使用Python与SL4A开发Android应用

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"《Pro Android Python with SL4A》是一本关于使用Python开发安卓应用程序的专著，作者Paul Ferrill。这本书旨在通过SL4A库（Scripting Layer for Android）来教你如何用Python构建Android应用，同时该库也支持Perl和Lua语言。书中详细介绍了从入门到进阶的各种步骤，包括Android SDK的导航、Eclipse的使用、Android API的探索，以及如何使用Python进行后台脚本编写、创建GUI等。" 在Android平台上，Python通常不是首选的开发语言，因为Java是官方推荐的原生开发语言。然而，对于一些简单的设置调整或快速原型开发，使用Python和SL4A项目可以极大地简化工作流程。SL4A提供了一个接口，允许开发者使用Python等脚本语言与Android设备的硬件和软件功能交互，如访问传感器、控制设备、处理网络通信等。本书的第一章是介绍，引导读者进入Android和Python开发的世界，解释为什么Python在某些场景下是Android开发的理想选择。第二章至第四章逐步介绍了开始开发前的准备工作，包括安装Android SDK、设置开发环境Eclipse，以及熟悉Android开发的基本工具和概念。第五章深入探讨了Android API，这是开发者构建应用的核心部分，涵盖了各种Android系统服务和组件的使用。第六章介绍了如何利用Python进行后台脚本编写，这对于实现定时任务或者无用户界面的服务非常有用。第七章和第八章则聚焦于Python脚本实用工具和基于对话框的GUI，帮助开发者创建用户交互界面。第九章进一步扩展了GUI的话题，通过HTML和Python结合的方式构建更复杂的图形界面。第十章讲述了应用的打包和分发过程，这是将开发成果推向市场的关键步骤。最后，书中的索引方便读者查找特定主题。通过学习这本书，读者不仅能够掌握Python在Android开发中的应用，还能了解到如何利用SL4A库的优势，以更高效、更简洁的方式创建功能丰富的Android应用。无论是对Python编程有经验的开发者还是希望尝试新领域的初学者，都能从中受益匪浅。

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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