Python之經常使用模塊（待更新）

模塊，用一砣代碼實現了某個功能的代碼集合。 

相似於函數式編程和麪向過程編程，函數式編程則完成一個功能，其餘代碼用來調用便可，提供了代碼的重用性和代碼間的耦合。而對於一個複雜的功能來，可能須要多個函數才能完成（函數又能夠在不一樣的.py文件中），n個 .py 文件組成的代碼集合就稱爲模塊。

如：os 是系統相關的模塊；file是文件操做相關的模塊

模塊分爲三種：

• 自定義模塊
• 內置模塊
• 開源模塊

 

自定義模塊

 

一、定義模塊

情景一：

　　

情景二：

　　

情景三：

　　

二、導入模塊

Python之因此應用愈來愈普遍，在必定程度上也依賴於其爲程序員提供了大量的模塊以供使用，若是想要使用模塊，則須要導入。導入模塊有一下幾種方法：

import module
from module.xx.xx import xx
from module.xx.xx import xx as rename  
from module.xx.xx import *

導入模塊其實就是告訴Python解釋器去解釋那個py文件

• 導入一個py文件，解釋器解釋該py文件
• 導入一個包，解釋器解釋該包下的 __init__.py 文件

 

開源模塊

 

1、下載安裝

下載安裝有兩種方式：

yum 
pip
apt-get
...

方式一

下載源碼
解壓源碼
進入目錄
編譯源碼    python setup.py build
安裝源碼    python setup.py install

方式二

注：在使用源碼安裝時，須要使用到gcc編譯和python開發環境，因此，須要先執行：

yum install gcc
yum install python-devel
或
apt-get python-dev

安裝成功後，模塊會自動安裝到 sys.path 中的某個目錄中，如：

/usr/lib/python2.7/site-packages/

2、導入模塊

同自定義模塊中導入的方式

3、模塊 paramiko

paramiko是一個用於作遠程控制的模塊，使用該模塊能夠對遠程服務器進行命令或文件操做，值得一說的是，fabric和ansible內部的遠程管理就是使用的paramiko來現實。

一、下載安裝

# pycrypto，因爲 paramiko 模塊內部依賴pycrypto，因此先下載安裝pycrypto
 
# 下載安裝 pycrypto
wget http://files.cnblogs.com/files/wupeiqi/pycrypto-2.6.1.tar.gz
tar -xvf pycrypto-2.6.1.tar.gz
cd pycrypto-2.6.1
python setup.py build
python setup.py install
 
# 進入python環境，導入Crypto檢查是否安裝成功
 
# 下載安裝 paramiko
wget http://files.cnblogs.com/files/wupeiqi/paramiko-1.10.1.tar.gz
tar -xvf paramiko-1.10.1.tar.gz
cd paramiko-1.10.1
python setup.py build
python setup.py install
 
# 進入python環境，導入paramiko檢查是否安裝成功

二、使用模塊

#!/usr/bin/env python
#coding:utf-8

import paramiko

ssh = paramiko.SSHClient()
ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())
ssh.connect('192.168.1.108', 22, 'alex', '123')
stdin, stdout, stderr = ssh.exec_command('df')
print stdout.read()
ssh.close();

執行命令 - 經過用戶名和密碼鏈接服務器

import paramiko

private_key_path = '/home/auto/.ssh/id_rsa'
key = paramiko.RSAKey.from_private_key_file(private_key_path)

ssh = paramiko.SSHClient()
ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())
ssh.connect('主機名 ', 端口, '用戶名', key)

stdin, stdout, stderr = ssh.exec_command('df')
print stdout.read()
ssh.close()

執行命令 - 過密鑰連接服務器

import os,sys
import paramiko

t = paramiko.Transport(('182.92.219.86',22))
t.connect(username='wupeiqi',password='123')
sftp = paramiko.SFTPClient.from_transport(t)
sftp.put('/tmp/test.py','/tmp/test.py') 
t.close()


import os,sys
import paramiko

t = paramiko.Transport(('182.92.219.86',22))
t.connect(username='wupeiqi',password='123')
sftp = paramiko.SFTPClient.from_transport(t)
sftp.get('/tmp/test.py','/tmp/test2.py')
t.close()

上傳或者下載文件 - 經過用戶名和密碼

import paramiko

pravie_key_path = '/home/auto/.ssh/id_rsa'
key = paramiko.RSAKey.from_private_key_file(pravie_key_path)

t = paramiko.Transport(('182.92.219.86',22))
t.connect(username='wupeiqi',pkey=key)

sftp = paramiko.SFTPClient.from_transport(t)
sftp.put('/tmp/test3.py','/tmp/test3.py') 

t.close()

import paramiko

pravie_key_path = '/home/auto/.ssh/id_rsa'
key = paramiko.RSAKey.from_private_key_file(pravie_key_path)

t = paramiko.Transport(('182.92.219.86',22))
t.connect(username='wupeiqi',pkey=key)

sftp = paramiko.SFTPClient.from_transport(t)
sftp.get('/tmp/test3.py','/tmp/test4.py') 

t.close()

上傳或下載文件 - 經過密鑰

 

內置模塊

 

time & datetime模塊

import time
import datetime

time
print(time.clock())  #返回處理器時間，3.3之後廢棄 4.444098792316153e-07
print(time.process_time()) #返回處理器時間 0.031200199999999997
print(time.time())     #返回當前系統時間戳 1463472071.3892002
print(time.ctime())    #返回當前系統時間 Tue May 17 16:01:11 2016
print(time.ctime(time.time()-86400))   #轉換成字符串格式 Mon May 16 16:01:11 2016
print(time.gmtime(time.time()-86400))  #將時間戳轉換成struct_time格式 time.struct_time(tm_year=2016, tm_mon=5, tm_mday=16, tm_hour=8, tm_min=1, tm_sec=11, tm_wday=0, tm_yday=137, tm_isdst=0)
print(time.localtime(time.time()-86400))  #將時間戳轉換成struct_time格式,本地時間。 time.struct_time(tm_year=2016, tm_mon=5, tm_mday=16, tm_hour=16, tm_min=13, tm_sec=25, tm_wday=0, tm_yday=137, tm_isdst=0)
print(time.mktime(time.localtime()))  #與time.localtime()功能相反,將struct_time格式轉回成時間戳格式  1463472904.0
time.sleep(4) #sleep 每隔四秒以執行
print(time.strftime("%Y-%m-%d %H:%M:%S",time.gmtime()) ) #將struct_time格式轉成指定的字符串格式  2016-05-17 08:16:22

datetime
print(datetime.date.today()) #輸出格式 2016-05-17
print(datetime.date.fromtimestamp(time.time()-86400) ) # 將時間戳轉成日期格式 2016-05-16
current_time = datetime.datetime.now() #
print(current_time) #輸出2016-05-17 16:17:59.863200
print(current_time.timetuple()) #返回struct_time格式  time.struct_time(tm_year=2016, tm_mon=5, tm_mday=17, tm_hour=16, tm_min=17, tm_sec=59, tm_wday=1, tm_yday=138, tm_isdst=-1)

#datetime.replace([year[, month[, day[, hour[, minute[, second[, microsecond[, tzinfo]]]]]]]])
print(current_time.replace(2016,5,17)) #輸出2016-05-17 16:19:33.753200,返回當前時間,但指定的值將被替換

str_to_date = datetime.datetime.strptime("21/11/06 16:30", "%d/%m/%y %H:%M") #將字符串轉換成日期格式
new_date1 = datetime.datetime.now() + datetime.timedelta(days=10) #比如今加10天 2016-05-27 16:21:16.279200
new_date2 = datetime.datetime.now() + datetime.timedelta(days=-10) #比如今減10天 2016-05-07 16:21:44.459200
new_date3 = datetime.datetime.now() + datetime.timedelta(hours=-10) #比如今減10小時 2016-05-17 06:22:01.299200
new_date4 = datetime.datetime.now() + datetime.timedelta(seconds=120) #比如今+120s 2016-05-17 16:24:10.917200
new_date5 = datetime.datetime.now() + datetime.timedelta(weeks=20) #比如今+10周 2016-10-04 16:23:02.904200
print(new_date5)

Directive	Meaning	Notes
%a	Locale’s abbreviated weekday name.
%A	Locale’s full weekday name.
%b	Locale’s abbreviated month name.
%B	Locale’s full month name.
%c	Locale’s appropriate date and time representation.
%d	Day of the month as a decimal number [01,31].
%H	Hour (24-hour clock) as a decimal number [00,23].
%I	Hour (12-hour clock) as a decimal number [01,12].
%j	Day of the year as a decimal number [001,366].
%m	Month as a decimal number [01,12].
%M	Minute as a decimal number [00,59].
%p	Locale’s equivalent of either AM or PM.	(1)
%S	Second as a decimal number [00,61].	(2)
%U	Week number of the year (Sunday as the first day of the week) as a decimal number [00,53]. All days in a new year preceding the first Sunday are considered to be in week 0.	(3)
%w	Weekday as a decimal number [0(Sunday),6].
%W	Week number of the year (Monday as the first day of the week) as a decimal number [00,53]. All days in a new year preceding the first Monday are considered to be in week 0.	(3)
%x	Locale’s appropriate date representation.
%X	Locale’s appropriate time representation.
%y	Year without century as a decimal number [00,99].
%Y	Year with century as a decimal number.
%z	Time zone offset indicating a positive or negative time difference from UTC/GMT of the form +HHMM or -HHMM, where H represents decimal hour digits and M represents decimal minute digits [-23:59, +23:59].
%Z	Time zone name (no characters if no time zone exists).
%%	A literal '%' character.

