实例介绍
【实例简介】
这个是MIT的edx中Introduction to Computer Science and Programming Using Python 计算机科学及python编程导论课程的的教材，这个是最新版本，我在网上找了三四天才找到的，是2013年8月份的，绿色封皮那个。
Introduction to Computation and Programming Using Python Revised and expanded edition John V Guttag The mit Press Cambridge, massachusetts London, England c 2013 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher. MIT Press books may be purchased at special quantity discounts for business or sales promotional use. For information, please email special_sales@mitpress mit edu or write to Special Sales department, The mit Press, 55 Hayward street Cam bridge, ma o2142 Printed and bound in the united states of america Library of Congress Cataloging-in-Publication Data Guttag, john Introduction to computation and programming using Python /John V Guttag Revised and expanded edition p ages cm Includes index isbn 978-0-262-52500-8(pbk: alk. paper) 1. Python(Computer program language) 2. Computer programming. I Title QA7673P48G882013 005.133-dc23 10987654321 To my family olga David Andrea Michae Mark Addie CONTENTS PREFACE X111 ACKNOWLEDGMENTS 1 GETTING STARTED 2 INTRODUCTION TO PYTHON 2.1 The Basic Elements of Python 1789 2.1.1 Objects, Expressions, and Numerical Types………… 2.1.2 Variables and Assignment 11 2.1 3 IDLE 13 2.2 Branching Programs...... 14 2.3 Strings and Input 16 2.3.1 Input.….,…,…,…,…,,…,…,……,……, 18 2.4 Iteration 18 3 SOME SIMPLE NUMERICAL PROGRAMS 21 3. 1 Exhaustive enumeration 21 3.2 For l 23 3.3 Approximate Solutions and Bisection Search 25 3. 4 A Few Words about Using Floats 29 3.5 Newton-Raphse 32 4 FUNCTIONS. SCOPING. and abstraction 34 4.1 Functions and Scoping 35 4. unction Definitions ............,.......................................................35 4.1.2 Keyword Arguments and Default values…… 36 4.1.3 Scoping pecifications 41 4.3 Recursion 44 43. 1 Fibonacci numbers 45 4.3.2 Palindromes 48 4.4 Global variables 50 4.5 Module 51 4.6 Files 53 5 STRUCTURED TYPES. MUTABILITY AND HIGHER-ORDER FUNCTIONS.56 5.1 Tuples.…… ∴56 5.1.1 Sequences and Multiple assignment..……… 57 5.2 Lists and Mutability 58 5.2.1 Cloning 63 5.2.2 List Comprehension 63 5.3 Functions as Objects 64 5.4 Strings, Tuples, and Lists 66 5.5 Dictionaries∴ ∴67 6 TESTING AND DEBUGGING 70 6.1 Testing… 70 6. 1. 1 Black-Box Testing...... ·看音,看垂垂 6.1.2 Glass- Box Testing……… 73 6.1.3 Conducting Tests 74 62 Debugging……… 7 6.2.1 Learning to Debug.……,,…,………………,78 6.2.2 Designing the Experiment ∴79 6.2.3 When the Going Gets Tough………… 6.2.4 And when you have found“The”Bug .82 7 EXCEPTIONS AND ASSERTIONS ·····.;··. ∴84 7.1 Handling Exceptions………………………84 7.2 Exceptions as a Control Flow Mechanism 7.3 Assertions 90 8 CLASSES AND OBJECT-ORIENTED PROGRAMMING 91 8.1 Abstract Data Types and Classes 91 8.1.1 Designing Programs Using Abstract Data Types 96 8.1.2 Using Classes to Keep Track of Students and Faculty 96 8.2 Inheritance 99 8.2.1 Multiple Levels of Inheritance……………………,101 8.2.2 The Substitution Principle…… 102 8.3 Encapsulation and Information Hiding 103 8.3.1 Generators∴ 106 8.4 Mortgages, an Extended Example…………,108 IX 9 A SIMPLISTIC INTRODUCTION TO ALGORITHMIC COMPLEXITY. ...........113 9.1 Thinking About Computational Complexity ..113 9.2 Asymptotic notation ··: 116 9.3 Some important Complexity Classes…… 118 9.3.1 Constant Complexity 118 9.3.2 Logarithmic Complexity 118 9.3.3 Linear complexity 119 9.3.4 Log-Linear Complexity ∴120 9.3.5 Polynomial complexity 120 9.3.6 Exponential Complexity 121 9.3.7 Comparisons of Complexity Classes. 123 10 SOME SIMPLE ALGORITHMS AND DATA STRUCTURES. .........,..............125 10. 1 Search algorithms 126 10.1.1 Linear Search and Using Indirection to Access Elements..... 126 10.1.2 Binary Search and Exploiting Assumptions 128 10.2 Sorting algorithms…………,,,…,, 131 10.2.1 Merge Sort 132 10.2.2 Exploiting Functions as Parameters ∴135 10.2.3 Sorting in Python 136 10.3 Hash Tables 137 11 PLOTTING AND MORE ABOUT CLASSES 141 11.1 Plotting Using Pylab 141 11.2 Plotting Mortgages, an Extended Example ..146 12 STOCHASTIC PROGRAMS. PROBABILITY AND STATISTICS 152 2.1 Stochastic Programs 153 12.2 Inferential statistics and simulation 155 12. 3 Distributions 166 12.3.1 Normal distributions and Confidence levels 168 12.3.2 Uniform Distributions 番,:垂音,D音着·音音( ∴170 12.3.3 Exponential and Geometric Distributions... l71 12. 3. 4 Benford's distribution ∴173 12. 4 How Often does the better Team win? 174 12.5 Hashing and collisions ∴.177 【实例截图】
【核心代码】
