5. 数据结构 Python v3.4.3 官方教程
2016-01-11 17:43:52

# 5. 数据结构

## 5.1. 详解列表

list.append(x)

list.extend(L)

list.insert(ix)

list.remove(x)

list.pop([i])

list.clear()

list.index(x)

list.count(x)

list.sort(cmp=Nonekey=Nonereverse=False)

list.reverse()

list.copy()

`>>> a = [66.25, 333, 333, 1, 1234.5] >>> print(a.count(333), a.count(66.25), a.count('x')) 2 1 0 >>> a.insert(2, -1) >>> a.append(333) >>> a [66.25, 333, -1, 333, 1, 1234.5, 333] >>> a.index(333) 1 >>> a.remove(333) >>> a [66.25, -1, 333, 1, 1234.5, 333] >>> a.reverse() >>> a [333, 1234.5, 1, 333, -1, 66.25] >>> a.sort() >>> a [-1, 1, 66.25, 333, 333, 1234.5] >>> a.pop() 1234.5 >>> a [-1, 1, 66.25, 333, 333] `

### 5.1.1. 将列表作为堆栈使用

`>>> stack = [3, 4, 5] >>> stack.append(6) >>> stack.append(7) >>> stack [3, 4, 5, 6, 7] >>> stack.pop() 7 >>> stack [3, 4, 5, 6] >>> stack.pop() 6 >>> stack.pop() 5 >>> stack [3, 4] `

### 5.1.2. 将列表当作队列使用

`>>> from collections import 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']) `

### 5.1.3. 列表解析

`>>> squares = [] >>> for x in range(10): ...  squares.append(x**2) ... >>> squares [0, 1, 4, 9, 16, 25, 36, 49, 64, 81] `

`squares = list(map(lambda x: x**2, range(10))) `

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

`>>> [(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)] `

`>>> combs = [] >>> for x in [1,2,3]: ...  for y in [3,1,4]: ...  if x != y: ...  combs.append((x, y)) ... >>> combs [(1, 3), (1, 4), (2, 3), (2, 1), (2, 4), (3, 1), (3, 4)] `

`>>> vec = [-4, -2, 0, 2, 4] >>> # create a new list with the values doubled >>> [x*2 for x in vec] [-8, -4, 0, 4, 8] >>> # filter the list to exclude negative numbers >>> [x for x in vec if x >= 0] [0, 2, 4] >>> # apply a function to all the elements >>> [abs(x) for x in vec] [4, 2, 0, 2, 4] >>> # call a method on each element >>> freshfruit = ['  banana', '  loganberry ', 'passion fruit  '] >>> [weapon.strip() for weapon in freshfruit] ['banana', 'loganberry', 'passion fruit'] >>> # create a list of 2-tuples like (number, square) >>> [(x, x**2) for x in range(6)] [(0, 0), (1, 1), (2, 4), (3, 9), (4, 16), (5, 25)] >>> # the tuple must be parenthesized, otherwise an error is raised >>> [x, x**2 for x in range(6)]  File "<stdin>", line 1, in ?  [x, x**2 for x in range(6)]  ^ SyntaxError: invalid syntax >>> # flatten a list using a listcomp with two 'for' >>> vec = [[1,2,3], [4,5,6], [7,8,9]] >>> [num for elem in vec for num in elem] [1, 2, 3, 4, 5, 6, 7, 8, 9] `

`>>> from math import pi >>> [str(round(pi, i)) for i in range(1, 6)] ['3.1', '3.14', '3.142', '3.1416', '3.14159'] `

### 5.1.4. 嵌套的列表解析

`>>> matrix = [ ...  [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]] `

`>>> transposed = [] >>> for i in range(4): ...  transposed.append([row[i] for row in matrix]) ... >>> transposed [[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]] `

`>>> transposed = [] >>> for i in range(4): ...  # the following 3 lines implement the nested listcomp ...  transposed_row = [] ...  for row in matrix: ...  transposed_row.append(row[i]) ...  transposed.append(transposed_row) ... >>> transposed [[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]] `

`>>> list(zip(*matrix)) [(1, 5, 9), (2, 6, 10), (3, 7, 11), (4, 8, 12)] `

## 5.2. del语句

`>>> a = [-1, 1, 66.25, 333, 333, 1234.5] >>> del a[0] >>> a [1, 66.25, 333, 333, 1234.5] >>> del a[2:4] >>> a [1, 66.25, 1234.5] >>> del a[:] >>> a [] `

del 也可以用于删除整个变量：

`>>> del a `

## 5.3. 元组和序列

`>>> t = 12345, 54321, 'hello!' >>> t[0] 12345 >>> t (12345, 54321, 'hello!') >>> # Tuples may be nested: ... u = t, (1, 2, 3, 4, 5) >>> u ((12345, 54321, 'hello!'), (1, 2, 3, 4, 5)) >>> # Tuples are immutable: ... t[0] = 88888 Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: 'tuple' object does not support item assignment >>> # but they can contain mutable objects: ... v = ([1, 2, 3], [3, 2, 1]) >>> v ([1, 2, 3], [3, 2, 1]) `

