何谓Python
Python是一门具有强类型(即变量类型是强制要求的)、动态性、隐式类型(不需要做变量声明)、大小写敏感(var和VAR代表了不同的变量)以及面向对象(一切皆为对象)等特点的编程语言。
怎么获取帮助
如果你想知道一个对象(object)是如何工作的，那么你所需要做的就是调用 help(<object>)！另外还有一些有用的方法，dir()会显示该对象的所有方法，还 有<object>.__doc__会显示其文档：
| 1 2 3 4 5 6 7 8 9 10 11 | >>> help ( 5 ) Help on int object : (etc etc) >>> dir ( 5 ) [ '__abs__' , '__add__' , ...] >>> abs .__doc__ ' abs (number) - > number Return the absolute value of the argument.' |
语法
Python中没有强制的语句终止字符，且代码块是通过缩进来指示的。缩进表示一个代码块的开始，逆缩进则表示一个代码块的结束。声明以冒号(:) 字符结束，并且开启一个缩进级别。单行注释以井号字符(#)开头，多行注释则以多行字符串的形式出现。赋值（事实上是将对象绑定到名字）通过等号 (“=”)实现，双等号(“==”)用于相等判断，”+=”和”-=”用于增加/减少运算(由符号右边的值确定增加/减少的值)。这适用于许多数据类型， 包括字符串。你也可以在一行上使用多个变量。例如：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | >>> myvar = 3 >>> myvar + = 2 >>> myvar 5 >>> myvar - = 1 >>> myvar 4 """This is a multiline comment. The following lines concatenate the two strings.""" >>> mystring = "Hello" >>> mystring + = " world." >>> print mystring Hello world. # This swaps the variables in one line(!). # It doesn't violate strong typing because values aren't # actually being assigned, but new objects are bound to # the old names. >>> myvar, mystring = mystring, myvar |
数据类型
Python具有列表（list）、元组（tuple）和字典（dictionaries）三种基本的数据结构，而集合(sets)则包含在集合库 中(但从Python2.5版本开始正式成为Python内建类型)。列表的特点跟一维数组类似（当然你也可以创建类似多维数组的“列表的列表”），字典 则是具有关联关系的数组（通常也叫做哈希表），而元组则是不可变的一维数组（Python中“数组”可以包含任何类型的元素，这样你就可以使用混合元素， 例如整数、字符串或是嵌套包含列表、字典或元组）。数组中第一个元素索引值(下标)为0，使用负数索引值能够从后向前访问数组元素，-1表示最后一个元 素。数组元素还能指向函数。来看下面的用法：
| 1 2 3 4 5 6 7 8 9 10 | >>> sample = [ 1 , [ "another" , "list" ], ( "a" , "tuple" )] >>> mylist = [ "List item 1" , 2 , 3.14 ] >>> mylist[ 0 ] = "List item 1 again" # We're changing the item. >>> mylist[ - 1 ] = 3.21 # Here, we refer to the last item. >>> mydict = { "Key 1" : "Value 1" , 2 : 3 , "pi" : 3.14 } >>> mydict[ "pi" ] = 3.15 # This is how you change dictionary values. >>> mytuple = ( 1 , 2 , 3 ) >>> myfunction = len >>> print myfunction(mylist) 3 |
字符串
Python中的字符串使用单引号(‘)或是双引号(“)来进行标示，并且你还能够在通过某一种标示的字符串中使用另外一种标示符(例如 “He said ‘hello’.”)。而多行字符串可以通过三个连续的单引号(”’)或是双引号(“”")来进行标示。Python可以通过u”This is a unicode string”这样的语法使用Unicode字符串。如果想通过变量来填充字符串，那么可以使用取模运算符(%)和一个元组。使用方式是在目标字符串中从 左至右使用%s来指代变量的位置，或者使用字典来代替，示例如下：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | >>> print "Name: % s\ Number: % s\ String: % s " % (myclass.name, 3, 3 * " - ") Name: Poromenos Number: 3 String: - - - strString = """This is a multiline string.""" # WARNING: Watch out for the trailing s in "%(key)s". >>> print "This %(verb)s a %(noun)s." % { "noun" : "test" , "verb" : "is" } This is a test. |
流程控制
Python中可以使用if、for和while来实现流程控制。Python中并没有select，取而代之使用if来实现。使用for来枚举列 表中的元素。如果希望生成一个由数字组成的列表，则可以使用range(<number>)函数。以下是这些声明的语法示例：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | rangelist = range ( 10 ) >>> print rangelist [ 0 , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ] for number in rangelist: # Check if number is one of # the numbers in the tuple. if number in ( 3 , 4 , 7 , 9 ): # "Break" terminates a for without # executing the "else" clause. break else : # "Continue" starts the next iteration # of the loop. It's rather useless here, # as it's the last statement of the loop. continue else : # The "else" clause is optional and is # executed only if the loop didn't "break". pass # Do nothing if rangelist[ 1 ] = = 2 : print "The second item (lists are 0-based) is 2" elif rangelist[ 1 ] = = 3 : print "The second item (lists are 0-based) is 3" else : print "Dunno" while rangelist[ 1 ] = = 1 : pass |
函数
