好記性不如爛筆頭
帶關鍵字的格式化
>>>
>>> print "Hello %(name)s !" % {'name':'James'}
Hello James !
>>>
>>> print "Hello {name} !".format(name="James")
Hello James !
>>>
使用dict.__missing__() 避免出現KeyError
If a subclass of dict defines a method __missing__() and key is not present, the d[key] operation calls that method with the key(key as argument). The d[key] operation then returns or raises whatever is returned or raised by the __missing__(key) call.
>>>
>>> class Counter(dict):
... def __missing__(self, key):
... return 0
...
>>> c = Counter()
>>> print c['num']
0
>>> c['num'] += 1
>>> print c['num']
1
>>>
>>> c
{'num': 1}
>>>
__getattr__ 調用默認方法
>>>
>>> class A(object):
... def __init__(self,num):
... self.num = num
... print 'init...'
... def mydefault(self, *args, **kwargs):
... print 'default func...'
... print args
... print kwargs
... def __getattr__(self,name):
... print 'No %(name)s found, goto default...' % {'name':name}
... return self.mydefault
...
>>> a1 = A(9)
init...
>>> a1.fn1()
No fn1 found, goto default...
default func...
()
{}
>>> a1.fn2(1,2)
No fn2 found, goto default...
default func...
(1, 2)
{}
>>> a1.fn3(name='standby',age=18)
No fn3 found, goto default...
default func...
()
{'age': 18, 'name': 'standby'}
>>>
>>>
obj.xxx = aaa 觸發類的 __setattr__ obj.xxx 觸發類的 __getattr__ obj['xxx'] = 'vvv' 觸發類的 __setitem__ obj['xxx'] 觸發類的 __getitem__ with app1.app_context(): 觸發 __enter__ __exit__
__new__ 和 __init__ 的執行順序
>>> >>> class B(object): ... def fn(self): ... print 'B fn' ... def __init__(self): ... print "B INIT" ... >>> class A(object): ... def fn(self): ... print 'A fn' ... def __new__(cls,a): ... print "NEW", a ... if a>10: ... return super(A, cls).__new__(cls) ... return B() ... def __init__(self,a): ... print "INIT", a ... >>> >>> a1 = A(5) NEW 5 B INIT >>> a1.fn() B fn >>> a2=A(20) NEW 20 INIT 20 >>> a2.fn() A fn >>>
類繼承之 __class__
>>> >>> class A(object): ... def show(self): ... print 'base show' ... >>> class B(A): ... def show(self): ... print 'derived show' ... >>> obj = B() >>> obj.show() derived show >>> >>> obj.__class__ <class '__main__.B'> >>> >>> obj.__class__ = A >>> obj.__class__ <class '__main__.A'> >>> obj.show() base show >>>
對象方法 __call__
>>>
>>> class A(object):
... def obj_func(self, *args, **kwargs):
... print args
... print kwargs
... def __call__(self, *args, **kwargs):
... print 'Object method ...'
... return self.obj_func(*args, **kwargs)
...
>>> a1=A()
>>> a1(9,name='standby',city='beijing')
Object method ...
