该博客内容参考http://www.cnblogs.com/wupeiqi/articles/4943406.html
内置函数 一
详细见python文档，猛击这里
文件操作
操作文件时，一般需要经历如下步骤：
- 打开文件
- 操作文件
一、打开文件
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文件句柄 = file('文件路径', '模式')
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注：python中打开文件有两种方式，即：open(...) 和 file(...) ，本质上前者在内部会调用后者来进行文件操作，推荐使用 open。
打开文件时，需要指定文件路径和以何等方式打开文件，打开后，即可获取该文件句柄，日后通过此文件句柄对该文件操作。
打开文件的模式有：
- r，只读模式（默认）。
- w，只写模式。【不可读；不存在则创建；存在则删除内容；】
- a，追加模式。【可读； 不存在则创建；存在则只追加内容；】
"+" 表示可以同时读写某个文件
- r+，可读写文件。【可读；可写；可追加】
- w+，写读
- a+，同a
"U"表示在读取时，可以将 \r \n \r\n自动转换成 \n （与 r 或 r+ 模式同使用）
- rU
- r+U
"b"表示处理二进制文件（如：FTP发送上传ISO镜像文件，linux可忽略，windows处理二进制文件时需标注）
- rb
- wb
- ab
二、操作操作
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class file(object):
def close(self): # real signature unknown; restored from __doc__
关闭文件
"""
close() -> None or (perhaps) an integer. Close the file.
Sets data attribute .closed to True. A closed file cannot be used for
further I/O operations. close() may be called more than once without
error. Some kinds of file objects (for example, opened by popen())
may return an exit status upon closing.
"""
def fileno(self): # real signature unknown; restored from __doc__
文件描述符
"""
fileno() -> integer "file descriptor".
This is needed for lower-level file interfaces, such os.read().
"""
return 0 def flush(self): # real signature unknown; restored from __doc__
刷新文件内部缓冲区
""" flush() -> None. Flush the internal I/O buffer. """
pass
def isatty(self): # real signature unknown; restored from __doc__
判断文件是否是同意tty设备
""" isatty() -> true or false. True if the file is connected to a tty device. """
return False
def next(self): # real signature unknown; restored from __doc__
获取下一行数据，不存在，则报错
""" x.next() -> the next value, or raise StopIteration """
pass
def read(self, size=None): # real signature unknown; restored from __doc__
读取指定字节数据
"""
read([size]) -> read at most size bytes, returned as a string.
If the size argument is negative or omitted, read until EOF is reached.
Notice that when in non-blocking mode, less data than what was requested
may be returned, even if no size parameter was given.
"""
pass
def readinto(self): # real signature unknown; restored from __doc__
读取到缓冲区，不要用，将被遗弃
""" readinto() -> Undocumented. Don't use this; it may go away. """
pass
def readline(self, size=None): # real signature unknown; restored from __doc__
仅读取一行数据
"""
readline([size]) -> next line from the file, as a string.
Retain newline. A non-negative size argument limits the maximum
number of bytes to return (an incomplete line may be returned then).
Return an empty string at EOF.
"""
pass
def readlines(self, size=None): # real signature unknown; restored from __doc__
读取所有数据，并根据换行保存值列表
"""
readlines([size]) -> list of strings, each a line from the file.
Call readline() repeatedly and return a list of the lines so read.
The optional size argument, if given, is an approximate bound on the
total number of bytes in the lines returned.
"""
return []
def seek(self, offset, whence=None): # real signature unknown; restored from __doc__
指定文件中指针位置
"""
seek(offset[, whence]) -> None. Move to new file position.
Argument offset is a byte count. Optional argument whence defaults to
0 (offset from start of file, offset should be >= 0); other values are 1
(move relative to current position, positive or negative), and 2 (move
relative to end of file, usually negative, although many platforms allow
seeking beyond the end of a file). If the file is opened in text mode,
only offsets returned by tell() are legal. Use of other offsets causes
undefined behavior.
Note that not all file objects are seekable.
"""
pass
def tell(self): # real signature unknown; restored from __doc__
获取当前指针位置
""" tell() -> current file position, an integer (may be a long integer). """
pass
def truncate(self, size=None): # real signature unknown; restored from __doc__
截断数据，仅保留指定之前数据
"""
truncate([size]) -> None. Truncate the file to at most size bytes.
