| |
| :mod:`collections` --- High-performance container datatypes |
| =========================================================== |
| |
| .. module:: collections |
| :synopsis: High-performance datatypes |
| .. moduleauthor:: Raymond Hettinger <python@rcn.com> |
| .. sectionauthor:: Raymond Hettinger <python@rcn.com> |
| |
| .. versionadded:: 2.4 |
| |
| .. testsetup:: * |
| |
| from collections import * |
| import itertools |
| __name__ = '<doctest>' |
| |
| This module implements high-performance container datatypes. Currently, |
| there are two datatypes, :class:`deque` and :class:`defaultdict`, and |
| one datatype factory function, :func:`namedtuple`. |
| |
| .. versionchanged:: 2.5 |
| Added :class:`defaultdict`. |
| |
| .. versionchanged:: 2.6 |
| Added :func:`namedtuple`. |
| |
| The specialized containers provided in this module provide alternatives |
| to Python's general purpose built-in containers, :class:`dict`, |
| :class:`list`, :class:`set`, and :class:`tuple`. |
| |
| Besides the containers provided here, the optional :mod:`bsddb` |
| module offers the ability to create in-memory or file based ordered |
| dictionaries with string keys using the :meth:`bsddb.btopen` method. |
| |
| In addition to containers, the collections module provides some ABCs |
| (abstract base classes) that can be used to test whether a class |
| provides a particular interface, for example, is it hashable or |
| a mapping. |
| |
| .. versionchanged:: 2.6 |
| Added abstract base classes. |
| |
| ABCs - abstract base classes |
| ---------------------------- |
| |
| The collections module offers the following ABCs: |
| |
| ========================= ===================== ====================== ==================================================== |
| ABC Inherits Abstract Methods Mixin Methods |
| ========================= ===================== ====================== ==================================================== |
| :class:`Container` ``__contains__`` |
| :class:`Hashable` ``__hash__`` |
| :class:`Iterable` ``__iter__`` |
| :class:`Iterator` :class:`Iterable` ``next`` ``__iter__`` |
| :class:`Sized` ``__len__`` |
| :class:`Callable` ``__call__`` |
| |
| :class:`Sequence` :class:`Sized`, ``__getitem__`` ``__contains__``. ``__iter__``, ``__reversed__``. |
| :class:`Iterable`, ``index``, and ``count`` |
| :class:`Container` |
| |
| :class:`MutableSequence` :class:`Sequence` ``__setitem__`` Inherited Sequence methods and |
| ``__delitem__``, ``append``, ``reverse``, ``extend``, ``pop``, |
| and ``insert`` ``remove``, and ``__iadd__`` |
| |
| :class:`Set` :class:`Sized`, ``__le__``, ``__lt__``, ``__eq__``, ``__ne__``, |
| :class:`Iterable`, ``__gt__``, ``__ge__``, ``__and__``, ``__or__`` |
| :class:`Container` ``__sub__``, ``__xor__``, and ``isdisjoint`` |
| |
| :class:`MutableSet` :class:`Set` ``add`` and Inherited Set methods and |
| ``discard`` ``clear``, ``pop``, ``remove``, ``__ior__``, |
| ``__iand__``, ``__ixor__``, and ``__isub__`` |
| |
| :class:`Mapping` :class:`Sized`, ``__getitem__`` ``__contains__``, ``keys``, ``items``, ``values``, |
| :class:`Iterable`, ``get``, ``__eq__``, and ``__ne__`` |
| :class:`Container` |
| |
| :class:`MutableMapping` :class:`Mapping` ``__setitem__`` and Inherited Mapping methods and |
| ``__delitem__`` ``pop``, ``popitem``, ``clear``, ``update``, |
| and ``setdefault`` |
| |
| |
| :class:`MappingView` :class:`Sized` ``__len__`` |
| :class:`KeysView` :class:`MappingView`, ``__contains__``, |
| :class:`Set` ``__iter__`` |
| :class:`ItemsView` :class:`MappingView`, ``__contains__``, |
| :class:`Set` ``__iter__`` |
| :class:`ValuesView` :class:`MappingView` ``__contains__``, ``__iter__`` |
| ========================= ===================== ====================== ==================================================== |
| |
| These ABCs allow us to ask classes or instances if they provide |
| particular functionality, for example:: |
| |
| size = None |
| if isinstance(myvar, collections.Sized): |
| size = len(myvar) |
| |
| Several of the ABCs are also useful as mixins that make it easier to develop |
| classes supporting container APIs. For example, to write a class supporting |
