deque objects

class collections.deque([iterable[, maxlen]])¶

Returns a new deque object initialized left-to-right (using append()) with data from iterable. If 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 O(1) performance in either direction.

Though list objects support similar operations, they are optimized for fast fixed-length operations and incur O(n) memory movement costs for pop(0) and insert(0, v) operations which change both the size and position of the underlying data representation.

If maxlen is not specified or is None, deques may grow to an arbitrary length. Otherwise, the deque is bounded to the specified maximum length. Once a bounded length deque is full, when new items are added, a corresponding number of items are discarded from the opposite end. Bounded length deques provide functionality similar to the tail filter in Unix. They are also useful for tracking transactions and other pools of data where only the most recent activity is of interest.

Changed in version 2.6: Added maxlen

Deque objects support the following methods:

deque.append(x)¶

Add x to the right side of the deque.

deque.appendleft(x)¶

Add x to the left side of the deque.

deque.clear()¶

Remove all elements from the deque leaving it with length 0.

deque.extend(iterable)¶

Extend the right side of the deque by appending elements from the iterable argument.

deque.extendleft(iterable)¶

Extend the left side of the deque by appending elements from iterable. Note, the series of left appends results in reversing the order of elements in the iterable argument.

deque.pop()¶

Remove and return an element from the right side of the deque. If no elements are present, raises an IndexError.

deque.popleft()¶

Remove and return an element from the left side of the deque. If no elements are present, raises an IndexError.

deque.remove(value)¶

Removed the first occurrence of value. If not found, raises a ValueError.

deque.rotate(n)¶

Rotate the deque n steps to the right. If n is negative, rotate to the left. Rotating one step to the right is equivalent to: d.appendleft(d.pop()).

In addition to the above, deques support iteration, pickling, len(d), reversed(d), copy.copy(d), copy.deepcopy(d), membership testing with the in operator, and subscript references such as d[-1].

Example:

>>> 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'])

def delete_nth(d, n):
    d.rotate(-n)
    d.popleft()
    d.rotate(n)

>>> 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']]]]

def tail(filename, n=10):
    'Return the last n lines of a file'
    return deque(open(filename), n)

defaultdict objects

class collections.defaultdict([default_factory[, ...]])¶

Returns a new dictionary-like object. defaultdict is a subclass of the builtin dict class. It overrides one method and adds one writable instance variable. The remaining functionality is the same as for the dict class and is not documented here.

The first argument provides the initial value for the default_factory attribute; it defaults to None. All remaining arguments are treated the same as if they were passed to the dict constructor, including keyword arguments.

defaultdict objects support the following method in addition to the standard dict operations:

defaultdict.__missing__(key)¶

If the default_factory attribute is None, this raises an KeyError exception with the key as argument.

If default_factory is not None, it is called without arguments to provide a default value for the given key, this value is inserted in the dictionary for the key, and returned.

If calling default_factory raises an exception this exception is propagated unchanged.

This method is called by the __getitem__() method of the dict class when the requested key is not found; whatever it returns or raises is then returned or raised by __getitem__().

defaultdict objects support the following instance variable:

defaultdict.default_factory¶

This attribute is used by the __missing__() method; it is initialized from the first argument to the constructor, if present, or to None, if absent.

>>> s = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)]
>>> d = defaultdict(list)
>>> for k, v in s:
...     d[k].append(v)
...
>>> d.items()
[('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]

>>> d = {}
>>> for k, v in s:
...     d.setdefault(k, []).append(v)
...
>>> d.items()
[('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]

>>> s = 'mississippi'
>>> d = defaultdict(int)
>>> for k in s:
...     d[k] += 1
...
>>> d.items()
[('i', 4), ('p', 2), ('s', 4), ('m', 1)]

>>> def constant_factory(value):
...     return lambda: value
>>> d = defaultdict(constant_factory('<missing>'))
>>> d.update(name='John', action='ran')
>>> '%(name)s %(action)s to %(object)s' % d
'John ran to <missing>'

>>> s = [('red', 1), ('blue', 2), ('red', 3), ('blue', 4), ('red', 1), ('blue', 4)]
>>> d = defaultdict(set)
>>> for k, v in s:
...     d[k].add(v)
...
>>> d.items()
[('blue', set([2, 4])), ('red', set([1, 3]))]

namedtuple() Factory Function for Tuples with Named Fields

Named tuples assign meaning to each position in a tuple and allow for more readable, self-documenting code. They can be used wherever regular tuples are used, and they add the ability to access fields by name instead of position index.

collections.namedtuple(typename, fieldnames[, verbose])¶

Returns a new tuple subclass named typename. The new subclass is used to create tuple-like objects that have fields accessable by attribute lookup as well as being indexable and iterable. Instances of the subclass also have a helpful docstring (with typename and fieldnames) and a helpful __repr__() method which lists the tuple contents in a name=value format.

