Python 3 object-oriented programming :: unleash the power of Python 3 objects /
Python 3 is more versatile and easier to use than ever. It runs on all major platforms in a huge array of use cases. Coding in Python minimizes development time and increases productivity in comparison to other languages. Clean, maintainable code is easy to both read and write using Python's cl...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham :
Packt Publishing,
2015.
|
| Ausgabe: | Second edition. |
| Schriftenreihe: | Community experience distilled.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Python 3 is more versatile and easier to use than ever. It runs on all major platforms in a huge array of use cases. Coding in Python minimizes development time and increases productivity in comparison to other languages. Clean, maintainable code is easy to both read and write using Python's clear, concise syntax. Object-oriented programming is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Many modern programming languages utilize the powerful concepts behind object-oriented programming and Python is no exception. Starting with a detailed analysis of object-oriented analysis and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This book fully explains classes, data encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on when you can use each principle to develop well-designed software. |
| Beschreibung: | Includes index. |
| Beschreibung: | 1 online resource : illustrations |
| ISBN: | 9781784395957 1784395951 |
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| 505 | 8 | |a More argumentsInitializing the object; Explaining yourself; Modules and packages; Organizing the modules; Absolute imports; Relative imports; Organizing module contents; Who can access my data?; Third-party libraries; Case study; Exercises; Summary; Chapter 3: When Objects Are Alike; Basic inheritance; Extending built-ins; Overriding and super; Multiple inheritance; The diamond problem; Different sets of arguments; Polymorphism; Abstract base classes; Using an abstract base class; Creating an abstract base class; Demystifying the magic; Case study; Exercises; Summary. | |
| 505 | 8 | |a Chapter 4: Expecting the UnexpectedRaising exceptions; Raising an exception; The effects of an exception; Handling exceptions; The Exception hierarchy; Defining our own exceptions; Case study; Exercises; Summary; Chapter 5: When to Use Object-oriented Programming; Treat objects as objects; Adding behavior to class data with properties; Properties in detail; Decorators -- another way to create properties; Deciding when to use properties; Manager objects; Removing duplicate code; In practice; Case study; Exercises; Summary; Chapter 6: Python Data Structures; Empty objects. | |
| 505 | 8 | |a Tuples and named tuplesNamed tuples; Dictionaries; Dictionary use cases; Using defaultdict; Counter; Lists; Sorting lists; Sets; Extending built-ins; Queues; FIFO queues; LIFO queues; Priority queues; Case study; Exercises; Summary; Chapter 7: Python Object-oriented Shortcuts; Python built-in functions; The len() function; Reversed; Enumerate; File I/O; Placing it in context; An alternative to method overloading; Default arguments; Variable argument lists; Unpacking arguments; Functions are objects too; Using functions as attributes; Callable objects; Case study; Exercises; Summary. | |
| 505 | 8 | |a Chapter 8: Strings and SerializationStrings; String manipulation; String formatting; Escaping braces; Keyword arguments; Container lookups; Object lookups; Making it look right; Strings are Unicode; Converting bytes to text; Converting text to bytes; Mutable byte strings; Regular expressions; Matching patterns; Matching a selection of characters; Escaping characters; Matching multiple characters; Grouping patterns together; Getting information from regular expressions; Making repeated regular expressions efficient; Serializing objects; Customizing pickles; Serializing web objects; Case study. | |
| 520 | |a Python 3 is more versatile and easier to use than ever. It runs on all major platforms in a huge array of use cases. Coding in Python minimizes development time and increases productivity in comparison to other languages. Clean, maintainable code is easy to both read and write using Python's clear, concise syntax. Object-oriented programming is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Many modern programming languages utilize the powerful concepts behind object-oriented programming and Python is no exception. Starting with a detailed analysis of object-oriented analysis and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This book fully explains classes, data encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on when you can use each principle to develop well-designed software. | ||
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| contents | Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Introduction tothe second edition; Table of Contents; Preface; Chapter 1: Object-oriented Design; Introducing object-oriented; Objects and classes; Specifying attributes and behaviors; Data describes objects; Behaviors are actions; Hiding details and creating the public interface; Composition; Inheritance; Inheritance provides abstraction; Multiple inheritance; Case study; Exercises; Summary; Chapter 2: Objects in Python; Creating Python classes; Adding attributes; Making it do something; Talking to yourself. More argumentsInitializing the object; Explaining yourself; Modules and packages; Organizing the modules; Absolute imports; Relative imports; Organizing module contents; Who can access my data?; Third-party libraries; Case study; Exercises; Summary; Chapter 3: When Objects Are Alike; Basic inheritance; Extending built-ins; Overriding and super; Multiple inheritance; The diamond problem; Different sets of arguments; Polymorphism; Abstract base classes; Using an abstract base class; Creating an abstract base class; Demystifying the magic; Case study; Exercises; Summary. Chapter 4: Expecting the UnexpectedRaising exceptions; Raising