| the full :class:`Set` API, it only necessary to supply the three underlying |
| abstract methods: :meth:`__contains__`, :meth:`__iter__`, and :meth:`__len__`. |
| The ABC supplies the remaining methods such as :meth:`__and__` and |
| :meth:`isdisjoint` :: |
| |
| class ListBasedSet(collections.Set): |
| ''' Alternate set implementation favoring space over speed |
| and not requiring the set elements to be hashable. ''' |
| def __init__(self, iterable): |
| self.elements = lst = [] |
| for value in iterable: |
| if value not in lst: |
| lst.append(value) |
| def __iter__(self): |
| return iter(self.elements) |
| def __contains__(self, value): |
| return value in self.elements |
| def __len__(self): |
| return len(self.elements) |
| |
| s1 = ListBasedSet('abcdef') |
| s2 = ListBasedSet('defghi') |
| overlap = s1 & s2 # The __and__() method is supported automatically |
| |
| Notes on using :class:`Set` and :class:`MutableSet` as a mixin: |
| |
| (1) |
| Since some set operations create new sets, the default mixin methods need |
| a way to create new instances from an iterable. The class constructor is |
| assumed to have a signature in the form ``ClassName(iterable)``. |
| That assumption is factored-out to an internal classmethod called |
| :meth:`_from_iterable` which calls ``cls(iterable)`` to produce a new set. |
| If the :class:`Set` mixin is being used in a class with a different |
| constructor signature, you will need to override :meth:`from_iterable` |
| with a classmethod that can construct new instances from |
| an iterable argument. |
| |
| (2) |
| To override the comparisons (presumably for speed, as the |
| semantics are fixed), redefine :meth:`__le__` and |
| then the other operations will automatically follow suit. |
| |
| (3) |
| The :class:`Set` mixin provides a :meth:`_hash` method to compute a hash value |
| for the set; however, :meth:`__hash__` is not defined because not all sets |
| are hashable or immutable. To add set hashabilty using mixins, |
| inherit from both :meth:`Set` and :meth:`Hashable`, then define |
| ``__hash__ = Set._hash``. |
| |
| .. seealso:: |
| |
| * `OrderedSet recipe <http://code.activestate.com/recipes/576694/>`_ for an |
| example built on :class:`MutableSet`. |
| |
| * For more about ABCs, see the :mod:`abc` module and :pep:`3119`. |
| |
| |
| :class:`deque` objects |
| ---------------------- |
| |
| .. class:: deque([iterable[, maxlen]]) |
| |
| Returns a new deque object initialized left-to-right (using :meth:`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 :class:`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. |
| |
| .. versionadded:: 2.4 |
| |
| 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. |
| |
| .. versionchanged:: 2.6 |
| Added *maxlen* parameter. |
| |
| Deque objects support the following methods: |
| |
| |
| .. method:: append(x) |
| |
| Add *x* to the right side of the deque. |
| |
| |
| .. method:: appendleft(x) |
| |
| Add *x* to the left side of the deque. |
| |
| |
| .. method:: clear() |
| |
| Remove all elements from the deque leaving it with length 0. |
| |
| |
| .. method:: extend(iterable) |
| |
| Extend the right side of the deque by appending elements from the iterable |
| argument. |
| |
| |
| .. method:: 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. |
| |
| |
| .. method:: pop() |
| |
| Remove and return an element from the right side of the deque. If no |
| elements are present, raises an :exc:`IndexError`. |
| |
| |
| .. method:: popleft() |
| |
| Remove and return an element from the left side of the deque. If no |
| elements are present, raises an :exc:`IndexError`. |
| |
| |
| .. method:: remove(value) |
| |
| Removed the first occurrence of *value*. If not found, raises a |
| :exc:`ValueError`. |
| |
| .. versionadded:: 2.5 |
| |
| |
| .. method:: 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 :keyword:`in` operator, and subscript references such as ``d[-1]``. Indexed |
| access is O(1) at both ends but slows to O(n) in the middle. For fast random |
| access, use lists instead. |
| |
| Example: |
| |