 

random模塊

隨機數

mport random
print random.random()
print random.randint(1,2)
print random.randrange(1,10)

生成隨機驗證碼

import  random
tmp = ""
for i in range(6):
    rad1 = random.randrange(4)
    if rad1 ==1 or rad1 ==3:
        rad2 = random.randrange(0,9)
        tmp += str(rad2)
    else:
        rad3 = random.randrange(65,90)
        tmp += chr(rad3)
print(tmp)

sys模塊

import sys
import time
print(sys.argv)    #['C:/Users/Administrator/PycharmProjects/zyl/day-6/datetime,time模塊/SYS.PY.py']

print(sys.path)    #返回模塊的搜索路徑，初始化時使用PYTHONPATH環境變量的值

print(exit())   #退出程序，正常退出時exit(0)

print(sys.version)  #3.5.1 (v3.5.1:37a07cee5969, Dec  6 2015, 01:54:25) [MSC v.1900 64 bit (AMD64)]

print(sys.maxsize)   #9223372036854775807  最大的Int值

print(sys.platform)  #win32       操做系統類型


####################################安裝包流程不換行顯示##################################
for  i in range(31):
    sys.stdout.write("\r")         #清空當前數據網上疊加
    sys.stdout.write("%s%% | %s " %(int(i/30*100),int(i/30*100)*"#"))
    sys.stdout.flush()
    time.sleep(0.3)

####################################安裝流程換行顯示####################################

for i in range(101):
    sys.stdout.write("\r")
    sys.stdout.write("%s%% | %s \n" %(i,i*"#"))
    sys.stdout.flush()
    time.sleep(0.1)

　

json & pickle 模塊

用於序列化的兩個模塊

• json，用於字符串 和 python數據類型間進行轉換
• pickle，用於python特有的類型 和 python的數據類型間進行轉換

Json模塊提供了四個功能：dumps、dump、loads、load

pickle模塊提供了四個功能：dumps、dump、loads、load

import pickle

accounts = {
    1000: {
        'name':'Zhangyanlin',
        'email': '75501664@126.com',
        'passwd': 'abc123',
        'balance': 15000,
        'phone': 13651054608,
        'bank_acc':{
            'ICBC':14324234,
            'CBC' : 235234,
            'ABC' : 35235423
        }
    },
    1001: {
        'name': 'CaiXin Guo',
        'email': 'caixin@126.com',
        'passwd': 'abc145323',
        'balance': -15000,
        'phone': 1345635345,
        'bank_acc': {
            'ICBC': 4334343,
        }
    },
}

################################原始寫入文件中去###############################
with open("zhang","wb") as f:
    f.write(pickle.dumps(accounts))               #打開文件將原數據保存到文件中


################################購物環節#######################################
with open("zhang","rb") as f:
   zhang_dic = pickle.loads(f.read())             #讀取出文件裏的內容賦值給zhang_dic變量

zhang_dic[1000]['balance'] -= 1000              #購物消費100，總價減去1000塊錢


with open("zhang","wb") as f:
    f.write(pickle.dumps(zhang_dic))              #寫入到數據中去

##############################刷新購物後文件裏面的數據#########################

with open("zhang","rb") as f:
    shop_old = pickle.loads(f.read())          #把新數據更新到文件中去
print(shop_old)

pickle 購物實例

 

#json.loads(參數)將字符串轉換成python識別的字符
li = '[11,22,33,44,55,66,77,88,99]'
dic = '{"sdkf":"123","askd":"123"}'
print(json.loads(li),type(json.loads(li)))    #列表類型
print(json.loads(dic),type(json.loads(dic)))  #字典類型

#json.dumps(參數)將python字符轉換成其餘語言識別的字符
li = [11,22,33,44,55]
dic = {"sdkf":"123","askd":"123"}
print(json.dumps(li),type(json.dumps(li)))        #轉成字符串
print(json.dumps(dic),type(json.dumps(dic)))      #轉成字符串

Json實例

 

 

collection系列

一、計數器（counter）

Counter是對字典類型的補充，用於追蹤值的出現次數。

ps：具有字典的全部功能 + 本身的功能

c = Counter('abcdeabcdabcaba')
print c
輸出：Counter({'a': 5, 'b': 4, 'c': 3, 'd': 2, 'e': 1})

########################################################################
###  Counter
########################################################################

class Counter(dict):
    '''Dict subclass for counting hashable items.  Sometimes called a bag
    or multiset.  Elements are stored as dictionary keys and their counts
    are stored as dictionary values.

    >>> c = Counter('abcdeabcdabcaba')  # count elements from a string

    >>> c.most_common(3)                # three most common elements
    [('a', 5), ('b', 4), ('c', 3)]
    >>> sorted(c)                       # list all unique elements
    ['a', 'b', 'c', 'd', 'e']
    >>> ''.join(sorted(c.elements()))   # list elements with repetitions
    'aaaaabbbbcccdde'
    >>> sum(c.values())                 # total of all counts

    >>> c['a']                          # count of letter 'a'
    >>> for elem in 'shazam':           # update counts from an iterable
    ...     c[elem] += 1                # by adding 1 to each element's count
    >>> c['a']                          # now there are seven 'a'
    >>> del c['b']                      # remove all 'b'
    >>> c['b']                          # now there are zero 'b'

    >>> d = Counter('simsalabim')       # make another counter
    >>> c.update(d)                     # add in the second counter
    >>> c['a']                          # now there are nine 'a'

    >>> c.clear()                       # empty the counter
    >>> c
    Counter()

    Note:  If a count is set to zero or reduced to zero, it will remain
    in the counter until the entry is deleted or the counter is cleared:

    >>> c = Counter('aaabbc')
    >>> c['b'] -= 2                     # reduce the count of 'b' by two
    >>> c.most_common()                 # 'b' is still in, but its count is zero
    [('a', 3), ('c', 1), ('b', 0)]

    '''
    # References:
    #   http://en.wikipedia.org/wiki/Multiset
    #   http://www.gnu.org/software/smalltalk/manual-base/html_node/Bag.html
    #   http://www.demo2s.com/Tutorial/Cpp/0380__set-multiset/Catalog0380__set-multiset.htm
    #   http://code.activestate.com/recipes/259174/
    #   Knuth, TAOCP Vol. II section 4.6.3

    def __init__(self, iterable=None, **kwds):
        '''Create a new, empty Counter object.  And if given, count elements
        from an input iterable.  Or, initialize the count from another mapping
        of elements to their counts.

        >>> c = Counter()                           # a new, empty counter
        >>> c = Counter('gallahad')                 # a new counter from an iterable
        >>> c = Counter({'a': 4, 'b': 2})           # a new counter from a mapping
        >>> c = Counter(a=4, b=2)                   # a new counter from keyword args

        '''
        super(Counter, self).__init__()
        self.update(iterable, **kwds)

    def __missing__(self, key):
        """ 對於不存在的元素，返回計數器爲0 """
        'The count of elements not in the Counter is zero.'
        # Needed so that self[missing_item] does not raise KeyError
        return 0

    def most_common(self, n=None):
        """ 數量大於等n的全部元素和計數器 """
        '''List the n most common elements and their counts from the most
        common to the least.  If n is None, then list all element counts.

        >>> Counter('abcdeabcdabcaba').most_common(3)
        [('a', 5), ('b', 4), ('c', 3)]

        '''
        # Emulate Bag.sortedByCount from Smalltalk
        if n is None:
            return sorted(self.iteritems(), key=_itemgetter(1), reverse=True)
        return _heapq.nlargest(n, self.iteritems(), key=_itemgetter(1))

    def elements(self):
        """ 計數器中的全部元素，注：此處非全部元素集合，而是包含全部元素集合的迭代器 """
        '''Iterator over elements repeating each as many times as its count.

        >>> c = Counter('ABCABC')
        >>> sorted(c.elements())
        ['A', 'A', 'B', 'B', 'C', 'C']

        # Knuth's example for prime factors of 1836:  2**2 * 3**3 * 17**1
        >>> prime_factors = Counter({2: 2, 3: 3, 17: 1})
        >>> product = 1
        >>> for factor in prime_factors.elements():     # loop over factors
        ...     product *= factor                       # and multiply them
        >>> product

        Note, if an element's count has been set to zero or is a negative
        number, elements() will ignore it.

        '''
        # Emulate Bag.do from Smalltalk and Multiset.begin from C++.
        return _chain.from_iterable(_starmap(_repeat, self.iteritems()))

    # Override dict methods where necessary

    @classmethod
    def fromkeys(cls, iterable, v=None):
        # There is no equivalent method for counters because setting v=1
        # means that no element can have a count greater than one.
        raise NotImplementedError(
            'Counter.fromkeys() is undefined.  Use Counter(iterable) instead.')

    def update(self, iterable=None, **kwds):
        """ 更新計數器，其實就是增長；若是原來沒有，則新建，若是有則加一 """
        '''Like dict.update() but add counts instead of replacing them.

        Source can be an iterable, a dictionary, or another Counter instance.

        >>> c = Counter('which')
        >>> c.update('witch')           # add elements from another iterable
        >>> d = Counter('watch')
        >>> c.update(d)                 # add elements from another counter
        >>> c['h']                      # four 'h' in which, witch, and watch

        '''
        # The regular dict.update() operation makes no sense here because the
        # replace behavior results in the some of original untouched counts
        # being mixed-in with all of the other counts for a mismash that
        # doesn't have a straight-forward interpretation in most counting
        # contexts.  Instead, we implement straight-addition.  Both the inputs
        # and outputs are allowed to contain zero and negative counts.

        if iterable is not None:
            if isinstance(iterable, Mapping):
                if self:
                    self_get = self.get
                    for elem, count in iterable.iteritems():
                        self[elem] = self_get(elem, 0) + count
                else:
                    super(Counter, self).update(iterable) # fast path when counter is empty
            else:
                self_get = self.get
                for elem in iterable:
                    self[elem] = self_get(elem, 0) + 1
        if kwds:
            self.update(kwds)

    def subtract(self, iterable=None, **kwds):
        """ 相減，原來的計數器中的每個元素的數量減去後添加的元素的數量 """
        '''Like dict.update() but subtracts counts instead of replacing them.
        Counts can be reduced below zero.  Both the inputs and outputs are
        allowed to contain zero and negative counts.

        Source can be an iterable, a dictionary, or another Counter instance.

        >>> c = Counter('which')
        >>> c.subtract('witch')             # subtract elements from another iterable
        >>> c.subtract(Counter('watch'))    # subtract elements from another counter
        >>> c['h']                          # 2 in which, minus 1 in witch, minus 1 in watch
        >>> c['w']                          # 1 in which, minus 1 in witch, minus 1 in watch
        -1

        '''
        if iterable is not None:
            self_get = self.get
            if isinstance(iterable, Mapping):
                for elem, count in iterable.items():
                    self[elem] = self_get(elem, 0) - count
            else:
                for elem in iterable:
                    self[elem] = self_get(elem, 0) - 1
        if kwds:
            self.subtract(kwds)

    def copy(self):
        """ 拷貝 """
        'Return a shallow copy.'
        return self.__class__(self)

    def __reduce__(self):
        """ 返回一個元組（類型，元組） """
        return self.__class__, (dict(self),)

    def __delitem__(self, elem):
        """ 刪除元素 """
        'Like dict.__delitem__() but does not raise KeyError for missing values.'
        if elem in self:
            super(Counter, self).__delitem__(elem)

    def __repr__(self):
        if not self:
            return '%s()' % self.__class__.__name__
        items = ', '.join(map('%r: %r'.__mod__, self.most_common()))
        return '%s({%s})' % (self.__class__.__name__, items)

    # Multiset-style mathematical operations discussed in:
    #       Knuth TAOCP Volume II section 4.6.3 exercise 19
    #       and at http://en.wikipedia.org/wiki/Multiset
    #
    # Outputs guaranteed to only include positive counts.
    #
    # To strip negative and zero counts, add-in an empty counter:
    #       c += Counter()

    def __add__(self, other):
        '''Add counts from two counters.

        >>> Counter('abbb') + Counter('bcc')
        Counter({'b': 4, 'c': 2, 'a': 1})

        '''
        if not isinstance(other, Counter):
            return NotImplemented
        result = Counter()
        for elem, count in self.items():
            newcount = count + other[elem]
            if newcount > 0:
                result[elem] = newcount
        for elem, count in other.items():
            if elem not in self and count > 0:
                result[elem] = count
        return result

    def __sub__(self, other):
        ''' Subtract count, but keep only results with positive counts.

