mirror of https://github.com/python/cpython
670 lines
22 KiB
ReStructuredText
670 lines
22 KiB
ReStructuredText
.. _tut-structures:
|
|
|
|
***************
|
|
Data Structures
|
|
***************
|
|
|
|
This chapter describes some things you've learned about already in more detail,
|
|
and adds some new things as well.
|
|
|
|
.. _tut-morelists:
|
|
|
|
More on Lists
|
|
=============
|
|
|
|
The list data type has some more methods. Here are all of the methods of list
|
|
objects:
|
|
|
|
|
|
.. method:: list.append(x)
|
|
:noindex:
|
|
|
|
Add an item to the end of the list; equivalent to ``a[len(a):] = [x]``.
|
|
|
|
|
|
.. method:: list.extend(L)
|
|
:noindex:
|
|
|
|
Extend the list by appending all the items in the given list; equivalent to
|
|
``a[len(a):] = L``.
|
|
|
|
|
|
.. method:: list.insert(i, x)
|
|
:noindex:
|
|
|
|
Insert an item at a given position. The first argument is the index of the
|
|
element before which to insert, so ``a.insert(0, x)`` inserts at the front of
|
|
the list, and ``a.insert(len(a), x)`` is equivalent to ``a.append(x)``.
|
|
|
|
|
|
.. method:: list.remove(x)
|
|
:noindex:
|
|
|
|
Remove the first item from the list whose value is *x*. It is an error if there
|
|
is no such item.
|
|
|
|
|
|
.. method:: list.pop([i])
|
|
:noindex:
|
|
|
|
Remove the item at the given position in the list, and return it. If no index
|
|
is specified, ``a.pop()`` removes and returns the last item in the list. (The
|
|
square brackets around the *i* in the method signature denote that the parameter
|
|
is optional, not that you should type square brackets at that position. You
|
|
will see this notation frequently in the Python Library Reference.)
|
|
|
|
|
|
.. method:: list.index(x)
|
|
:noindex:
|
|
|
|
Return the index in the list of the first item whose value is *x*. It is an
|
|
error if there is no such item.
|
|
|
|
|
|
.. method:: list.count(x)
|
|
:noindex:
|
|
|
|
Return the number of times *x* appears in the list.
|
|
|
|
|
|
.. method:: list.sort()
|
|
:noindex:
|
|
|
|
Sort the items of the list, in place.
|
|
|
|
|
|
.. method:: list.reverse()
|
|
:noindex:
|
|
|
|
Reverse the elements of the list, in place.
|
|
|
|
An example that uses most of the list methods::
|
|
|
|
>>> 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]
|
|
|
|
|
|
.. _tut-lists-as-stacks:
|
|
|
|
Using Lists as Stacks
|
|
---------------------
|
|
|
|
.. sectionauthor:: Ka-Ping Yee <ping@lfw.org>
|
|
|
|
|
|
The list methods make it very easy to use a list as a stack, where the last
|
|
element added is the first element retrieved ("last-in, first-out"). To add an
|
|
item to the top of the stack, use :meth:`append`. To retrieve an item from the
|
|
top of the stack, use :meth:`pop` without an explicit index. For example::
|
|
|
|
>>> 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]
|
|
|
|
|
|
.. _tut-lists-as-queues:
|
|
|
|
Using Lists as Queues
|
|
---------------------
|
|
|
|
.. sectionauthor:: Ka-Ping Yee <ping@lfw.org>
|
|
|
|
It is also possible to use a list as a queue, where the first element added is
|
|
the first element retrieved ("first-in, first-out"); however, lists are not
|
|
efficient for this purpose. While appends and pops from the end of list are
|
|
fast, doing inserts or pops from the beginning of a list is slow (because all
|
|
of the other elements have to be shifted by one).
|
|
|
|
To implement a queue, use :class:`collections.deque` which was designed to
|
|
have fast appends and pops from both ends. For example::
|
|
|
|
>>> 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'])
|
|
|
|
|
|
.. _tut-listcomps:
|
|
|
|
List Comprehensions
|
|
-------------------
|
|
|
|
List comprehensions provide a concise way to create lists.
