python零基础进阶较为全面的python教程，零基础小白进阶，基础操作知识出发学习python。

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详细说明：较为全面的python教程，零基础小白进阶，基础操作知识出发学习python。Preface Remixing an Open Book It is quite natural for academics who are continuously told to "publish or perish to want to always create something from scratch that is their own fresh creation This book is an experiment in not starting from scratch, but instead"remixin the book titled Think Python: How to Think like a Computer Scientist written by Allen B. Downey, Jeff Elkner, and others In December of 2009, I was preparing to teach $1502- Networked Programming at the University of Michigan for the fifth semester in a row and decided it was time to write a Python textbook that focused on exploring data instead of understanding algorithms and abstractions. My goal in $I502 is to teach people lifelong data handling skills using Python. Few of my students were planning to be professional computer programmers. Instead, they planned to be librarians, managers, lawyers biologists, economists, etc, who happened to want to skillfully use technology in their chosen field never seemed to find the perfect data-oriented Python book for my course, so I set out to write just such a book. Luckily at a faculty meeting three weeks before I was about to start my new book from scratch over the holiday break, Dr. Atul Prakash showed me the Think Python book which he had used to teach his Python course that semester. It is a well-written Computer Science text with a focus on short, direct explanations and ease of learning The overall book structure has been changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis from the very beginning Chapters 2-10 are similar to the Think Python book, but there have been major changes. Number-oriented examples and exercises have been replaced with data oriented exercises. Topics are presented in the order needed to build increasingl sophisticated data analysis solutions. Some topics like try and except are pulled forward and presented as part of the chapter on conditionals. Functions are given very light treatment until they are needed to handle program complexity rather than introduced as an early lesson in abstraction. Nearly all user-defined functions have been removed from the example code and exercises outside of Chapter 4. The word "recursion, does not appear in the book at all In chapters 1 and 11-16, all of the material is brand new, focusing on real-world uses and simple examples of Python for data analysis including regular expressions for searching and parsing, automating tasks on your computer, retrieving data across the network, scraping web pages for data, object-oriented programming using web services, parsing XML and json data, creating and using databases using Structured Query Language, and visualizing data The ultimate goal of all of these changes is to shift from a Computer Science to an Informatics focus and to only include topics into a first technology class that can be useful even if one chooses not to become a professional programmer Except, of course, for this line Students who find this book interesting and want to further explore should look at Allen B. Downey's Think Python book. Because there is a lot of overlap be- tween the two books, students will quickly pick up skills in the additional areas of technical programming and algorithmic thinking that are covered in Think python And given that the books have a similar writing style, they should be able to move quickly through Think Python with a minimum of effort As the copyright holder of Think Python, Allen has given me permission to change the book's license on the material from his book that remains in this book from the GNU Free Documentation License to the more recent Creative Commons Attribu tion- Share Alike license. This follows a general shift in open documentation licenses moving from the GFDl to the CC-BY-SA(. g, Wikipedia). US SIn CC-BY-SA license maintains the book's strong copyleft tradition while making it even more straightforward for new authors to reuse this material as they see fit I feel that this book serves as an example of why open materials are so important to the future of education, and i want to thank Allen B. Downey and Cambridge University Press for their forward-looking decision to make the book available under an open copyright. I hope they are pleased with the results of my efforts and I hope that you, the reader, are pleased with our collective efforts I would like to thank Allen B. Downey and Lauren Cowles for their help, patience and guidance in dealing with and resolving the copyright issues around this book Charles severance www.dr-chuck.com Ann arbor. MI. USa September 9, 2013 Charles Severance is a Clinical Associate Professor at the University of michigan School of Information Contents 1 Why should you learn to write programs? 1.1 Creativity and motivation 1.2 Computer hardware architecture 1.3 Understanding programming 1.4 Words and sentences 1.5 Conversing with Python 1.6 Terminology: interpreter and compiler 1.7 Writing a program 10 1. 