Python与SL4A打造实用的Android应用开发指南

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《Pro Android Python with SL4A 2011》是一本专为Android平台设计的应用开发指南，主要使用Python语言和少量JavaScript编写实用应用。该书强调了在Android设备上通过Python进行轻量级开发的优势，尤其是在处理简单设置调整等场景时，相比于Java，Python更为高效。作者Paul Ferrill引领读者步入Android应用开发的世界，从第1章的入门介绍开始，逐步深入。第2章讲解如何快速入门，让读者了解所需的工具和技术。第3章详细介绍了Android SDK的导航，这对于理解和操作Android开发环境至关重要。第4章转向使用Eclipse进行Python应用程序的开发，Eclipse作为一款流行的集成开发环境，提供了丰富的支持和便利性。随着章节推进，读者将学习到如何探索和利用Android API（第5章），这是构建应用程序的基础。接下来，作者将焦点转向Python的高级特性。第6章介绍了背景脚本编程，帮助开发者实现自动化任务和设备控制。第7章则涵盖了Python脚本工具的使用，提升开发效率。对于用户界面设计，第8章探讨了基于Python对话框的GUI设计，而第9章则扩展到HTML结合Python创建的GUI，展示更多交互式界面的可能性。本书的核心部分在于第10章，它指导读者如何打包和分发他们的应用程序，确保它们能够在实际环境中流畅运行。最后，附录中的索引为查阅书中内容提供了方便，便于读者快速找到所需的信息。《Pro Android Python with SL4A 2011》不仅是一本技术指南，还包含了实用技巧和案例分析，旨在帮助读者掌握如何利用Python语言和SL4A框架开发出既高效又具有吸引力的Android应用。无论你是初学者还是经验丰富的开发者，这本书都能提供深入且全面的学习资源。

CHAPTER 1 ■ INTRODUCTION

Shell

If you’re a shell script wizard, then you’ll feel right at home with SL4A’s shell interpreter. It’s essentially

the same bash script environment you would see at a typical Linux terminal prompt. You’ll find all the

familiar commands for manipulating files like cp, ls, mkdir, and mv.

Python

Python has a wide usage and heavy following, especially within Google. In fact, its following is so

significant they hired the inventor of the language, Guido van Rossum. Python has been around for quite

a while and has many open source projects written in the language. It also has seen the most interest as

far as SL4A is concerned, so you’ll find more examples and discussions in the forums than for any of the

other languages. For that reason, I will spend a little more time introducing the language, trying to hit

the highlights of things that will be important from an SL4A perspective.

Language Basics

Knowing the Python language is not an absolute requirement for this book, but it will help. The first

thing you need to know about Python is that everything is an object. The second thing is that whitespace

is meaningful in Python. By that, I mean Python uses either tabs or actual spaces (ASCII 32) instead of

curly braces to control code execution (see Figure 1-2). Third, it’s important to remember that Python is

a case-sensitive language.

Figure 1-2. Example of whitespace usage in Python

Python is a great language to use when teaching an “introduction to computer programming”

course. Every installation of standard Python comes with a command-line interpreter where you can

type in a line of code and immediately see the result. To launch the interpreter, simply enter python at a

command prompt (Windows) or terminal window (Linux and Mac OS X). At this point, you should see a

few lines with version information followed by the triple arrow prompt (>>>), letting you know that

you’re inside the Python interpreter as shown here:

CHAPTER 1 ■ INTRODUCTION

C:\Users\paul>python

Python 2.6.6 (r266:84297, Aug 24 2010, 18:13:38) [MSC v.1500 64 bit (AMD64)] on

win32

Type "help", "copyright", "credits" or "license" for more information.

>>>

Python uses a number of naming conventions that you will see if you examine much Python code.

The first is the double underscore, which is used in Python to “mangle” or change names as a way to

define private variables and methods used inside a class. You will see this notation used for “special”

methods such as __init__(self). If a class has the special __init__ method, it will be invoked whenever

a new instantiation of that class occurs.

For example:

>>> class Point:

def __init__(self, x, y):

self.x = x

self.y = y

>>> xy = Point(1,2)

>>> xy.x, xy.y

(1, 2)

As you can see from the example, self is used as a reserved word in Python and refers to the first

argument of a method. It’s actually a Python convention and, in reality, has no special meaning to

Python. However, because it’s a widely accepted convention, you’ll want to stick with it to avoid any

potential issues. Technically, self is a reference to the class or function itself. Methods within a class

may call other methods in the same class by using the method attributes of the self argument.

Python has a short list of built-in constants. The main ones you’ll run into are False, True, and None.

False and True are of type bool and show up primarily in logical tests or to create an infinite loop.

One of the things that frequently confuses new users of the language is the variety of data types. The

following sections give quick overview of the key data types you’ll need to use Python and SL4A.