|
|
Common applications are to make new lists where each element is the result of
|
|
some operations applied to each member of another sequence or iterable, or to
|
|
create a subsequence of those elements that satisfy a certain condition.
|
|
|
|
For example, assume we want to create a list of squares, like::
|
|
|
|
>>> squares = []
|
|
>>> for x in range(10):
|
|
... squares.append(x**2)
|
|
...
|
|
>>> squares
|
|
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
|
|
|
|
We can obtain the same result with::
|
|
|
|
squares = [x**2 for x in range(10)]
|
|
|
|
This is also equivalent to ``squares = map(lambda x: x**2, range(10))``,
|
|
but it's more concise and readable.
|
|
|
|
A list comprehension consists of brackets containing an expression followed
|
|
by a :keyword:`for` clause, then zero or more :keyword:`for` or :keyword:`if`
|
|
clauses. The result will be a new list resulting from evaluating the expression
|
|
in the context of the :keyword:`for` and :keyword:`if` clauses which follow it.
|
|
For example, this listcomp combines the elements of two lists if they are not
|
|
equal::
|
|
|
|
>>> [(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)]
|
|
|
|
and it's equivalent to::
|
|
|
|
>>> 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)]
|
|
|
|
Note how the order of the :keyword:`for` and :keyword:`if` statements is the
|
|
same in both these snippets.
|
|
|
|
If the expression is a tuple (e.g. the ``(x, y)`` in the previous example),
|
|
it must be parenthesized. ::
|
|
|
|
>>> 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]
|
|
|
|
List comprehensions can contain complex expressions and nested functions::
|
|
|
|
>>> from math import pi
|
|
>>> [str(round(pi, i)) for i in range(1, 6)]
|
|
['3.1', '3.14', '3.142', '3.1416', '3.14159']
|
|
|
|
Nested List Comprehensions
|
|
--------------------------
|
|
|
|
The initial expression in a list comprehension can be any arbitrary expression,
|
|
including another list comprehension.
|
|
|
|
Consider the following example of a 3x4 matrix implemented as a list of
|
|
3 lists of length 4::
|
|
|
|
>>> matrix = [
|
|
... [1, 2, 3, 4],
|
|
... [5, 6, 7, 8],
|
|
... [9, 10, 11, 12],
|
|
... ]
|
|
|
|
The following list comprehension will transpose rows and columns::
|
|
|
|
>>> [[row[i] for row in matrix] for i in range(4)]
|
|
[[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]
|
|
|
|
As we saw in the previous section, the nested listcomp is evaluated in
|
|
the context of the :keyword:`for` that follows it, so this example is
|
|
equivalent to::
|
|
|
|
>>> 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]]
|
|
|
|
which, in turn, is the same as::
|
|
|
|
>>> 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]]
|
|
|
|
In the real world, you should prefer built-in functions to complex flow statements.
|
|
The :func:`zip` function would do a great job for this use case::
|
|
|
|
>>> list(zip(*matrix))
|
|
[(1, 5, 9), (2, 6, 10), (3, 7, 11), (4, 8, 12)]
|
|
|
|
See :ref:`tut-unpacking-arguments` for details on the asterisk in this line.
|
|
|
|
.. _tut-del:
|
|
|
|
The :keyword:`del` statement
|
|
============================
|
|
|
|
There is a way to remove an item from a list given its index instead of its
|
|
value: the :keyword:`del` statement. This differs from the :meth:`pop` method
|
|
which returns a value. The :keyword:`del` statement can also be used to remove
|
|
slices from a list or clear the entire list (which we did earlier by assignment
|
|
of an empty list to the slice). For example::
|
|
|
|
>>> 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
|
|
[]
|
|
|
|
:keyword:`del` can also be used to delete entire variables::
|
|
|
|
>>> del a
|
|
|
|
Referencing the name ``a`` hereafter is an error (at least until another value
|
|
is assigned to it). We'll find other uses for :keyword:`del` later.