        >>> Counter('abbbc') - Counter('bccd')
        Counter({'b': 2, 'a': 1})

        '''
        if not isinstance(other, Counter):
            return NotImplemented
        result = Counter()
        for elem, count in self.items():
            newcount = count - other[elem]
            if newcount > 0:
                result[elem] = newcount
        for elem, count in other.items():
            if elem not in self and count < 0:
                result[elem] = 0 - count
        return result

    def __or__(self, other):
        '''Union is the maximum of value in either of the input counters.

        >>> Counter('abbb') | Counter('bcc')
        Counter({'b': 3, 'c': 2, 'a': 1})

        '''
        if not isinstance(other, Counter):
            return NotImplemented
        result = Counter()
        for elem, count in self.items():
            other_count = other[elem]
            newcount = other_count if count < other_count else count
            if newcount > 0:
                result[elem] = newcount
        for elem, count in other.items():
            if elem not in self and count > 0:
                result[elem] = count
        return result

    def __and__(self, other):
        ''' Intersection is the minimum of corresponding counts.

        >>> Counter('abbb') & Counter('bcc')
        Counter({'b': 1})

        '''
        if not isinstance(other, Counter):
            return NotImplemented
        result = Counter()
        for elem, count in self.items():
            other_count = other[elem]
            newcount = count if count < other_count else other_count
            if newcount > 0:
                result[elem] = newcount
        return result

Counter

collection

 

二、有序字典(orderedDict )

orderdDict是對字典類型的補充，他記住了字典元素添加的順序

class OrderedDict(dict):
    'Dictionary that remembers insertion order'
    # An inherited dict maps keys to values.
    # The inherited dict provides __getitem__, __len__, __contains__, and get.
    # The remaining methods are order-aware.
    # Big-O running times for all methods are the same as regular dictionaries.

    # The internal self.__map dict maps keys to links in a doubly linked list.
    # The circular doubly linked list starts and ends with a sentinel element.
    # The sentinel element never gets deleted (this simplifies the algorithm).
    # Each link is stored as a list of length three:  [PREV, NEXT, KEY].

    def __init__(self, *args, **kwds):
        '''Initialize an ordered dictionary.  The signature is the same as
        regular dictionaries, but keyword arguments are not recommended because
        their insertion order is arbitrary.

        '''
        if len(args) > 1:
            raise TypeError('expected at most 1 arguments, got %d' % len(args))
        try:
            self.__root
        except AttributeError:
            self.__root = root = []                     # sentinel node
            root[:] = [root, root, None]
            self.__map = {}
        self.__update(*args, **kwds)

    def __setitem__(self, key, value, dict_setitem=dict.__setitem__):
        'od.__setitem__(i, y) <==> od[i]=y'
        # Setting a new item creates a new link at the end of the linked list,
        # and the inherited dictionary is updated with the new key/value pair.
        if key not in self:
            root = self.__root
            last = root[0]
            last[1] = root[0] = self.__map[key] = [last, root, key]
        return dict_setitem(self, key, value)

    def __delitem__(self, key, dict_delitem=dict.__delitem__):
        'od.__delitem__(y) <==> del od[y]'
        # Deleting an existing item uses self.__map to find the link which gets
        # removed by updating the links in the predecessor and successor nodes.
        dict_delitem(self, key)
        link_prev, link_next, _ = self.__map.pop(key)
        link_prev[1] = link_next                        # update link_prev[NEXT]
        link_next[0] = link_prev                        # update link_next[PREV]

    def __iter__(self):
        'od.__iter__() <==> iter(od)'
        # Traverse the linked list in order.
        root = self.__root
        curr = root[1]                                  # start at the first node
        while curr is not root:
            yield curr[2]                               # yield the curr[KEY]
            curr = curr[1]                              # move to next node

    def __reversed__(self):
        'od.__reversed__() <==> reversed(od)'
        # Traverse the linked list in reverse order.
        root = self.__root
        curr = root[0]                                  # start at the last node
        while curr is not root:
            yield curr[2]                               # yield the curr[KEY]
            curr = curr[0]                              # move to previous node

    def clear(self):
        'od.clear() -> None.  Remove all items from od.'
        root = self.__root
        root[:] = [root, root, None]
        self.__map.clear()
        dict.clear(self)

    # -- the following methods do not depend on the internal structure --

    def keys(self):
        'od.keys() -> list of keys in od'
        return list(self)

    def values(self):
        'od.values() -> list of values in od'
        return [self[key] for key in self]

    def items(self):
        'od.items() -> list of (key, value) pairs in od'
        return [(key, self[key]) for key in self]

    def iterkeys(self):
        'od.iterkeys() -> an iterator over the keys in od'
        return iter(self)

    def itervalues(self):
        'od.itervalues -> an iterator over the values in od'
        for k in self:
            yield self[k]

    def iteritems(self):
        'od.iteritems -> an iterator over the (key, value) pairs in od'
        for k in self:
            yield (k, self[k])

    update = MutableMapping.update

    __update = update # let subclasses override update without breaking __init__

    __marker = object()

    def pop(self, key, default=__marker):
        '''od.pop(k[,d]) -> v, remove specified key and return the corresponding
        value.  If key is not found, d is returned if given, otherwise KeyError
        is raised.

        '''
        if key in self:
            result = self[key]
            del self[key]
            return result
        if default is self.__marker:
            raise KeyError(key)
        return default

    def setdefault(self, key, default=None):
        'od.setdefault(k[,d]) -> od.get(k,d), also set od[k]=d if k not in od'
        if key in self:
            return self[key]
        self[key] = default
        return default

    def popitem(self, last=True):
        '''od.popitem() -> (k, v), return and remove a (key, value) pair.
        Pairs are returned in LIFO order if last is true or FIFO order if false.

        '''
        if not self:
            raise KeyError('dictionary is empty')
        key = next(reversed(self) if last else iter(self))
        value = self.pop(key)
        return key, value

    def __repr__(self, _repr_running={}):
        'od.__repr__() <==> repr(od)'
        call_key = id(self), _get_ident()
        if call_key in _repr_running:
            return '...'
        _repr_running[call_key] = 1
        try:
            if not self:
                return '%s()' % (self.__class__.__name__,)
            return '%s(%r)' % (self.__class__.__name__, self.items())
        finally:
            del _repr_running[call_key]

    def __reduce__(self):
        'Return state information for pickling'
        items = [[k, self[k]] for k in self]
        inst_dict = vars(self).copy()
        for k in vars(OrderedDict()):
            inst_dict.pop(k, None)
        if inst_dict:
            return (self.__class__, (items,), inst_dict)
        return self.__class__, (items,)

    def copy(self):
        'od.copy() -> a shallow copy of od'
        return self.__class__(self)

    @classmethod
    def fromkeys(cls, iterable, value=None):
        '''OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S.
        If not specified, the value defaults to None.

        '''
        self = cls()
        for key in iterable:
            self[key] = value
        return self

    def __eq__(self, other):
        '''od.__eq__(y) <==> od==y.  Comparison to another OD is order-sensitive
        while comparison to a regular mapping is order-insensitive.

        '''
        if isinstance(other, OrderedDict):
            return dict.__eq__(self, other) and all(_imap(_eq, self, other))
        return dict.__eq__(self, other)

    def __ne__(self, other):
        'od.__ne__(y) <==> od!=y'
        return not self == other

    # -- the following methods support python 3.x style dictionary views --

    def viewkeys(self):
        "od.viewkeys() -> a set-like object providing a view on od's keys"
        return KeysView(self)

    def viewvalues(self):
        "od.viewvalues() -> an object providing a view on od's values"
        return ValuesView(self)

    def viewitems(self):
        "od.viewitems() -> a set-like object providing a view on od's items"
        return ItemsView(self)

orderedDict

 

三、默認字典(defaultdict) 

學前需求：

有以下值集合 [11,22,33,44,55,66,77,88,99,90...]，將全部大於 66 的值保存至字典的第一個key中，將小於 66 的值保存至第二個key的值中。
即： {'k1': 大於66 , 'k2': 小於66}

values = [11, 22, 33,44,55,66,77,88,99,90]

my_dict = {}

for value in  values:
    if value>66:
        if my_dict.has_key('k1'):
            my_dict['k1'].append(value)
        else:
            my_dict['k1'] = [value]
    else:
        if my_dict.has_key('k2'):
            my_dict['k2'].append(value)
        else:
            my_dict['k2'] = [value]

原生字典

from collections import defaultdict

values = [11, 22, 33,44,55,66,77,88,99,90]

my_dict = defaultdict(list)

for value in  values:
    if value>66:
        my_dict['k1'].append(value)
    else:
        my_dict['k2'].append(value)

defaultdict解決方法

defaultdict是對字典的類型的補充，他默認給字典的值設置了一個類型。

class defaultdict(dict):
    """
    defaultdict(default_factory[, ...]) --> dict with default factory
    
    The default factory is called without arguments to produce
    a new value when a key is not present, in __getitem__ only.
    A defaultdict compares equal to a dict with the same items.
    All remaining arguments are treated the same as if they were
    passed to the dict constructor, including keyword arguments.
    """
    def copy(self): # real signature unknown; restored from __doc__
        """ D.copy() -> a shallow copy of D. """
        pass

    def __copy__(self, *args, **kwargs): # real signature unknown
        """ D.copy() -> a shallow copy of D. """
        pass

    def __getattribute__(self, name): # real signature unknown; restored from __doc__
        """ x.__getattribute__('name') <==> x.name """
        pass

    def __init__(self, default_factory=None, **kwargs): # known case of _collections.defaultdict.__init__
        """
        defaultdict(default_factory[, ...]) --> dict with default factory
        
        The default factory is called without arguments to produce
        a new value when a key is not present, in __getitem__ only.
        A defaultdict compares equal to a dict with the same items.
        All remaining arguments are treated the same as if they were
        passed to the dict constructor, including keyword arguments.
        
