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Sandeep Nagar - Introduction to Python for Engineers and Scientists: Open Source Solutions for Numerical Computation

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Introduction to Python for Engineers and Scientists: Open Source Solutions for Numerical Computation
Author:
Sandeep Nagar
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Apress
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Year:
2017
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Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.

In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First youll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts.

What Youll Learn

Understand the fundamentals of the Python programming language
Apply Python to numerical computational programming projects in engineering and science
Discover the Pythonic way of life
Apply data types, operators, and arrays
Carry out plotting for visualization
Work with functions and loops

Who This Book Is For

Engineers, scientists, researchers, and students who are new to Python. Some prior programming experience would be helpful but not required.

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Sandeep Nagar 2018

Sandeep Nagar Introduction to Python for Engineers and Scientists

1. Philosophy of Python

Sandeep Nagar 1

(1)

New York, USA

1.1 Introduction

Python emerged as a leader [] programming language.

The philosophy of Python can be defined in a single sentence:

Python is a multipurpose, portable, object-oriented, high-level programming language that enables an interactive environment to code in a minimalistic way.

Lets look at the individual characteristics of Python.

1.1.1 High-Level Programming

A high-level programming language is a language that is separated from the details of a particular computer. A low-level language is one where users directly feed the machine code to a processor for obtaining results. A high-level language provides facilities like library functions for performing the low-level tasks and also provides ways to define the code in a form readable to humans, which is then translated into machine language to be fed to a processor.

1.1.2 Interactive Environment

To a large extent, Python derives its philosophy from the ABC language. The syntax structure was largely derived from C and UNIXs Bourne shell environments. They served as inspiration for the interpretative nature of the working environment. The interpretive nature means that Python presents a REPL-based interactive environment to a developer. The interactive shell of the Python programming language is commonly known as REPL (Read-Evaluate-Print- Loops ) because it

reads what a user types,
evaluates what it reads,
prints out the return value after evaluation, and
loops back and does it all over again.

This kind of interactive working environment proves especially useful for debugging. It also helps in prototyping a problem where each step can be visualized for its output in a live fashion. Users can check the results of a particular code as soon as they finish writing it. The way to work with Pythons REPL is to write the code, analyze the results, and continue this process until the final result is computed. In addition to allowing quick and easy evaluation of Python statements, the language also showcases the following:

A searchable history
- Users can press the Up and Down keys on the keyboard to browse through past commands instead of writing them again.
Tab completion
- Users can simply press the Tab key after writing a few letters for a command and it will auto-complete it.
- Consequently, tab completion eliminates syntax errors.
- If more than one option matches when the Tab key is pressed, the options are displayed at the command prompt so users can choose which one they intended.
Many helpful key bindings
- The key bindings depend on the operating systems.
- The key bindings help in quick operations where key combinations are equivalent to a particular operation.
Help and documentation
- Getting help on topics and locating documentation is quite easy in python.
- Users can feed any argument as a string (that is, characters enclosed within double quotation marks) to the built-in function help() .

In addition to being interactive, Python is an interpreted language. Whereas other languages require source code to be converted into an executable and then run on a machinein other words, AOT (ahead-of- time ) compilationPython runs the program directly from source code. Python converts the source code into an intermediate form called bytecodes and then translates the bytecodes into the native language of the computer and runs it. This is a type of OTF (on-the-fly) compilation, enabling portability and making it easier for a developer to write and check the program in an interactive manner.

1.1.3 Object Orientation

Most primitive programming languages were procedural in nature. In other words, a set of procedures was defined to compute a problem and the flow of information was controlled within these procedures to obtain a desired output. Hence, a program was merely divided into blocks of codes that interacted with each other where one block of code defined a computation subtask belonging to a computational problem understudy. Conversely, an object-oriented programming (OOP) language deals with data as an object on which different methods act to produce a desired result. Everything computable is treated as an object. Its nature is defined as its properties. These properties can be probed by functions, which are called methods. The abstract nature of objects makes it possible to invent objects of the users choice and apply the programming concepts for a variety of applications.

1.1.4 Multipurpose Nature

As discussed in the preceding section, the OOP-based architecture of Python enables developers from different walks of life to use and enrich the language in their fields of expertise. Virtually all fields of computations have used Python. You can define a module specific for one kind of problem. In fact, Python modules exist for specific fields of studies, as shown in Table .

Table 1-1

List of Fields of Study and Corresponding Python Modules

Field of Study	Name of Python Module
Scientific Computation	scipy, numpy, sympy
Statistics	pandas
Networking	networkx
Cryptography	pyOpenSSL
Game Development	PyGame
Graphic User Interface	pyQT
Machine Learning	scikit-learn, tensorflow
Image Processing	scikit-image
Plotting	Matplotlib
Database	SQLAlchemy
HTML and XML parsing	BeautifulSoup
Natural Language Processing	nltk
Testing	nose

It is impossible to list all the modules for a given application as the modules are being created on a daily basis. Table lists the most widely used modules at the time of writing. Developers from all over the world are using and developing modules at a tremendous pace. Since Python can be used in a wide arena of computing domains, it is truly the most multipurpose programming language yet.

1.1.5 Minimalistic Design

The minimalistic design philosophy of Python means that it emphasizes code readability . It also provides a syntax structure that allows programmers to express concepts in fewer lines of code than in languages such as C++ and Java. Moreover, Python provides the means to write programs that can be scaled up easily. Python features a dynamic type system where a Python interpreter guesses the type of an object by its definition, which avoids the users need to define the same.

The core philosophy of the language is summarized by Tim Peters in the document The Zen of Python (PEP 20) [], which includes the following aphorisms:

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