python中list列表的高级函数

  在Python所有的数据结构中,list具有重要地位,并且非常的方便,这篇文章主要是讲解list列表的高级应用。

  此文章为python英文文档的翻译版本,你也可以查看英文版:https://docs.python.org/2/tutorial/datastructures.html

  use a list as a stack: #像栈一样使用列表

  stack = [3, 4, 5]

  stack.append(6)

  stack.append(7)

  stack

  [3, 4, 5, 6, 7]

  stack.pop() #删除最后一个对象

  7

  stack

  [3, 4, 5, 6]

  stack.pop()

  6

  stack.pop()

  5

  stack

  [3, 4]

  use a list as a queue: #像队列一样使用列表

  > from collections import deque #这里需要使用模块deque

  > queue = deque(["Eric", "John", "Michael"])

  > queue.append("Terry") # Terry arrives

  > queue.append("Graham") # Graham arrives

  > queue.popleft() # The first to arrive now leaves

  'Eric'

  > queue.popleft() # The second to arrive now leaves

  'John'

  > queue # Remaining queue in order of arrival

  deque(['Michael', 'Terry', 'Graham'])

  three built-in functions: 三个重要的内建函数

  filter(), map(), and reduce().

  1)、filter(function, sequence)::

  按照function函数的规则在列表sequence中筛选数据

  > def f(x): return x % 3 == 0 or x % 5 == 0

  ... #f函数为定义整数对象x,x性质为是3或5的倍数

  > filter(f, range(2, 25)) #筛选

  [3, 5, 6, 9, 10, 12, 15, 18, 20, 21, 24]

  2)、map(function, sequence):

  map函数实现按照function函数的规则对列表sequence做同样的处理,

  这里sequence不局限于列表,元组同样也可。

  > def cube(x): return x*x*x #这里是立方计算 还可以使用 x**3的方法

  ...

  > map(cube, range(1, 11)) #对列表的每个对象进行立方计算

  [1, 8, 27, 64, 125, 216, 343, 512, 729, 1000]

  注意:这里的参数列表不是固定不变的,主要看自定义函数的参数个数,map函数可以变形为:def func(x,y) map(func,sequence1,sequence2) 举例:

  seq = range(8) #定义一个列表

  > def add(x, y): return x+y #自定义函数,有两个形参

  ...

  > map(add, seq, seq) #使用map函数,后两个参数为函数add对应的操作数,如果列表长度不一致会出现错误

  [0, 2, 4, 6, 8, 10, 12, 14]

  3)、reduce(function, sequence):

  reduce函数功能是将sequence中数据,按照function函数操作,如 将列表第一个数与第二个数进行function操作,得到的结果和列表中下一个数据进行function操作,一直循环下去…

  举例:

  def add(x,y): return x+y

  ...

  reduce(add, range(1, 11))

  55

  List comprehensions:

  这里将介绍列表的几个应用:

  squares = [x**2 for x in range(10)]

  #生成一个列表,列表是由列表range(10)生成的列表经过平方计算后的结果。

  [(x, y) for x in [1,2,3] for y in [3,1,4] if x != y]

  #[(1, 3), (1, 4), (2, 3), (2, 1), (2, 4), (3, 1), (3, 4)] 这里是生成了一个列表,列表的每一项为元组,每个元组是由x和y组成,x是由列表[1,2,3]提供,y来源于[3,1,4],并且满足法则x!=y。

  Nested List Comprehensions:

  这里比较难翻译,就举例说明一下吧:

  matrix = [ #此处定义一个矩阵

  ... [1, 2, 3, 4],

  ... [5, 6, 7, 8],

  ... [9, 10, 11, 12],

  ... ]

  [[row[i] for row in matrix] for i in range(4)]

  #[[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]

  这里两层嵌套比较麻烦,简单讲解一下:对矩阵matrix,for row in matrix来取出矩阵的每一行,row[i]为取出每行列表中的第i个(下标),生成一个列表,然后i又是来源于for i in range(4) 这样就生成了一个列表的列表。

  The del statement:

  删除列表指定数据,举例:

  > a = [-1, 1, 66.25, 333, 333, 1234.5]

  >del a[0] #删除下标为0的元素

  >a

  [1, 66.25, 333, 333, 1234.5]

  >del a[2:4] #从列表中删除下标为2,3的元素

  >a

  [1, 66.25, 1234.5]

  >del a[:] #全部删除 效果同 del a

  >a

  []

  Sets: 集合

  > basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']

  >>> fruit = set(basket) # create a set without duplicates

  >>> fruit

  set(['orange', 'pear', 'apple', 'banana'])

  >>> 'orange' in fruit # fast membership testing

  True

  >>> 'crabgrass' in fruit

  False

  >>> # Demonstrate set operations on unique letters from two words

  ...