函数通过“def”关键字进行声明。可选参数以集合的方式出现在函数声明中并紧跟着必选参数，可选参数可以在函数声明中被赋予一个默认值。已命名的 参数需要赋值。函数可以返回一个元组（使用元组拆包可以有效返回多个值）。Lambda函数是由一个单独的语句组成的特殊函数，参数通过引用进行传递，但 对于不可变类型(例如元组，整数，字符串等)则不能够被改变。这是因为只传递了该变量的内存地址，并且只有丢弃了旧的对象后，变量才能绑定一个对象，所以 不可变类型是被替换而不是改变（译者注：虽然Python传递的参数形式本质上是引用传递，但是会产生值传递的效果）。例如：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | # 作用等同于 def funcvar(x): return x + 1 funcvar = lambda x: x + 1 >>> print funcvar( 1 ) 2 # an_int 和 a_string 是可选参数，它们有默认值 # 如果调用 passing_example 时只指定一个参数，那么 an_int 缺省为 2 ，a_string 缺省为 A default string。如果调用 passing_example 时指定了前面两个参数，a_string 仍缺省为 A default string。 # a_list 是必备参数，因为它没有指定缺省值。 def passing_example(a_list, an_int = 2 , a_string = "A default string" ): a_list.append( "A new item" ) an_int = 4 return a_list, an_int, a_string >>> my_list = [ 1 , 2 , 3 ] >>> my_int = 10 >>> print passing_example(my_list, my_int) ([ 1 , 2 , 3 , 'A new item' ], 4 , "A default string" ) >>> my_list [ 1 , 2 , 3 , 'A new item' ] >>> my_int 10 |
类
Python支持有限的多继承形式。私有变量和方法可以通过添加至少两个前导下划线和最多尾随一个下划线的形式进行声明（如“__spam”，这只是惯例，而不是Python的强制要求）。当然，我们也可以给类的实例取任意名称。例如：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | class MyClass( object ): common = 10 def __init__( self ): self .myvariable = 3 def myfunction( self , arg1, arg2): return self .myvariable # This is the class instantiation >>> classinstance = MyClass() >>> classinstance.myfunction( 1 , 2 ) 3 # This variable is shared by all classes. >>> classinstance2 = MyClass() >>> classinstance.common 10 >>> classinstance2.common 10 # Note how we use the class name # instead of the instance. >>> MyClass.common = 30 >>> classinstance.common 30 >>> classinstance2.common 30 # This will not update the variable on the class, # instead it will bind a new object to the old # variable name. >>> classinstance.common = 10 >>> classinstance.common 10 >>> classinstance2.common 30 >>> MyClass.common = 50 # This has not changed, because "common" is # now an instance variable. >>> classinstance.common 10 >>> classinstance2.common 50 # This class inherits from MyClass. The example # class above inherits from "object", which makes # it what's called a "new-style class". # Multiple inheritance is declared as: # class OtherClass(MyClass1, MyClass2, MyClassN) class OtherClass(MyClass): # The "self" argument is passed automatically # and refers to the class instance, so you can set # instance variables as above, but from inside the class. def __init__( self , arg1): self .myvariable = 3 print arg1 >>> classinstance = OtherClass( "hello" ) hello >>> classinstance.myfunction( 1 , 2 ) 3 # This class doesn't have a .test member, but # we can add one to the instance anyway. Note # that this will only be a member of classinstance. >>> classinstance.test = 10 >>> classinstance.test 10 |
异常
Python中的异常由 try-except [exceptionname] 块处理，例如：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | def some_function(): try : # Division by zero raises an exception 10 / 0 except ZeroDivisionError: print "Oops, invalid." else : # Exception didn't occur, we're good. pass finally : # This is executed after the code block is run # and all exceptions have been handled, even # if a new exception is raised while handling. print "We're done with that." >>> some_function() Oops, invalid. We're done with that. |
导入
外部库可以使用 import [libname] 关键字来导入。同时，你还可以用 from [libname] import [funcname] 来导入所需要的函数。例如：
| 1 2 3 4 5 6 | import random from time import clock randomint = random.randint( 1 , 100 ) >>> print randomint 64 |
文件I / O
Python针对文件的处理有很多内建的函数库可以调用。例如，这里演示了如何序列化文件(使用pickle库将数据结构转换为字符串)：
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | import pickle mylist = [ "This" , "is" , 4 , 13327 ] # Open the file C:\\binary.dat for writing. The letter r before the # filename string is used to prevent backslash escaping. myfile = open (r "C:\\binary.dat" , "w" ) pickle.dump(mylist, myfile) myfile.close() myfile = open (r "C:\\text.txt" , "w" ) myfile.write( "This is a sample string" ) myfile.close() myfile = open (r "C:\\text.txt" ) >>> print myfile.read() 'This is a sample string' myfile.close() # Open the file for reading. myfile = open (r "C:\\binary.dat" ) loadedlist = pickle.load(myfile) myfile.close() >>> print loadedlist [ 'This' , 'is' , 4 , 13327 ] |
当然，避免不了要出一些错误，欢迎大家指正。了解更多