mirror of https://github.com/python/cpython
210 lines
6.7 KiB
TeX
210 lines
6.7 KiB
TeX
\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}{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:
|
|
|
|
This pure python implementation of \code{del d[n]} shows how to use the
|
|
\method{rotate()} method as a building block for implementing a variety
|
|
of class{deque} operations:
|
|
|
|
\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 using multiple calls to
|
|
\method{popleft()}, applying the reduction function, and using
|
|
\method{append()} for adding 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}
|