--- a/Doc/tutorial/classes.rst	Tue Oct 08 21:51:06 2013 -0500
+++ b/Doc/tutorial/classes.rst	Wed Oct 09 09:54:32 2013 +0300
@@ -609,7 +609,7 @@
 A piece of Python code that expects a particular abstract data type can often be
 passed a class that emulates the methods of that data type instead.  For
 instance, if you have a function that formats some data from a file object, you
-can define a class with methods :meth:`read` and :meth:`readline` that get the
+can define a class with methods :meth:`read` and :meth:`!readline` that get the
 data from a string buffer instead, and pass it as an argument.
 
 .. (Unfortunately, this technique has its limitations: a class can't define
@@ -693,9 +693,10 @@
 This style of access is clear, concise, and convenient.  The use of iterators
 pervades and unifies Python.  Behind the scenes, the :keyword:`for` statement
 calls :func:`iter` on the container object.  The function returns an iterator
-object that defines the method :meth:`next` which accesses elements in the
-container one at a time.  When there are no more elements, :meth:`next` raises a
-:exc:`StopIteration` exception which tells the :keyword:`for` loop to terminate.
+object that defines the method :meth:`~iterator.next` which accesses elements
+in the container one at a time.  When there are no more elements,
+:meth:`~iterator.next` raises a :exc:`StopIteration` exception which tells the
+:keyword:`for` loop to terminate.
 This example shows how it all works::
 
    >>> s = 'abc'