(9,)
{'city': 'beijing', 'name': 'standby'}
>>>
補充：html
>>> >>> class test(object): ... def __init__(self, value): ... self.x = value ... def __call__(self, value): ... return self.x * value ... >>> a = test(4) >>> print a(5) 20 >>>
補充：python
- 什麼後面能夠加括號？（只有4種表現形式） - 函數 執行函數 - 類 執行類的__init__方法 - 方法 obj.func - 對象 前提：類裏有 __call__ 方法 obj() 直接執行類的 __call__方法
關於類的繼承
>>> >>> class Parent(object): ... x = 1 ... >>> class Child1(Parent): ... pass ... >>> class Child2(Parent): ... pass ... >>> Child1.x = 2 >>> Parent.x = 3 >>> print Parent.x, Child1.x, Child2.x 3 2 3 >>>
類屬性和對象屬性
類屬性 >>> >>> class Student: ... score = [] ... >>> stu1 = Student() >>> stu2 = Student() >>> stu1.score.append(99) >>> stu1.score.append(96) >>> stu2.score.append(98) >>> >>> >>> stu2.score [99, 96, 98] >>> >>> 對象屬性 >>> >>> class Student: ... def __init__(self):; ... self.lst = [] ... >>> stu1 = Student() >>> stu2 = Student() >>> >>> >>> stu1.lst.append(1) >>> stu1.lst.append(2) >>> stu2.lst.append(9) >>> >>> stu1.lst [1, 2] >>> >>> stu2.lst [9] >>>
一行代碼實現列表偶數位加3後求和
>>> a = [1,2,3,4,5,6] >>> [item+3 for item in a if a.index(item)%2==0] [4, 6, 8] >>> result = sum([item+3 for item in a if a.index(item)%2==0]) >>> result 18 >>>
字符串鏈接
>>> >>> name = 'hi ' 'standby' ' !' >>> name 'hi standby !' >>>
Python解釋器中的 '_'
_ 即Python解釋器上一次返回的值express
>>> >>> range(5) [0, 1, 2, 3, 4] >>> _ [0, 1, 2, 3, 4] >>>
嵌套列表推導式
>>> >>> [(i, j) for i in range(3) for j in range(i)] [(1, 0), (2, 0), (2, 1)] >>>
Python3 中的unpack
>>> >>> first, second, *rest, last = range(10) >>> first 0 >>> second 1 >>> last 9 >>> rest [2, 3, 4, 5, 6, 7, 8] >>>
關於__setattr__ __getattr__ __getitem__ __setitem__ 參考：http://www.cnblogs.com/standby/p/7045718.html編程
Python把經常使用數字緩存在內存裏 *****
>>> >>> a = 1 >>> b = 1 >>> a is b True >>> >>> >>> a = 256 >>> b = 256 >>> a is b True >>> >>> a = 257 >>> b = 257 >>> a is b False >>> >>> a = 300 >>> b = 300 >>> a is b False >>>
注意：在[-5,256]之間的數字用在內存中的id號是相同的；緩存
Python爲了提升運行效率而將這些經常使用數字緩存到內存裏了，因此他們的id號是相同的；閉包
另外，對a,b,c,....等的賦值也只是一種引用而已：app
>>> >>> id(9) 10183288 >>> num = 9 >>> id(num) 10183288 >>>
Python對於短字符串會使用同一個空間，可是對於長字符串會從新開闢空間
>>> >>> a = 'I love PythonSomething!' >>> b = 'I love PythonSomething!' >>> c = [1, 2, 3] >>> d = [1, 2, 3] >>> >>> a is b False >>> c is d False >>> >>> id(a) 139848068316272 >>> id(b) 139848068316336 >>> id(c) 139848068310152 >>> id(d) 139848068309936 >>>
字符串 * 操做
>>>
>>> def func(a):
... a = a + '2'
... a = a*2
... return a
...