The fieldnames are a single string with each fieldname separated by whitespace and/or commas (for example ‘x y’ or ‘x, y’). Alternatively, the fieldnames can be specified as a list of strings (such as [‘x’, ‘y’]).

Any valid Python identifier may be used for a fieldname except for names starting and ending with double underscores. Valid identifiers consist of letters, digits, and underscores but do not start with a digit and cannot be a keyword such as class, for, return, global, pass, print, or raise.

If verbose is true, will print the class definition.

Named tuple instances do not have per-instance dictionaries, so they are lightweight and require no more memory than regular tuples.

Example:

>>> Point = namedtuple('Point', 'x y', verbose=True)
class Point(tuple):
        'Point(x, y)'
        __slots__ = ()
        __fields__ = ('x', 'y')
        def __new__(cls, x, y):
            return tuple.__new__(cls, (x, y))
        def __repr__(self):
            return 'Point(x=%r, y=%r)' % self
        def __asdict__(self):
            'Return a new dict mapping field names to their values'
            return dict(zip(('x', 'y'), self))
        def __replace__(self, **kwds):
            'Return a new Point object replacing specified fields with new values'
            return Point(**dict(zip(('x', 'y'), self) + kwds.items()))
        x = property(itemgetter(0))
        y = property(itemgetter(1))

>>> p = Point(11, y=22)     # instantiate with positional or keyword arguments
>>> p[0] + p[1]             # indexable like the regular tuple (11, 22)
33
>>> x, y = p                # unpack like a regular tuple
>>> x, y
(11, 22)
>>> p.x + p.y               # fields also accessable by name
33
>>> p                       # readable __repr__ with a name=value style
Point(x=11, y=22)

Named tuples are especially useful for assigning field names to result tuples returned by the csv or sqlite3 modules:

EmployeeRecord = namedtuple('EmployeeRecord', 'name, age, title, department, paygrade')

from itertools import starmap
import csv
for record in starmap(EmployeeRecord, csv.reader(open("employees.csv", "rb"))):
    print(emp.name, emp.title)

import sqlite3
conn = sqlite3.connect('/companydata')
cursor = conn.cursor()
cursor.execute('SELECT name, age, title, department, paygrade FROM employees')
for emp in starmap(EmployeeRecord, cursor.fetchall()):
    print emp.name, emp.title

When casting a single record to a named tuple, use the star-operator [1] to unpack the values:

>>> t = [11, 22]
>>> Point(*t)               # the star-operator unpacks any iterable object
Point(x=11, y=22)

When casting a dictionary to a named tuple, use the double-star-operator:

>>> d = {'x': 11, 'y': 22}
>>> Point(**d)
Point(x=11, y=22)

In addition to the methods inherited from tuples, named tuples support two additonal methods and a read-only attribute.

somenamedtuple.__asdict__()¶

Return a new dict which maps field names to their corresponding values:

>>> p.__asdict__()
{'x': 11, 'y': 22}

somenamedtuple.__replace__(kwargs)¶

Return a new instance of the named tuple replacing specified fields with new values:

>>> p = Point(x=11, y=22)
>>> p.__replace__(x=33)
Point(x=33, y=22)

>>> for partnum, record in inventory.items():
...     inventory[partnum] = record.__replace__(price=newprices[partnum], updated=time.now())

somenamedtuple.__fields__¶

Return a tuple of strings listing the field names. This is useful for introspection and for creating new named tuple types from existing named tuples.

>>> p.__fields__                                  # view the field names
('x', 'y')

>>> Color = namedtuple('Color', 'red green blue')
>>> Pixel = namedtuple('Pixel', Point.__fields__ + Color.__fields__)
>>> Pixel(11, 22, 128, 255, 0)
Pixel(x=11, y=22, red=128, green=255, blue=0)'

Since a named tuple is a regular Python class, it is easy to add or change functionality. For example, the display format can be changed by overriding the __repr__() method:

>>> Point = namedtuple('Point', 'x y')
>>> Point.__repr__ = lambda self: 'Point(%.3f, %.3f)' % self
>>> Point(x=10, y=20)
Point(10.000, 20.000)

Default values can be implemented by starting with a prototype instance and customizing it with __replace__():

>>> Account = namedtuple('Account', 'owner balance transaction_count')
>>> model_account = Account('<owner name>', 0.0, 0)
>>> johns_account = model_account.__replace__(owner='John')

Footnotes