What is Python?
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You have decided to learn Python and I can only congratulate you. I will try to anticipate your questions and leave no one behind.
In this chapter, I will first explain what a programming language is. We will then briefly see the story of Python, so that you at least know where this language comes from! This chapter is theoretical but I urge you to read it anyway.
The final section will cover the installation of Python, an essential step to continue this tutorial. Whether you are working with Windows, Linux or Mac OS X, you will find precise explanations of the installation.
Come on, we attack!
A programming language? What is it ?
Human communication
No, this is not a biological or philosophical explanation, do not leave!
Very simply, if you come to understand these sequences of strange and disconcerting symbols that are the letters of the alphabet, it is because we respect certain conventions, in language and in writing. In French, there are rules of grammar and spelling, I do not teach you anything. You communicate by knowing more or less consciously these rules and by applying them more or less well, as the case may be.
However, these rules can easily be circumvented: no one can claim to know all the rules of French grammar and spelling, and few people care. After all, even if you make mistakes, people with whom you communicate can easily understand you.
When you communicate with a computer, however, it's very different.
My computer communicates too!
Yes, your computer communicates constantly with you and you communicate with him constantly. Okay, he tells you very rarely that he is hungry, that the summer promises to be scorching and that the last disc of this well-known band was crying.
There is nothing magic if, when you click on the small cross at the top right of the current application, it understands that it must close.
Machine language
In fact, your computer is also based on a language to communicate with you or with itself. The operations that a computer can perform at the base are most classic and consist of the addition of two numbers, their subtraction, their multiplication, their division, whole or not. And yet, these five operations are amply enough to run the most complex simulation software or super-realistic games.
All these programs work roughly the same way:
- a sequence of instructions written in machine language composes the program;
- when running the program, these instructions describe to the computer what to do (the computer can not guess).
By schematizing voluntarily, an instruction could ask the program to close if you click on the cross at the top right of your screen, or stay in the background if that is his pleasure. However, in machine language, such an action alone requires a large number of instructions.
But hey, you can imagine, talking with the computer in machine language, which includes only the binary, it is neither very rewarding nor very practical, and in any case not very funny.
We have invented programming languages to facilitate communication with the computer.
What can Python do?
Python is a powerful language that is both easy to learn and rich in possibilities. From the moment you install it on your computer, you have many features built into the language that we will discover throughout this book.
It is also very easy to extend the existing features, as we will see. Thus, there are so-called libraries that help the developer to work on particular projects. Several libraries can thus be installed to, for example, develop graphical interfaces in Python.
Concretely, that's what we can do with Python:
- small, very simple programs, called scripts, loaded with a very precise mission on your computer;
- complete programs, such as games, office suites, multimedia software, email clients ...
- very complex projects, such as software packages (set of several software that can work together, mainly used in the professional world).
Python and the XML
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Introduction to web development with Python and Django
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Django Web Framework and Python
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Advanced Python, course with exercises
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Processing WSDL in Python
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Think Python, Free PDF tutorial
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Learning Python language
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Making Games with Python & Pygame
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Python for Everybody
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A Practical Introduction to Python Programming
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A Byte of Python
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Algorithmic Problem Solving with Python
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Annotated Algorithms in Python: with Applications in Physics, Biology, and Finance
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A Python Book: Beginning Python, Advanced Python, and Python Exercises
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Automate the Boring Stuff with Python: Practical Programming for Total Beginners
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A Whirlwind Tour of Python
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Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference Using Python and PyMC
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Building Skills in Python: A Programmer's Introduction to Python
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Classic Computer Science Problems in Python
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Deep Learning with Python
This book introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.
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Essential Python
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Fast Lane to Python
This book aims to enable the reader to quickly acquire a Python foundation. The material particularly feel quite comfortable to anyone with background in an object-oriented programming (OOP) language such as C++ or Java.
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From Python to NumPy
NumPy is one of the most important scientific computing libraries available for Python. This book teaches you how to achieve expert level competency to perform complex operations, with in-depth coverage of advanced concepts.
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Hands-on Python Tutorial
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How To Code in Python 3
An introduction to computer programming with Python 3. Helps the readers in learning the key concepts of Python and understanding how programs work while also imparting foundational logic that can serve the readers in other domains.
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How to Think Like a Computer Scientist: Learning with Python 3 Documentation
This book is an introduction to computer science using the Python programming language. It covers the basics of computer programming, including variables and values, functions, conditionals and control flow, program development and debugging. Later chapters cover basic algorithms and data structures.
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Introduction to Scientific Programming with Python
This book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming.
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IPython Interactive Computing and Visualization Cookbook
This book contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning.
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Learning to Program Using Python
An introduction to computer programming, using the easy, yet powerful, Python programming language. Python, a cross-platform language used by such organizations as Google and NASA, lets you work quickly and efficiently, allowing you to concentrate on your work rather than the language.
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Learning with Python: How to Think Like a Computer Scientist
The user-friendly, object-oriented programming language Python is quickly becoming the most popular introductory programming language for both students and instructors.
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Make Games with Python on Raspberry Pi
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Modeling and Simulation in Python
This book is an introduction to physical modeling using a computational approach. It is organized in three parts:
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Natural Language Processing with Python – Analyzing Text with the Natural Language Toolkit
This online version of the NLTK book is updated for Python 3 and NLTK 3 on 2015.
