FCL/interim/QEMU: comparison symbian-qemu-0.9.1-12/python-2.6.1/Doc/tutorial/datastructures.rst

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-:ffa851df0825
+:2fb8b9db1c86
+.. _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>
+You can also use a list conveniently as a queue, where the first element added
+is the first element retrieved ("first-in, first-out").  To add an item to the
+back of the queue, use :meth:`append`.  To retrieve an item from the front of
+the queue, use :meth:`pop` with ``0`` as the index.  For example::
+>>> queue = ["Eric", "John", "Michael"]
+>>> queue.append("Terry")           # Terry arrives
+>>> queue.append("Graham")          # Graham arrives
+>>> queue.pop(0)
+'Eric'
+>>> queue.pop(0)
+'John'
+>>> queue
+['Michael', 'Terry', 'Graham']
+.. _tut-functional:
+Functional Programming Tools
+----------------------------
+There are three built-in functions that are very useful when used with lists:
+:func:`filter`, :func:`map`, and :func:`reduce`.
+``filter(function, sequence)`` returns a sequence consisting of those items from
+the sequence for which ``function(item)`` is true. If *sequence* is a
+:class:`string` or :class:`tuple`, the result will be of the same type;
+otherwise, it is always a :class:`list`. For example, to compute some primes::
+>>> def f(x): return x % 2 != 0 and x % 3 != 0
+...
+>>> filter(f, range(2, 25))
+[5, 7, 11, 13, 17, 19, 23]
+``map(function, sequence)`` calls ``function(item)`` for each of the sequence's
+items and returns a list of the return values.  For example, to compute some
+cubes::
+>>> def cube(x): return x*x*x
+...
+>>> map(cube, range(1, 11))
+[1, 8, 27, 64, 125, 216, 343, 512, 729, 1000]
+More than one sequence may be passed; the function must then have as many
+arguments as there are sequences and is called with the corresponding item from
+each sequence (or ``None`` if some sequence is shorter than another).  For
+example::
+>>> seq = range(8)
+>>> def add(x, y): return x+y
+...
+>>> map(add, seq, seq)
+[0, 2, 4, 6, 8, 10, 12, 14]
+``reduce(function, sequence)`` returns a single value constructed by calling the
+binary function *function* on the first two items of the sequence, then on the
+result and the next item, and so on.  For example, to compute the sum of the
+numbers 1 through 10::
+>>> def add(x,y): return x+y
+...
+>>> reduce(add, range(1, 11))
+55
+If there's only one item in the sequence, its value is returned; if the sequence
+is empty, an exception is raised.
+A third argument can be passed to indicate the starting value.  In this case the
+starting value is returned for an empty sequence, and the function is first
+applied to the starting value and the first sequence item, then to the result
+and the next item, and so on.  For example, ::
+>>> def sum(seq):
+...     def add(x,y): return x+y
+...     return reduce(add, seq, 0)
+...
+>>> sum(range(1, 11))
+55
+>>> sum([])
+0
+Don't use this example's definition of :func:`sum`: since summing numbers is
+such a common need, a built-in function ``sum(sequence)`` is already provided,
+and works exactly like this.
+.. versionadded:: 2.3
+List Comprehensions
+-------------------
+List comprehensions provide a concise way to create lists without resorting to
+use of :func:`map`, :func:`filter` and/or :keyword:`lambda`. The resulting list
+definition tends often to be clearer than lists built using those constructs.
+Each list comprehension consists of an expression followed by a :keyword:`for`
+clause, then zero or more :keyword:`for` or :keyword:`if` clauses.  The result
+will be a list resulting from evaluating the expression in the context of the
+:keyword:`for` and :keyword:`if` clauses which follow it.  If the expression
+would evaluate to a tuple, it must be parenthesized. ::
+>>> freshfruit = ['  banana', '  loganberry ', 'passion fruit  ']
+>>> [weapon.strip() for weapon in freshfruit]
+['banana', 'loganberry', 'passion fruit']
+>>> vec = [2, 4, 6]
+>>> [3*x for x in vec]
+[6, 12, 18]
+>>> [3*x for x in vec if x > 3]
+[12, 18]
+>>> [3*x for x in vec if x < 2]
+[]
+>>> [[x,x**2] for x in vec]
+[[2, 4], [4, 16], [6, 36]]
+>>> [x, x**2 for x in vec]	# error - parens required for tuples
+File "<stdin>", line 1, in ?