>>>
>>> func("hello")
'hello2hello2'
>>>
Python浮點數比較
>>> >>> 0.1 0.10000000000000001 >>> 0.2 0.20000000000000001 >>> 0.1 + 0.2 0.30000000000000004 >>> >>> 0.3 0.29999999999999999 >>> >>> 0.1 + 0.2 == 0.3 False >>>
Python裏的 '~' 取反
>>> >>> 5 5 >>> ~5 -6 >>> ~~5 5 >>> ~~~5 -6 >>> ~~~~5 5 >>>
~5 即對5取反，獲得的是 -6 ， 爲何？python2.7
參考：http://www.javashuo.com/article/p-rotslhii-gs.html 和 http://blog.csdn.net/u011080472/article/details/51280919ide
- 原碼就是符號位加上真值的絕對值；函數式編程
- 反碼的表示方法是：正數的反碼就是其自己；負數的反碼是在其原碼的基礎上, 符號位不變，其他各個位取反；
- 補碼的表示方式是：正數的補碼就是其自己；負數的補碼是在其原碼的基礎上, 符號位不變, 其他各位取反, 最後+1 (即在反碼的基礎上+1)；
| 真值 | 原碼 | 反碼 | 補碼 | |
| 5 | +000 0101 | 0000 0101 | 0000 0101 | 0000 0101 |
| -5 | -000 0101 | 1000 0101 | 1111 1010 | 1111 1011 |
對5取反即對 0000 0101 取反， 獲得 1111 1010，那這個值的十進制是多少呢？
由於 負數在計算機中是以補碼形式表示的， 因此實際上就是求哪一個值的補碼是 1111 1010，
按照上面的規則反向計算：
1111 1010 減1 獲得其反碼錶示：1111 1001
在保證符號位不變，其他各位取反：1000 0110 就是該值的原碼，對應真值就是 -000 0110 ，對應十進制就是 -6 。
那麼對 -6 取反，獲得的是多少呢？
對-6取反即對 -6 的補碼取反，就是對1111 1010取反，獲得 0000 0101，很明顯是一個正數。
而正數原碼==正數反碼==正數補碼，因此該值的原碼就是 0000 0101，真值就是 +000 0101，對應十進制就是 5。
bool()
>>>
>>> bool('True')
True
>>> bool('False')
True
>>> bool('')
False
>>> bool()
False
>>>
>>>
>>> bool(1)
True
>>> bool(0)
False
>>>
等價於
>>> >>> True==False==False False >>> >>> True==False and False==False False >>>
>>> >>> 1 in [0,1] True >>> 1 in [0,1] == True False >>> >>> (1 in [0,1]) == True True >>> >>> 1 in ([0,1] == True) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: argument of type 'bool' is not iterable >>> >>> >>> >>> (1 in [0,1]) and ([0,1] == True) False >>>
Note that comparisons, membership tests, and identity tests,
all have the same precedence and have a left-to-right chaining feature as described in the Comparisons section.
參考：https://stackoverflow.com/questions/31354429/why-is-true-is-false-false-false-in-python
while 結合 break
>>> >>> i = 0 >>> while i < 5: ... print(i) ... i += 1 ... if i == 3: ... break ... else: ... print(0) ... 0 1 2 >>>
set給list去重
>>> >>> nums = set([1,1,2,3,3,3,4]) >>> >>> nums set([1, 2, 3, 4]) >>> >>> type(nums) <type 'set'> >>> >>> len(nums) 4 >>> >>> >>> li = list(nums) >>> li [1, 2, 3, 4] >>> >>> type(li) <type 'list'> >>>
函數是第一類對象（First-Class Object）
在 Python 中萬物皆爲對象，函數也不例外，
函數做爲對象能夠賦值給一個變量、能夠做爲元素添加到集合對象中、
可做爲參數值傳遞給其它函數，還能夠當作函數的返回值，這些特性就是第一類對象所特有的。
函數能夠嵌套，函數中裏面嵌套的函數不能在函數外面訪問，只能是在函數內部使用：
def get_length(text):
def clean(t):
return t[1:]
res = clean(text)
return len(res)
print(get_length('standby'))
Python裏的高階函數
函數接受一個或多個函數做爲輸入或者函數輸出（返回）的值是函數時，咱們稱這樣的函數爲高階函數。
Python內置函數中，典型的高階函數是 map 函數，map 接受一個函數和一個迭代對象做爲參數，
調用 map 時，依次迭代把迭代對象的元素做爲參數調用該函數。
def foo(text):
return len(text)
li = map(foo, ["the","zen","of","python"])
print(li) # <map object at 0x0000000001119FD0>
li = list(li)