Size defaults to the current file position, as returned by tell().
"""
pass
def write(self, p_str): # real signature unknown; restored from __doc__
写内容
"""
write(str) -> None. Write string str to file.
Note that due to buffering, flush() or close() may be needed before
the file on disk reflects the data written.
"""
pass
def writelines(self, sequence_of_strings): # real signature unknown; restored from __doc__
将一个字符串列表写入文件
"""
writelines(sequence_of_strings) -> None. Write the strings to the file.
Note that newlines are not added. The sequence can be any iterable object
producing strings. This is equivalent to calling write() for each string.
"""
pass
def xreadlines(self): # real signature unknown; restored from __doc__
可用于逐行读取文件，非全部
"""
xreadlines() -> returns self.
For backward compatibility. File objects now include the performance
optimizations previously implemented in the xreadlines module.
"""
pass
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三、with
为了避免打开文件后忘记关闭，可以通过管理上下文，即：
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with open('log','r') as f:
...
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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 后，with又支持同时对多个文件的上下文进行管理，即：
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with open('log1') as obj1, open('log2') as obj2:
pass
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四、那么问题来了...
1、如何在线上环境优雅的修改配置文件?
- rU
- r+U
"b"表示处理二进制文件（如：FTP发送上传ISO镜像文件，linux可忽略，windows处理二进制文件时需标注）
- rb
- wb
- ab
二、操作操作
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class file(object):
def close(self): # real signature unknown; restored from __doc__
关闭文件
"""
close() -> None or (perhaps) an integer. Close the file.
Sets data attribute .closed to True. A closed file cannot be used for
further I/O operations. close() may be called more than once without
error. Some kinds of file objects (for example, opened by popen())
may return an exit status upon closing.
"""
def fileno(self): # real signature unknown; restored from __doc__
文件描述符
"""
fileno() -> integer "file descriptor".
This is needed for lower-level file interfaces, such os.read().
"""
return 0 def flush(self): # real signature unknown; restored from __doc__
刷新文件内部缓冲区
""" flush() -> None. Flush the internal I/O buffer. """
pass
def isatty(self): # real signature unknown; restored from __doc__
判断文件是否是同意tty设备
""" isatty() -> true or false. True if the file is connected to a tty device. """
return False
def next(self): # real signature unknown; restored from __doc__
获取下一行数据，不存在，则报错
""" x.next() -> the next value, or raise StopIteration """
pass
def read(self, size=None): # real signature unknown; restored from __doc__
读取指定字节数据
"""
read([size]) -> read at most size bytes, returned as a string.
If the size argument is negative or omitted, read until EOF is reached.
Notice that when in non-blocking mode, less data than what was requested
may be returned, even if no size parameter was given.
"""
pass
def readinto(self): # real signature unknown; restored from __doc__
读取到缓冲区，不要用，将被遗弃
""" readinto() -> Undocumented. Don't use this; it may go away. """
pass
def readline(self, size=None): # real signature unknown; restored from __doc__
仅读取一行数据
"""
readline([size]) -> next line from the file, as a string.
Retain newline. A non-negative size argument limits the maximum
number of bytes to return (an incomplete line may be returned then).
Return an empty string at EOF.
"""
pass
def readlines(self, size=None): # real signature unknown; restored from __doc__
读取所有数据，并根据换行保存值列表
"""
readlines([size]) -> list of strings, each a line from the file.
Call readline() repeatedly and return a list of the lines so read.
The optional size argument, if given, is an approximate bound on the
total number of bytes in the lines returned.
"""
return []
def seek(self, offset, whence=None): # real signature unknown; restored from __doc__
指定文件中指针位置
"""
seek(offset[, whence]) -> None. Move to new file position.
Argument offset is a byte count. Optional argument whence defaults to
0 (offset from start of file, offset should be >= 0); other values are 1
(move relative to current position, positive or negative), and 2 (move
relative to end of file, usually negative, although many platforms allow
seeking beyond the end of a file). If the file is opened in text mode,
only offsets returned by tell() are legal. Use of other offsets causes
undefined behavior.
Note that not all file objects are seekable.