这个是MIT的edx中Introduction to Computer Science and Programming Using Python 计算机科学及python编程导论课程的的教材，这个是最新版本，我在网上找了三四天才找到的，是2013年8月份的，绿色封皮那个。
Introduction to Computation and Programming Using Python Revised and expanded edition John V Guttag The mit Press Cambridge, massachusetts London, England c 2013 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher. MIT Press books may be purchased at special quantity discounts for business or sales promotional use. For information, please email special_sales@mitpress mit edu or write to Special Sales department, The mit Press, 55 Hayward street Cam bridge, ma o2142 Printed and bound in the united states of america Library of Congress Cataloging-in-Publication Data Guttag, john Introduction to computation and programming using Python /John V Guttag Revised and expanded edition p ages cm Includes index isbn 978-0-262-52500-8(pbk: alk. paper) 1. Python(Computer program language) 2. Computer programming. I Title QA7673P48G882013 005.133-dc23 10987654321 To my family olga David Andrea Michae Mark Addie CONTENTS PREFACE X111 ACKNOWLEDGMENTS 1 GETTING STARTED 2 INTRODUCTION TO PYTHON 2.1 The Basic Elements of Python 1789 2.1.1 Objects, Expressions, and Numerical Types………… 2.1.2 Variables and Assignment 11 2.1 3 IDLE 13 2.2 Branching Programs...... 14 2.3 Strings and Input 16 2.3.1 Input.….,…,…,…,…,,…,…,……,……, 18 2.4 Iteration 18 3 SOME SIMPLE NUMERICAL PROGRAMS 21 3. 1 Exhaustive enumeration 21 3.2 For l 23 3.3 Approximate Solutions and Bisection Search 25 3. 4 A Few Words about Using Floats 29 3.5 Newton-Raphse 32 4 FUNCTIONS. SCOPING. and abstraction 34 4.1 Functions and Scoping 35 4. unction Definitions ............,.......................................................35 4.1.2 Keyword Arguments and Default values…… 36 4.1.3 Scoping pecifications 41 4.3 Recursion 44 43. 1 Fibonacci numbers 45 4.3.2 Palindromes 48 4.4 Global variables 50 4.5 Module 51 4.6 Files 53 5 STRUCTURED TYPES. MUTABILITY AND HIGHER-ORDER FUNCTIONS.56 5.1 Tuples.…… ∴56 5.1.1 Sequences and Multiple assignment..……… 57 5.2 Lists and Mutability 58 5.2.1 Cloning 63 5.2.2 List Comprehension 63 5.3 Functions as Objects 64 5.4 Strings, Tuples, and Lists 66 5.5 Dictionaries∴ ∴67 6 TESTING AND DEBUGGING 70 6.1 Testing… 70 6. 1. 1 Black-Box Testing...... ·看音,看垂垂 6.1.2 Glass- Box Testing……… 73 6.1.3 Conducting Tests 74 62 Debugging……… 7 6.2.1 Learning to Debug.……,,…,………………,78 6.2.2 Designing the Experiment ∴79 6.2.3 When the Going Gets Tough………… 6.2.4 And when you have found“The”Bug .82 7 EXCEPTIONS AND ASSERTIONS ·····.;··. ∴84 7.1 Handling Exceptions………………………84 7.2 Exceptions as a Control Flow Mechanism 7.3 Assertions 90 8 CLASSES AND OBJECT-ORIENTED PROGRAMMING 91 8.1 Abstract Data Types and Classes 91 8.1.1 Designing Programs Using Abstract Data Types 96 8.1.2 Using Classes to Keep Track of Students and Faculty 96 8.2 Inheritance 99 8.2.1 Multiple Levels of Inheritance……………………,101 8.2.2 The Substitution Principle…… 102 8.3 Encapsulation and Information Hiding 103 8.3.1 Generators∴ 106 8.4 Mortgages, an Extended Example…………,108 IX 9 A SIMPLISTIC INTRODUCTION TO ALGORITHMIC COMPLEXITY. ...........113 9.1 Thinking About Computational Complexity ..113 9.2 Asymptotic notation ··: 116 9.3 Some important Complexity Classes…… 118 9.3.1 Constant Complexity 118 9.3.2 Logarithmic Complexity 118 9.3.3 Linear complexity 119 9.3.4 Log-Linear Complexity ∴120 9.3.5 Polynomial complexity 120 9.3.6 Exponential Complexity 121 9.3.7 Comparisons of Complexity Classes. 123 10 SOME SIMPLE ALGORITHMS AND DATA STRUCTURES. .........,..............125 10. 1 Search algorithms 126 10.1.1 Linear Search and Using Indirection to Access Elements..... 126 10.1.2 Binary Search and Exploiting Assumptions 128 10.2 Sorting algorithms…………,,,…,, 131 10.2.1 Merge Sort 132 10.2.2 Exploiting Functions as Parameters ∴135 10.2.3 Sorting in Python 136 10.3 Hash Tables 137 11 PLOTTING AND MORE ABOUT CLASSES 141 11.1 Plotting Using Pylab 141 11.2 Plotting Mortgages, an Extended Example ..146 12 STOCHASTIC PROGRAMS. PROBABILITY AND STATISTICS 152 2.1 Stochastic Programs 153 12.2 Inferential statistics and simulation 155 12. 3 Distributions 166 12.3.1 Normal distributions and Confidence levels 168 12.3.2 Uniform Distributions 番,:垂音,D音着·音音( ∴170 12.3.3 Exponential and Geometric Distributions... l71 12. 3. 4 Benford's distribution ∴173 12. 4 How Often does the better Team win? 174 12.5 Hashing and collisions ∴.177 【实例截图】
【核心代码】
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