print(li) # [3, 3, 2, 6]
lambda應用場景
- 函數式編程
有一個列表： list1 = [3,5,-4,-1,0,-2,-6]，須要按照每一個元素的絕對值升序排序，如何作？
# 使用lambda的方式 >>> >>> list1 [3, 5, -4, -1, 0, -2, -6] >>> >>> sorted(list1, key=lambda i : abs(i)) [0, -1, -2, 3, -4, 5, -6] >>> # 不使用lambda的方式 >>> >>> def foo(x): ... return abs(x) ... >>> sorted(list1, key=foo) [0, -1, -2, 3, -4, 5, -6] >>>
如何把一個字典按照value進行排序？
>>>
>>> dic = {'a': 9, 'c': 3, 'b': 1, 'd': 7, 'f': 12}
>>> dic
{'a': 9, 'f': 12, 'c': 3, 'd': 7, 'b': 1}
>>>
>>> from collections import Iterable
>>> isinstance(dic.items(),Iterable)
True
>>>
>>> dic.items()
dict_items([('a', 9), ('f', 12), ('c', 3), ('d', 7), ('b', 1)])
>>>
>>> sorted(dic.items(), key=lambda x:x[1])
[('b', 1), ('c', 3), ('d', 7), ('a', 9), ('f', 12)]
>>>
- 閉包
# 不用lambda的方式 >>> >>> def my_add(n): ... def wrapper(x): ... return x+n ... return wrapper ... >>> add_3 = my_add(3) >>> add_3(7) 10 >>> # 使用lambda的方式 >>> >>> def my_add(n): ... return lambda x:x+n ... >>> add_3 = my_add(3) >>> add_3(7) 10 >>>
方法和函數的區別
#!/usr/bin/python3
from types import MethodType,FunctionType
class Foo(object):
def __init__(self):
pass
def func(self):
print('func...')
obj = Foo()
print(obj.func) # 自動傳遞 self
# <bound method Foo.func of <__main__.Foo object at 0x7f86121505f8>>
print(Foo.func)
# <function Foo.func at 0x7f861214e488>
print(isinstance(obj.func,MethodType)) # True
print(isinstance(obj.func,FunctionType)) # False
print(isinstance(Foo.func,MethodType)) # False
print(isinstance(Foo.func,FunctionType)) # True
時間戳轉換成年月日時分秒
>>> from datetime import datetime
>>> ts=1531123200
>>> date_str = datetime.fromtimestamp(ts).strftime('%Y-%m-%d %H:%M:%S')
>>> date_str
'2018-07-09 16:00:00'
>>>
In [11]: import time
In [12]: ts = int(time.time())
In [13]: ts
Out[13]: 1559549982
In [14]: time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(ts))
Out[14]: '2019-06-03 16:19:42'
In [15]:
年月日時分秒轉換成時間戳
>>> date_str '2018-07-09 16:00:00' >>> >>> date_struct=time.strptime(date_str,'%Y-%m-%d %H:%M:%S') >>> date_struct time.struct_time(tm_year=2018, tm_mon=7, tm_mday=9, tm_hour=16, tm_min=0, tm_sec=0, tm_wday=0, tm_yday=190, tm_isdst=-1) >>> >>> int(time.mktime(date_struct)) 1531123200 >>>
In [16]: d Out[16]: '2019-06-03 16:19:42' In [17]: time.mktime(time.strptime(d, "%Y-%m-%d %H:%M:%S")) Out[17]: 1559549982.0 In [18]:
獲取當前月初和月末時間戳
>>> import time >>> import datetime >>> >>> start_st = datetime.datetime.now() >>> start_st datetime.datetime(2018, 7, 17, 16, 45, 39, 95228) >>> startts = int(time.mktime((start_st.year, start_st.month-1, 1, 0, 0, 0, 0, 0, -1))) >>> startts # 當前月初時間戳 1527782400 >>> >>> stopts = int(time.mktime((start_st.year, start_st.month, 1, 0, 0, 0, 0, 0, -1))) - 1 >>> stopts 1530374399 # 當前月末時間戳 >>>