  >>> a = set('abracadabra')

  >>> b = set('alacazam')

  >>> a # unique letters in a

  set(['a', 'r', 'b', 'c', 'd'])

  >>> a - b # letters in a but not in b

  set(['r', 'd', 'b'])

  >>> a | b # letters in either a or b

  set(['a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'])

  >>> a & b # letters in both a and b

  set(['a', 'c'])

  >>> a ^ b # letters in a or b but not both

  set(['r', 'd', 'b', 'm', 'z', 'l'])

  Dictionaries:字典

  >>> tel = {'jack': 4098, 'sape': 4139}

  >>> tel['guido'] = 4127 #相当于向字典中添加数据

  >>> tel

  {'sape': 4139, 'guido': 4127, 'jack': 4098}

  >>> tel['jack'] #取数据

  4098

  >>> del tel['sape'] #删除数据

  >>> tel['irv'] = 4127 #修改数据

  >>> tel

  {'guido': 4127, 'irv': 4127, 'jack': 4098}

  >>> tel.keys() #取字典的所有key值

  ['guido', 'irv', 'jack']

  >>> 'guido' in tel #判断元素的key是否在字典中

  True

  >>> tel.get('irv') #取数据

  4127

  也可以使用规则生成字典:

  >>> {x: x**2 for x in (2, 4, 6)}

  {2: 4, 4: 16, 6: 36}

  enumerate():遍历元素及下标

  enumerate 函数用于遍历序列中的元素以及它们的下标:

  >>> for i, v in enumerate(['tic', 'tac', 'toe']):

  ... print i, v

  ...

  0 tic

  1 tac

  2 toe

  zip():郑州人流医院哪家好 http://mobile.zhongyuan120.com/

  zip()是Python的一个内建函数,它接受一系列可迭代的对象作为参数,将对象中对应的元素打包成一个个tuple(元组),然后返回由这些tuples组成的list(列表)。若传入参数的长度不等,则返回list的长度和参数中长度最短的对象相同。利用*号操作符,可以将list unzip(解压)。

  >>> questions = ['name', 'quest', 'favorite color']

  >>> answers = ['lancelot', 'the holy grail', 'blue']

  >>> for q, a in zip(questions, answers):

  ... print 'What is your {0}? It is {1}.'.format(q, a)

  ...

  What is your name? It is lancelot.

  What is your quest? It is the holy grail.

  What is your favorite color? It is blue.

  有关zip举一个简单点儿的例子:>>

  > a = [1,2,3]

  >>> b = [4,5,6]

  >>> c = [4,5,6,7,8]

  >>> zipped = zip(a,b)

  [(1, 4), (2, 5), (3, 6)]

  >>> zip(a,c)

  [(1, 4), (2, 5), (3, 6)]

  >>> zip(*zipped)

  [(1, 2, 3), (4, 5, 6)]

  reversed():反转

  >>> for i in reversed(xrange(1,10,2)):

  ... print i

  ...

  sorted(): 排序

  > basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']

  > for f in sorted(set(basket)): #这里使用了set函数

  ... print f

  ...

  apple

  banana

  orange

  pear

  python的set和其他语言类似, 是一个 基本功能包括关系测试和消除重复元素.

  To change a sequence you are iterating over while inside the loop (for example to duplicate certain items), it is recommended that you first make a copy. Looping over a sequence does not implicitly make a copy. The slice notation makes this especially convenient:

  >>> words = ['cat', 'window', 'defenestrate']

  >>> for w in words[:]: # Loop over a slice copy of the entire list.

  ... if len(w) > 6:

  ... words.insert(0, w)

  ...

  >>> words

  ['defenestrate', 'cat', 'window', 'defenestrate']

posted @ 2020-03-06 10:55  网管布吉岛  阅读(410)  评论(0编辑  收藏  举报