        # (copied from class doc)
        """
        pass

    def __missing__(self, key): # real signature unknown; restored from __doc__
        """
        __missing__(key) # Called by __getitem__ for missing key; pseudo-code:
          if self.default_factory is None: raise KeyError((key,))
          self[key] = value = self.default_factory()
          return value
        """
        pass

    def __reduce__(self, *args, **kwargs): # real signature unknown
        """ Return state information for pickling. """
        pass

    def __repr__(self): # real signature unknown; restored from __doc__
        """ x.__repr__() <==> repr(x) """
        pass

    default_factory = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default
    """Factory for default value called by __missing__()."""

defaultdict

四、可命名元組(namedtuple) 

根據nametuple能夠建立一個包含tuple全部功能以及其餘功能的類型。

import collections
 
Mytuple = collections.namedtuple('Mytuple',['x', 'y', 'z'])

class Mytuple(__builtin__.tuple)
 |  Mytuple(x, y)
 |  
 |  Method resolution order:
 |      Mytuple
 |      __builtin__.tuple
 |      __builtin__.object
 |  
 |  Methods defined here:
 |  
 |  __getnewargs__(self)
 |      Return self as a plain tuple.  Used by copy and pickle.
 |  
 |  __getstate__(self)
 |      Exclude the OrderedDict from pickling
 |  
 |  __repr__(self)
 |      Return a nicely formatted representation string
 |  
 |  _asdict(self)
 |      Return a new OrderedDict which maps field names to their values
 |  
 |  _replace(_self, **kwds)
 |      Return a new Mytuple object replacing specified fields with new values
 |  
 |  ----------------------------------------------------------------------
 |  Class methods defined here:
 |  
 |  _make(cls, iterable, new=<built-in method __new__ of type object>, len=<built-in function len>) from __builtin__.type
 |      Make a new Mytuple object from a sequence or iterable
 |  
 |  ----------------------------------------------------------------------
 |  Static methods defined here:
 |  
 |  __new__(_cls, x, y)
 |      Create new instance of Mytuple(x, y)
 |  
 |  ----------------------------------------------------------------------
 |  Data descriptors defined here:
 |  
 |  __dict__
 |      Return a new OrderedDict which maps field names to their values
 |  
 |  x
 |      Alias for field number 0
 |  
 |  y
 |      Alias for field number 1
 |  
 |  ----------------------------------------------------------------------
 |  Data and other attributes defined here:
 |  
 |  _fields = ('x', 'y')
 |  
 |  ----------------------------------------------------------------------
 |  Methods inherited from __builtin__.tuple:
 |  
 |  __add__(...)
 |      x.__add__(y) <==> x+y
 |  
 |  __contains__(...)
 |      x.__contains__(y) <==> y in x
 |  
 |  __eq__(...)
 |      x.__eq__(y) <==> x==y
 |  
 |  __ge__(...)
 |      x.__ge__(y) <==> x>=y
 |  
 |  __getattribute__(...)
 |      x.__getattribute__('name') <==> x.name
 |  
 |  __getitem__(...)
 |      x.__getitem__(y) <==> x[y]
 |  
 |  __getslice__(...)
 |      x.__getslice__(i, j) <==> x[i:j]
 |      
 |      Use of negative indices is not supported.
 |  
 |  __gt__(...)
 |      x.__gt__(y) <==> x>y
 |  
 |  __hash__(...)
 |      x.__hash__() <==> hash(x)
 |  
 |  __iter__(...)
 |      x.__iter__() <==> iter(x)
 |  
 |  __le__(...)
 |      x.__le__(y) <==> x<=y
 |  
 |  __len__(...)
 |      x.__len__() <==> len(x)
 |  
 |  __lt__(...)
 |      x.__lt__(y) <==> x<y
 |  
 |  __mul__(...)
 |      x.__mul__(n) <==> x*n
 |  
 |  __ne__(...)
 |      x.__ne__(y) <==> x!=y
 |  
 |  __rmul__(...)
 |      x.__rmul__(n) <==> n*x
 |  
 |  __sizeof__(...)
 |      T.__sizeof__() -- size of T in memory, in bytes
 |  
 |  count(...)
 |      T.count(value) -> integer -- return number of occurrences of value
 |  
 |  index(...)
 |      T.index(value, [start, [stop]]) -> integer -- return first index of value.
 |      Raises ValueError if the value is not present.

Mytuple

Mytuple

五、雙向隊列(deque)

一個線程安全的雙向隊列

class deque(object):
    """
    deque([iterable[, maxlen]]) --> deque object
    
    Build an ordered collection with optimized access from its endpoints.
    """
    def append(self, *args, **kwargs): # real signature unknown
        """ Add an element to the right side of the deque. """
        pass

    def appendleft(self, *args, **kwargs): # real signature unknown
        """ Add an element to the left side of the deque. """
        pass

    def clear(self, *args, **kwargs): # real signature unknown
        """ Remove all elements from the deque. """
        pass

    def count(self, value): # real signature unknown; restored from __doc__
        """ D.count(value) -> integer -- return number of occurrences of value """
        return 0

    def extend(self, *args, **kwargs): # real signature unknown
        """ Extend the right side of the deque with elements from the iterable """
        pass

    def extendleft(self, *args, **kwargs): # real signature unknown
        """ Extend the left side of the deque with elements from the iterable """
        pass

    def pop(self, *args, **kwargs): # real signature unknown
        """ Remove and return the rightmost element. """
        pass

    def popleft(self, *args, **kwargs): # real signature unknown
        """ Remove and return the leftmost element. """
        pass

    def remove(self, value): # real signature unknown; restored from __doc__
        """ D.remove(value) -- remove first occurrence of value. """
        pass

    def reverse(self): # real signature unknown; restored from __doc__
        """ D.reverse() -- reverse *IN PLACE* """
        pass

    def rotate(self, *args, **kwargs): # real signature unknown
        """ Rotate the deque n steps to the right (default n=1).  If n is negative, rotates left. """
        pass

    def __copy__(self, *args, **kwargs): # real signature unknown
        """ Return a shallow copy of a deque. """
        pass

    def __delitem__(self, y): # real signature unknown; restored from __doc__
        """ x.__delitem__(y) <==> del x[y] """
        pass

    def __eq__(self, y): # real signature unknown; restored from __doc__
        """ x.__eq__(y) <==> x==y """
        pass

    def __getattribute__(self, name): # real signature unknown; restored from __doc__
        """ x.__getattribute__('name') <==> x.name """
        pass

    def __getitem__(self, y): # real signature unknown; restored from __doc__
        """ x.__getitem__(y) <==> x[y] """
        pass

    def __ge__(self, y): # real signature unknown; restored from __doc__
        """ x.__ge__(y) <==> x>=y """
        pass

    def __gt__(self, y): # real signature unknown; restored from __doc__
        """ x.__gt__(y) <==> x>y """
        pass

    def __iadd__(self, y): # real signature unknown; restored from __doc__
        """ x.__iadd__(y) <==> x+=y """
        pass

    def __init__(self, iterable=(), maxlen=None): # known case of _collections.deque.__init__
        """
        deque([iterable[, maxlen]]) --> deque object
        
        Build an ordered collection with optimized access from its endpoints.
        # (copied from class doc)
        """
        pass

    def __iter__(self): # real signature unknown; restored from __doc__
        """ x.__iter__() <==> iter(x) """
        pass

    def __len__(self): # real signature unknown; restored from __doc__
        """ x.__len__() <==> len(x) """
        pass

    def __le__(self, y): # real signature unknown; restored from __doc__
        """ x.__le__(y) <==> x<=y """
        pass

    def __lt__(self, y): # real signature unknown; restored from __doc__
        """ x.__lt__(y) <==> x<y """
        pass

    @staticmethod # known case of __new__
    def __new__(S, *more): # real signature unknown; restored from __doc__
        """ T.__new__(S, ...) -> a new object with type S, a subtype of T """
        pass

    def __ne__(self, y): # real signature unknown; restored from __doc__
        """ x.__ne__(y) <==> x!=y """
        pass

    def __reduce__(self, *args, **kwargs): # real signature unknown
        """ Return state information for pickling. """
        pass

    def __repr__(self): # real signature unknown; restored from __doc__
        """ x.__repr__() <==> repr(x) """
        pass

    def __reversed__(self): # real signature unknown; restored from __doc__
        """ D.__reversed__() -- return a reverse iterator over the deque """
        pass

    def __setitem__(self, i, y): # real signature unknown; restored from __doc__
        """ x.__setitem__(i, y) <==> x[i]=y """
        pass

    def __sizeof__(self): # real signature unknown; restored from __doc__
        """ D.__sizeof__() -- size of D in memory, in bytes """
        pass

    maxlen = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default
    """maximum size of a deque or None if unbounded"""


    __hash__ = None

deque

注：既然有雙向隊列，也有單項隊列（先進先出 FIFO ）

class Queue:
    """Create a queue object with a given maximum size.

    If maxsize is <= 0, the queue size is infinite.
    """
    def __init__(self, maxsize=0):
        self.maxsize = maxsize
        self._init(maxsize)
        # mutex must be held whenever the queue is mutating.  All methods
        # that acquire mutex must release it before returning.  mutex
        # is shared between the three conditions, so acquiring and
        # releasing the conditions also acquires and releases mutex.
        self.mutex = _threading.Lock()
        # Notify not_empty whenever an item is added to the queue; a
        # thread waiting to get is notified then.
        self.not_empty = _threading.Condition(self.mutex)
        # Notify not_full whenever an item is removed from the queue;
        # a thread waiting to put is notified then.
        self.not_full = _threading.Condition(self.mutex)
        # Notify all_tasks_done whenever the number of unfinished tasks
        # drops to zero; thread waiting to join() is notified to resume
        self.all_tasks_done = _threading.Condition(self.mutex)
        self.unfinished_tasks = 0

    def task_done(self):
        """Indicate that a formerly enqueued task is complete.

        Used by Queue consumer threads.  For each get() used to fetch a task,
        a subsequent call to task_done() tells the queue that the processing
        on the task is complete.

        If a join() is currently blocking, it will resume when all items
        have been processed (meaning that a task_done() call was received
        for every item that had been put() into the queue).

        Raises a ValueError if called more times than there were items
        placed in the queue.
        """
        self.all_tasks_done.acquire()
        try:
            unfinished = self.unfinished_tasks - 1
            if unfinished <= 0:
                if unfinished < 0:
                    raise ValueError('task_done() called too many times')
                self.all_tasks_done.notify_all()
            self.unfinished_tasks = unfinished
        finally:
            self.all_tasks_done.release()

    def join(self):
        """Blocks until all items in the Queue have been gotten and processed.

        The count of unfinished tasks goes up whenever an item is added to the
        queue. The count goes down whenever a consumer thread calls task_done()
        to indicate the item was retrieved and all work on it is complete.

        When the count of unfinished tasks drops to zero, join() unblocks.
        """
        self.all_tasks_done.acquire()
        try:
            while self.unfinished_tasks:
                self.all_tasks_done.wait()
        finally:
            self.all_tasks_done.release()

    def qsize(self):
        """Return the approximate size of the queue (not reliable!)."""
        self.mutex.acquire()
        n = self._qsize()
        self.mutex.release()
        return n

    def empty(self):
        """Return True if the queue is empty, False otherwise (not reliable!)."""
        self.mutex.acquire()
        n = not self._qsize()
        self.mutex.release()
        return n

    def full(self):
        """Return True if the queue is full, False otherwise (not reliable!)."""
        self.mutex.acquire()
        n = 0 < self.maxsize == self._qsize()
        self.mutex.release()
        return n

    def put(self, item, block=True, timeout=None):
        """Put an item into the queue.

        If optional args 'block' is true and 'timeout' is None (the default),
        block if necessary until a free slot is available. If 'timeout' is
        a non-negative number, it blocks at most 'timeout' seconds and raises
        the Full exception if no free slot was available within that time.
        Otherwise ('block' is false), put an item on the queue if a free slot
        is immediately available, else raise the Full exception ('timeout'
        is ignored in that case).
        """
        self.not_full.acquire()
        try:
            if self.maxsize > 0:
                if not block:
                    if self._qsize() == self.maxsize:
                        raise Full
                elif timeout is None:
                    while self._qsize() == self.maxsize:
                        self.not_full.wait()
                elif timeout < 0:
                    raise ValueError("'timeout' must be a non-negative number")
                else:
                    endtime = _time() + timeout
                    while self._qsize() == self.maxsize:
                        remaining = endtime - _time()
                        if remaining <= 0.0:
                            raise Full
                        self.not_full.wait(remaining)
            self._put(item)
            self.unfinished_tasks += 1
            self.not_empty.notify()
        finally:
            self.not_full.release()

    def put_nowait(self, item):
        """Put an item into the queue without blocking.

