Название: Introduction to Computer Programming with PythonАвтор: Harris Wang
Издательство: Remix
Год: 2023
Страниц: 500
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB
This introduction to computer programming with Python begins with some of the basics of computing and programming before diving into the fundamental elements and building blocks of computer programs in Python language. From the installation of Python, Python interactive programming, and integrated development environments to raising and handling exceptions, using compound data types to solve problems, and implement divide-and-conquer processes using functions, classes and modules, this textbook will set students up for success in programming and computing study and practice. The included exercises and projects are designed to hone students’ skills.
Python is an interpreted programming language rather than a compiled programming language. Programs written in Python don’t need to be compiled into target machine code. Instead, they only need to be translated into bytecodes, then executed by a Python Virtual Machine (PVM), which is built into the Python interpreter.
Python was designed with the principle of “programming for everyone.” Programs written in Python are clean and easy to read. Yet Python is a general-purpose programming language and very powerful to code in. Programming in Python has the least overhead, especially when compared to Java.
More importantly, Python supports different programming paradigms, including structured programming, imperative programming, object-oriented programming, functional programming, and procedural programming. Logic programming is probably the only exception; it is not supported by Python.
Python is very powerful for two reasons. The first reason, as you will see later, is that Python has many powerful language constructs and statements to represent data and operations on various data. The second reason is that there are thousands of third-party packages/libraries/modules available for all kinds of programming needs in addition to the large standard libraries included with every release of Python. For example, Python is widely used for data analytics and machine learning with the support of the NumPy, SciPy, Pandas, Matplotlib, and TensorFlow libraries.
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