pic_cooming_soonPython Programming

Python is a widely used high-level programming language for general-purpose programming, created by Guido van Rossum and first released in 1991. An interpreted language, Python has a design philosophy which emphasizes code readability (notably using whitespace indentation to delimit code blocks rather than curly brackets or keywords), and a syntax which allows programmers to express concepts in fewer lines of code than possible in languages such as C++ or Java. The language provides constructs intended to enable writing clear programs on both a small and large scale.

Python features a dynamic type system and automatic memory management and supports multiple programming paradigms, including object-oriented, imperative, functional programming, and procedural styles. It has a large and comprehensive standard library.

Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems. CPython, the reference implementation of Python, is open source software and has a community-based development model, as do nearly all of its variant implementations. CPython is managed by the non-profit Python Software Foundation.

Read: Think Python: How to Think Like a Computer Scientist. 2nd Edition” PDF Below

 

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Read: “Python Programming – An Introduction to Computer Science” Below

 

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Read: “Introduction to Programming in Python” Online

Online Lectures

MIT 6.00 Introduction to Computation and Programming Using Python

Course website

Professor Eric Grimson & Professor John V. Guttag

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This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language.

Lec 1 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008

Lec 2 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008

Lec 21 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008

Lec 22 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008

Further Reading:
  1. Guttag: Introduction to Computation and Programming Using Python. Paperback – 2 Aug 2013

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This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of “data science” for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT’s OpenCourseWare) and was developed for use not only in a conventional classroom but in a massive open online course (or MOOC) offered by the pioneering MIT-Harvard collaboration edX. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

  • Paperback: 296 pages
  • Publisher: MIT Press; revised and expanded ed edition (2 Aug. 2013)
  • Language: English
  • ISBN-10: 0262525003
  • ISBN-13: 978-0262525008
  • Product Dimensions: 21.6 x 1.3 x 27.9 cm

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2. Langtangen: A Primer on Scientific Programming with Python (Texts in Computational Science and Engineering)

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The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches “Matlab-style” and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.

From the reviews:

Langtangen … does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. … Summing Up: Highly recommended.
F. H. Wild III, Choice, Vol. 47 (8), April 2010

Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.”
John D. Cook, The Mathematical Association of America, September 2011

This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science.
Alex Small, IEEE, CiSE Vol. 14 (2), March/April 2012

  • Hardcover: 872 pages
  • Publisher: Springer; 4th ed. 2014 edition (31 July 2014)
  • Language: English
  • ISBN-10: 3642549586
  • ISBN-13: 978-3642549588
  • Product Dimensions: 26.2 x 18 x 4.3 cm

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