|
|
|
|
|
|
.. _tut-tuples:
|
|
|
|
Tuples and Sequences
|
|
====================
|
|
|
|
We saw that lists and strings have many common properties, such as indexing and
|
|
slicing operations. They are two examples of *sequence* data types (see
|
|
:ref:`typesseq`). Since Python is an evolving language, other sequence data
|
|
types may be added. There is also another standard sequence data type: the
|
|
*tuple*.
|
|
|
|
A tuple consists of a number of values separated by commas, for instance::
|
|
|
|
>>> 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])
|
|
|
|
|
|
As you see, on output tuples are always enclosed in parentheses, so that nested
|
|
tuples are interpreted correctly; they may be input with or without surrounding
|
|
parentheses, although often parentheses are necessary anyway (if the tuple is
|
|
part of a larger expression). It is not possible to assign to the individual
|
|
items of a tuple, however it is possible to create tuples which contain mutable
|
|
objects, such as lists.
|
|
|
|
Though tuples may seem similar to lists, they are often used in different
|
|
situations and for different purposes.
|
|
Tuples are :term:`immutable`, and usually contain an heterogeneous sequence of
|
|
elements that are accessed via unpacking (see later in this section) or indexing
|
|
(or even by attribute in the case of :func:`namedtuples <collections.namedtuple>`).
|
|
Lists are :term:`mutable`, and their elements are usually homogeneous and are
|
|
accessed by iterating over the list.
|
|
|
|
A special problem is the construction of tuples containing 0 or 1 items: the
|
|
syntax has some extra quirks to accommodate these. Empty tuples are constructed
|
|
by an empty pair of parentheses; a tuple with one item is constructed by
|
|
following a value with a comma (it is not sufficient to enclose a single value
|
|
in parentheses). Ugly, but effective. For example::
|
|
|
|
>>> empty = ()
|
|
>>> singleton = 'hello', # <-- note trailing comma
|
|
>>> len(empty)
|
|
0
|
|
>>> len(singleton)
|
|
1
|
|
>>> singleton
|
|
('hello',)
|
|
|
|
The statement ``t = 12345, 54321, 'hello!'`` is an example of *tuple packing*:
|
|
the values ``12345``, ``54321`` and ``'hello!'`` are packed together in a tuple.
|
|
The reverse operation is also possible::
|
|
|
|
>>> x, y, z = t
|
|
|
|
This is called, appropriately enough, *sequence unpacking* and works for any
|
|
sequence on the right-hand side. Sequence unpacking requires that there are as
|
|
many variables on the left side of the equals sign as there are elements in the
|
|
sequence. Note that multiple assignment is really just a combination of tuple
|
|
packing and sequence unpacking.
|
|
|
|
|
|
.. _tut-sets:
|
|
|
|
Sets
|
|
====
|
|
|
|
Python also includes a data type for *sets*. A set is an unordered collection
|
|
with no duplicate elements. Basic uses include membership testing and
|
|
eliminating duplicate entries. Set objects also support mathematical operations
|
|
like union, intersection, difference, and symmetric difference.
|
|
|
|
Curly braces or the :func:`set` function can be used to create sets. Note: To
|
|
create an empty set you have to use ``set()``, not ``{}``; the latter creates an
|
|
empty dictionary, a data structure that we discuss in the next section.
|
|
|
|
Here is a brief demonstration::
|
|
|
|
>>> 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'}
|
|
|
|
Like :ref:`for lists <tut-listcomps>`, there is a set comprehension syntax::
|
|
|
|
>>> a = {x for x in 'abracadabra' if x not in 'abc'}
|
|
>>> a
|
|
{'r', 'd'}
|
|
|
|
|
|
|
|
.. _tut-dictionaries:
|
|
|
|
Dictionaries
|
|
============
|
|
|
|
Another useful data type built into Python is the *dictionary* (see
|
|
:ref:`typesmapping`). Dictionaries are sometimes found in other languages as
|
|
"associative memories" or "associative arrays". Unlike sequences, which are
|
|
indexed by a range of numbers, dictionaries are indexed by *keys*, which can be
|
|
any immutable type; strings and numbers can always be keys. Tuples can be used
|
|
as keys if they contain only strings, numbers, or tuples; if a tuple contains
|
|
any mutable object either directly or indirectly, it cannot be used as a key.