| .. doctest:: |
| |
| >>> 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']) |
| |
| |
| :class:`deque` Recipes |
| ^^^^^^^^^^^^^^^^^^^^^^ |
| |
| This section shows various approaches to working with deques. |
| |
| Bounded length deques provide functionality similar to the ``tail`` filter |
| in Unix:: |
| |
| def tail(filename, n=10): |
| 'Return the last n lines of a file' |
| return deque(open(filename), n) |
| |
| Another approach to using deques is to maintain a sequence of recently |
| added elements by appending to the right and popping to the left:: |
| |
| def moving_average(iterable, n=3): |
| # moving_average([40, 30, 50, 46, 39, 44]) --> 40.0 42.0 45.0 43.0 |
| # http://en.wikipedia.org/wiki/Moving_average |
| it = iter(iterable) |
| d = deque(itertools.islice(it, n-1)) |
| d.appendleft(0) |
| s = sum(d) |
| for elem in it: |
| s += elem - d.popleft() |
| d.append(elem) |
| yield s / float(n) |
| |
| The :meth:`rotate` method provides a way to implement :class:`deque` slicing and |
| deletion. For example, a pure Python implementation of ``del d[n]`` relies on |
| the :meth:`rotate` method to position elements to be popped:: |
| |
| def delete_nth(d, n): |
| d.rotate(-n) |
| d.popleft() |
| d.rotate(n) |
| |
| To implement :class:`deque` slicing, use a similar approach applying |
| :meth:`rotate` to bring a target element to the left side of the deque. Remove |
| old entries with :meth:`popleft`, add new entries with :meth:`extend`, and then |
| reverse the rotation. |
| With minor variations on that approach, it is easy to implement Forth style |
| stack manipulations such as ``dup``, ``drop``, ``swap``, ``over``, ``pick``, |
| ``rot``, and ``roll``. |
| |
| |
| :class:`defaultdict` objects |
| ---------------------------- |
| |
| .. class:: defaultdict([default_factory[, ...]]) |
| |
| Returns a new dictionary-like object. :class:`defaultdict` is a subclass of the |
| built-in :class:`dict` class. It overrides one method and adds one writable |
| instance variable. The remaining functionality is the same as for the |
| :class:`dict` class and is not documented here. |
| |
| The first argument provides the initial value for the :attr:`default_factory` |
| attribute; it defaults to ``None``. All remaining arguments are treated the same |
| as if they were passed to the :class:`dict` constructor, including keyword |
| arguments. |
| |
| .. versionadded:: 2.5 |
| |
| :class:`defaultdict` objects support the following method in addition to the |
| standard :class:`dict` operations: |
| |
| |
| .. method:: defaultdict.__missing__(key) |
| |
| If the :attr:`default_factory` attribute is ``None``, this raises a |
| :exc:`KeyError` exception with the *key* as argument. |
| |
| If :attr:`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 :attr:`default_factory` raises an exception this exception is |
| propagated unchanged. |
| |
| This method is called by the :meth:`__getitem__` method of the |
| :class:`dict` class when the requested key is not found; whatever it |
| returns or raises is then returned or raised by :meth:`__getitem__`. |
| |
| |
| :class:`defaultdict` objects support the following instance variable: |
| |
| |
| .. attribute:: defaultdict.default_factory |
| |
| This attribute is used by the :meth:`__missing__` method; it is |
| initialized from the first argument to the constructor, if present, or to |
| ``None``, if absent. |
| |
| |
| :class:`defaultdict` Examples |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| |
| Using :class:`list` as the :attr:`default_factory`, it is easy to group a |
| sequence of key-value pairs into a dictionary of lists: |
| |
| >>> 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])] |
| |
| When each key is encountered for the first time, it is not already in the |
| mapping; so an entry is automatically created using the :attr:`default_factory` |
| function which returns an empty :class:`list`. The :meth:`list.append` |
| operation then attaches the value to the new list. When keys are encountered |
| again, the look-up proceeds normally (returning the list for that key) and the |