        Only enqueue the item if a free slot is immediately available.
        Otherwise raise the Full exception.
        """
        return self.put(item, False)

    def get(self, block=True, timeout=None):
        """Remove and return an item from the queue.

        If optional args 'block' is true and 'timeout' is None (the default),
        block if necessary until an item is available. If 'timeout' is
        a non-negative number, it blocks at most 'timeout' seconds and raises
        the Empty exception if no item was available within that time.
        Otherwise ('block' is false), return an item if one is immediately
        available, else raise the Empty exception ('timeout' is ignored
        in that case).
        """
        self.not_empty.acquire()
        try:
            if not block:
                if not self._qsize():
                    raise Empty
            elif timeout is None:
                while not self._qsize():
                    self.not_empty.wait()
            elif timeout < 0:
                raise ValueError("'timeout' must be a non-negative number")
            else:
                endtime = _time() + timeout
                while not self._qsize():
                    remaining = endtime - _time()
                    if remaining <= 0.0:
                        raise Empty
                    self.not_empty.wait(remaining)
            item = self._get()
            self.not_full.notify()
            return item
        finally:
            self.not_empty.release()

    def get_nowait(self):
        """Remove and return an item from the queue without blocking.

        Only get an item if one is immediately available. Otherwise
        raise the Empty exception.
        """
        return self.get(False)

    # Override these methods to implement other queue organizations
    # (e.g. stack or priority queue).
    # These will only be called with appropriate locks held

    # Initialize the queue representation
    def _init(self, maxsize):
        self.queue = deque()

    def _qsize(self, len=len):
        return len(self.queue)

    # Put a new item in the queue
    def _put(self, item):
        self.queue.append(item)

    # Get an item from the queue
    def _get(self):
        return self.queue.popleft()

Queue

 

OS模塊

用於提供系統級別的操做：

os.getcwd()                 獲取當前工做目錄，即當前python腳本工做的目錄路徑
os.chdir("dirname")         改變當前腳本工做目錄；至關於shell下cd
os.curdir                   返回當前目錄: ('.')
os.pardir                   獲取當前目錄的父目錄字符串名：('..')
os.makedirs('dir1/dir2')    可生成多層遞歸目錄
os.removedirs('dirname1')   若目錄爲空，則刪除，並遞歸到上一級目錄，如若也爲空，則刪除，依此類推
os.mkdir('dirname')         生成單級目錄；至關於shell中mkdir dirname
os.rmdir('dirname')         刪除單級空目錄，若目錄不爲空則沒法刪除，報錯；至關於shell中rmdir dirname
os.listdir('dirname')       列出指定目錄下的全部文件和子目錄，包括隱藏文件，並以列表方式打印
os.remove()                 刪除一個文件
os.rename("oldname","new")  重命名文件/目錄
os.stat('path/filename')    獲取文件/目錄信息
os.sep                      操做系統特定的路徑分隔符，win下爲"\\",Linux下爲"/"
os.linesep                  當前平臺使用的行終止符，win下爲"\t\n",Linux下爲"\n"
os.pathsep                  用於分割文件路徑的字符串
os.name                     字符串指示當前使用平臺。win->'nt'; Linux->'posix'
os.system("bash command")   運行shell命令，直接顯示
os.environ                  獲取系統環境變量
os.path.abspath(path)       返回path規範化的絕對路徑
os.path.split(path)         將path分割成目錄和文件名二元組返回
os.path.dirname(path)       返回path的目錄。其實就是os.path.split(path)的第一個元素
os.path.basename(path)      返回path最後的文件名。如何path以／或\結尾，那麼就會返回空值。即os.path.split(path)的第二個元素
os.path.exists(path)        若是path存在，返回True；若是path不存在，返回False
os.path.isabs(path)         若是path是絕對路徑，返回True
os.path.isfile(path)        若是path是一個存在的文件，返回True。不然返回False
os.path.isdir(path)         若是path是一個存在的目錄，則返回True。不然返回False
os.path.join(path1[, path2[, ...]])  將多個路徑組合後返回，第一個絕對路徑以前的參數將被忽略
os.path.getatime(path)      返回path所指向的文件或者目錄的最後存取時間
os.path.getmtime(path)      返回path所指向的文件或者目錄的最後修改時間

　　

hashlib

用於加密相關的操做，代替了md5模塊和sha模塊，主要提供 SHA1, SHA224, SHA256, SHA384, SHA512 ，MD5 算法

import hashlib
 
# ######## md5 ########
hash = hashlib.md5()
# help(hash.update)
hash.update(bytes('admin', encoding='utf-8'))
print(hash.hexdigest())
print(hash.digest())
 
 
######## sha1 ########
 
hash = hashlib.sha1()
hash.update(bytes('admin', encoding='utf-8'))
print(hash.hexdigest())
 
# ######## sha256 ########
 
hash = hashlib.sha256()
hash.update(bytes('admin', encoding='utf-8'))
print(hash.hexdigest())
 
 
# ######## sha384 ########
 
hash = hashlib.sha384()
hash.update(bytes('admin', encoding='utf-8'))
print(hash.hexdigest())
 
# ######## sha512 ########
 
hash = hashlib.sha512()
hash.update(bytes('admin', encoding='utf-8'))
print(hash.hexdigest())

以上加密算法雖然依然很是厲害，但時候存在缺陷，即：經過撞庫能夠反解。因此，有必要對加密算法中添加自定義key再來作加密。

import hashlib
 
# ######## md5 ########
 
hash = hashlib.md5(bytes('898oaFs09f',encoding="utf-8"))
hash.update(bytes('admin',encoding="utf-8"))
print(hash.hexdigest())

python內置還有一個 hmac 模塊，它內部對咱們建立 key 和 內容 進行進一步的處理而後再加密

import hmac
 
h = hmac.new(bytes('898oaFs09f',encoding="utf-8"))
h.update(bytes('admin',encoding="utf-8"))
print(h.hexdigest())

import hashlib

def hash(pwd):
    hash = hashlib.md5(bytes("zhangyanlin",encoding='utf-8'))
    hash.update(bytes(pwd,encoding='utf-8'))
    return hash.hexdigest()

def login(username,passwd):
    with open("db",'r',encoding="utf-8") as f:
        for i in f:
            i  = i.strip().split("|")
            if i[0] == username and i[1] == hash(passwd):
                return True

def zc_login(username,passwd):
    with open("db","a",encoding='utf-8') as f:
        use_pwd =  username + "|" + hash(passwd) + "\n"
        f.write(use_pwd)
        return True


choice = input("1.登陸；2.註冊 \n請您選擇：")
if choice == "1":
    for i in range(3):
        user = input("請輸入用戶名：")
        pwd  = input("請輸入密碼：")
        login_1 = login(user,pwd)
        if login_1:
            print("登陸成功")
            break
        else:
            print('登陸失敗！')
            continue
elif choice == "2":
    user = input("請輸入用戶名：")
    pwd  = input("請輸入密碼：")
    login_2 = zc_login(user,pwd)
    if login_2:
        print("註冊成功！")

實例

 

XML

XML是實現不一樣語言或程序之間進行數據交換的協議，XML文件格式以下：

<data>
    <country name="Liechtenstein">
        <rank updated="yes">2</rank>
        <year>2023</year>
        <gdppc>141100</gdppc>
        <neighbor direction="E" name="Austria" />
        <neighbor direction="W" name="Switzerland" />
    </country>
    <country name="Singapore">
        <rank updated="yes">5</rank>
        <year>2026</year>
        <gdppc>59900</gdppc>
        <neighbor direction="N" name="Malaysia" />
    </country>
    <country name="Panama">
        <rank updated="yes">69</rank>
        <year>2026</year>
        <gdppc>13600</gdppc>
        <neighbor direction="W" name="Costa Rica" />
        <neighbor direction="E" name="Colombia" />
    </country>
</data>

一、解析XML

from xml.etree import ElementTree as ET


# 打開文件，讀取XML內容
str_xml = open('xo.xml', 'r').read()

# 將字符串解析成xml特殊對象，root代指xml文件的根節點
root = ET.XML(str_xml)

利用ElementTree.XML將字符串解析成xml對象

from xml.etree import ElementTree as ET

# 直接解析xml文件
tree = ET.parse("xo.xml")

# 獲取xml文件的根節點
root = tree.getroot()

利用ElementTree.parse將文件直接解析成xml對象

二、操做XML

XML格式類型是節點嵌套節點，對於每個節點均有如下功能，以便對當前節點進行操做：

class Element:
    """An XML element.

    This class is the reference implementation of the Element interface.

    An element's length is its number of subelements.  That means if you
    want to check if an element is truly empty, you should check BOTH
    its length AND its text attribute.

    The element tag, attribute names, and attribute values can be either
    bytes or strings.

    *tag* is the element name.  *attrib* is an optional dictionary containing
    element attributes. *extra* are additional element attributes given as
    keyword arguments.

    Example form:
        <tag attrib>text<child/>...</tag>tail

    """

    當前節點的標籤名
    tag = None
    """The element's name."""

    當前節點的屬性

    attrib = None
    """Dictionary of the element's attributes."""

    當前節點的內容
    text = None
    """
    Text before first subelement. This is either a string or the value None.
    Note that if there is no text, this attribute may be either
    None or the empty string, depending on the parser.

    """

    tail = None
    """
    Text after this element's end tag, but before the next sibling element's
    start tag.  This is either a string or the value None.  Note that if there
    was no text, this attribute may be either None or an empty string,
    depending on the parser.

    """

    def __init__(self, tag, attrib={}, **extra):
        if not isinstance(attrib, dict):
            raise TypeError("attrib must be dict, not %s" % (
                attrib.__class__.__name__,))
        attrib = attrib.copy()
        attrib.update(extra)
        self.tag = tag
        self.attrib = attrib
        self._children = []

    def __repr__(self):
        return "<%s %r at %#x>" % (self.__class__.__name__, self.tag, id(self))

    def makeelement(self, tag, attrib):
        建立一個新節點
        """Create a new element with the same type.

        *tag* is a string containing the element name.
        *attrib* is a dictionary containing the element attributes.

        Do not call this method, use the SubElement factory function instead.

        """
        return self.__class__(tag, attrib)

    def copy(self):
        """Return copy of current element.

        This creates a shallow copy. Subelements will be shared with the
        original tree.

        """
        elem = self.makeelement(self.tag, self.attrib)
        elem.text = self.text
        elem.tail = self.tail
        elem[:] = self
        return elem

    def __len__(self):
        return len(self._children)

    def __bool__(self):
        warnings.warn(
            "The behavior of this method will change in future versions.  "
            "Use specific 'len(elem)' or 'elem is not None' test instead.",
            FutureWarning, stacklevel=2
            )
        return len(self._children) != 0 # emulate old behaviour, for now

    def __getitem__(self, index):
        return self._children[index]

    def __setitem__(self, index, element):
        # if isinstance(index, slice):
        #     for elt in element:
        #         assert iselement(elt)
        # else:
        #     assert iselement(element)
        self._children[index] = element

    def __delitem__(self, index):
        del self._children[index]

    def append(self, subelement):
        爲當前節點追加一個子節點
        """Add *subelement* to the end of this element.

