Fix some documentation examples involving the repr of a float.

Doc/faq/design.rst

@@ -75,9 +75,9 @@ necessary to make ``eval(repr(f)) == f`` true for any float f.  The ``str()``
 function prints fewer digits and this often results in the more sensible number
 that was probably intended::
 
-   >>> 0.2
-   0.20000000000000001
-   >>> print 0.2
+   >>> 1.1 - 0.9
+   0.20000000000000007
+   >>> print 1.1 - 0.9
    0.2
 
 One of the consequences of this is that it is error-prone to compare the result

Doc/library/decimal.rst

@@ -35,9 +35,9 @@ arithmetic.  It offers several advantages over the :class:`float` datatype:
   people learn at school." -- excerpt from the decimal arithmetic specification.
 
 * Decimal numbers can be represented exactly.  In contrast, numbers like
-  :const:`1.1` do not have an exact representation in binary floating point. End
-  users typically would not expect :const:`1.1` to display as
-  :const:`1.1000000000000001` as it does with binary floating point.
+  :const:`1.1` and :const:`2.2` do not have an exact representations in binary
+  floating point.  End users typically would not expect ``1.1 + 2.2`` to display
+  as :const:`3.3000000000000003` as it does with binary floating point.
 
 * The exactness carries over into arithmetic.  In decimal floating point, ``0.1
   + 0.1 + 0.1 - 0.3`` is exactly equal to zero.  In binary floating point, the result
@@ -193,7 +193,7 @@ floating point flying circus:
    >>> str(a)
    '1.34'
    >>> float(a)
-   1.3400000000000001
+   1.34
    >>> round(a, 1)     # round() first converts to binary floating point
    1.3
    >>> int(a)

Doc/library/math.rst

@@ -90,7 +90,7 @@ Number-theoretic and representation functions
    loss of precision by tracking multiple intermediate partial sums::
 
         >>> sum([.1, .1, .1, .1, .1, .1, .1, .1, .1, .1])
-        0.99999999999999989
+        0.9999999999999999
         >>> fsum([.1, .1, .1, .1, .1, .1, .1, .1, .1, .1])
         1.0
 

Doc/library/sqlite3.rst

@@ -83,7 +83,7 @@ This example uses the iterator form::
    >>> for row in c:
    ...    print row
    ...
-   (u'2006-01-05', u'BUY', u'RHAT', 100, 35.140000000000001)
+   (u'2006-01-05', u'BUY', u'RHAT', 100, 35.14)
    (u'2006-03-28', u'BUY', u'IBM', 1000, 45.0)
    (u'2006-04-06', u'SELL', u'IBM', 500, 53.0)
    (u'2006-04-05', u'BUY', u'MSOFT', 1000, 72.0)
@@ -601,7 +601,7 @@ Now we plug :class:`Row` in::
     >>> type(r)
     <type 'sqlite3.Row'>
     >>> r
-    (u'2006-01-05', u'BUY', u'RHAT', 100.0, 35.140000000000001)
+    (u'2006-01-05', u'BUY', u'RHAT', 100.0, 35.14)
     >>> len(r)
     5
     >>> r[2]

Doc/library/turtle.rst

@@ -875,7 +875,7 @@ Color control
        >>> tup = (0.2, 0.8, 0.55)
        >>> turtle.pencolor(tup)
        >>> turtle.pencolor()
-       (0.20000000000000001, 0.80000000000000004, 0.5490196078431373)
+       (0.2, 0.8, 0.5490196078431373)
        >>> colormode(255)
        >>> turtle.pencolor()
        (51, 204, 140)

Doc/tutorial/floatingpoint.rst

@@ -115,7 +115,7 @@ Another consequence is that since 0.1 is not exactly 1/10, summing ten values of
    ...     sum += 0.1
    ...
    >>> sum
-   0.99999999999999989
+   0.9999999999999999
 
 Binary floating-point arithmetic holds many surprises like this.  The problem
 with "0.1" is explained in precise detail below, in the "Representation Error"

Doc/tutorial/inputoutput.rst

@@ -49,10 +49,10 @@ Some examples::
    'Hello, world.'
    >>> repr(s)
    "'Hello, world.'"
-   >>> str(0.1)
-   '0.1'
-   >>> repr(0.1)
-   '0.10000000000000001'
+   >>> str(1.0/7.0)
+   '0.142857142857'
+   >>> repr(1.0/7.0)
+   '0.14285714285714285'
    >>> x = 10 * 3.25
    >>> y = 200 * 200
    >>> s = 'The value of x is ' + repr(x) + ', and y is ' + repr(y) + '...'

Doc/tutorial/stdlib2.rst

@@ -362,10 +362,13 @@ results in decimal floating point and binary floating point. The difference
 becomes significant if the results are rounded to the nearest cent::
 
    >>> from decimal import *
-   >>> Decimal('0.70') * Decimal('1.05')
+   >>> x = Decimal('0.70') * Decimal('1.05')
+   >>> x
    Decimal('0.7350')
-   >>> .70 * 1.05
-   0.73499999999999999
+   >>> x.quantize(Decimal('0.01'))  # round to nearest cent
+   Decimal('0.74')
+   >>> round(.70 * 1.05, 2)         # same calculation with floats
+   0.73
 
 The :class:`Decimal` result keeps a trailing zero, automatically inferring four
 place significance from multiplicands with two place significance.  Decimal