an exception; The effects of an exception; Handling exceptions; The Exception hierarchy; Defining our own exceptions; Case study; Exercises; Summary; Chapter 5: When to Use Object-oriented Programming; Treat objects as objects; Adding behavior to class data with properties; Properties in detail; Decorators -- another way to create properties; Deciding when to use properties; Manager objects; Removing duplicate code; In practice; Case study; Exercises; Summary; Chapter 6: Python Data Structures; Empty objects. Tuples and named tuplesNamed tuples; Dictionaries; Dictionary use cases; Using defaultdict; Counter; Lists; Sorting lists; Sets; Extending built-ins; Queues; FIFO queues; LIFO queues; Priority queues; Case study; Exercises; Summary; Chapter 7: Python Object-oriented Shortcuts; Python built-in functions; The len() function; Reversed; Enumerate; File I/O; Placing it in context; An alternative to method overloading; Default arguments; Variable argument lists; Unpacking arguments; Functions are objects too; Using functions as attributes; Callable objects; Case study; Exercises; Summary. Chapter 8: Strings and SerializationStrings; String manipulation; String formatting; Escaping braces; Keyword arguments; Container lookups; Object lookups; Making it look right; Strings are Unicode; Converting bytes to text; Converting text to bytes; Mutable byte strings; Regular expressions; Matching patterns; Matching a selection of characters; Escaping characters; Matching multiple characters; Grouping patterns together; Getting information from regular expressions; Making repeated regular expressions efficient; Serializing objects; Customizing pickles; Serializing web objects; Case study. |
| ctrlnum | (OCoLC)922580702 |
| dewey-full | 005.1/17 |
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| dewey-ones | 005 - Computer programming, programs, data, security |
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| dewey-sort | 15.1 217 |
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| discipline | Informatik |
| edition | Second edition. |
| format | Electronic eBook |
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| series | Community experience distilled. |
| series2 | Community experience distilled |
| spelling | Phillips, Dusty, author. http://id.loc.gov/authorities/names/no2014131244 Python 3 object-oriented programming : unleash the power of Python 3 objects / Dusty Phillips. Second edition. Birmingham : Packt Publishing, 2015. 1 online resource : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier text file Community experience distilled Online resource; title from PDF title page (EBSCO, viewed December 21, 2015). Includes index. Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Introduction tothe second edition; Table of Contents; Preface; Chapter 1: Object-oriented Design; Introducing object-oriented; Objects and classes; Specifying attributes and behaviors; Data describes objects; Behaviors are actions; Hiding details and creating the public interface; Composition; Inheritance; Inheritance provides abstraction; Multiple inheritance; Case study; Exercises; Summary; Chapter 2: Objects in Python; Creating Python classes; Adding attributes; Making it do something; Talking to yourself. More argumentsInitializing the object; Explaining yourself; Modules and packages; Organizing the modules; Absolute imports; Relative imports; Organizing module contents; Who can access my data?; Third-party libraries; Case study; Exercises; Summary; Chapter 3: When Objects Are Alike; Basic inheritance; Extending built-ins; Overriding and super; Multiple inheritance; The diamond problem; Different sets of arguments; Polymorphism; Abstract base classes; Using an abstract base class; Creating an abstract base class; Demystifying the magic; Case study; Exercises; Summary. Chapter 4: Expecting the UnexpectedRaising exceptions; Raising an exception; The effects of an exception; Handling exceptions; The Exception hierarchy; Defining our own exceptions; Case study; Exercises; Summary; Chapter 5: When to Use Object-oriented Programming; Treat objects as objects; Adding behavior to class data with properties; Properties in detail; Decorators -- another way to create properties; Deciding when to use properties; Manager objects; Removing duplicate code; In practice; Case study; Exercises; Summary; Chapter 6: Python Data Structures; Empty objects. Tuples and named tuplesNamed tuples; Dictionaries; Dictionary use cases; Using defaultdict; Counter; Lists; Sorting lists; Sets; Extending built-ins; Queues; FIFO queues; LIFO queues; Priority queues; Case study; Exercises; Summary; Chapter 7: Python Object-oriented Shortcuts; Python built-in functions; The len() function; Reversed; Enumerate; File I/O; Placing it in context; An alternative to method overloading; Default arguments; Variable argument lists; Unpacking arguments; Functions are objects too; Using functions as attributes; Callable objects; Case study; Exercises; Summary. Chapter 8: Strings and SerializationStrings; String manipulation; String formatting; Escaping braces; Keyword arguments; Container lookups; Object lookups; Making it look right; Strings are Unicode; Converting bytes to text; Converting text to bytes; Mutable byte strings; Regular expressions; Matching patterns; Matching a selection of characters; Escaping characters; Matching multiple characters; Grouping patterns together; Getting information from regular expressions; Making repeated regular expressions efficient; Serializing objects; Customizing pickles; Serializing web objects; Case study. Python 3 is more versatile and easier to use than ever. It runs on all major platforms in a huge array of use cases. Coding in Python minimizes development time and increases productivity in comparison to other languages. Clean, maintainable code is easy to both read and write using Python's clear, concise syntax. Object-oriented programming is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Many modern programming languages utilize the powerful concepts behind object-oriented programming and Python is no exception. Starting with a detailed analysis of object-oriented analysis and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This book fully explains classes, data encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on when you can use each principle to develop well-designed software. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Object-oriented programming (Computer science) http://id.loc.gov/authorities/subjects/sh87007503 Python (Langage de programmation) Programmation orientée objet (Informatique) COMPUTERS Programming Languages Python. bisacsh Object-oriented programming (Computer science) fast Python (Computer program language) fast Print version: Phillips, Dusty. Python 3 Object-oriented Programming. Olton Birmingham : Packt Publishing Ltd, ©2015 9781784398781 Community experience distilled. http://id.loc.gov/authorities/names/no2011030603 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1055466 Volltext |
| spellingShingle | Phillips, Dusty Python 3 object-oriented programming : unleash the power of Python 3 objects / Community experience distilled. Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Introduction tothe second edition; Table of Contents; Preface; Chapter 1: Object-oriented Design; Introducing object-oriented; Objects and classes; Specifying attributes and behaviors; Data describes objects; Behaviors are actions; Hiding details and creating the public interface; Composition; Inheritance; Inheritance provides abstraction; Multiple inheritance; Case study; Exercises; Summary; Chapter 2: Objects in Python; Creating Python classes; Adding attributes; Making it do something; Talking to yourself. More argumentsInitializing the object; Explaining yourself; Modules and packages; Organizing the modules; Absolute imports; Relative imports; Organizing module contents; Who can access my data?; Third-party libraries; Case study; Exercises; Summary; Chapter 3: When Objects Are Alike; Basic inheritance; Extending built-ins; Overriding and super; Multiple inheritance; The diamond problem; Different sets of arguments; Polymorphism; Abstract base classes; Using an abstract base class; Creating an abstract base class; Demystifying the magic; Case study; Exercises; Summary. Chapter 4: Expecting the UnexpectedRaising exceptions; Raising an exception; The effects of an exception; Handling exceptions; The Exception hierarchy; Defining our own exceptions; Case study; Exercises; Summary; Chapter 5: When to Use Object-oriented Programming; Treat objects as objects; Adding behavior to class data with properties; Properties in detail; Decorators -- another way to create properties; Deciding when to use properties; Manager objects; Removing duplicate code; In practice; Case study; Exercises; Summary; Chapter 6: Python Data Structures; Empty objects. Tuples and named tuplesNamed tuples; Dictionaries; Dictionary use cases; Using defaultdict; Counter; Lists; Sorting lists; Sets; Extending built-ins; Queues; FIFO queues; LIFO queues; Priority queues; Case study; Exercises; Summary; Chapter 7: Python Object-oriented Shortcuts; Python built-in functions; The len() function; Reversed; Enumerate; File I/O; Placing it in context; An alternative to method overloading; Default arguments; Variable argument lists; Unpacking arguments; Functions are objects too; Using functions as attributes; Callable objects; Case study; Exercises; Summary. Chapter 8: Strings and SerializationStrings; String manipulation; String formatting; Escaping braces; Keyword arguments; Container lookups; Object lookups; Making it look right; Strings are Unicode; Converting bytes to text; Converting text to bytes; Mutable byte strings; Regular expressions; Matching patterns; Matching a selection of characters; Escaping characters; Matching multiple characters; Grouping patterns together; Getting information from regular expressions; Making repeated regular expressions efficient; Serializing objects; Customizing pickles; Serializing web objects; Case study. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Object-oriented programming (Computer science) http://id.loc.gov/authorities/subjects/sh87007503 Python (Langage de programmation) Programmation orientée objet (Informatique) COMPUTERS Programming Languages Python. bisacsh Object-oriented programming (Computer science) fast Python (Computer program language) fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh96008834 http://id.loc.gov/authorities/subjects/sh87007503 |
| title | Python 3 object-oriented programming : unleash the power of Python 3 objects / |
| title_auth | Python 3 object-oriented programming : unleash the power of Python 3 objects / |
| title_exact_search | Python 3 object-oriented programming : unleash the power of Python 3 objects / |
| title_full | Python 3 object-oriented programming : unleash the power of Python 3 objects / Dusty Phillips. |
| title_fullStr | Python 3 object-oriented programming : unleash the power of Python 3 objects / Dusty Phillips. |
| title_full_unstemmed | Python 3 object-oriented programming : unleash the power of Python 3 objects / Dusty Phillips. |
| title_short | Python 3 object-oriented programming : |
| title_sort | python 3 object oriented programming unleash the power of python 3 objects |
| title_sub | unleash the power of Python 3 objects / |
| topic | Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Object-oriented programming (Computer science) http://id.loc.gov/authorities/subjects/sh87007503 Python (Langage de programmation) Programmation orientée objet (Informatique) COMPUTERS Programming Languages Python. bisacsh Object-oriented programming (Computer science) fast Python (Computer program language) fast |
| topic_facet | Python (Computer program language) Object-oriented programming (Computer science) Python (Langage de programmation) Programmation orientée objet (Informatique) COMPUTERS Programming Languages Python. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1055466 |
| work_keys_str_mv | AT phillipsdusty python3objectorientedprogrammingunleashthepowerofpython3objects |