|
|
You can't use lists as keys, since lists can be modified in place using index
|
|
assignments, slice assignments, or methods like :meth:`append` and
|
|
:meth:`extend`.
|
|
|
|
It is best to think of a dictionary as an unordered set of *key: value* pairs,
|
|
with the requirement that the keys are unique (within one dictionary). A pair of
|
|
braces creates an empty dictionary: ``{}``. Placing a comma-separated list of
|
|
key:value pairs within the braces adds initial key:value pairs to the
|
|
dictionary; this is also the way dictionaries are written on output.
|
|
|
|
The main operations on a dictionary are storing a value with some key and
|
|
extracting the value given the key. It is also possible to delete a key:value
|
|
pair with ``del``. If you store using a key that is already in use, the old
|
|
value associated with that key is forgotten. It is an error to extract a value
|
|
using a non-existent key.
|
|
|
|
Performing ``list(d.keys())`` on a dictionary returns a list of all the keys
|
|
used in the dictionary, in arbitrary order (if you want it sorted, just use
|
|
``sorted(d.keys())`` instead). [1]_ To check whether a single key is in the
|
|
dictionary, use the :keyword:`in` keyword.
|
|
|
|
Here is a small example using a dictionary::
|
|
|
|
>>> 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
|
|
|
|
The :func:`dict` constructor builds dictionaries directly from sequences of
|
|
key-value pairs::
|
|
|
|
>>> dict([('sape', 4139), ('guido', 4127), ('jack', 4098)])
|
|
{'sape': 4139, 'jack': 4098, 'guido': 4127}
|
|
|
|
In addition, dict comprehensions can be used to create dictionaries from
|
|
arbitrary key and value expressions::
|
|
|
|
>>> {x: x**2 for x in (2, 4, 6)}
|
|
{2: 4, 4: 16, 6: 36}
|
|
|
|
When the keys are simple strings, it is sometimes easier to specify pairs using
|
|
keyword arguments::
|
|
|
|
>>> dict(sape=4139, guido=4127, jack=4098)
|
|
{'sape': 4139, 'jack': 4098, 'guido': 4127}
|
|
|
|
|
|
.. _tut-loopidioms:
|
|
|
|
Looping Techniques
|
|
==================
|
|
|
|
When looping through dictionaries, the key and corresponding value can be
|
|
retrieved at the same time using the :meth:`items` method. ::
|
|
|
|
>>> knights = {'gallahad': 'the pure', 'robin': 'the brave'}
|
|
>>> for k, v in knights.items():
|
|
... print(k, v)
|
|
...
|
|
gallahad the pure
|
|
robin the brave
|
|
|
|
When looping through a sequence, the position index and corresponding value can
|
|
be retrieved at the same time using the :func:`enumerate` function. ::
|
|
|
|
>>> for i, v in enumerate(['tic', 'tac', 'toe']):
|
|
... print(i, v)
|
|
...
|
|
0 tic
|
|
1 tac
|
|
2 toe
|
|
|
|
To loop over two or more sequences at the same time, the entries can be paired
|
|
with the :func:`zip` function. ::
|
|
|
|
>>> 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.
|
|
|
|
To loop over a sequence in reverse, first specify the sequence in a forward
|
|
direction and then call the :func:`reversed` function. ::
|
|
|
|
>>> for i in reversed(range(1, 10, 2)):
|
|
... print(i)
|
|
...
|
|
9
|
|
7
|
|
5
|
|
3
|
|
1
|
|
|
|
To loop over a sequence in sorted order, use the :func:`sorted` function which
|
|
returns a new sorted list while leaving the source unaltered. ::
|
|
|
|
>>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
|
|
>>> for f in sorted(set(basket)):
|
|
... print(f)
|
|
...
