Python基础（三）

本章内容：

深浅拷贝

函数（全局与局部变量）

内置函数

文件处理

三元运算

lambda 表达式

递归（斐波那契数列）

冒泡排序

深浅拷贝

一、数字和字符串

对于 数字 和 字符串 而言，赋值、浅拷贝和深拷贝无意义，因为其永远指向同一个内存地址。

import copy
#定义变量   数字、字符串
n1 = 123
#n1 = 'nick'
print(id(n1))

#赋值
n2 = n1
print(id(n2))

#浅拷贝
n3 = copy.copy(n1)
print(id(n3))

#深拷贝
n4 = copy.deepcopy(n1)
print(id(n4))

class TextIOWrapper(_TextIOBase):
"""
Character and line based layer over a BufferedIOBase object, buffer.

encoding gives the name of the encoding that the stream will be
decoded or encoded with. It defaults to locale.getpreferredencoding(False).

errors determines the strictness of encoding and decoding (see
help(codecs.Codec) or the documentation for codecs.register) and
defaults to "strict".

newline controls how line endings are handled. It can be None, '',
'\n', '\r', and '\r\n'.  It works as follows:

* On input, if newline is None, universal newlines mode is
enabled. Lines in the input can end in '\n', '\r', or '\r\n', and
these are translated into '\n' before being returned to the
caller. If it is '', universal newline mode is enabled, but line
endings are returned to the caller untranslated. If it has any of
the other legal values, input lines are only terminated by the given
string, and the line ending is returned to the caller untranslated.

* On output, if newline is None, any '\n' characters written are
translated to the system default line separator, os.linesep. If
newline is '' or '\n', no translation takes place. If newline is any
of the other legal values, any '\n' characters written are translated
to the given string.

If line_buffering is True, a call to flush is implied when a call to
write contains a newline character.
"""
def close(self, *args, **kwargs): # real signature unknown
关闭文件
pass

def fileno(self, *args, **kwargs): # real signature unknown
文件描述符
pass

def flush(self, *args, **kwargs): # real signature unknown
刷新文件内部缓冲区
pass

def isatty(self, *args, **kwargs): # real signature unknown
判断文件是否是同意tty设备
pass

def read(self, *args, **kwargs): # real signature unknown
读取指定字节数据
pass

def readable(self, *args, **kwargs): # real signature unknown
是否可读
pass

def readline(self, *args, **kwargs): # real signature unknown
仅读取一行数据
pass

def seek(self, *args, **kwargs): # real signature unknown
指定文件中指针位置
pass

def seekable(self, *args, **kwargs): # real signature unknown
指针是否可操作
pass

def tell(self, *args, **kwargs): # real signature unknown
获取指针位置
pass

def truncate(self, *args, **kwargs): # real signature unknown
截断数据，仅保留指定之前数据
pass

def writable(self, *args, **kwargs): # real signature unknown
是否可写
pass

def write(self, *args, **kwargs): # real signature unknown
写内容
pass

def __getstate__(self, *args, **kwargs): # real signature unknown
pass

def __init__(self, *args, **kwargs): # real signature unknown
pass

@staticmethod # known case of __new__
def __new__(*args, **kwargs): # real signature unknown
""" Create and return a new object.  See help(type) for accurate signature. """
pass

def __next__(self, *args, **kwargs): # real signature unknown
""" Implement next(self). """
pass

def __repr__(self, *args, **kwargs): # real signature unknown
""" Return repr(self). """
pass

buffer = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

closed = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

encoding = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

errors = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

line_buffering = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

name = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

newlines = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

_CHUNK_SIZE = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

_finalizing = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

3.x
三、管理上下文

为了避免打开文件后忘记关闭，可以通过管理上下文，即：

with open('log','r') as f:

...

如此方式，当with代码块执行完毕时，内部会自动关闭并释放文件资源。

在Python 2.7 及以后，with又支持同时对多个文件的上下文进行管理，即：

with open('log1') as obj1, open('log2') as obj2:
pass

###### 从一文件挨行读取并写入二文件 #########

with open('test.log','r') as obj1 , open('test1.log','w') as obj2:
for line in obj1:
obj2.write(line)

三元运算

三元运算（三目运算），是对简单的条件语句的缩写。

result = 值1 if 条件 else 值2

# 如果条件成立，那么将 “值1” 赋值给result变量，否则，将“值2”赋值给result变量

########## 三 元 运 算 ############
name = "nick" if 1==1 else "jenny"
print(name)

　　

lambda表达式

对于简单的函数，存在一种简便的表示方式，即：lambda表达式

######## 普 通 函 数 ########
# 定义函数（普通方式）
def func(arg):
return arg + 1

# 执行函数
result = func(123)

######## lambda 表 达 式 ########

# 定义函数（lambda表达式）
my_lambda = lambda arg : arg + 1

# 执行函数
result = my_lambda(123)

##### 列表重新判断操作排序 #####

li = [11,15,9,21,1,2,68,95]

s = sorted(map(lambda x:x if x > 11 else x * 9,li))

print(s)

######################

ret = sorted(filter(lambda x:x>22, [55,11,22,33,]))

print(ret)

递归

递归算法是一种直接或者间接地调用自身算法的过程。在计算机编写程序中，递归算法对解决一大类问题是十分有效的，它往往使算法的描述简洁而且易于理解。

递归算法解决问题的特点：

递归就是在过程或函数里调用自身。

在使用递归策略时，必须有一个明确的递归结束条件，称为递归出口。

递归算法解题通常显得很简洁，但递归算法解题的运行效率较低。所以一般不提倡用递归算法设计程序。

在递归调用的过程当中系统为每一层的返回点、局部量等开辟了栈来存储。递归次数过多容易造成栈溢出等。所以一般不提倡用递归算法设计程序。

利用函数编写如下数列：

斐波那契数列指的是这样一个数列 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233，377，610，987，1597，2584，4181，6765，10946，17711，28657，46368...

def func(arg1,arg2):
if arg1 == 0:
print arg1, arg2
arg3 = arg1 + arg2
print arg3
func(arg2, arg3)

func(0,1)

　　

#写函数，利用递归获取斐波那契数列中的第 10 个数
#方法一
def fie(n):
if n == 0 or n == 1:
return n
else:
return (fie(n-1)+fie(n-2))
ret = fie(10)
print(ret)
#方法二
def num(a,b,n):
if n == 10:
return a
print(a)
c = a + b
a = num(b,c,n + 1)
return a

s = num(0,1,1)
print(s)

冒泡排序

将一个不规则的数组按从小到大的顺序进行排序

data = [10,4,33,21,54,8,11,5,22,2,17,13,3,6,1,]

print("before sort:",data)

for j in range(1,len(data)):
for i in range(len(data) - j):
if data[i] > data[i + 1]:
temp = data[i]
data[i] = data[i + 1]
data[i + 1] = temp
print(data)

print("after sort:",data)