8 What is a program 1. 9 The building blocks of programs 1.10 What could possibly go wrong? 12 1.11 Debugging 1.12 The learning journey 1.13 Glossary 15 1.14 Exercises 2 Variables, expressions, and statements 19 2.1 Values and types 19 2.2 Variables 20 2.3 Variable names and keywords 21 2.4 Statements 21 2.5 Operators and operands 22 2.6 Expressions 23 2.7 Order of operations 23 2.8 Modulus operator 24 2.9 String operations 24 CONTENTS 2.10 Asking the user for input 25 2.11 Comments 26 2.12 Choosing mnemonic variable names 27 2. 13 Debugging 2.14 Glossary 2.15 Exercises 30 3 Conditional execution 31 3.1 Boolean expressions 3.2 Logical operators 32 3.3 Conditional execution 32 3.4 Alternative execution 33 3.5 Chained conditionals 34 3.6 Nested conditionals 35 3.7 Catching exceptions using try and except 36 3.8 Short-circuit evaluation of logical expressions 3.9 Debugging 39 3.10 Glossary 39 3.11 Exercises 4 Functions 43 4.1 Function calls 43 4.2 Built-in functions 43 4.3 Type conversion functions 44 4.4 Math functions 4. Random numbers 46 4.6 Adding new functions 47 4.7 Definitions and uses 48 4.8 Flow of execution 49 4.9 Parameters and arguments 49 4.10 Fruitful functions and void functions 4.11 Why functions? 52 4.12D Debugging 52 4.13 Glossary 53 4.14 Exercises 54 CONTENTS 5 Iteration 57 5.1 Updating variable 57 5.2 The while statement 57 5.3 Infinite lo 58 Infinite lo d break 5.5 Finishing iterations with continue 59 5.6 Definite loops using for 5.7 Loop patterns 61 5.7.1 Counting and g loop 5.7.2 Maximum and minimum loops 62 58 Debugging 64 5.9 Glo ssary 64 5.10 Exercises 64 6 Strings 67 6.1 A string is a sequence 6.2 Getting the length of a string using len 6.3 Traversal through a string with a loop 6.4 String slices 6.5 Strings are immutable 70 6.6 Looping and counting 70 6.7 The in operator 6. 8 String comparison 6.9 string methods 6.10 Parsing strings 74 6.11 Format operator 74 6.12 Debugging 75 6.13 Glossary 76 6.14 Exercises 77 7 Files 79 7.1 Persistence 79 7. 2 Opening files 7. 3 Text files and lines 7.4 Reading files CONTENTS 7.5 Searching through a file 83 7.6 Letting the user choose the file name 7.7 Using try, except, and open 86 7.8 Writing files 87 7.9 Debugging 7.10 Glossary 7.11 Exercises 8 Lists 91 8.1 A list is a sequence 2 Lists are mutable 92 8.3 Traversing a list 92 4 List operations 93 List slices 8.6 List methods 94 8.7 Deleting elements 8. 8 Lists and functions 96 8.9 Lists and strings 97 8.10 Parsing lines 98 8.11 Objects and values 99 8.12 Aliasing 100 8.13 List arguments 8.14 Debugging 102 8.15 losser 8.16 Exercises 105 9 Dictionaries 107 9.1 Dictionary as a set of counters ..109 9.2 Dictionaries and files 110 9.3 Looping and dictionaries .,,111 9.4 Advanced text parsing 113 9.5 Debugging 114 9.6 Glossary 115 9. 7 Exercises 115 CONTENTS 10 Tuples 117 10.1 Tuples are immutable 10.2 Comparing tuples 118 10.3 Tuple assignment 120 10.4 Dictionaries and tuples 121 10.5 Multiple assignment with dictionaries 122 10.6 The most common words 123 10.7 USing tuples as keys in dictionaries 124 10.8 Sequences: strings, lists, and tuples -Oh My! 124 10.9 Debugging 125 10.10 Glossary 125 10.11 Exercises 126 1 Regular expressions 127 11.1 Character matching in regular expressions 128 11.2 Extracting data using regular expressions 129 11.3 Combining searching and extracting 132 11.4 Escape character 136 11.5 Summary 136 11.6 Bonus section for Unix/ Linux users .137 11. 7 Debugging 138 11.8 Glossary 138 11.9 Exercises 139 12 Networked programs 141 12.1HypertextTransferProtocol-http 141 12.2 The World's Simplest Web Browser .142 12.3 reTrieving an image over Http 144 12. 4 Retrieving web pages with urllib 146 12.5 Reading binary files using urllib 147 12.6 Parsing HTML and scraping the web 148 12.7 Parsing HTML using regular expressions 148 12.8 Parsing HTML using BeautifulSoup 150 12.9 Bonus section for Unix/Linux users 153 12.10 Glossary 153 12.11 Exercises 154 CONTENTS 13 USing Web services 155 13.1 eXtensible Markup Language-XML 155 13.2 Parsing XML 156 13.3 Looping through nodes 157 13.4 JavaScript Object Notation - JSON 158 13.5 Parsing JSON 158 13.6 Application Programming Interfaces 159 13.7 Google geocoding web service 161 13.8 Security and API usage 163 13.9 Glossary 168 13.10 Exercises 168 14 Object-Oriented Programming 169 naging larger programs 169 4.2 Getting Sta 170 14.3 USing Objects 170 14.4 Starting with Programs 171 14.5 Subdividing a Problem- Encapsulation 173 14.6 Our First Python Object 174 14.7Cl 176 14.8 Object Lifecycle 177 14.9 Many Instances 178 L4.10 Inheritance 179 14.11 Summary 180 14.12 Glossary 181 15 Using Databases and SQL 183 15.1 What is a database? 183 15.2 Database concepts 183 15.3 Database Browser for SQLite 184 15.4 Creating a database table 184 15.5 Structured Query Language summary ..187 15.6 Spidering Twitter using a database 189 15.7 Basic data modeling 194 15.8 Programming with multiple tables 195

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