|
|
apple
|
|
banana
|
|
orange
|
|
pear
|
|
|
|
|
|
.. _tut-conditions:
|
|
|
|
More on Conditions
|
|
==================
|
|
|
|
The conditions used in ``while`` and ``if`` statements can contain any
|
|
operators, not just comparisons.
|
|
|
|
The comparison operators ``in`` and ``not in`` check whether a value occurs
|
|
(does not occur) in a sequence. The operators ``is`` and ``is not`` compare
|
|
whether two objects are really the same object; this only matters for mutable
|
|
objects like lists. All comparison operators have the same priority, which is
|
|
lower than that of all numerical operators.
|
|
|
|
Comparisons can be chained. For example, ``a < b == c`` tests whether ``a`` is
|
|
less than ``b`` and moreover ``b`` equals ``c``.
|
|
|
|
Comparisons may be combined using the Boolean operators ``and`` and ``or``, and
|
|
the outcome of a comparison (or of any other Boolean expression) may be negated
|
|
with ``not``. These have lower priorities than comparison operators; between
|
|
them, ``not`` has the highest priority and ``or`` the lowest, so that ``A and
|
|
not B or C`` is equivalent to ``(A and (not B)) or C``. As always, parentheses
|
|
can be used to express the desired composition.
|
|
|
|
The Boolean operators ``and`` and ``or`` are so-called *short-circuit*
|
|
operators: their arguments are evaluated from left to right, and evaluation
|
|
stops as soon as the outcome is determined. For example, if ``A`` and ``C`` are
|
|
true but ``B`` is false, ``A and B and C`` does not evaluate the expression
|
|
``C``. When used as a general value and not as a Boolean, the return value of a
|
|
short-circuit operator is the last evaluated argument.
|
|
|
|
It is possible to assign the result of a comparison or other Boolean expression
|
|
to a variable. For example, ::
|
|
|
|
>>> string1, string2, string3 = '', 'Trondheim', 'Hammer Dance'
|
|
>>> non_null = string1 or string2 or string3
|
|
>>> non_null
|
|
'Trondheim'
|
|
|
|
Note that in Python, unlike C, assignment cannot occur inside expressions. C
|
|
programmers may grumble about this, but it avoids a common class of problems
|
|
encountered in C programs: typing ``=`` in an expression when ``==`` was
|
|
intended.
|
|
|
|
|
|
.. _tut-comparing:
|
|
|
|
Comparing Sequences and Other Types
|
|
===================================
|
|
|
|
Sequence objects may be compared to other objects with the same sequence type.
|
|
The comparison uses *lexicographical* ordering: first the first two items are
|
|
compared, and if they differ this determines the outcome of the comparison; if
|
|
they are equal, the next two items are compared, and so on, until either
|
|
sequence is exhausted. If two items to be compared are themselves sequences of
|
|
the same type, the lexicographical comparison is carried out recursively. If
|
|
all items of two sequences compare equal, the sequences are considered equal.
|
|
If one sequence is an initial sub-sequence of the other, the shorter sequence is
|
|
the smaller (lesser) one. Lexicographical ordering for strings uses the Unicode
|
|
codepoint number to order individual characters. Some examples of comparisons
|
|
between sequences of the same type::
|
|
|
|
(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)
|
|
|
|
Note that comparing objects of different types with ``<`` or ``>`` is legal
|
|
provided that the objects have appropriate comparison methods. For example,
|
|
mixed numeric types are compared according to their numeric value, so 0 equals
|
|
0.0, etc. Otherwise, rather than providing an arbitrary ordering, the
|
|
interpreter will raise a :exc:`TypeError` exception.
|
|
|
|
|
|
.. rubric:: Footnotes
|
|
|
|
.. [1] Calling ``d.keys()`` will return a :dfn:`dictionary view` object. It
|
|
supports operations like membership test and iteration, but its contents
|
|
are not independent of the original dictionary -- it is only a *view*.
|