IP地址轉換成數字，從而進行比較，適用於地址庫
>>> ips = ['8.8.8.8','202.106.0.20']
>>>
>>> map(lambda ip:sum([256**j*int(i) for j,i in enumerate(ip.split('.')[::-1])]), ips)
[134744072, 3395944468]
>>>
使用yield逐行讀取多個文件併合並
#!/usr/bin/python2.7
def get_line_by_yield():
with open('total.txt','r') as rf_total, open('extra.txt','r') as rf_extra:
for line in rf_total:
extra = rf_extra.readline()
lst = line.strip().split() + extra.strip().split()
yield lst
with open('new_total.txt','w') as wf:
for lst in get_line_by_yield():
wf.write('%s\n' % ''.join(map(lambda i: str(i).rjust(20), lst)))
逐行讀取
def read_line(path):
with open(path,'r') as rf:
for line in rf:
yield line
檢查進程是否 running
In [16]: import signal In [17]: from os import kill In [18]: kill(17335, 0) # 17335 是進程ID，第二個參數傳0/signal.SIG_DFL 返回值如果None則表示正在運行 In [19]: kill(17335, 15) # 給進程傳遞15/signal.SIGTERM，即終止該進程 In [20]: kill(17335, 0) # 再次檢查發現該進程已經再也不running，則raise一個OSError --------------------------------------------------------------------------- OSError Traceback (most recent call last) <ipython-input-20-cbb7c9624124> in <module>() ----> 1 kill(17335, 0) OSError: [Errno 3] No such process In [21]:
1 In [12]: import signal 2 3 In [13]: signal.SIGKILL 4 Out[13]: 9 5 6 In [14]: signal.SIGTERM 7 Out[14]: 15 8 9 In [15]: signal.__dict__.items() 10 Out[15]: 11 [('SIGHUP', 1), 12 ('SIG_DFL', 0), 13 ('SIGSYS', 31), 14 ('SIGQUIT', 3), 15 ('SIGUSR1', 10), 16 ('SIGFPE', 8), 17 ('SIGPWR', 30), 18 ('SIGTSTP', 20), 19 ('ITIMER_REAL', 0L), 20 ('SIGCHLD', 17), 21 ('SIGCONT', 18), 22 ('SIGIOT', 6), 23 ('SIGBUS', 7), 24 ('SIGXCPU', 24), 25 ('SIGPROF', 27), 26 ('SIGCLD', 17), 27 ('SIGUSR2', 12), 28 ('default_int_handler', <function signal.default_int_handler>), 29 ('pause', <function signal.pause>), 30 ('SIGKILL', 9), 31 ('NSIG', 65), 32 ('SIGTRAP', 5), 33 ('SIGINT', 2), 34 ('SIGIO', 29), 35 ('__package__', None), 36 ('getsignal', <function signal.getsignal>), 37 ('SIGILL', 4), 38 ('SIGPOLL', 29), 39 ('SIGABRT', 6), 40 ('SIGALRM', 14), 41 ('__doc__', 42 'This module provides mechanisms to use signal handlers in Python.\n\nFunctions:\n\nalarm() -- cause SIGALRM after a specified time [Unix only]\nsetitimer() -- cause a signal (described below) after a specified\n float time and the timer may restart then [Unix only]\ngetitimer() -- get current value of timer [Unix only]\nsignal() -- set the action for a given signal\ngetsignal() -- get the signal action for a given signal\npause() -- wait until a signal arrives [Unix only]\ndefault_int_handler() -- default SIGINT handler\n\nsignal constants:\nSIG_DFL -- used to refer to the system default handler\nSIG_IGN -- used to ignore the signal\nNSIG -- number of defined signals\nSIGINT, SIGTERM, etc. -- signal numbers\n\nitimer constants:\nITIMER_REAL -- decrements in real time, and delivers SIGALRM upon\n expiration\nITIMER_VIRTUAL -- decrements only when the process is executing,\n and delivers SIGVTALRM upon expiration\nITIMER_PROF -- decrements both when the process is executing and\n when the system is executing on behalf of the process.