`>>> empty = () >>> singleton = 'hello', # <-- note trailing comma >>> len(empty) 0 >>> len(singleton) 1 >>> singleton ('hello',) `

`>>> x, y, z = t `

## 5.4. 集合

Python 还包含了一个数据类型 集合集合中的元素不会重复且没有顺序。集合的基本用途包括成员测试和消除重复条目。集合对象还支持并集、 交集、 差和对称差等数学运算。

`>>> basket = {'apple', 'orange', 'apple', 'pear', 'orange', 'banana'} >>> print(basket) # show that duplicates have been removed {'orange', 'banana', 'pear', 'apple'} >>> 'orange' in basket # fast membership testing True >>> 'crabgrass' in basket False >>> # Demonstrate set operations on unique letters from two words ... >>> a = set('abracadabra') >>> b = set('alacazam') >>> a # unique letters in a {'a', 'r', 'b', 'c', 'd'} >>> a - b # letters in a but not in b {'r', 'd', 'b'} >>> a | b # letters in either a or b {'a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'} >>> a & b # letters in both a and b {'a', 'c'} >>> a ^ b # letters in a or b but not both {'r', 'd', 'b', 'm', 'z', 'l'} `

`>>> a = {x for x in 'abracadabra' if x not in 'abc'} >>> a {'r', 'd'} `

## 5.5. 字典

Python 中内置的另一种有用的数据类型是字典（见映射的类型 —— 字典)。有时候你会发现字典在其它语言中被称为 “associative memories” 或者 “associative arrays”。与序列不同，序列由数字做索引，字典由  做索引，键可以是任意不可变类型；字符串和数字永远可以拿来做键。如果元组只包含字符串、 数字或元组，它们可以用作键；如果元组直接或间接地包含任何可变对象，不能用作键。不能用列表作为键，因为列表可以用索引、切片或者 append() 和extend() 方法修改。

list(d.keys())返回字典中所有键组成的列表，列表的顺序是随机的（如果你想它是有序的，只需使用sorted(d.keys())代替）。[2]要检查某个键是否在字典中，可以使用 in 关键字。

`>>> tel = {'jack': 4098, 'sape': 4139} >>> tel['guido'] = 4127 >>> tel {'sape': 4139, 'guido': 4127, 'jack': 4098} >>> tel['jack'] 4098 >>> del tel['sape'] >>> tel['irv'] = 4127 >>> tel {'guido': 4127, 'irv': 4127, 'jack': 4098} >>> list(tel.keys()) ['irv', 'guido', 'jack'] >>> sorted(tel.keys()) ['guido', 'irv', 'jack'] >>> 'guido' in tel True >>> 'jack' not in tel False `

dict() 构造函数直接从键-值对序列创建字典：

`>>> dict([('sape', 4139), ('guido', 4127), ('jack', 4098)]) {'sape': 4139, 'jack': 4098, 'guido': 4127} `

`>>> {x: x**2 for x in (2, 4, 6)} {2: 4, 4: 16, 6: 36} `

`>>> dict(sape=4139, guido=4127, jack=4098) {'sape': 4139, 'jack': 4098, 'guido': 4127} `

## 5.6. 遍历的技巧

`>>> knights = {'gallahad': 'the pure', 'robin': 'the brave'} >>> for k, v in knights.items(): ...  print(k, v) ... gallahad the pure robin the brave `

`>>> for i, v in enumerate(['tic', 'tac', 'toe']): ...  print(i, v) ... 0 tic 1 tac 2 toe `

`>>> 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. `

`>>> for i in reversed(range(1, 10, 2)): ...  print(i) ... 9 7 5 3 1 `

`>>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana'] >>> for f in sorted(set(basket)): ...  print(f) ... apple banana orange pear `

`>>> 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'] `

## 5.7. 深入条件控制

while 和 if 语句中使用的条件可以包含任意的操作，而不仅仅是比较。

`>>> string1, string2, string3 = '', 'Trondheim', 'Hammer Dance' >>> non_null = string1 or string2 or string3 >>> non_null 'Trondheim' `

## 5.8. 序列和其它类型的比较

`(1, 2, 3) < (1, 2, 4) [1, 2, 3] < [1, 2, 4] 'ABC' < 'C' < 'Pascal' < 'Python' (1, 2, 3, 4) < (1, 2, 4) (1, 2) < (1, 2, -1) (1, 2, 3) == (1.0, 2.0, 3.0) (1, 2, ('aa', 'ab')) < (1, 2, ('abc', 'a'), 4) `

 [1] 其它语言也许会返回可变对象，这么做可以连续地调用方法，比如d->insert("a")->remove("b")->sort();。
 [2] 调用 d.keys() 会返回一个 字典视图 对象。 该对象支持成员测试和迭代操作，但它的内容依赖原字典——它只是一个 视图。