        The new element will appear in document order after the last existing
        subelement (or directly after the text, if it's the first subelement),
        but before the end tag for this element.

        """
        self._assert_is_element(subelement)
        self._children.append(subelement)

    def extend(self, elements):
        爲當前節點擴展 n 個子節點
        """Append subelements from a sequence.

        *elements* is a sequence with zero or more elements.

        """
        for element in elements:
            self._assert_is_element(element)
        self._children.extend(elements)

    def insert(self, index, subelement):
        在當前節點的子節點中插入某個節點，即：爲當前節點建立子節點，而後插入指定位置
        """Insert *subelement* at position *index*."""
        self._assert_is_element(subelement)
        self._children.insert(index, subelement)

    def _assert_is_element(self, e):
        # Need to refer to the actual Python implementation, not the
        # shadowing C implementation.
        if not isinstance(e, _Element_Py):
            raise TypeError('expected an Element, not %s' % type(e).__name__)

    def remove(self, subelement):
        在當前節點在子節點中刪除某個節點
        """Remove matching subelement.

        Unlike the find methods, this method compares elements based on
        identity, NOT ON tag value or contents.  To remove subelements by
        other means, the easiest way is to use a list comprehension to
        select what elements to keep, and then use slice assignment to update
        the parent element.

        ValueError is raised if a matching element could not be found.

        """
        # assert iselement(element)
        self._children.remove(subelement)

    def getchildren(self):
        獲取全部的子節點（廢棄）
        """(Deprecated) Return all subelements.

        Elements are returned in document order.

        """
        warnings.warn(
            "This method will be removed in future versions.  "
            "Use 'list(elem)' or iteration over elem instead.",
            DeprecationWarning, stacklevel=2
            )
        return self._children

    def find(self, path, namespaces=None):
        獲取第一個尋找到的子節點
        """Find first matching element by tag name or path.

        *path* is a string having either an element tag or an XPath,
        *namespaces* is an optional mapping from namespace prefix to full name.

        Return the first matching element, or None if no element was found.

        """
        return ElementPath.find(self, path, namespaces)

    def findtext(self, path, default=None, namespaces=None):
        獲取第一個尋找到的子節點的內容
        """Find text for first matching element by tag name or path.

        *path* is a string having either an element tag or an XPath,
        *default* is the value to return if the element was not found,
        *namespaces* is an optional mapping from namespace prefix to full name.

        Return text content of first matching element, or default value if
        none was found.  Note that if an element is found having no text
        content, the empty string is returned.

        """
        return ElementPath.findtext(self, path, default, namespaces)

    def findall(self, path, namespaces=None):
        獲取全部的子節點
        """Find all matching subelements by tag name or path.

        *path* is a string having either an element tag or an XPath,
        *namespaces* is an optional mapping from namespace prefix to full name.

        Returns list containing all matching elements in document order.

        """
        return ElementPath.findall(self, path, namespaces)

    def iterfind(self, path, namespaces=None):
        獲取全部指定的節點，並建立一個迭代器（能夠被for循環）
        """Find all matching subelements by tag name or path.

        *path* is a string having either an element tag or an XPath,
        *namespaces* is an optional mapping from namespace prefix to full name.

        Return an iterable yielding all matching elements in document order.

        """
        return ElementPath.iterfind(self, path, namespaces)

    def clear(self):
        清空節點
        """Reset element.

        This function removes all subelements, clears all attributes, and sets
        the text and tail attributes to None.

        """
        self.attrib.clear()
        self._children = []
        self.text = self.tail = None

    def get(self, key, default=None):
        獲取當前節點的屬性值
        """Get element attribute.

        Equivalent to attrib.get, but some implementations may handle this a
        bit more efficiently.  *key* is what attribute to look for, and
        *default* is what to return if the attribute was not found.

        Returns a string containing the attribute value, or the default if
        attribute was not found.

        """
        return self.attrib.get(key, default)

    def set(self, key, value):
        爲當前節點設置屬性值
        """Set element attribute.

        Equivalent to attrib[key] = value, but some implementations may handle
        this a bit more efficiently.  *key* is what attribute to set, and
        *value* is the attribute value to set it to.

        """
        self.attrib[key] = value

    def keys(self):
        獲取當前節點的全部屬性的 key

        """Get list of attribute names.

        Names are returned in an arbitrary order, just like an ordinary
        Python dict.  Equivalent to attrib.keys()

        """
        return self.attrib.keys()

    def items(self):
        獲取當前節點的全部屬性值，每一個屬性都是一個鍵值對
        """Get element attributes as a sequence.

        The attributes are returned in arbitrary order.  Equivalent to
        attrib.items().

        Return a list of (name, value) tuples.

        """
        return self.attrib.items()

    def iter(self, tag=None):
        在當前節點的子孫中根據節點名稱尋找全部指定的節點，並返回一個迭代器（能夠被for循環）。
        """Create tree iterator.

        The iterator loops over the element and all subelements in document
        order, returning all elements with a matching tag.

        If the tree structure is modified during iteration, new or removed
        elements may or may not be included.  To get a stable set, use the
        list() function on the iterator, and loop over the resulting list.

        *tag* is what tags to look for (default is to return all elements)

        Return an iterator containing all the matching elements.

        """
        if tag == "*":
            tag = None
        if tag is None or self.tag == tag:
            yield self
        for e in self._children:
            yield from e.iter(tag)

    # compatibility
    def getiterator(self, tag=None):
        # Change for a DeprecationWarning in 1.4
        warnings.warn(
            "This method will be removed in future versions.  "
            "Use 'elem.iter()' or 'list(elem.iter())' instead.",
            PendingDeprecationWarning, stacklevel=2
        )
        return list(self.iter(tag))

    def itertext(self):
        在當前節點的子孫中根據節點名稱尋找全部指定的節點的內容，並返回一個迭代器（能夠被for循環）。
        """Create text iterator.

        The iterator loops over the element and all subelements in document
        order, returning all inner text.

        """
        tag = self.tag
        if not isinstance(tag, str) and tag is not None:
            return
        if self.text:
            yield self.text
        for e in self:
            yield from e.itertext()
            if e.tail:
                yield e.tail

節點功能一覽表

因爲 每一個節點 都具備以上的方法，而且在上一步驟中解析時均獲得了root（xml文件的根節點），so   能夠利用以上方法進行操做xml文件。

a. 遍歷XML文檔的全部內容

from xml.etree import ElementTree as ET

############ 解析方式一 ############
"""
# 打開文件，讀取XML內容
str_xml = open('xo.xml', 'r').read()

# 將字符串解析成xml特殊對象，root代指xml文件的根節點
root = ET.XML(str_xml)
"""
############ 解析方式二 ############

# 直接解析xml文件
tree = ET.parse("xo.xml")

# 獲取xml文件的根節點
root = tree.getroot()


### 操做

# 頂層標籤
print(root.tag)


# 遍歷XML文檔的第二層
for child in root:
    # 第二層節點的標籤名稱和標籤屬性
    print(child.tag, child.attrib)
    # 遍歷XML文檔的第三層
    for i in child:
        # 第二層節點的標籤名稱和內容
        print(i.tag,i.text)

a

b、遍歷XML中指定的節點

from xml.etree import ElementTree as ET

############ 解析方式一 ############
"""
# 打開文件，讀取XML內容
str_xml = open('xo.xml', 'r').read()

# 將字符串解析成xml特殊對象，root代指xml文件的根節點
root = ET.XML(str_xml)
"""
############ 解析方式二 ############

# 直接解析xml文件
tree = ET.parse("xo.xml")

# 獲取xml文件的根節點
root = tree.getroot()


### 操做

# 頂層標籤
print(root.tag)


# 遍歷XML中全部的year節點
for node in root.iter('year'):
    # 節點的標籤名稱和內容
    print(node.tag, node.text)

b

c、修改節點內容

因爲修改的節點時，均是在內存中進行，其不會影響文件中的內容。因此，若是想要修改，則須要從新將內存中的內容寫到文件。

from xml.etree import ElementTree as ET

############ 解析方式一 ############

# 打開文件，讀取XML內容
str_xml = open('xo.xml', 'r').read()

# 將字符串解析成xml特殊對象，root代指xml文件的根節點
root = ET.XML(str_xml)

############ 操做 ############

# 頂層標籤
print(root.tag)

# 循環全部的year節點
for node in root.iter('year'):
    # 將year節點中的內容自增一
    new_year = int(node.text) + 1
    node.text = str(new_year)

    # 設置屬性
    node.set('name', 'alex')
    node.set('age', '18')
    # 刪除屬性
    del node.attrib['name']


############ 保存文件 ############
tree = ET.ElementTree(root)
tree.write("newnew.xml", encoding='utf-8')

解析字符串方式，修改，保存

from xml.etree import ElementTree as ET

############ 解析方式二 ############

# 直接解析xml文件
tree = ET.parse("xo.xml")

# 獲取xml文件的根節點
root = tree.getroot()

############ 操做 ############

# 頂層標籤
print(root.tag)

# 循環全部的year節點
for node in root.iter('year'):
    # 將year節點中的內容自增一
    new_year = int(node.text) + 1
    node.text = str(new_year)

    # 設置屬性
    node.set('name', 'alex')
    node.set('age', '18')
    # 刪除屬性
    del node.attrib['name']


############ 保存文件 ############
tree.write("newnew.xml", encoding='utf-8')

解析文件方式，修改，保存

d、刪除節點

from xml.etree import ElementTree as ET

############ 解析字符串方式打開 ############

# 打開文件，讀取XML內容
str_xml = open('xo.xml', 'r').read()

# 將字符串解析成xml特殊對象，root代指xml文件的根節點
root = ET.XML(str_xml)

############ 操做 ############

# 頂層標籤
print(root.tag)

# 遍歷data下的全部country節點
for country in root.findall('country'):
    # 獲取每個country節點下rank節點的內容
    rank = int(country.find('rank').text)

    if rank > 50:
        # 刪除指定country節點
        root.remove(country)

############ 保存文件 ############
tree = ET.ElementTree(root)
tree.write("newnew.xml", encoding='utf-8')

解析字符串方式打開，刪除，保存

from xml.etree import ElementTree as ET

############ 解析文件方式 ############

# 直接解析xml文件
tree = ET.parse("xo.xml")

# 獲取xml文件的根節點
root = tree.getroot()

############ 操做 ############

# 頂層標籤
print(root.tag)

# 遍歷data下的全部country節點
for country in root.findall('country'):
    # 獲取每個country節點下rank節點的內容
    rank = int(country.find('rank').text)

    if rank > 50:
        # 刪除指定country節點
        root.remove(country)

############ 保存文件 ############
tree.write("newnew.xml", encoding='utf-8')

