624 lines
20 KiB
ReStructuredText
624 lines
20 KiB
ReStructuredText
.. _tut-structures:
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***************
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Data Structures
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***************
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This chapter describes some things you've learned about already in more detail,
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and adds some new things as well.
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.. _tut-morelists:
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More on Lists
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=============
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The list data type has some more methods. Here are all of the methods of list
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objects:
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.. method:: list.append(x)
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:noindex:
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Add an item to the end of the list; equivalent to ``a[len(a):] = [x]``.
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.. method:: list.extend(L)
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:noindex:
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Extend the list by appending all the items in the given list; equivalent to
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``a[len(a):] = L``.
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.. method:: list.insert(i, x)
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:noindex:
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Insert an item at a given position. The first argument is the index of the
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element before which to insert, so ``a.insert(0, x)`` inserts at the front of
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the list, and ``a.insert(len(a), x)`` is equivalent to ``a.append(x)``.
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.. method:: list.remove(x)
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:noindex:
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Remove the first item from the list whose value is *x*. It is an error if there
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is no such item.
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.. method:: list.pop([i])
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:noindex:
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Remove the item at the given position in the list, and return it. If no index
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is specified, ``a.pop()`` removes and returns the last item in the list. (The
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square brackets around the *i* in the method signature denote that the parameter
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is optional, not that you should type square brackets at that position. You
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will see this notation frequently in the Python Library Reference.)
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.. method:: list.index(x)
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:noindex:
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Return the index in the list of the first item whose value is *x*. It is an
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error if there is no such item.
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.. method:: list.count(x)
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:noindex:
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Return the number of times *x* appears in the list.
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.. method:: list.sort()
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:noindex:
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Sort the items of the list, in place.
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.. method:: list.reverse()
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:noindex:
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Reverse the elements of the list, in place.
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An example that uses most of the list methods::
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>>> a = [66.25, 333, 333, 1, 1234.5]
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>>> print(a.count(333), a.count(66.25), a.count('x'))
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2 1 0
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>>> a.insert(2, -1)
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>>> a.append(333)
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>>> a
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[66.25, 333, -1, 333, 1, 1234.5, 333]
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>>> a.index(333)
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1
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>>> a.remove(333)
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>>> a
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[66.25, -1, 333, 1, 1234.5, 333]
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>>> a.reverse()
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>>> a
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[333, 1234.5, 1, 333, -1, 66.25]
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>>> a.sort()
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>>> a
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[-1, 1, 66.25, 333, 333, 1234.5]
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.. _tut-lists-as-stacks:
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Using Lists as Stacks
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---------------------
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.. sectionauthor:: Ka-Ping Yee <ping@lfw.org>
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The list methods make it very easy to use a list as a stack, where the last
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element added is the first element retrieved ("last-in, first-out"). To add an
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item to the top of the stack, use :meth:`append`. To retrieve an item from the
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top of the stack, use :meth:`pop` without an explicit index. For example::
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>>> stack = [3, 4, 5]
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>>> stack.append(6)
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>>> stack.append(7)
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>>> stack
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[3, 4, 5, 6, 7]
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>>> stack.pop()
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7
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>>> stack
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[3, 4, 5, 6]
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>>> stack.pop()
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6
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>>> stack.pop()
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5
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>>> stack
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[3, 4]
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.. _tut-lists-as-queues:
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Using Lists as Queues
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---------------------
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.. sectionauthor:: Ka-Ping Yee <ping@lfw.org>
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You can also use a list conveniently as a queue, where the first element added
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is the first element retrieved ("first-in, first-out"). To add an item to the
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back of the queue, use :meth:`append`. To retrieve an item from the front of
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the queue, use :meth:`pop` with ``0`` as the index. For example::
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>>> queue = ["Eric", "John", "Michael"]
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>>> queue.append("Terry") # Terry arrives
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>>> queue.append("Graham") # Graham arrives
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>>> queue.pop(0)
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'Eric'
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>>> queue.pop(0)
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'John'
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>>> queue
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['Michael', 'Terry', 'Graham']
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List Comprehensions
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-------------------
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List comprehensions provide a concise way to create lists from sequences.
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Common applications are to make lists where each element is the result of
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some operations applied to each member of the sequence, or to create a
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subsequence of those elements that satisfy a certain condition.