\n Coupled with ITIMER_VIRTUAL, this timer is usually\n used to profile the time spent by the application\n in user and kernel space. SIGPROF is delivered upon\n expiration.\n\n\n*** IMPORTANT NOTICE ***\nA signal handler function is called with two arguments:\nthe first is the signal number, the second is the interrupted stack frame.'), 43 ('SIG_IGN', 1), 44 ('getitimer', <function signal.getitimer>), 45 ('SIGURG', 23), 46 ('SIGPIPE', 13), 47 ('SIGWINCH', 28), 48 ('__name__', 'signal'), 49 ('SIGTERM', 15), 50 ('SIGVTALRM', 26), 51 ('ITIMER_PROF', 2L), 52 ('SIGRTMIN', 34), 53 ('SIGRTMAX', 64), 54 ('ITIMER_VIRTUAL', 1L), 55 ('set_wakeup_fd', <function signal.set_wakeup_fd>), 56 ('setitimer', <function signal.setitimer>), 57 ('signal', <function signal.signal>), 58 ('SIGSEGV', 11), 59 ('siginterrupt', <function signal.siginterrupt>), 60 ('SIGXFSZ', 25), 61 ('SIGTTIN', 21), 62 ('SIGSTOP', 19), 63 ('ItimerError', signal.ItimerError), 64 ('SIGTTOU', 22), 65 ('alarm', <function signal.alarm>)] 66 67 In [16]: dict((k, v) for v, k in reversed(sorted(signal.__dict__.items())) 68 ...: if v.startswith('SIG') and not v.startswith('SIG_')) 69 Out[16]: 70 {1: 'SIGHUP', 71 2: 'SIGINT', 72 3: 'SIGQUIT', 73 4: 'SIGILL', 74 5: 'SIGTRAP', 75 6: 'SIGABRT', 76 7: 'SIGBUS', 77 8: 'SIGFPE', 78 9: 'SIGKILL', 79 10: 'SIGUSR1', 80 11: 'SIGSEGV', 81 12: 'SIGUSR2', 82 13: 'SIGPIPE', 83 14: 'SIGALRM', 84 15: 'SIGTERM', 85 17: 'SIGCHLD', 86 18: 'SIGCONT', 87 19: 'SIGSTOP', 88 20: 'SIGTSTP', 89 21: 'SIGTTIN', 90 22: 'SIGTTOU', 91 23: 'SIGURG', 92 24: 'SIGXCPU', 93 25: 'SIGXFSZ', 94 26: 'SIGVTALRM', 95 27: 'SIGPROF', 96 28: 'SIGWINCH', 97 29: 'SIGIO', 98 30: 'SIGPWR', 99 31: 'SIGSYS', 100 34: 'SIGRTMIN', 101 64: 'SIGRTMAX'} 102 103 In [17]:
1 def check_if_process_is_alive(self): 2 try: 3 kill(self.current_pid, 0) 4 kill(self.parent_pid, 0) 5 except: 6 # do something... 7 exit(0)
多指標排序問題
In [26]: lst = [('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10)]
In [27]: import operator
In [28]: sorted(lst, key=operator.itemgetter(1))
Out[28]: [('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10)]
In [29]: sorted(lst, key=operator.itemgetter(1,2)) # 先根據第二個域排序，而後再根據第三個域排序
Out[29]: [('john', 'A', 15), ('dave', 'B', 10), ('jane', 'B', 12)]
In [30]:
兩個純數字列表元素個數相等，按序相加求和，獲得一個新的列表
length = len(lst1) lst = reduce(lambda x,y:[x[i]+y[i] for i in range(length)], [lst1,lst2], [0]*length)