"""
pass
def tell(self): # real signature unknown; restored from __doc__
获取当前指针位置
""" tell() -> current file position, an integer (may be a long integer). """
pass
def truncate(self, size=None): # real signature unknown; restored from __doc__
截断数据，仅保留指定之前数据
"""
truncate([size]) -> None. Truncate the file to at most size bytes.
Size defaults to the current file position, as returned by tell().
"""
pass
def write(self, p_str): # real signature unknown; restored from __doc__
写内容
"""
write(str) -> None. Write string str to file.
Note that due to buffering, flush() or close() may be needed before
the file on disk reflects the data written.
"""
pass
def writelines(self, sequence_of_strings): # real signature unknown; restored from __doc__
将一个字符串列表写入文件
"""
writelines(sequence_of_strings) -> None. Write the strings to the file.
Note that newlines are not added. The sequence can be any iterable object
producing strings. This is equivalent to calling write() for each string.
"""
pass
def xreadlines(self): # real signature unknown; restored from __doc__
可用于逐行读取文件，非全部
"""
xreadlines() -> returns self.
For backward compatibility. File objects now include the performance
optimizations previously implemented in the xreadlines module.
"""
pass
|
三、with
为了避免打开文件后忘记关闭，可以通过管理上下文，即：
|
1
2
3
|
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 后，with又支持同时对多个文件的上下文进行管理，即：
|
1
2
|
with open('log1') as obj1, open('log2') as obj2:
pass
|
四、那么问题来了...
1、如何在线上环境优雅的修改配置文件?
global
log 127.0.0.1 local2
daemon
maxconn 256
log 127.0.0.1 local2 info
defaults
log global
mode http
timeout connect 5000ms
timeout client 50000ms
timeout server 50000ms
option dontlognull listen stats :8888
stats enable
stats uri /admin
stats auth admin:1234 frontend oldboy.org
bind 0.0.0.0:80
option httplog
option httpclose
option forwardfor
log global
acl www hdr_reg(host) -i www.oldboy.org
use_backend www.oldboy.org if www backend www.oldboy.org
server 100.1.7.9 100.1.7.9 weight 20 maxconn 3000
原配置文件
需求
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import json
def fetch(keys): #查询
user_list=[]
flag=False #标志位
with open ('log.txt') as obj: #打开文件进行管理
for line in obj: # 对文件句柄obj进行遍历
line_str=line.strip() # 得到去空格后的字符串
if line_str=="backend %s" %keys: #输入的字符串==backend 'key' 则把标志位置为True 然后重新循环
flag=True
continue
if line_str.startswith('backend') and flag: #遍历到首字符串为backend 并且 flag为True的情况下则退出循环，至此得到查询的内容。 加flag是为了误跳出循环。
break
if flag and line_str: #标志位为True且line_str为非空格则把内容加入到user_list列表 作为自定义函数的返回值。
user_list.append(line_str)
return user_list #keys=raw_input("please input your fetch:")
#print 'your fetch %s' %keys
#print fetch(keys)
def add1 (user_dic):
backend_user=user_dic['backend'] #把传入的字典进行分割把把相应的key传给变量，后续使用。
backend_user1='backend %s' %backend_user
#server 100.1.7.9 100.1.7.10 weight 20 maxconn 3000
record_user='\n%s server:%s weight:%d maxconn:%d\n' %(7*(" "),user_dic['record']['server'],user_dic['record']['weight'],user_dic['record']['maxconn'])
result_fetch=fetch(backend_user) #把上个函数查询的结果返回给变量，给后续使用，若为空列表则bool值为False
if result_fetch: # 如果返回值为空则把log全部写入到log1文件且在最后追加新的字符串，如果返回值非空的话，
flag=False # 先检查新加的字符串是否存在，存在则输出“输入的字符串已存在”不存在则把新加的字符串
s=False # 追加到上个函数的返回值列表，在把新增的字符串写入文件的时候需要新增一个标志位
if record_user.strip() in result_fetch:#s 如果 s为false 表示没有写入 if not s 为True执行写入动作。
print '你输入的字符串已存在！'
else:
result_fetch.append(record_user)
print result_fetch
with open('log.txt','r') as obj1,open('log1.txt','w') as obj2:
for line in obj1:
if line.strip() ==backend_user1:
flag=True
obj2.write(line)
continue
if line.startswith('backend') and flag:
flag=False
if flag:
if not s:
for lines in result_fetch:
obj2.write('\n%s' %(8*" "))
obj2.write(lines)
s=True
else:
obj2.write(line)
else:
with open('log.txt') as obj1,open('log1.txt','w') as obj2:
for line in obj1:
obj2.write(line)
obj2.write('\n')
obj2.write(backend_user+'\n')
obj2.write(record_user) def del1(backend):
flag=True
del_user=fetch(backend)
with open('log.txt') as obj1,open('log1.txt','w') as obj2:
for line in obj1:
if line.strip()=='backend %s' %backend:
flag=False
continue
if line.startswith('backend') and not flag:
flag=True
# obj2.write(line)
if flag:
obj2.write(line) s= '{"backend": "www.oldboy.org", "record":{"server": "10.1.7.91","weight": 20,"maxconn": 30}}'
dic_user=json.loads(s)
#print dic_user
add1(dic_user)
#del1('www.oldboy.org')
#keys=raw_input("please input your fetch:")
#print 'your fetch %s' %keys
#print fetch(keys)
demo
二、 函数的定义和使用
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def 函数名(参数):
...