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Non-Programmer's Tutorial for Python 3
This book is a tutorial for the Python 3 programming language designed for someone with no programming experience. Starting from no programming knowledge, the book teaches how to create programs with examples, explanations and exercises.
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Practices of the Python Pro
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Problem Solving with Algorithms and Data Structures Using Python
This books is about computer science. It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence.
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Programming Computer Vision with Python: Tools and Algorithms for Analyzing Images
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Programming for Computations - Python: A Gentle Introduction to Numerical Simulations with Python
This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students.
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Programming for Computations - Python: A Gentle Introduction to Numerical Simulations with Python 3.6
This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages
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Python 3 Patterns, Recipes and Idioms
This book is aimed at more experienced Python programmers who are looking to deepen their understanding of the language and modern programming idioms. Much of the material focuses on some of the more advanced techniques used by libraries, frameworks, and applications.
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Python and Coding Theory
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Python Data Science Handbook: Essential Tools for Working with Data
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all - IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.
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Python for Everybody: Exploring Data in Python 3
Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.
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Python for Informatics: Exploring Information
This book is designed to introduce students to programming and computational thinking through the lens of exploring data. You can think of Python as your tool to solve problems that are far beyond the capability of a spreadsheet. It is an easy-to-use and easy-to learn programming language that is freely available on Windows, Macintosh, and Linux computers.
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Python for You and Me
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Python in Hydrology
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Python Machine Learning Projects
This book tries to equip the developers of today and tomorrow with tools they can use to better understand, evaluate, and shape machine learning.
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Python Notes for Professionals
This book goes beyond the basics to teach beginner- and intermediate-level Python programmers the little-known tools and constructs that build concise, maintainable code. Design better architecture and write easy-to-understand code using highly adoptable techniques that result in more robust and efficient applications.
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Python Scientific Lecture Notes (Scipy Lecture Notes)
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Python Scripting for Spatial Data Processing
This book is a Python tutorial for beginners aiming at teaching spatial data processing. It is used as part of the courses taught in Remote Sensing and GIS at Aberystwyth University, UK.
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Solving PDEs in Python: The FEniCS Tutorial I
This book offers a concise and gentle introduction to finite element programming in Python based on the popular FEniCS software library. Using a series of examples, including the Poisson equation, the equations of linear elasticity, the incompressible Navier–Stokes equations, and systems of nonlinear advection–diffusion–reaction equations, it guides readers through the essential steps to quickly solving a PDE in FEniCS, such as how to define a finite variational problem, how to set boundary conditions, how to solve linear and nonlinear systems, and how to visualize solutions and structure finite element Python programs.
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Test-Driven Development with Python
By taking you through the development of a real web application from beginning to end, this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You'll learn how to write and run tests before building each part of your app, and then develop the minimum amount of code required to pass those tests. The result? Clean code that works.
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The Coder's Apprentice: Learning Programming with Python 3
This book is aimed at teaching Python 3 to students and teenagers who are completely new to programming. Contrary to many of the other books that teach Python programming, this book assumes no previous knowledge of programming on the part of the students, and contains numerous exercises that allow students to train their programming skills.
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Think Bayes: Bayesian Statistics in Python
If you know how to program with Python and also know a little about probability, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you'll begin to apply these techniques to real-world problems.
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Think DSP: Digital Signal Processing in Python
This book is an introduction to signal processing and system analysis using a computational approach, using Python as the programming language. The premise of this book (like the others in the Think X series) is that if you know how to program, you can use that skill to learn other things. By the end of the first chapter, you'll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Subsequent chapters follow a logical progression that develops the important ideas incrementally, with a focus on applications.
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O'Reilly® Think Python, 2nd Edition, - How to Think Like a Computer Scientist
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Think Python: An Introduction to Software Design
Python for Software Design is a concise introduction to software design using the Python programming language. Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging.
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Think Python - How to Think Like a Computer Scientist
Think Python is an introduction to Python programming for students with no programming experience. It starts with the most basic concepts of programming, and is carefully designed to define all terms when they are first used and to develop each new concept in a logical progression. Larger pieces, like recursion and object-oriented programming are divided into a sequence of smaller steps and introduced over the course of several chapters.
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Think Stats, 2nd Edition: Exploratory Data Analysis in Python
If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.
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Problem Solving with Algorithms and Data Structures Using Python
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Biopython: Tutorial and Cookbook
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Programming for Computations - Python, 2nd Edition
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Modeling and Simulation in Python
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How To Code in Python 3
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Fundamentals of Python Programming
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Mastering Python
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Think Python, 2nd Edition
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Invent Your Own Computer Games with Python
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Raspberry Pi Cookbook for Python Programmers
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A Byte of Python
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Annotated Algorithms in Python
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Hacking Secret Ciphers with Python
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A Practical Introduction to Python Programming
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Programming Computer Vision with Python
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Making Games with Python & Pygame
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A Byte of Python
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Annotated Algorithms in Python
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A Whirlwind Tour of Python
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Biopython: Tutorial and Cookbook
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Classic Computer Science Problems in Python
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Programming for Computations - Python
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Python Tutorial for Beginners in PDF
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