| :meth:`list.append` operation adds another value to the list. This technique is |
| simpler and faster than an equivalent technique using :meth:`dict.setdefault`: |
| |
| >>> d = {} |
| >>> for k, v in s: |
| ... d.setdefault(k, []).append(v) |
| ... |
| >>> d.items() |
| [('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])] |
| |
| Setting the :attr:`default_factory` to :class:`int` makes the |
| :class:`defaultdict` useful for counting (like a bag or multiset in other |
| languages): |
| |
| >>> s = 'mississippi' |
| >>> d = defaultdict(int) |
| >>> for k in s: |
| ... d[k] += 1 |
| ... |
| >>> d.items() |
| [('i', 4), ('p', 2), ('s', 4), ('m', 1)] |
| |
| When a letter is first encountered, it is missing from the mapping, so the |
| :attr:`default_factory` function calls :func:`int` to supply a default count of |
| zero. The increment operation then builds up the count for each letter. |
| |
| The function :func:`int` which always returns zero is just a special case of |
| constant functions. A faster and more flexible way to create constant functions |
| is to use :func:`itertools.repeat` which can supply any constant value (not just |
| zero): |
| |
| >>> def constant_factory(value): |
| ... return itertools.repeat(value).next |
| >>> d = defaultdict(constant_factory('<missing>')) |
| >>> d.update(name='John', action='ran') |
| >>> '%(name)s %(action)s to %(object)s' % d |
| 'John ran to <missing>' |
| |
| Setting the :attr:`default_factory` to :class:`set` makes the |
| :class:`defaultdict` useful for building a dictionary of sets: |
| |
| >>> 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]))] |
| |
| |
| :func:`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. |
| |
| .. function:: namedtuple(typename, field_names, [verbose]) |
| |
| Returns a new tuple subclass named *typename*. The new subclass is used to |
| create tuple-like objects that have fields accessible by attribute lookup as |
| well as being indexable and iterable. Instances of the subclass also have a |
| helpful docstring (with typename and field_names) and a helpful :meth:`__repr__` |
| method which lists the tuple contents in a ``name=value`` format. |
| |
| The *field_names* are a single string with each fieldname separated by whitespace |
| and/or commas, for example ``'x y'`` or ``'x, y'``. Alternatively, *field_names* |
| can be a sequence of strings such as ``['x', 'y']``. |
| |
| Any valid Python identifier may be used for a fieldname except for names |
| starting with an underscore. Valid identifiers consist of letters, digits, |
| and underscores but do not start with a digit or underscore and cannot be |
| a :mod:`keyword` such as *class*, *for*, *return*, *global*, *pass*, *print*, |
| or *raise*. |
| |
| If *verbose* is true, the class definition is printed just before being built. |
| |
| Named tuple instances do not have per-instance dictionaries, so they are |
| lightweight and require no more memory than regular tuples. |
| |
| .. versionadded:: 2.6 |
| |
| Example: |
| |
| .. doctest:: |
| :options: +NORMALIZE_WHITESPACE |
| |
| >>> Point = namedtuple('Point', 'x y') |
| >>> p = Point(11, y=22) # instantiate with positional or keyword arguments |
| >>> p[0] + p[1] # indexable like the plain tuple (11, 22) |
| 33 |
| >>> x, y = p # unpack like a regular tuple |
| >>> x, y |
| (11, 22) |
| >>> p.x + p.y # fields also accessible by name |
| 33 |
| >>> p # readable __repr__ with a name=value style |
| Point(x=11, y=22) |
| |
| >>> Point = namedtuple('Point', 'x y', verbose=True) # show the class definition |
| class Point(tuple): |
| 'Point(x, y)' |
| <BLANKLINE> |
| __slots__ = () |
| <BLANKLINE> |
| _fields = ('x', 'y') |
| <BLANKLINE> |
| def __new__(_cls, x, y): |
| return _tuple.__new__(_cls, (x, y)) |
| <BLANKLINE> |
| @classmethod |
| def _make(cls, iterable, new=tuple.__new__, len=len): |
| 'Make a new Point object from a sequence or iterable' |
| result = new(cls, iterable) |
| if len(result) != 2: |
| raise TypeError('Expected 2 arguments, got %d' % len(result)) |
| return result |
| <BLANKLINE> |
| def __repr__(self): |
| return 'Point(x=%r, y=%r)' % self |