或者直接使用numpy.array
補充reduce+lambda合併多個列表
In [15]: lst = [[1,2,3],['a','c'],['hello','world'],[2,2,2,111]] In [16]: reduce(lambda x,y: x+y, lst) Out[16]: [1, 2, 3, 'a', 'c', 'hello', 'world', 2, 2, 2, 111] In [17]:
擴展現例1：
lst= [[{u'timestamp': 1545214320, u'value': 222842128},
{u'timestamp': 1545214380, u'value': 224080288},
{u'timestamp': 1545214440, u'value': 253812496},
{u'timestamp': 1545214500, u'value': 295170240},
{u'timestamp': 1545214560, u'value': 221196224},
{u'timestamp': 1545214620, u'value': 252992096}],
[{u'timestamp': 1545214320, u'value': 228121600},
{u'timestamp': 1545214380, u'value': 225682656},
{u'timestamp': 1545214440, u'value': 256428064},
{u'timestamp': 1545214500, u'value': 292691424},
{u'timestamp': 1545214560, u'value': 241462336},
{u'timestamp': 1545214620, u'value': 250864528}],
[{u'timestamp': 1545214320, u'value': 232334304},
{u'timestamp': 1545214380, u'value': 230452032},
{u'timestamp': 1545214440, u'value': 246094880},
{u'timestamp': 1545214500, u'value': 260281088},
{u'timestamp': 1545214560, u'value': 233277120},
{u'timestamp': 1545214620, u'value': 258726192}]]
# 要求：把上述列表合併
# 方法一：使用Python內置函數
In [83]: reduce(lambda x,y:[ { 'timestamp':x[i]['timestamp'], 'value':x[i]['value']+y[i]['value'] } for i in range(6) ], a)
Out[83]:
[{'timestamp': 1545214320, 'value': 683298032},
{'timestamp': 1545214380, 'value': 680214976},
{'timestamp': 1545214440, 'value': 756335440},
{'timestamp': 1545214500, 'value': 848142752},
{'timestamp': 1545214560, 'value': 695935680},
{'timestamp': 1545214620, 'value': 762582816}]
In [84]:
# 方法二：笨辦法
In [87]: b = a.pop(0)
In [88]:
In [88]: for i in a:
...: for idx in range(len(i)):
...: b[idx]['value'] += i[idx]['value']
...:
In [89]: b
Out[89]:
[{u'timestamp': 1545214320, u'value': 683298032},
{u'timestamp': 1545214380, u'value': 680214976},
{u'timestamp': 1545214440, u'value': 756335440},
{u'timestamp': 1545214500, u'value': 848142752},
{u'timestamp': 1545214560, u'value': 695935680},
{u'timestamp': 1545214620, u'value': 762582816}]
In [90]:
擴展現例2：
In [48]: a
Out[48]:
[{'A078102C949EC2AB': [1, 2, 3, 4]},
{'457D37015E77700E': [2, 2, 2, 2]},
{'5095060C4552175D': [3, 3, 3, 3]}]
In [49]: reduce(lambda x,y: dict(x.items()+y.items()), a)
Out[49]:
{'457D37015E77700E': [2, 2, 2, 2],
'5095060C4552175D': [3, 3, 3, 3],
'A078102C949EC2AB': [1, 2, 3, 4]}
In [50]:
awk指定字段求和
awk -F '=' '{count+=$4} END{print count}' file.log
找出在列表1中但不在列表2中的元素
list(set(lst1).difference(set(lst2)))
解析url，把字段轉換成字典
# 方法一
In [5]: url = 'index?name=standby&age=18&city=beijing'
In [6]: parameter = url.split('?')[1]
In [7]: parameter
Out[7]: 'name=standby&age=18&city=beijing'
In [8]: dict(map(lambda x:x.split('='),parameter.split('&')))