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Each list comprehension consists of an expression followed by a :keyword:`for`
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clause, then zero or more :keyword:`for` or :keyword:`if` clauses. The result
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will be a list resulting from evaluating the expression in the context of the
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:keyword:`for` and :keyword:`if` clauses which follow it. If the expression
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would evaluate to a tuple, it must be parenthesized.
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Here we take a list of numbers and return a list of three times each number::
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>>> vec = [2, 4, 6]
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>>> [3*x for x in vec]
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[6, 12, 18]
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Now we get a little fancier::
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>>> [[x, x**2] for x in vec]
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[[2, 4], [4, 16], [6, 36]]
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Here we apply a method call to each item in a sequence::
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>>> freshfruit = [' banana', ' loganberry ', 'passion fruit ']
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>>> [weapon.strip() for weapon in freshfruit]
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['banana', 'loganberry', 'passion fruit']
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Using the :keyword:`if` clause we can filter the stream::
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>>> [3*x for x in vec if x > 3]
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[12, 18]
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>>> [3*x for x in vec if x < 2]
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[]
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Tuples can often be created without their parentheses, but not here::
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>>> [x, x**2 for x in vec] # error - parens required for tuples
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File "<stdin>", line 1, in ?
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[x, x**2 for x in vec]
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^
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SyntaxError: invalid syntax
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>>> [(x, x**2) for x in vec]
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[(2, 4), (4, 16), (6, 36)]
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Here are some nested for loops and other fancy behavior::
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>>> vec1 = [2, 4, 6]
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>>> vec2 = [4, 3, -9]
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>>> [x*y for x in vec1 for y in vec2]
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[8, 6, -18, 16, 12, -36, 24, 18, -54]
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>>> [x+y for x in vec1 for y in vec2]
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[6, 5, -7, 8, 7, -5, 10, 9, -3]
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>>> [vec1[i]*vec2[i] for i in range(len(vec1))]
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[8, 12, -54]
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List comprehensions can be applied to complex expressions and nested functions::
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>>> [str(round(355/113, i)) for i in range(1, 6)]
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['3.1', '3.14', '3.142', '3.1416', '3.14159']
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Nested List Comprehensions
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--------------------------
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If you've got the stomach for it, list comprehensions can be nested. They are a
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powerful tool but -- like all powerful tools -- they need to be used carefully,
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if at all.
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Consider the following example of a 3x3 matrix held as a list containing three
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lists, one list per row::
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>>> mat = [
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... [1, 2, 3],
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... [4, 5, 6],
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... [7, 8, 9],
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... ]
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Now, if you wanted to swap rows and columns, you could use a list
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comprehension::
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>>> print([[row[i] for row in mat] for i in [0, 1, 2]])
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[[1, 4, 7], [2, 5, 8], [3, 6, 9]]
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Special care has to be taken for the *nested* list comprehension:
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To avoid apprehension when nesting list comprehensions, read from right to
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left.
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A more verbose version of this snippet shows the flow explicitly::
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for i in [0, 1, 2]:
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for row in mat:
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print(row[i], end="")
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print()
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In real world, you should prefer builtin functions to complex flow statements.
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The :func:`zip` function would do a great job for this use case::
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>>> list(zip(*mat))
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[(1, 4, 7), (2, 5, 8), (3, 6, 9)]
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See :ref:`tut-unpacking-arguments` for details on the asterisk in this line.
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.. _tut-del:
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The :keyword:`del` statement
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============================
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There is a way to remove an item from a list given its index instead of its
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value: the :keyword:`del` statement. This differs from the :meth:`pop` method
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which returns a value. The :keyword:`del` statement can also be used to remove
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slices from a list or clear the entire list (which we did earlier by assignment
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of an empty list to the slice). For example::
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>>> a = [-1, 1, 66.25, 333, 333, 1234.5]
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>>> del a[0]
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>>> a
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[1, 66.25, 333, 333, 1234.5]
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>>> del a[2:4]
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>>> a
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[1, 66.25, 1234.5]
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>>> del a[:]
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>>> a
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[]
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:keyword:`del` can also be used to delete entire variables::
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>>> del a
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Referencing the name ``a`` hereafter is an error (at least until another value
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is assigned to it). We'll find other uses for :keyword:`del` later.
