1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
|
\section{\module{collections} ---
High-performance container datatypes}
\declaremodule{standard}{collections}
\modulesynopsis{High-performance datatypes}
\moduleauthor{Raymond Hettinger}{python@rcn.com}
\sectionauthor{Raymond Hettinger}{python@rcn.com}
\versionadded{2.4}
This module implements high-performance container datatypes. Currently, the
only datatype is a deque. Future additions may include B-trees
and Fibonacci heaps.
\begin{funcdesc}{deque}{\optional{iterable}}
Returns a new deque objected initialized left-to-right (using
\method{append()}) with data from \var{iterable}. If \var{iterable}
is not specified, the new deque is empty.
Deques are a generalization of stacks and queues (the name is pronounced
``deck'' and is short for ``double-ended queue''). Deques support
thread-safe, memory efficient appends and pops from either side of the deque
with approximately the same \code{O(1)} performance in either direction.
Though \class{list} objects support similar operations, they are optimized
for fast fixed-length operations and incur \code{O(n)} memory movement costs
for \samp{pop(0)} and \samp{insert(0, v)} operations which change both the
size and position of the underlying data representation.
\versionadded{2.4}
\end{funcdesc}
Deque objects support the following methods:
\begin{methoddesc}{append}{x}
Add \var{x} to the right side of the deque.
\end{methoddesc}
\begin{methoddesc}{appendleft}{x}
Add \var{x} to the left side of the deque.
\end{methoddesc}
\begin{methoddesc}{clear}{}
Remove all elements from the deque leaving it with length 0.
\end{methoddesc}
\begin{methoddesc}{extend}{iterable}
Extend the right side of the deque by appending elements from
the iterable argument.
\end{methoddesc}
\begin{methoddesc}{extendleft}{iterable}
Extend the left side of the deque by appending elements from
\var{iterable}. Note, the series of left appends results in
reversing the order of elements in the iterable argument.
\end{methoddesc}
\begin{methoddesc}{pop}{}
Remove and return an element from the right side of the deque.
If no elements are present, raises a \exception{IndexError}.
\end{methoddesc}
\begin{methoddesc}{popleft}{}
Remove and return an element from the left side of the deque.
If no elements are present, raises a \exception{IndexError}.
\end{methoddesc}
\begin{methoddesc}{remove}{value}
Removed the first occurrence of \var{value}. If not found,
raises a \exception{ValueError}.
\versionadded{2.5}
\end{methoddesc}
\begin{methoddesc}{rotate}{n}
Rotate the deque \var{n} steps to the right. If \var{n} is
negative, rotate to the left. Rotating one step to the right
is equivalent to: \samp{d.appendleft(d.pop())}.
\end{methoddesc}
In addition to the above, deques support iteration, pickling, \samp{len(d)},
\samp{reversed(d)}, \samp{copy.copy(d)}, \samp{copy.deepcopy(d)},
membership testing with the \keyword{in} operator, and subscript references
such as \samp{d[-1]}.
Example:
\begin{verbatim}
>>> from collections import deque
>>> d = deque('ghi') # make a new deque with three items
>>> for elem in d: # iterate over the deque's elements
... print elem.upper()
G
H
I
>>> d.append('j') # add a new entry to the right side
>>> d.appendleft('f') # add a new entry to the left side
>>> d # show the representation of the deque
deque(['f', 'g', 'h', 'i', 'j'])
>>> d.pop() # return and remove the rightmost item
'j'
>>> d.popleft() # return and remove the leftmost item
'f'
>>> list(d) # list the contents of the deque
['g', 'h', 'i']
>>> d[0] # peek at leftmost item
'g'
>>> d[-1] # peek at rightmost item
'i'
>>> list(reversed(d)) # list the contents of a deque in reverse
['i', 'h', 'g']
>>> 'h' in d # search the deque
True
>>> d.extend('jkl') # add multiple elements at once
>>> d
deque(['g', 'h', 'i', 'j', 'k', 'l'])
>>> d.rotate(1) # right rotation
>>> d
deque(['l', 'g', 'h', 'i', 'j', 'k'])
>>> d.rotate(-1) # left rotation
>>> d
deque(['g', 'h', 'i', 'j', 'k', 'l'])
>>> deque(reversed(d)) # make a new deque in reverse order
deque(['l', 'k', 'j', 'i', 'h', 'g'])
>>> d.clear() # empty the deque
>>> d.pop() # cannot pop from an empty deque
Traceback (most recent call last):
File "<pyshell#6>", line 1, in -toplevel-
d.pop()
IndexError: pop from an empty deque
>>> d.extendleft('abc') # extendleft() reverses the input order
>>> d
deque(['c', 'b', 'a'])
\end{verbatim}
\subsection{Recipes \label{deque-recipes}}
This section shows various approaches to working with deques.
The \method{rotate()} method provides a way to implement \class{deque}
slicing and deletion. For example, a pure python implementation of
\code{del d[n]} relies on the \method{rotate()} method to position
elements to be popped:
\begin{verbatim}
def delete_nth(d, n):
d.rotate(-n)
d.popleft()
d.rotate(n)
\end{verbatim}
To implement \class{deque} slicing, use a similar approach applying
\method{rotate()} to bring a target element to the left side of the deque.
Remove old entries with \method{popleft()}, add new entries with
\method{extend()}, and then reverse the rotation.
With minor variations on that approach, it is easy to implement Forth style
stack manipulations such as \code{dup}, \code{drop}, \code{swap}, \code{over},
\code{pick}, \code{rot}, and \code{roll}.
A roundrobin task server can be built from a \class{deque} using
\method{popleft()} to select the current task and \method{append()}
to add it back to the tasklist if the input stream is not exhausted:
\begin{verbatim}
def roundrobin(*iterables):
pending = deque(iter(i) for i in iterables)
while pending:
task = pending.popleft()
try:
yield task.next()
except StopIteration:
continue
pending.append(task)
>>> for value in roundrobin('abc', 'd', 'efgh'):
... print value
a
d
e
b
f
c
g
h
\end{verbatim}
Multi-pass data reduction algorithms can be succinctly expressed and
efficiently coded by extracting elements with multiple calls to
\method{popleft()}, applying the reduction function, and calling
\method{append()} to add the result back to the queue.
For example, building a balanced binary tree of nested lists entails
reducing two adjacent nodes into one by grouping them in a list:
\begin{verbatim}
def maketree(iterable):
d = deque(iterable)
while len(d) > 1:
pair = [d.popleft(), d.popleft()]
d.append(pair)
return list(d)
>>> print maketree('abcdefgh')
[[[['a', 'b'], ['c', 'd']], [['e', 'f'], ['g', 'h']]]]
\end{verbatim}
|