解析文件方式打開，刪除，保存

三、建立XML文檔

from xml.etree import ElementTree as ET


# 建立根節點
root = ET.Element("famliy")


# 建立節點大兒子
son1 = ET.Element('son', {'name': '兒1'})
# 建立小兒子
son2 = ET.Element('son', {"name": '兒2'})

# 在大兒子中建立兩個孫子
grandson1 = ET.Element('grandson', {'name': '兒11'})
grandson2 = ET.Element('grandson', {'name': '兒12'})
son1.append(grandson1)
son1.append(grandson2)


# 把兒子添加到根節點中
root.append(son1)
root.append(son1)

tree = ET.ElementTree(root)
tree.write('oooo.xml',encoding='utf-8', short_empty_elements=False)

一

from xml.etree import ElementTree as ET

# 建立根節點
root = ET.Element("famliy")


# 建立大兒子
# son1 = ET.Element('son', {'name': '兒1'})
son1 = root.makeelement('son', {'name': '兒1'})
# 建立小兒子
# son2 = ET.Element('son', {"name": '兒2'})
son2 = root.makeelement('son', {"name": '兒2'})

# 在大兒子中建立兩個孫子
# grandson1 = ET.Element('grandson', {'name': '兒11'})
grandson1 = son1.makeelement('grandson', {'name': '兒11'})
# grandson2 = ET.Element('grandson', {'name': '兒12'})
grandson2 = son1.makeelement('grandson', {'name': '兒12'})

son1.append(grandson1)
son1.append(grandson2)


# 把兒子添加到根節點中
root.append(son1)
root.append(son1)

tree = ET.ElementTree(root)
tree.write('oooo.xml',encoding='utf-8', short_empty_elements=False)

二

from xml.etree import ElementTree as ET


# 建立根節點
root = ET.Element("famliy")


# 建立節點大兒子
son1 = ET.SubElement(root, "son", attrib={'name': '兒1'})
# 建立小兒子
son2 = ET.SubElement(root, "son", attrib={"name": "兒2"})

# 在大兒子中建立一個孫子
grandson1 = ET.SubElement(son1, "age", attrib={'name': '兒11'})
grandson1.text = '孫子'


et = ET.ElementTree(root)  #生成文檔對象
et.write("test.xml", encoding="utf-8", xml_declaration=True, short_empty_elements=False)

三

因爲原生保存的XML時默認無縮進，若是想要設置縮進的話， 須要修改保存方式：

from xml.etree import ElementTree as ET
from xml.dom import minidom


def prettify(elem):
    """將節點轉換成字符串，並添加縮進。
    """
    rough_string = ET.tostring(elem, 'utf-8')
    reparsed = minidom.parseString(rough_string)
    return reparsed.toprettyxml(indent="\t")

# 建立根節點
root = ET.Element("famliy")


# 建立大兒子
# son1 = ET.Element('son', {'name': '兒1'})
son1 = root.makeelement('son', {'name': '兒1'})
# 建立小兒子
# son2 = ET.Element('son', {"name": '兒2'})
son2 = root.makeelement('son', {"name": '兒2'})

# 在大兒子中建立兩個孫子
# grandson1 = ET.Element('grandson', {'name': '兒11'})
grandson1 = son1.makeelement('grandson', {'name': '兒11'})
# grandson2 = ET.Element('grandson', {'name': '兒12'})
grandson2 = son1.makeelement('grandson', {'name': '兒12'})

son1.append(grandson1)
son1.append(grandson2)


# 把兒子添加到根節點中
root.append(son1)
root.append(son1)


raw_str = prettify(root)

f = open("xxxoo.xml",'w',encoding='utf-8')
f.write(raw_str)
f.close()

縮進

四、命名空間

from xml.etree import ElementTree as ET

ET.register_namespace('com',"http://www.company.com") #some name

# build a tree structure
root = ET.Element("{http://www.company.com}STUFF")
body = ET.SubElement(root, "{http://www.company.com}MORE_STUFF", attrib={"{http://www.company.com}hhh": "123"})
body.text = "STUFF EVERYWHERE!"

# wrap it in an ElementTree instance, and save as XML
tree = ET.ElementTree(root)

tree.write("page.xml",
           xml_declaration=True,
           encoding='utf-8',
           method="xml")

命名

 

requests

 

Python標準庫中提供了：urllib等模塊以供Http請求，可是，它的 API 太渣了。它是爲另外一個時代、另外一個互聯網所建立的。它須要巨量的工做，甚至包括各類方法覆蓋，來完成最簡單的任務。

import urllib.request


f = urllib.request.urlopen('http://www.webxml.com.cn//webservices/qqOnlineWebService.asmx/qqCheckOnline?qqCode=424662508')
result = f.read().decode('utf-8')

發送GET請求

import urllib.request

req = urllib.request.Request('http://www.example.com/')
req.add_header('Referer', 'http://www.python.org/')
r = urllib.request.urlopen(req)

result = f.read().decode('utf-8')

發送攜帶請求頭的GET請求

 

Requests 是使用 Apache2 Licensed 許可證的 基於Python開發的HTTP 庫，其在Python內置模塊的基礎上進行了高度的封裝，從而使得Pythoner進行網絡請求時，變得美好了許多，使用Requests能夠垂手可得的完成瀏覽器可有的任何操做。

一、安裝模塊

pip3 install requests

 

二、使用模塊

# 一、無參數實例
 
import requests
 
ret = requests.get('https://github.com/timeline.json')
 
print(ret.url)
print(ret.text)
 
 
 
# 二、有參數實例
 
import requests
 
payload = {'key1': 'value1', 'key2': 'value2'}
ret = requests.get("http://httpbin.org/get", params=payload)
 
print(ret.url)
print(ret.text)

GET請求

# 一、基本POST實例
 
import requests
 
payload = {'key1': 'value1', 'key2': 'value2'}
ret = requests.post("http://httpbin.org/post", data=payload)
 
print(ret.text)
 
 
# 二、發送請求頭和數據實例
 
import requests
import json
 
url = 'https://api.github.com/some/endpoint'
payload = {'some': 'data'}
headers = {'content-type': 'application/json'}
 
ret = requests.post(url, data=json.dumps(payload), headers=headers)
 
print(ret.text)
print(ret.cookies)

POST請求

requests.get(url, params=None, **kwargs)
requests.post(url, data=None, json=None, **kwargs)
requests.put(url, data=None, **kwargs)
requests.head(url, **kwargs)
requests.delete(url, **kwargs)
requests.patch(url, data=None, **kwargs)
requests.options(url, **kwargs)
 
# 以上方法均是在此方法的基礎上構建
requests.request(method, url, **kwargs)

其餘請求

 

三、Http請求和XML實例

實例：檢測QQ帳號是否在線

import urllib
import requests
from xml.etree import ElementTree as ET

# 使用內置模塊urllib發送HTTP請求，或者XML格式內容
"""
f = urllib.request.urlopen('http://www.webxml.com.cn//webservices/qqOnlineWebService.asmx/qqCheckOnline?qqCode=424662508')
result = f.read().decode('utf-8')
"""


# 使用第三方模塊requests發送HTTP請求，或者XML格式內容
r = requests.get('http://www.webxml.com.cn//webservices/qqOnlineWebService.asmx/qqCheckOnline?qqCode=424662508')
result = r.text

# 解析XML格式內容
node = ET.XML(result)

# 獲取內容
if node.text == "Y":
    print("在線")
else:
    print("離線")

QQ

實例：查看火車停靠信息

import urllib
import requests
from xml.etree import ElementTree as ET

# 使用內置模塊urllib發送HTTP請求，或者XML格式內容
"""
f = urllib.request.urlopen('http://www.webxml.com.cn/WebServices/TrainTimeWebService.asmx/getDetailInfoByTrainCode?TrainCode=G666&UserID=')
result = f.read().decode('utf-8')
"""

# 使用第三方模塊requests發送HTTP請求，或者XML格式內容
r = requests.get('http://www.webxml.com.cn/WebServices/TrainTimeWebService.asmx/getDetailInfoByTrainCode?TrainCode=G666&UserID=')
result = r.text

# 解析XML格式內容
root = ET.XML(result)
for node in root.iter('TrainDetailInfo'):
    print(node.find('TrainStation').text,node.find('StartTime').text,node.tag,node.attrib)

火車票

 

綜合應用實例

一、經過HTTP請求和XML實現獲取電視節目

     API：http://www.webxml.com.cn/webservices/ChinaTVprogramWebService.asmx  

#--------------------------------------------經過HTTP請求和XML實現獲取電視節目-------------------------------------

############################得到支持的省市（地區）和分類電視列表 DataSet###############################################
import requests
from xml.etree import ElementTree as EL
#
# f = requests.get("http://www.webxml.com.cn/webservices/ChinaTVprogramWebService.asmx/getAreaDataSet")
# relust = f.text
#
#
# root = EL.XML(relust)
#
#
# for node in root.iter("AreaList"):
#     print(node.find("Area").text)
#
#################################得到支持的省市（地區）和分類電視名稱 String()########################################

# f = requests.get("http://www.webxml.com.cn/webservices/ChinaTVprogramWebService.asmx/getAreaString")
# root = f.text
#
# relust = EL.XML(root)
# # print(relust)
#
# for i in relust:
#     print(i.text)

####################################經過電視臺ID得到該電視臺頻道列表 DataSet#########################################

# f = requests.get("http://www.webxml.com.cn/webservices/ChinaTVprogramWebService.asmx/getTVchannelDataSet?theTVstationID=4")
#
# root = f.text
# # print(root)
#
# relust = EL.XML(root)
# # print(relust)
#
# for node in relust.iter("TvChanne"):
#     print(node.find("tvChannel").text)


############################### 經過電視臺ID得到該電視臺頻道名稱 String()###############################################

# f = requests.get("http://www.webxml.com.cn/webservices/ChinaTVprogramWebService.asmx/getTVchannelString?theTVstationID=4")
#
# root = f.text
#
# relust = EL.XML(root)
#
# for i in relust:
#     print(i.text)

############################### 經過頻道ID得到該頻道節目列表 DataSet###############################################
# f = requests.get("http://www.webxml.com.cn/webservices/ChinaTVprogramWebService.asmx/getTVprogramDateSet?theTVchannelID=3&theDate=&userID=")
# root = f.text
#
# relust = EL.XML(root)
# print(relust)
#
# for node in relust.iter("tvProgramTable"):
#     print("時間:%s   節目：%s  頻道:%s " %(node.find('playTime').text,node.find('tvProgram').text,node.find('tvStationInfo').text) )


#################################################經過頻道ID得到該頻道節目 String()#######################################
# f = requests.get("http://www.webxml.com.cn/webservices/ChinaTVprogramWebService.asmx/getTVprogramString?theTVchannelID=2&theDate=&userID=")
# root = f.text
#
# relust = EL.XML(root)
#
#
# for i in relust:
#     print(i.text)


############################################經過省市ID或分類電視ID得到電視臺列表 DataSet################################

# f = requests.get("http://www.webxml.com.cn/webservices/ChinaTVprogramWebService.asmx/getTVstationDataSet?theAreaID=8")
# root = f.text
#
# relust = EL.XML(root)
#
# for node in relust.iter("TvStation"):
#     print(node.find("tvStationName").text)