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Tuples and Sequences
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====================
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We saw that lists and strings have many common properties, such as indexing and
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slicing operations. They are two examples of *sequence* data types (see
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:ref:`typesseq`). Since Python is an evolving language, other sequence data
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types may be added. There is also another standard sequence data type: the
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*tuple*.
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A tuple consists of a number of values separated by commas, for instance::
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>>> t = 12345, 54321, 'hello!'
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>>> t[0]
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12345
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>>> t
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(12345, 54321, 'hello!')
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>>> # Tuples may be nested:
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... u = t, (1, 2, 3, 4, 5)
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>>> u
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((12345, 54321, 'hello!'), (1, 2, 3, 4, 5))
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As you see, on output tuples are always enclosed in parentheses, so that nested
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tuples are interpreted correctly; they may be input with or without surrounding
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parentheses, although often parentheses are necessary anyway (if the tuple is
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part of a larger expression).
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Tuples have many uses. For example: (x, y) coordinate pairs, employee records
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from a database, etc. Tuples, like strings, are immutable: it is not possible
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to assign to the individual items of a tuple (you can simulate much of the same
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effect with slicing and concatenation, though). It is also possible to create
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tuples which contain mutable objects, such as lists.
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A special problem is the construction of tuples containing 0 or 1 items: the
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syntax has some extra quirks to accommodate these. Empty tuples are constructed
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by an empty pair of parentheses; a tuple with one item is constructed by
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following a value with a comma (it is not sufficient to enclose a single value
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in parentheses). Ugly, but effective. For example::
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>>> empty = ()
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>>> singleton = 'hello', # <-- note trailing comma
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>>> len(empty)
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0
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>>> len(singleton)
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1
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>>> singleton
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('hello',)
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The statement ``t = 12345, 54321, 'hello!'`` is an example of *tuple packing*:
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the values ``12345``, ``54321`` and ``'hello!'`` are packed together in a tuple.
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The reverse operation is also possible::
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>>> x, y, z = t
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This is called, appropriately enough, *sequence unpacking*. Sequence unpacking
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requires the list of variables on the left to have the same number of elements
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as the length of the sequence. Note that multiple assignment is really just a
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combination of tuple packing and sequence unpacking!
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There is a small bit of asymmetry here: packing multiple values always creates
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a tuple, and unpacking works for any sequence.
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.. XXX Add a bit on the difference between tuples and lists.
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.. _tut-sets:
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Sets
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====
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Python also includes a data type for *sets*. A set is an unordered collection
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with no duplicate elements. Basic uses include membership testing and
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eliminating duplicate entries. Set objects also support mathematical operations
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like union, intersection, difference, and symmetric difference.
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Curly braces or the :func:`set` function can be use to create sets. Note:
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To create an empty set you have to use set(), not {}; the latter creates
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an empty dictionary, a data structure that we discuss in the next section.
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Here is a brief demonstration::
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>>> basket = {'apple', 'orange', 'apple', 'pear', 'orange', 'banana'}
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>>> print(basket)
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{'orange', 'bananna', 'pear', 'apple'}
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>>> fruit = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
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>>> fruit = set(basket) # create a set without duplicates
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>>> fruit
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{'orange', 'pear', 'apple', 'banana'}
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>>> fruit = {'orange', 'apple'} # {} syntax is equivalent to [] for lists
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>>> fruit
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{'orange', 'apple'}
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>>> 'orange' in fruit # fast membership testing
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True
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>>> 'crabgrass' in fruit
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False
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>>> # Demonstrate set operations on unique letters from two words
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...
