How to Think Like a Computer Scientist — How to Think Like ...

How to Think Like a Computer Scientist -- How to Think Like a Computer Scientist: Learning with Python 3

How to Think Like a Computer Scientist: Learning with Python 3 ?

How to Think Like a Computer Scientist

next | index

Learning with Python 3 (RLE)

Version date: November 2011

by Peter Wentworth, Jeffrey Elkner, Allen B. Downey, and Chris Meyers

(based on 2nd edition by Jeffrey Elkner, Allen B. Downey, and Chris Meyers)

Corresponding author: p.wentworth@ru.ac.za

Source for this RLE version:

Search Page Copyright Notice Foreword Preface Preface-3 This Rhodes Local Edition (RLE) of the book Contributor List Chapter 1 The way of the program Chapter 2 Variables, expressions, and statements Chapter 3 Hello, little turtles! Chapter 4 Functions Chapter 5 Conditionals Chapter 6 Fruitful functions Chapter 7 Iteration Chapter 8 Strings Chapter 9 Tuples Chapter 10 Event handling Chapter 11 Lists Chapter 12 Modules Chapter 13 Files Chapter 14 List Algorithms Chapter 15 Classes and Objects - the Basics Chapter 16 Classes and Objects - Digging a little deeper Chapter 17 PyGame

[1/4/2012 9:36:22 PM]

How to Think Like a Computer Scientist -- How to Think Like a Computer Scientist: Learning with Python 3

Chapter 18 Recursion Chapter 19 Exceptions Chapter 20 Dictionaries Chapter 21 Even more OOP Chapter 22 Collections of Objects Chapter 23 Inheritance Chapter 24 Linked Lists Chapter 25 Stacks Chapter 26 Queues Chapter 27 Trees Appendix A Debugging Appendix B An odds-and-ends Workbook Appendix C Configuring Ubuntu for Python Development Appendix D Customizing and Contributing to the Book Appendix E Some Tips, Tricks, and Common Errors GNU Free Document License

Search Page

How to Think Like a Computer Scientist: Learning with Python 3 ?

next | index

? Copyright 2011, Peter Wentworth, Jeffrey Elkner, Allen B. Downey and Chris Meyers. Created using Sphinx 1.0.7.

[1/4/2012 9:36:22 PM]

Index -- How to Think Like a Computer Scientist: Learning with Python 3

How to Think Like a Computer Scientist: Learning with Python 3 ?

Index

Symbols | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W

Symbols

3n + 1 sequence

A

abbreviated assignment abecedarian series abstract data type (ADT) accumulator algorithm, [1], [2], [3]

deterministic aliases, [1], [2] alternative execution ambiguity

B

baked animation bar chart base case, [1] binary operator binary search binary tree bind blit block, [1] body, [1], [2], [3]

C

call graph canvas, [1] cargo chained conditional, [1] character chatterbox function child child class chunking, [1] class, [1] class attribute client

animation rate argument, [1] argv assignment, [1]

tuple assignment statement, [1], [2] assignment token attribute, [1], [2], [3], [4], [5]

boolean expression, [1] boolean function, [1] boolean value, [1] branch, [1] break statement breakpoint bug, [1] builtin scope bump bytecode

composition, [1], [2] (of functions)

composition of functions compound data type, [1], [2] compound statement, [1]

body header computation pattern concatenate concatenation, [1] condition, [1] conditional

[1/4/2012 9:36:26 PM]

index

Index -- How to Think Like a Computer Scientist: Learning with Python 3

clone, [1] collection, [1] command line command line argument command prompt comment, [1] comments comparison of strings comparison operator, [1] compile, [1]

D

data structure, [1] recursive

data type, [1] dead code, [1] debugging, [1], [2] decrement deep copy deep equality, [1] default value, [1] definite iteration definition

function, [1] recursive del statement, [1]

E

element, [1], [2] elif else embedded reference encapsulate encapsulation encode enumerate

chained conditional branching conditional execution conditional statement, [1] conditionals

nested constant time constructor continue statement, [1] control flow, [1] copy

deep shallow counter counting pattern cursor, [1]

delimiter, [1], [2] deterministic algorithm development plan, [1] dictionary, [1] dir function directory, [1] docstring, [1], [2] dot notation, [1] dot operator, [1] dot product Doyle, Arthur Conan

equality deep shallow

escape sequence, [1] eureka traversal evaluate event, [1] exception, [1], [2], [3]

handling executable expression, [1], [2]

boolean

[1/4/2012 9:36:26 PM]

Index -- How to Think Like a Computer Scientist: Learning with Python 3

F

fibonacci numbers field width FIFO file, [1]

text file handle file system float, [1], [2] flow of execution, [1], [2] for loop, [1], [2], [3], [4], [5] for loop traversal (for) formal language, [1] formatting

strings

G

game loop, [1] generalization, [1] generalize

H

hand trace handle, [1] handle an exception handler, [1] handling an exception

I

if if statement immediate mode immutable, [1], [2], [3] immutable data type, [1] implementation import statement, [1], [2], [3], [4] in and not in operator (in, not in) in operator increment incremental development, [1] indefinite iteration

fractal Cesaro torn square Sierpinski triangle

frame frame rate fruitful function, [1] fully qualified name function, [1], [2], [3]

argument composition len parameter pure function call function composition, [1] function definition, [1], [2] function type functional programming style fundamental ambiguity theorem

generic data structure global scope

header line help helper high-level language, [1] Holmes, Sherlock

initialization (of a variable) initializer method input input dialog instance, [1], [2] instantiate int, [1], [2] integer integer division, [1] Intel interface interpret, [1]

[1/4/2012 9:36:26 PM]

 ................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download