programming language, standard library, and interpreter.

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