Out[8]: {'age': '18', 'city': 'beijing', 'name': 'standby'}
In [9]:
# 方法二
In [9]: import urlparse
In [10]: query = urlparse.urlparse(url).query
In [11]: query
Out[11]: 'name=standby&age=18&city=beijing'
In [12]: dict([(k, v[0]) for k, v in urlparse.parse_qs(query).items()])
Out[12]: {'age': '18', 'city': 'beijing', 'name': 'standby'}
In [13]:
fromkeys使用的陷阱
In [1]: a = dict.fromkeys(['k1','k2','k3'],{})
In [2]: a
Out[2]: {'k1': {}, 'k2': {}, 'k3': {}}
In [3]: a['k1']['2018-10-10'] = 'hi'
In [4]: a
Out[4]:
{'k1': {'2018-10-10': 'hi'},
'k2': {'2018-10-10': 'hi'},
'k3': {'2018-10-10': 'hi'}}
In [5]:
In [5]: a = dict.fromkeys(['k1','k2','k3'],[])
In [6]: a['k1'].append(999)
In [7]: a
Out[7]: {'k1': [999], 'k2': [999], 'k3': [999]}
In [8]:
In [8]: a = dict.fromkeys(['k1','k2','k3'],0)
In [9]: a['k1'] += 9
In [10]: a
Out[10]: {'k1': 9, 'k2': 0, 'k3': 0}
In [11]:
dateutil庫解析時間對象
In [76]: import datetime
In [77]: datetime.datetime.strptime('2019-04-10','%Y-%m-%d')
Out[77]: datetime.datetime(2019, 4, 10, 0, 0)
In [78]: import dateutil
In [79]: dateutil.parser.parse('2019-04-10')
Out[79]: datetime.datetime(2019, 4, 10, 0, 0)
In [80]: dateutil.parser.parse('2019/04/10')
Out[80]: datetime.datetime(2019, 4, 10, 0, 0)
In [81]: dateutil.parser.parse('04/10/2019')
Out[81]: datetime.datetime(2019, 4, 10, 0, 0)
In [82]: dateutil.parser.parse('2019-Apr-10')
Out[82]: datetime.datetime(2019, 4, 10, 0, 0)
In [83]:
合併多個字典
# Python2.7
# 這種方式對資源的一種浪費
# 注意這種方式在Python3中會報錯：TypeError: unsupported operand type(s) for +: 'dict_items' and 'dict_items'
In [7]: lst
Out[7]:
[{'k1': [1, 1, 1, 1, 1, 1]},
{'k3': [3, 3, 3, 4, 4, 4]},
{'k5': [5, 5, 5, 6, 6, 6]}]
In [8]: reduce(lambda x,y: dict(x.items()+y.items()), lst)
Out[8]: {'k1': [1, 1, 1, 1, 1, 1], 'k3': [3, 3, 3, 4, 4, 4], 'k5': [5, 5, 5, 6, 6, 6]}
In [9]:
# Python3.6
In [67]: lst
Out[67]:
[{'k1': [1, 1, 1, 1, 1, 1]},
{'k3': [3, 3, 3, 4, 4, 4]},
{'k5': [5, 5, 5, 6, 6, 6]}]
In [68]: reduce(lambda x,y: {**x,**y}, lst)
Out[68]: {'k1': [1, 1, 1, 1, 1, 1], 'k3': [3, 3, 3, 4, 4, 4], 'k5': [5, 5, 5, 6, 6, 6]}
In [69]:
# 另外補充兩種兼容Py2和Py3的方法：
# 1. 使用字典的構造函數
reduce(lambda x,y: dict(x, **y), lst)
# 2. 笨辦法
{k: v for d in lst for k, v in d.items()}
zip的反操做/unzip
In [2]: lst Out[2]: [[1560239100, 16], [1560239400, 11], [1560239700, 14], [1560240000, 18], [1560240300, 18], [1560240600, 12], [1560240900, 19], [1560241200, 13], [1560241500, 16], [1560241800, 16]] In [3]: tss,vals = [ list(tpe) for tpe in zip(*[ i for i in lst ]) ] In [4]: tss Out[4]: [1560239100, 1560239400, 1560239700, 1560240000, 1560240300, 1560240600, 1560240900, 1560241200, 1560241500, 1560241800] In [5]: vals Out[5]: [16, 11, 14, 18, 18, 12, 19, 13, 16, 16] In [6]:
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