函数体
...
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函数的定义主要有如下要点：
- def：表示函数的关键字
- 函数名：函数的名称，日后根据函数名调用函数
- 函数体：函数中进行一系列的逻辑计算，如：发送邮件、计算出 [11,22,38,888,2]中的最大数等...
- 参数：为函数体提供数据
- 返回值：当函数执行完毕后，可以给调用者返回数据。
以上要点中，比较重要有参数和返回值：
1、返回值
函数是一个功能块，该功能到底执行成功与否，需要通过返回值来告知调用者。
def 发送短信():
发送短信的代码...
if 发送成功:
return True
else:
return False
while True:
# 每次执行发送短信函数，都会将返回值自动赋值给result
# 之后，可以根据result来写日志，或重发等操作
result = 发送短信()
if result == False:
记录日志，短信发送失败...
2、参数
为什么要有参数？
def CPU报警邮件()
#发送邮件提醒
连接邮箱服务器
发送邮件
关闭连接 def 硬盘报警邮件()
#发送邮件提醒
连接邮箱服务器
发送邮件
关闭连接 def 内存报警邮件()
#发送邮件提醒
连接邮箱服务器
发送邮件
关闭连接 while True： if cpu利用率 > 90%:
CPU报警邮件（） if 硬盘使用空间 > 90%:
硬盘报警邮件（） if 内存占用 > 80%:
内存报警邮件（）
无参数实例
def 发送邮件(邮件内容)
#发送邮件提醒
连接邮箱服务器
发送邮件
关闭连接
while True：
if cpu利用率 > 90%:
发送邮件("CPU报警了。")
if 硬盘使用空间 > 90%:
发送邮件("硬盘报警了。")
if 内存占用 > 80%:
发送邮件("内存报警了。")
有参数实例
函数的有三中不同的参数：
- 普通参数
- 默认参数
- 动态参数
# ######### 定义函数 ######### # name 叫做函数func的形式参数，简称：形参
def func(name):
print name # ######### 执行函数 #########
# 'wupeiqi' 叫做函数func的实际参数，简称：实参
func('wupeiqi')
普通参数
def func(name, age = 18):
print "%s:%s" %(name,age)
# 指定参数
func('wupeiqi', 19)
# 使用默认参数
func('alex')
注：默认参数需要放在参数列表最后
默认参数
def func(*args):
print args
# 执行方式一
func(11,33,4,4454,5)
# 执行方式二
li = [11,2,2,3,3,4,54]
func(*li)
动态参数1
def func(**kwargs):
print args
# 执行方式一
func(name＝'wupeiqi',age=18)
# 执行方式二
li = {'name':'wupeiqi', age:18, 'gender':'male'}
func(**li)
动态参数2
def func(*args, **kwargs):
print args
print kwargs
动态参数3
扩展：发送邮件实例
import smtplib
from email.mime.text import MIMEText
from email.utils import formataddr msg = MIMEText('邮件内容', 'plain', 'utf-8')
msg['From'] = formataddr(["武沛齐",'wptawy@126.com'])
msg['To'] = formataddr(["走人",'424662508@qq.com'])
msg['Subject'] = "主题" server = smtplib.SMTP("smtp.126.com", 25)
server.login("wptawy@126.com", "邮箱密码")
server.sendmail('wptawy@126.com', ['424662508@qq.com',], msg.as_string())
server.quit()
邮件实例
lambda表达式
学习条件运算时，对于简单的 if else 语句，可以使用三元运算来表示，即：
# 普通条件语句
if 1 == 1:
name = 'wupeiqi'
else:
name = 'alex' # 三元运算
name = 'wupeiqi' if 1 == 1 else 'alex'
对于简单的函数，也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 ###################### # 定义函数（lambda表达式）
my_lambda = lambda arg : arg + 1 # 执行函数
result = my_lambda(123)
lambda存在意义就是对简单函数的简洁表示
内置函数 二
一、map
遍历序列，对序列中每个元素进行操作，最终获取新的序列。