| <BLANKLINE> |
| def _asdict(t): |
| 'Return a new dict which maps field names to their values' |
| return {'x': t[0], 'y': t[1]} |
| <BLANKLINE> |
| def _replace(_self, **kwds): |
| 'Return a new Point object replacing specified fields with new values' |
| result = _self._make(map(kwds.pop, ('x', 'y'), _self)) |
| if kwds: |
| raise ValueError('Got unexpected field names: %r' % kwds.keys()) |
| return result |
| <BLANKLINE> |
| def __getnewargs__(self): |
| return tuple(self) |
| <BLANKLINE> |
| x = _property(_itemgetter(0)) |
| y = _property(_itemgetter(1)) |
| |
| Named tuples are especially useful for assigning field names to result tuples returned |
| by the :mod:`csv` or :mod:`sqlite3` modules:: |
| |
| EmployeeRecord = namedtuple('EmployeeRecord', 'name, age, title, department, paygrade') |
| |
| import csv |
| for emp in map(EmployeeRecord._make, 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 map(EmployeeRecord._make, cursor.fetchall()): |
| print emp.name, emp.title |
| |
| In addition to the methods inherited from tuples, named tuples support |
| three additional methods and one attribute. To prevent conflicts with |
| field names, the method and attribute names start with an underscore. |
| |
| .. method:: somenamedtuple._make(iterable) |
| |
| Class method that makes a new instance from an existing sequence or iterable. |
| |
| .. doctest:: |
| |
| >>> t = [11, 22] |
| >>> Point._make(t) |
| Point(x=11, y=22) |
| |
| .. method:: somenamedtuple._asdict() |
| |
| Return a new dict which maps field names to their corresponding values:: |
| |
| >>> p._asdict() |
| {'x': 11, 'y': 22} |
| |
| .. method:: 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], timestamp=time.now()) |
| |
| .. attribute:: somenamedtuple._fields |
| |
| Tuple of strings listing the field names. Useful for introspection |
| and for creating new named tuple types from existing named tuples. |
| |
| .. doctest:: |
| |
| >>> 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) |
| |
| To retrieve a field whose name is stored in a string, use the :func:`getattr` |
| function: |
| |
| >>> getattr(p, 'x') |
| 11 |
| |
| To convert a dictionary to a named tuple, use the double-star-operator |
| (as described in :ref:`tut-unpacking-arguments`): |
| |
| >>> d = {'x': 11, 'y': 22} |
| >>> Point(**d) |
| Point(x=11, y=22) |
| |
| Since a named tuple is a regular Python class, it is easy to add or change |
| functionality with a subclass. Here is how to add a calculated field and |
| a fixed-width print format: |
| |
| >>> class Point(namedtuple('Point', 'x y')): |
| ... __slots__ = () |
| ... @property |
| ... def hypot(self): |
| ... return (self.x ** 2 + self.y ** 2) ** 0.5 |
| ... def __str__(self): |
| ... return 'Point: x=%6.3f y=%6.3f hypot=%6.3f' % (self.x, self.y, self.hypot) |
| |
| >>> for p in Point(3, 4), Point(14, 5/7.): |
| ... print p |
| Point: x= 3.000 y= 4.000 hypot= 5.000 |
| Point: x=14.000 y= 0.714 hypot=14.018 |
| |
| The subclass shown above sets ``__slots__`` to an empty tuple. This keeps |
| keep memory requirements low by preventing the creation of instance dictionaries. |
| |
| Subclassing is not useful for adding new, stored fields. Instead, simply |
| create a new named tuple type from the :attr:`_fields` attribute: |
| |
| >>> Point3D = namedtuple('Point3D', Point._fields + ('z',)) |
| |
| Default values can be implemented by using :meth:`_replace` to |
| customize a prototype instance: |
| |
| >>> Account = namedtuple('Account', 'owner balance transaction_count') |
| >>> default_account = Account('<owner name>', 0.0, 0) |
| >>> johns_account = default_account._replace(owner='John') |
| |
| Enumerated constants can be implemented with named tuples, but it is simpler |
| and more efficient to use a simple class declaration: |
| |
| >>> Status = namedtuple('Status', 'open pending closed')._make(range(3)) |
| >>> Status.open, Status.pending, Status.closed |
| (0, 1, 2) |
| >>> class Status: |
| ... open, pending, closed = range(3) |
| |
| .. seealso:: |
| |
| `Named tuple recipe <http://code.activestate.com/recipes/500261/>`_ |
| adapted for Python 2.4. |
