Add a Guido inspired example for groupby().
diff --git a/Doc/lib/libitertools.tex b/Doc/lib/libitertools.tex
index 51570ee..d07ef2b 100644
--- a/Doc/lib/libitertools.tex
+++ b/Doc/lib/libitertools.tex
@@ -406,12 +406,25 @@
2 ['b', 'd', 'f']
3 ['g']
+# Find runs of consecutive numbers using groupby. The key to the solution
+# is differencing with a range so that consecutive numbers all appear in
+# same group.
+>>> data = [ 1, 4,5,6, 10, 15,16,17,18, 22, 25,26,27,28]
+>>> for k, g in groupby(enumerate(data), lambda (i,x):i-x):
+... print map(operator.itemgetter(1), g)
+...
+[1]
+[4, 5, 6]
+[10]
+[15, 16, 17, 18]
+[22]
+[25, 26, 27, 28]
\end{verbatim}
This section shows how itertools can be combined to create other more
powerful itertools. Note that \function{enumerate()} and \method{iteritems()}
-already have efficient implementations in Python. They are only included here
+already have efficient implementations. They are included here
to illustrate how higher level tools can be created from building blocks.
\begin{verbatim}
diff --git a/Lib/test/test_itertools.py b/Lib/test/test_itertools.py
index 31b1b7c..fe49f75 100644
--- a/Lib/test/test_itertools.py
+++ b/Lib/test/test_itertools.py
@@ -677,6 +677,20 @@
2 ['b', 'd', 'f']
3 ['g']
+# Find runs of consecutive numbers using groupby. The key to the solution
+# is differencing with a range so that consecutive numbers all appear in
+# same group.
+>>> data = [ 1, 4,5,6, 10, 15,16,17,18, 22, 25,26,27,28]
+>>> for k, g in groupby(enumerate(data), lambda (i,x):i-x):
+... print map(operator.itemgetter(1), g)
+...
+[1]
+[4, 5, 6]
+[10]
+[15, 16, 17, 18]
+[22]
+[25, 26, 27, 28]
+
>>> def take(n, seq):
... return list(islice(seq, n))