##########################################經過省市ID或分類電視ID得到電視臺名稱 String()################################

# f = requests.get("http://www.webxml.com.cn/webservices/ChinaTVprogramWebService.asmx/getTVstationString?theAreaID=-1")
# root = f.text
#
# relust = EL.XML(root)
#
# for i in relust:
#     print(i.text)

電視節目

二、經過HTTP請求和JSON實現獲取天氣情況

     API：http://wthrcdn.etouch.cn/weather_mini?city=北京

import json,requests

f = requests.get("http://wthrcdn.etouch.cn/weather_mini?city=北京")
root = f.text
# print(root,type(root))


new_root = json.loads(root)
print(new_root,type(new_root))


#------------------------------------------------------------------------------------------------------------------
response =requests.get("http://www.weather.com.cn/adat/sk/101010500.html")
response.encoding = "utf-8"
result = response.text
print(result,type(result))

new_result = json.loads(result)
print(new_result)

天氣預報

 

configparser

configparser模塊用於讀取基於Windows INI格式的.ini格式的配置文件。這些文件由命名段祖闖，每一個命名段獨有本身的變量賦值，格式以下：

# 註釋1
   A comment
 
[section1] # 節點
k1 = v1    # 值
k2:v2       # 值
 
[section2] # 節點
k1 = v1    # 值

格式

configparser模塊每每被忽視，但他是一個及其有用的工具，它能夠控制包含極其複雜的用戶配置或運行時環境的程序，例如：若編寫了必須在大興框架內運行的組件，那麼配置文件每每是提供運行時參數的理想方式

一、獲取全部節點

import configparser
 
config = configparser.ConfigParser()
config.read('xxxooo', encoding='utf-8')
ret = config.sections()   #獲取大節點
print(ret)

二、獲取指定節點下全部的鍵值對

import configparser
 
config = configparser.ConfigParser()
config.read('xxxooo', encoding='utf-8')
ret = config.items('section1') #鍵值對
print(ret)  

三、獲取指定節點下全部的鍵

import configparser
 
config = configparser.ConfigParser()
config.read('xxxooo', encoding='utf-8')
ret = config.options('section1')   #二級節點
print(ret)

四、獲取指定節點下指定key的值

import configparser
 
config = configparser.ConfigParser()
config.read('xxxooo', encoding='utf-8')
 
 
v = config.get('section1', 'k1') #獲取值的值
# v = config.getint('section1', 'k1')  #整形
# v = config.getfloat('section1', 'k1')   #浮點
# v = config.getboolean('section1', 'k1')   #布爾

五、檢查、刪除、添加節點

import configparser
 
config = configparser.ConfigParser()
config.read('xxxooo', encoding='utf-8')
 
 
# 檢查
has_sec = config.has_section('section1')
print(has_sec)
 
# 添加節點
config.add_section("SEC_1")
config.write(open('xxxooo', 'w'))
 
# 刪除節點
config.remove_section("SEC_1")
config.write(open('xxxooo', 'w'))

六、檢查、刪除、設置指定組內的鍵值對

import configparser
 
config = configparser.ConfigParser()
config.read('xxxooo', encoding='utf-8')
 
# 檢查
has_opt = config.has_option('section1', 'k1')
print(has_opt)
 
# 刪除
config.remove_option('section1', 'k1')
config.write(open('xxxooo', 'w'))
 
# 設置
config.set('section1', 'k10', "123")
config.write(open('xxxooo', 'w'))

 

系統命令subprocess

 

subprocess模塊包含的函數和對象用於簡化建立新進程的任務、控制輸入和輸出流，以及處理返回代碼。此模塊的豬獒功能包含在其餘各個模塊中，如os、popen、commands

格式

以上執行shell命令的相關的模塊和函數的功能均在 subprocess 模塊中實現，並提供了更豐富的功能。

popen（args，**parms）

以子進程形式執行一個新命令，而後返回表明新進程的popen對象，命令在args中指定，是字符串（如 「ls -l」）。parms表示關鍵字參數的集合，設置這些參數能夠控制子進程的各類屬性

參數：

• args：shell命令，能夠是字符串或者序列類型（如：list，元組）
• bufsize：指定緩衝。0 無緩衝,1 行緩衝,其餘 緩衝區大小,負值 系統緩衝
• stdin, stdout, stderr：分別表示程序的標準輸入、輸出、錯誤句柄
• preexec_fn：只在Unix平臺下有效，用於指定一個可執行對象（callable object），它將在子進程運行以前被調用
• close_sfs：在windows平臺下，若是close_fds被設置爲True，則新建立的子進程將不會繼承父進程的輸入、輸出、錯誤管道。
  因此不能將close_fds設置爲True同時重定向子進程的標準輸入、輸出與錯誤(stdin, stdout, stderr)。
• shell：同上
• cwd：用於設置子進程的當前目錄
• env：用於指定子進程的環境變量。若是env = None，子進程的環境變量將從父進程中繼承。
• universal_newlines：不一樣系統的換行符不一樣，True -> 贊成使用 \n
• startupinfo與createionflags只在windows下有效
  將被傳遞給底層的CreateProcess()函數，用於設置子進程的一些屬性，如：主窗口的外觀，進程的優先級等等 

 

import subprocess
ret1 = subprocess.Popen(["mkdir","t1"])
ret2 = subprocess.Popen("mkdir t2", shell=True)

普通命令

 

終端輸入的命令分爲兩種：

• 輸入便可獲得輸出，如：ifconfig
• 輸入進行某環境，依賴再輸入，如：python

 

 

import subprocess

obj = subprocess.Popen("mkdir t3", shell=True, cwd='/home/dev',)

View Code

 

import subprocess

obj = subprocess.Popen(["python"], stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE, universal_newlines=True)
obj.stdin.write("print(1)\n")
obj.stdin.write("print(2)")
obj.stdin.close()

cmd_out = obj.stdout.read()
obj.stdout.close()
cmd_error = obj.stderr.read()
obj.stderr.close()

print(cmd_out)
print(cmd_error)

View Code

import subprocess

obj = subprocess.Popen(["python"], stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE, universal_newlines=True)
obj.stdin.write("print(1)\n")
obj.stdin.write("print(2)")

out_error_list = obj.communicate()
print(out_error_list)

View Code

import subprocess

obj = subprocess.Popen(["python"], stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE, universal_newlines=True)
out_error_list = obj.communicate('print("hello")')
print(out_error_list)

View Code

 

 

call（args，**parms）

此函數與popen徹底相同，但他指揮簡單的執行命令而後返回他的狀態代碼。若是要執行一個命令，單又不須要捕捉他的輸出，可使用這個函數

執行命令，返回狀態碼

ret = subprocess.call(["ls", "-l"], shell=False)
ret = subprocess.call("ls -l", shell=True)

 

check_call（args，**parms）

同call函數，但若是退出代碼爲非0值，將引起異常，此異常將退出代碼保存在他的returncode屬性中。

執行命令，若是執行狀態碼是 0 ，則返回0，不然拋異常

subprocess.check_call(["ls", "-l"])
subprocess.check_call("exit 1", shell=True)

 

check_output（args，**parms）

執行命令，若是狀態碼是 0 ，則返回執行結果，不然拋異常

subprocess.check_output(["echo", "Hello World!"])
subprocess.check_output("exit 1", shell=True)

 

shutil

 

 

高級的 文件、文件夾、壓縮包 處理模塊

 

shutil.copyfileobj(fsrc, fdst[, length])
將文件內容拷貝到另外一個文件中

import shutil
 
shutil.copyfileobj(open('old.xml','r'), open('new.xml', 'w'))

shutil.copyfile(src, dst)
拷貝文件

shutil.copyfile('f1.log', 'f2.log')

shutil.copymode(src, dst)
僅拷貝權限。內容、組、用戶均不變

shutil.copymode('f1.log', 'f2.log')

shutil.copystat(src, dst)
拷貝狀態的信息，包括：mode bits, atime, mtime, flags

shutil.copystat('f1.log', 'f2.log')

shutil.copy(src, dst)
拷貝文件和權限

import shutil
 
shutil.copy('f1.log', 'f2.log')

shutil.copy2(src, dst)
拷貝文件和狀態信息

import shutil
 
shutil.copy2('f1.log', 'f2.log')

shutil.ignore_patterns(*patterns)
shutil.copytree(src, dst, symlinks=False, ignore=None)
遞歸的去拷貝文件夾

import shutil
 
shutil.copytree('folder1', 'folder2', ignore=shutil.ignore_patterns('*.pyc', 'tmp*'))

import shutil

shutil.copytree('f1', 'f2', symlinks=True, ignore=shutil.ignore_patterns('*.pyc', 'tmp*')) #複製除了括號裏面的

View Code

shutil.rmtree(path[, ignore_errors[, onerror]])
遞歸的去刪除文件

import shutil
 
shutil.rmtree('folder1')

shutil.move(src, dst)
遞歸的去移動文件，它相似mv命令，其實就是重命名。

import shutil
 
shutil.move('folder1', 'folder3')

shutil.make_archive(base_name, format,...)

建立壓縮包並返回文件路徑，例如：zip、tar

建立壓縮包並返回文件路徑，例如：zip、tar

• base_name： 壓縮包的文件名，也能夠是壓縮包的路徑。只是文件名時，則保存至當前目錄，不然保存至指定路徑，
  如：www                        =>保存至當前路徑
  如：/Users/wupeiqi/www =>保存至/Users/wupeiqi/
• format： 壓縮包種類，「zip」, 「tar」, 「bztar」，「gztar」
• root_dir： 要壓縮的文件夾路徑（默認當前目錄）
• owner： 用戶，默認當前用戶
• group： 組，默認當前組
• logger： 用於記錄日誌，一般是logging.Logger對象

#將 /Users/wupeiqi/Downloads/test 下的文件打包放置當前程序目錄
import shutil
ret = shutil.make_archive("wwwwwwwwww", 'gztar', root_dir='/Users/wupeiqi/Downloads/test')
  
  
#將 /Users/wupeiqi/Downloads/test 下的文件打包放置 /Users/wupeiqi/目錄
import shutil
ret = shutil.make_archive("/Users/wupeiqi/wwwwwwwwww", 'gztar', root_dir='/Users/wupeiqi/Downloads/test')

shutil 對壓縮包的處理是調用 ZipFile 和 TarFile 兩個模塊來進行的，詳細：

import zipfile

# 壓縮
z = zipfile.ZipFile('laxi.zip', 'w')
z.write('a.log')
z.write('data.data')
z.close()

# 解壓
z = zipfile.ZipFile('laxi.zip', 'r')
z.extractall()
z.close()

zip解壓

import tarfile

# 壓縮
tar = tarfile.open('your.tar','w')
tar.add('/Users/wupeiqi/PycharmProjects/bbs2.log', arcname='bbs2.log')
tar.add('/Users/wupeiqi/PycharmProjects/cmdb.log', arcname='cmdb.log')
tar.close()

# 解壓
tar = tarfile.open('your.tar','r')
tar.extractall()  # 可設置解壓地址
tar.close()

tar解壓