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Python Essentials电子书

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14人正在读 | 0人评论 9.8

作       者:Steven F. Lott

出  版  社:Packt Publishing

出版时间:2015-06-30

字       数:137.6万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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This book is designed for Python 2 developers who want to get to grips with Python 3 in a short period of time. It covers the key features of Python, assuming you are familiar with the fundamentals of Python 2.
目录展开

Python Essentials

Table of Contents

Python Essentials

Credits

About the Author

About the Reviewers

www.PacktPub.com

Support files, eBooks, discount offers, and more

Why subscribe?

Free access for Packt account holders

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Errata

Piracy

Questions

1. Getting Started

Installation or upgrade

Installing Python on Windows

Considering some alternatives

Upgrading to Python 3.4 in Mac OS X

Adding the Tkinter package

Upgrading to Python 3.4 in Linux

Using the Read-Evaluate-Print Loop (REPL)

Confirming that things are working

Doing simple arithmetic

Assigning results to variables

Using import to add features

Interacting with the help subsystem

Using the pydoc program

Creating simple script files

Simplified syntax rules

The Python ecosystem

The idea of extensibility via add-ons

Using the Python Package Index – PyPI

Using pip to gather modules

Using easy_install to add modules

Installing modules manually

Looking at other Python interpreters

Summary

2. Simple Data Types

Introducing the built-in operators

Making comparisons

Using integers

Using the bit-oriented operators

Using rational numbers

Using decimal numbers

Using floating-point numbers

Using complex numbers

The numeric tower

The math libraries

Using bits and Boolean values

Working with sequences

Slicing and dicing a sequence

Using string and bytes values

Writing string literals

Using raw string literals

Using byte string literals

Using the string operators

Converting between Unicode and bytes

Using string methods

Accessing the details of a string

Parsing strings into substrings

Using the tuple collection

The None object

The consequences of immutability

Using the built-in conversion functions

Summary

3. Expressions and Output

Expressions, operators, and data types

Using operators on non-numeric data

The print() function

Examining syntax rules

Splitting, partitioning, and joining strings

Using the format() method to make more readable output

Summary of the standard string libraries

Using the re module to parse strings

Using regular expressions

Creating a regular expression string

Working with Unicode, ASCII, and bytes

Using the locale module for personalization

Summary

4. Variables, Assignment and Scoping Rules

Simple assignment and variables

Multiple assignment

Using repeated assignment

Using the head, *tail assignment

Augmented assignment

The input() function

Python language concepts

Object types versus variable declarations

Avoiding confusion when naming variables

Garbage collection via reference counting

The little-used del statement

The Python namespace concept

Globals and locals

Summary

5. Logic, Comparisons, and Conditions

Boolean data and the bool() function

Comparison operators

Combining comparisons to simplify the logic

Testing float values

Comparing object IDs with the is operator

Equality and object hash values

Logic operators – and, or, not, if-else

Short-circuit (or non-strict) evaluation

The if-elif-else statement

Adding elif clauses

The pass statement as a placeholder

The assert statement

The logic of the None object

Summary

6. More Complex Data Types

The mutability and immutability distinction

Using the list collection

Using list operators

Mutating a list with subscripts

Mutating a list with method functions

Accessing a list

Using collection functions

Using the set collection

Using set operators

Mutating a set with method functions

Using augmented assignment with sets

Accessing a set with operators and method functions

Mappings

Using dictionary operators

Using dictionary mutators

Using methods for accessing items in a mapping

Using extensions from the collections module

Processing collections with the for statement

Using literal lists in a for statement

Using the range() and enumerate() functions

Iterating with the while statement

The continue and break statements

Breaking early from a loop

Using the else clause on a loop

Summary

7. Basic Function Definitions

Looking at the five kinds of callables

Defining functions with positional parameters

Defining multiple parameters

Using the return statement

Evaluating a function with positional or keyword arguments

Writing a function's docstring

Mutable and immutable argument values

Defining optional parameters via default values

A warning about mutable default values

Using the "everything else" notations of * and **

Using sequences and dictionaries to fill in *args and *kw

Nested function definitions

Working with namespaces

Assigning a global variable

Assigning a non-local variable

Defining lambdas

Writing additional function annotations

Summary

8. More Advanced Functions

Using the for statement with iterable collections

Iterators and iterable collections

Consequences and next steps

Using generator expressions and comprehensions

Limitations of generator expressions

Using multiple loops and conditions

Writing comprehensions

Defining generator functions with the yield statement

Using the higher-order functions

Writing our own higher-order functions

Using the built-in reductions – max, min, and reduce

Three ways to sort a sequence

Sorting via a key function

Sorting via wrapping and unwrapping

Functional programming design patterns

Summary

9. Exceptions

The core exception concept

Examining the exception object

Using the try and except statements

Using nested try statements

Matching exception classes in an except clause

Matching more general exceptions

The empty except clause

Creating our own exceptions

Using a finally clause

Use cases for exceptions

Issuing warnings instead of exceptions

Permission versus forgiveness – a Pythonic approach

Summary

10. Files, Databases, Networks, and Contexts

The essential file concept

Opening text files

Filtering text lines

Working with raw bytes

Using file-like objects

Using a context manager via the with statement

Closing file-like objects with contextlib

Using the shelve module as a database

Using the sqlite database

Using object-relational mapping

Web services and Internet protocols

Physical format considerations

Summary

11. Class Definitions

Creating a class

Writing the suite of statements in a class

Using instance variables and methods

Pythonic object-oriented programming

Trying to do type casting

Designing for encapsulation and privacy

Using properties

Using inheritance to simplify class definitions

Using multiple inheritance and the mixin design pattern

Using class methods and attributes

Using mutable class variables

Writing static methods

Using __slots__ to save storage

The ABCs of abstract base classes

Writing a callable class

Summary

12. Scripts, Modules, Packages, Libraries, and Applications

Script file rules

Running a script by the filename

Running a script by its module name

Running a script using OS shell rules

Choosing good script names

Creating a reusable module

Creating a hybrid library/application module

Creating a package

Designing alternative implementations

Seeing the package search path

Summary

13. Metaprogramming and Decorators

Simple metaprogramming with decorators

Defining our own decorator

More complex metaprogramming with metaclasses

Summary

14. Fit and Finish – Unit Testing, Packaging, and Documentation

Writing docstrings

Writing unit tests with doctest

Using the unittest library for testing

Combining doctest and unittest

Using other add-on test libraries

Logging events and conditions

Configuring the logging system

Writing documentation with RST markup

Creating HTML documentation from an RST source

Using the Sphinx tool

Organizing Python code

Summary

15. Next Steps

Leveraging the standard library

Leveraging PyPI – the Python Package Index

Types of applications

Building CLI applications

Getting command-line arguments with argparse

Using the cmd module for interactive applications

Building GUI applications

Using more sophisticated packages

Building web applications

Using a web framework

Building a RESTful web service with Flask

Plugging into a MapReduce framework

Summary

Index

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