+[x, x**2 for x in vec]
+^
+SyntaxError: invalid syntax
+>>> [(x, x**2) for x in vec]
+[(2, 4), (4, 16), (6, 36)]
+>>> vec1 = [2, 4, 6]
+>>> vec2 = [4, 3, -9]
+>>> [x*y for x in vec1 for y in vec2]
+[8, 6, -18, 16, 12, -36, 24, 18, -54]
+>>> [x+y for x in vec1 for y in vec2]
+[6, 5, -7, 8, 7, -5, 10, 9, -3]
+>>> [vec1[i]*vec2[i] for i in range(len(vec1))]
+[8, 12, -54]
+List comprehensions are much more flexible than :func:`map` and can be applied
+to complex expressions and nested functions::
+>>> [str(round(355/113.0, i)) for i in range(1,6)]
+['3.1', '3.14', '3.142', '3.1416', '3.14159']
+Nested List Comprehensions
+--------------------------
+If you've got the stomach for it, list comprehensions can be nested. They are a
+powerful tool but -- like all powerful tools -- they need to be used carefully,
+if at all.
+Consider the following example of a 3x3 matrix held as a list containing three
+lists, one list per row::
+>>> mat = [
+...        [1, 2, 3],
+...        [4, 5, 6],
+...        [7, 8, 9],
+...       ]
+Now, if you wanted to swap rows and columns, you could use a list
+comprehension::
+>>> print [[row[i] for row in mat] for i in [0, 1, 2]]
+[[1, 4, 7], [2, 5, 8], [3, 6, 9]]
+Special care has to be taken for the *nested* list comprehension:
+To avoid apprehension when nesting list comprehensions, read from right to
+left.
+A more verbose version of this snippet shows the flow explicitly::
+for i in [0, 1, 2]:
+for row in mat:
+print row[i],
+print
+In real world, you should prefer builtin functions to complex flow statements.
+The :func:`zip` function would do a great job for this use case::
+>>> zip(*mat)
+[(1, 4, 7), (2, 5, 8), (3, 6, 9)]
+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))
+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).
+Tuples have many uses.  For example: (x, y) coordinate pairs, employee records
+from a database, etc.  Tuples, like strings, are immutable: it is not possible
+to assign to the individual items of a tuple (you can simulate much of the same
+effect with slicing and concatenation, though).  It is also possible to create
+tuples which contain mutable objects, such as lists.
+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*. Sequence unpacking
+requires the list of variables on the left to have the same number of elements
+as the length of the sequence.  Note that multiple assignment is really just a
+combination of tuple packing and sequence unpacking!
+There is a small bit of asymmetry here:  packing multiple values always creates
+a tuple, and unpacking works for any sequence.
+.. XXX Add a bit on the difference between tuples and lists.
+.. _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.
+Here is a brief demonstration::
+>>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
+>>> fruit = set(basket)               # create a set without duplicates
+>>> fruit
+set(['orange', 'pear', 'apple', 'banana'])
+>>> 'orange' in fruit                 # fast membership testing
+True
+>>> 'crabgrass' in fruit
+False
+>>> # Demonstrate set operations on unique letters from two words
+...
+>>> a = set('abracadabra')
+>>> b = set('alacazam')
+>>> a                                  # unique letters in a
+set(['a', 'r', 'b', 'c', 'd'])
+>>> a - b                              # letters in a but not in b
+set(['r', 'd', 'b'])
+>>> a | b                              # letters in either a or b
+set(['a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'])
+>>> a & b                              # letters in both a and b
+set(['a', 'c'])
+>>> a ^ b                              # letters in a or b but not both
+set(['r', 'd', 'b', 'm', 'z', 'l'])
+.. _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.
+The :meth:`keys` method of a dictionary object returns a list of all the keys
+used in the dictionary, in arbitrary order (if you want it sorted, just apply
+the :meth:`sort` method to the list of keys).  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}
+>>> tel.keys()
+['guido', 'irv', 'jack']
+>>> 'guido' in tel
+True
+The :func:`dict` constructor builds dictionaries directly from lists of
+key-value pairs stored as tuples.  When the pairs form a pattern, list
+comprehensions can compactly specify the key-value list. ::
+>>> dict([('sape', 4139), ('guido', 4127), ('jack', 4098)])
+{'sape': 4139, 'jack': 4098, 'guido': 4127}
+>>> dict([(x, x**2) for x in (2, 4, 6)])     # use a list comprehension
+{2: 4, 4: 16, 6: 36}
+Later in the tutorial, we will learn about Generator Expressions which are even
+better suited for the task of supplying key-values pairs to the :func:`dict`
+constructor.
+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:`iteritems` method. ::
+>>> knights = {'gallahad': 'the pure', 'robin': 'the brave'}
+>>> for k, v in knights.iteritems():
+...     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(xrange(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 ASCII
+ordering for 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 is legal.  The outcome is
+deterministic but arbitrary: the types are ordered by their name. Thus, a list
+is always smaller than a string, a string is always smaller than a tuple, etc.
+[#]_ Mixed numeric types are compared according to their numeric value, so 0
+equals 0.0, etc.
+.. rubric:: Footnotes
+.. [#] The rules for comparing objects of different types should not be relied upon;
+they may change in a future version of the language.