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11 INTRODUCTION 12 PARALLEL PROGRAMMING 13 DESIGN PATTERNS AND PATTERN LANGUAGES 14 A PATTERN LANGUAGE FOR PARALLEL PROGRAMMING

List of Tables Introduction 1 Rapid Introduction to Procedural Programming Creating and Running Python Programs Python s Beautiful Heart Piece #1: Data Types Piece #2: Object References Piece #3: Collection Data Types Piece #4: Logical Operations Piece #5: Control Flow Statements Piece #6: Arithmetic Operators Piece #7: Input/Output Piece #8: Creating and Calling Functions Examples bigdigitspy generate_gridpy Summary Exercises 2 Data Types Identi ers and Keywords Integral Types Integers Booleans Floating-Point Types Floating-Point Numbers Complex Numbers Decimal Numbers Strings Comparing Strings Slicing and Striding Strings String Operators and Methods ix xv 1 9 9 14 14 16 18 21 26 30 33 36 39 39 42 44 47 51 51 54 54 58 58 59 62 63 65 68 69 71

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String Formatting with the strformat() Method Character Encodings Examples quadraticpy csv2htmlpy Summary Exercises 3 Collection Data Types Sequence Types Tuples Named Tuples Lists Set Types Sets Frozen Sets Mapping Types Dictionaries Default Dictionaries Ordered Dictionaries Iterating and Copying Collections Iterators and Iterable Operations and Functions Copying Collections Examples generate_usernamespy statisticspy Summary Exercises 4 Control Structures and Functions Control Structures Conditional Branching Looping Exception Handling Catching and Raising Exceptions Custom Exceptions Custom Functions Names and Docstrings Argument and Parameter Unpacking x

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Computers are used to model physical systems in many fields of science, medicine, and engineering Modelers, whether trying to predict the weather or render a scene in the next blockbuster movie, can usually use whatever computing power is available to make ever more detailed simulations Vast amounts of data, whether customer shopping patterns, telemetry data from space, or DNA sequences, require analysis To deliver the required power, computer designers combine multiple processing elements into a single larger system These so called parallel computers run multiple tasks simultaneously and solve bigger problems in less time Traditionally, parallel computers were rare and available for only the most critical problems Since the mid 1990s, however, the availability of parallel computers has changed dramatically With multithreading support built into the latest microprocessors and the emergence of multiple processor cores on a single silicon die, parallel computers are becoming ubiquitous Now, almost every university computer science department has at least one parallel computer Virtually all oil companies, automobile manufacturers, drug development companies, and special effects studios use parallel computing For example, in computer animation, rendering is the step where information from the animation files, such as lighting, textures, and shading, is applied to 3D models to generate the 2D image that makes up a frame of the film Parallel computing is essential to generate the needed number of frames (24 per second) for a feature length film Toy Story, the first completely computer generated feature length film, released by Pixar in 1995, was processed on a "renderfarm" consisting of 100 dual

Accessing Variables in the Global Scope Lambda Functions Assertions Example: make_html_skeletonpy Summary Exercise 5 Modules Modules and Packages Packages Custom Modules Overview of Python s Standard Library String Handling Command-Line Programming Mathematics and Numbers Times and Dates Algorithms and Collection Data Types File Formats, Encodings, and Data Persistence File, Directory, and Process Handling Networking and Internet Programming XML Other Modules Summary Exercise 6 Object-Oriented Programming The Object-Oriented Approach Object-Oriented Concepts and Terminology Custom Classes Attributes and Methods Inheritance and Polymorphism Using Properties to Control Attribute Access Creating Complete Fully Integrated Data Types Custom Collection Classes Creating Classes That Aggregate Collections Creating Collection Classes Using Aggregation Creating Collection Classes Using Inheritance Summary Exercises xi

Databases 4 Relational Database Management Systems 5 Why a Sound Data Model Is Important 6 Data Consistency 6 Scalability 8 Meeting Business Requirements 10 Easy Data Retrieval 10 Performance Tuning 13 The Process of Data Modeling 14 Modeling Theory 15 Business Requirements 16 Building the Logical Model 18 Building the Physical Model 19 Summary 21

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