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>>> a = set('abracadabra')
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>>> b = set('alacazam')
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>>> a # unique letters in a
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{'a', 'r', 'b', 'c', 'd'}
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>>> a - b # letters in a but not in b
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{'r', 'd', 'b'}
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>>> a | b # letters in either a or b
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{'a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'}
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>>> a & b # letters in both a and b
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{'a', 'c'}
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>>> a ^ b # letters in a or b but not both
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{'r', 'd', 'b', 'm', 'z', 'l'}
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Like for lists, there is a set comprehension syntax::
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>>> a = {x for x in 'abracadabra' if x not in 'abc'}
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>>> a
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{'r', 'd'}
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.. _tut-dictionaries:
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Dictionaries
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============
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Another useful data type built into Python is the *dictionary* (see
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:ref:`typesmapping`). Dictionaries are sometimes found in other languages as
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"associative memories" or "associative arrays". Unlike sequences, which are
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indexed by a range of numbers, dictionaries are indexed by *keys*, which can be
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any immutable type; strings and numbers can always be keys. Tuples can be used
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as keys if they contain only strings, numbers, or tuples; if a tuple contains
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any mutable object either directly or indirectly, it cannot be used as a key.
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You can't use lists as keys, since lists can be modified in place using index
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assignments, slice assignments, or methods like :meth:`append` and
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:meth:`extend`.
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It is best to think of a dictionary as an unordered set of *key: value* pairs,
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with the requirement that the keys are unique (within one dictionary). A pair of
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braces creates an empty dictionary: ``{}``. Placing a comma-separated list of
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key:value pairs within the braces adds initial key:value pairs to the
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dictionary; this is also the way dictionaries are written on output.
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The main operations on a dictionary are storing a value with some key and
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extracting the value given the key. It is also possible to delete a key:value
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pair with ``del``. If you store using a key that is already in use, the old
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value associated with that key is forgotten. It is an error to extract a value
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using a non-existent key.
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The :meth:`keys` method of a dictionary object returns a list of all the keys
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used in the dictionary, in arbitrary order (if you want it sorted, just apply
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the :meth:`sort` method to the list of keys). To check whether a single key is
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in the dictionary, use the :keyword:`in` keyword.
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Here is a small example using a dictionary::
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>>> tel = {'jack': 4098, 'sape': 4139}
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>>> tel['guido'] = 4127
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>>> tel
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{'sape': 4139, 'guido': 4127, 'jack': 4098}
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>>> tel['jack']
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4098
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>>> del tel['sape']
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>>> tel['irv'] = 4127
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>>> tel
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{'guido': 4127, 'irv': 4127, 'jack': 4098}
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>>> list(tel.keys())
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['guido', 'irv', 'jack']
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>>> 'guido' in tel
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True
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>>> 'jack' not in tel
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False
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The :func:`dict` constructor builds dictionaries directly from lists of
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key-value pairs stored as tuples. When the pairs form a pattern, list
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comprehensions can compactly specify the key-value list. ::
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>>> dict([('sape', 4139), ('guido', 4127), ('jack', 4098)])
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{'sape': 4139, 'jack': 4098, 'guido': 4127}
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In addition, dict comprehensions can be used to create dictionaries from
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arbitrary key and value expressions::
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>>> {x: x**2 for x in (2, 4, 6)}
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{2: 4, 4: 16, 6: 36}
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When the keys are simple strings, it is sometimes easier to specify pairs using
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keyword arguments::
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>>> dict(sape=4139, guido=4127, jack=4098)
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{'sape': 4139, 'jack': 4098, 'guido': 4127}
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.. XXX Find out the right way to do these DUBOIS
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.. _tut-loopidioms:
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Looping Techniques
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==================
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When looping through dictionaries, the key and corresponding value can be
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retrieved at the same time using the :meth:`items` method. ::
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>>> knights = {'gallahad': 'the pure', 'robin': 'the brave'}
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>>> for k, v in knights.items():
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... print(k, v)
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...
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gallahad the pure
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robin the brave
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When looping through a sequence, the position index and corresponding value can
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be retrieved at the same time using the :func:`enumerate` function. ::
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>>> for i, v in enumerate(['tic', 'tac', 'toe']):
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... print(i, v)
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...
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0 tic
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1 tac
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2 toe
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To loop over two or more sequences at the same time, the entries can be paired
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with the :func:`zip` function. ::
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>>> questions = ['name', 'quest', 'favorite color']
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>>> answers = ['lancelot', 'the holy grail', 'blue']
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>>> for q, a in zip(questions, answers):
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... print('What is your {0}? It is {1}.'.format(q, a))
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...
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What is your name? It is lancelot.
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What is your quest? It is the holy grail.
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What is your favorite color? It is blue.
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To loop over a sequence in reverse, first specify the sequence in a forward
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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 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 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.
|