Python Projects

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A guide to completing Python projects for those ready to take their skills to the next level Python Projects is the ultimate resource for the Python programmer with basic skills who is ready to move beyond tutorials and start building projects. The preeminent guide to bridge the gap between learning and doing, this book walks readers through the "where" and "how" of real-world Python programming with practical, actionable instruction. With a focus on real-world functionality, Python Projects details the ways that Python can be used to complete daily tasks and bring efficiency to businesses and individuals alike. Python Projects is written specifically for those who know the Python syntax and lay of the land, but may still be intimidated by larger, more complex projects. The book provides a walk-through of the basic set-up for an application and the building and packaging for a library, and explains in detail the functionalities related to the projects. Topics include: *How to maximize the power of the standard library modules *Where to get third party libraries, and the best practices for utilization *Creating, packaging, and reusing libraries within and across projects *Building multi-layered functionality including networks, data, and user interfaces *Setting up development environments and using virtualenv, pip, and more Written by veteran Python trainers, the book is structured for easy navigation and logical progression that makes it ideal for individual, classroom, or corporate training. For Python developers looking to apply their skills to real-world challenges, Python Projects is a goldmine of information and expert insight.

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InhaltsangabeINTRODUCTION xxv CHAPTER 1: REVIEWING CORE PYTHON 1 Exploring the Python Language and the Interpreter 2 Reviewing the Python Data Types 3 Numeric Types: Integer and Float 4 The Boolean Type 5 The None Type 6 Collection Types 6 Strings 7 Bytes and ByteArrays 8 Tuples 10 Lists 10 Dictionaries 12 Sets 13 Using Python Control Structures 15 Structuring Your Program 15 Using Sequences, Blocks and Comments 16 Selecting an Execution Path 17 Iteration 18 Handling Exceptions 20 Managing Context 21 Getting Data In and Out of Python 21 Interacting with Users 21 Using Text Files 23 Extending Python 24 Defining and Using Functions 24 Generator Functions 26 Lambda Functions 27 Defining and Using Classes and Objects 28 Creating and Using Modules and Packages 33 Using and Creating Modules 33 Using and Creating Packages 34 Creating an Example Package 36 Using Third?]Party Packages 42 Summary 43 CHAPTER 2: SCRIPTING WITH PYTHON 47 Accessing the Operating System 48 Obtaining Information About Users and Their Computer 49 Obtaining Information About the Current Process 53 Managing Other Programs 55 Managing Subprocesses More Effectively 58 Obtaining Information About Files (and Devices) 60 Navigating and Manipulating the File system 62 Plumbing the Directory Tree Depths 69 Working with Dates and Times 72 Using the time Module 72 Introducing the datetime Module 75 Introducing the calendar Module 76 Handling Common File Formats 76 Using Comma?]Separated Values 76 Working with Confi g Files 83 Working with XML and HTML Files 86 Parsing XML Files 86 Parsing HTML Files 89 Accessing Native APIs with ctypes and pywin32 93 Accessing the Operating System Libraries 94 Using ctypes with Windows 95 Using ctypes on Linux 96 Accessing a Windows Application Using COM 96 Automating Tasks Involving Multiple Applications 98 Using Python First 98 Using Operating System Utilities 98 Using Data Files 98 Using a Third?]Party Module 99 Interacting with Subprocesses via a CLI 99 Using Web Services for Server?]Based Applications 99 Using a Native Code API 100 Using GUI Robotics 100 Summary 100 CHAPTER 3: MANAGING DATA 103 Storing Data Using Python 104 Using DBM as a Persistent Dictionary 104 Using Pickle to Store and Retrieve Objects 109 Accessing Objects with shelve 111 Analyzing Data with Python 116 Analyzing Data Using Built?]In Features of Python 116 Analyzing Data with ittertools 119 Utility Functions 119 Data Processing Functions 121 Taming the Vagaries of groupby() 122 Using itertools to Analyze LendyDB Data 124 Managing Data Using SQL 125 Relational Database Concepts 126 Structured Query Language 127 Creating Tables 128 Inserting Data 129 Reading Data 130 Modifying Data 133 Linking Data Across Tables 134 Digging Deeper into Data Constraints 134 Revisiting SQLite Field Types 135 Modeling Relationships with Constraints 136 Many?]to?]Many Relationships 140 Migrating LendyDB to an SQL Database 143 Accessing SQL from Python 143 Using SQL Connections 143 Using a Cursor 143 Creating the LendyDB SQL Database 145 Inserting Test Data 146 Creating a LendyDB API 148 Exploring Other Data Management Options 154 Client?]Server Databases 154 NoSQL 155 The Cloud 155 Data Analysis with RPy 156 Summary 157 CHAPTER 4: BUILDING DESKTOP APPLICATIONS 161 Structuring Applications 162 Building Command-Line Interfaces 164 Building the Data Layer 164 Building the Core Logic Layer 165 Building the User Interface 169 Using the cmd Module to Build a Command-Line Interface 173 Reading Command-Line Arguments 175 Jazzing Up the Command-Line Interface with Some Dialogs 177 Programming GUIs with Tkinter 181 Introducing Key GUI Principles 181 Event?]Based

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