li = [11, 22, 33] new_list = map(lambda a: a + 100, li)
每个元素增加100
li = [11, 22, 33]
sl = [1, 2, 3]
new_list = map(lambda a, b: a + b, li, sl)
两个列表对应元素相加
二、filter
对于序列中的元素进行筛选，最终获取符合条件的序列
li = [11, 22, 33] new_list = filter(lambda arg: arg > 22, li) #filter第一个参数为空，将获取原来序列
获取列表中大于12的所有元素集合
三、reduce
对于序列内所有元素进行累计操作
li = [11, 22, 33] result = reduce(lambda arg1, arg2: arg1 + arg2, li) # reduce的第一个参数，函数必须要有两个参数
# reduce的第二个参数，要循环的序列
# reduce的第三个参数，初始值
获取列表所有元素的和
装饰器
装饰器是函数，只不过该函数可以具有特殊的含义，装饰器用来装饰函数或类，使用装饰器可以在函数执行前和执行后添加相应操作。
def wrapper(func):
def result():
print 'before'
func()
print 'after'
return result @wrapper
def foo():
print 'foo'
import functools def wrapper(func):
@functools.wraps(func)
def wrapper():
print 'before'
func()
print 'after'
return wrapper @wrapper
def foo():
print 'foo'
#!/usr/bin/env python
#coding:utf-8 def Before(request,kargs):
print 'before' def After(request,kargs):
print 'after' def Filter(before_func,after_func):
def outer(main_func):
def wrapper(request,kargs): before_result = before_func(request,kargs)
if(before_result != None):
return before_result; main_result = main_func(request,kargs)
if(main_result != None):
return main_result; after_result = after_func(request,kargs)
if(after_result != None):
return after_result; return wrapper
return outer @Filter(Before, After)
def Index(request,kargs):
print 'index' if __name__ == '__main__':
Index(1,2)
冒泡算法
需求：请按照从小到大对列表 [13, 22, 6, 99, 11] 进行排序
思路：相邻两个值进行比较，将较大的值放在右侧，依次比较！
li = [13, 22, 6, 99, 11] for m in range(4): # 等价于 #for m in range(len(li)-1):
if li[m]> li[m+1]:
temp = li[m+1]
li[m+1] = li[m]
li[m] = temp
第一步
li = [13, 22, 6, 99, 11] for m in range(4): # 等价于 #for m in range(len(li)-1):
if li[m]> li[m+1]:
temp = li[m+1]
li[m+1] = li[m]
li[m] = temp for m in range(3): # 等价于 #for m in range(len(li)-2):
if li[m]> li[m+1]:
temp = li[m+1]
li[m+1] = li[m]
li[m] = temp for m in range(2): # 等价于 #for m in range(len(li)-3):
if li[m]> li[m+1]:
temp = li[m+1]
li[m+1] = li[m]
li[m] = temp for m in range(1): # 等价于 #for m in range(len(li)-4):
if li[m]> li[m+1]:
temp = li[m+1]
li[m+1] = li[m]
li[m] = temp
print li
第二步
li = [13, 22, 6, 99, 11] for i in range(1,5):
for m in range(len(li)-i):
if li[m] > li[m+1]:
temp = li[m+1]
li[m+1] = li[m]
li[m] = temp
第三步
递归
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)