Dictionary: An Unordered Set of Key/Value Pairs Requiring Unique Keys

A Python dictionary maps directly to a JSON data structure. The syntax for defining a dictionary uses

curly braces to enclose entries and a colon between the key and value. Here’s what a simple dictionary

definition looks like:

students = {'barney' : 1001, 'betty' : 1002, 'fred' : 1003, 'wilma' : 1004}

To reference entries, use the key, as shown here:

students['barney'] = 999

students['betty'] = 1000

You can also use the dict() constructor to build dictionaries. When the key is a simple string, you

can create a new dictionary using arguments passed to dict() such as the following:

students = dict(barney=1001, betty=1002, fred=1003, wilma=1004)

CHAPTER 1 ■ INTRODUCTION

Because everything in Python is an object, you can expect to see methods associated with a

dictionary object. As you might expect, there are methods to return the keys and the values from a

dictionary. Here’s what that would look like for the students dictionary:

>>> students

{'barney': 1001, 'betty': 1002, 'fred': 1003, 'wilma': 1004}

>>> students.keys()

['barney', 'betty', 'fred', 'wilma']

>>> students.values()

[1001, 1002, 1003, 1004]

The square bracket convention denotes a list. Evaluating the students.keys() statement returns a

list of keys from the students dictionary.

List: A Built-In Python Sequence Similar to an Array in Other Languages

In Python, a sequence is defined as “an iterable which supports efficient element access using integer

indices via the __getitem__() special method and defines a len() method that returns the length of the

sequence.” An iterable is defined as “a container object capable of returning its members one at a time.”

Python provides direct language support for iteration because it’s one of the more common operations

in programming. List objects provide a number of methods to make working with them easier. From the

Python documentation:

• list.append(x): Add an item to the end of the list; equivalent to a[len(a):] = [x].

• list.extend(L): Extend the list by appending all the items in the given list;

equivalent to a[len(a):] = L.

• list.insert(I,x): Insert an item at a given position. The first argument is the

index of the element before which to insert, so a.insert(0, x) inserts at the front

of the list, and a.insert(len(a), x) is equivalent to a.append(x).

• list.remove(x): Remove the first item from the list whose value is x. It is an error if

there is no such item.

• list.pop([i]): Remove the item at the given position in the list and return it. If no

index is specified, a.pop() removes and returns the last item in the list. (The

square brackets around the i in the method signature denote that the parameter is

optional, not that you should type square brackets at that position.) You will see

this notation frequently in the Python Library Reference.

• list.index(x): Return the index in the list of the first item whose value is x. It is an

error if there is no such item.

• list.count(x): Return the number of times x appears in the list.

• list.sort: Sort the items of the list, in place.

• list.reverse(x): Reverse the elements of the list, in place.

CHAPTER 1 ■ INTRODUCTION

strip( [chars])

swapcase( )

title( )

translate( table[, deletechars])

upper( )

zfill( width)

With Python 2.6, the built-in str and unicode classes provide a very full-featured formatting and

substitution capability through the str.format() method. There’s also a Formatter class with an even

more extensive set of methods suitable for implementing a templating capability. Python uses the

percent sign with strings for formatting as well. Here’s an example of using the percent sign in a print

statement:

>>> Pi = 3.141593

>>> print "Pi = %10.2f" % Pi

Pi = 3.14

>>> print "Long Pi = %10.6f" % Pi

Long Pi = 3.141593

This is a good place to talk about the use of slices in Python. Any object with multiple items, such as

a string, can be addressed using a notation called a slice. To reference the items from j to k of string s,

use s[j:k]. Adding a third item to the slice notation includes a step so that s[j:k:l] references the

items from j to k, incremented by l. To reference items from the beginning of the list to the nth item, use

s[:n], and from the nth item to the end would use s[n:]. For example:

>>> mylist = [1,2,3,4,5,6,7,8,9]

>>> mylist[:3]

[1, 2, 3]

>>> mylist[3:]

[4, 5, 6, 7, 8, 9]

Note that Python uses zero-based referencing. So, the first or zeroth element of mylist would be

equal to 1. The syntax mylist[:3] says “return all elements of mylist from the beginning up to, but not

including, the fourth element.” Negative indices count from the end of the list.

Tuple: An Immutable List

As with the string type, a tuple is immutable, meaning it can’t be changed once created. Tuples are

defined using the same syntax as a list, except they are enclosed by parentheses instead of square

brackets. Here’s an example of a tuple:

>>> Sentence = ("Today", "is", "the", "first", "day", "of", "the", "rest", "of", "your",

"life.")

>>> Sentence

('Today', 'is', 'the', 'first', 'day', 'of', 'the', 'rest', 'of', 'your', 'life.')

>>> Sentence[0]

'Today'

>>> Sentence[1:3]

('is', 'the')

>>> Sentence[-1]

'life.'

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