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authorRaymond Hettinger <python@rcn.com>2003-04-23 00:09:42 (GMT)
committerRaymond Hettinger <python@rcn.com>2003-04-23 00:09:42 (GMT)
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Add comment on performance.
Fix missing right parenthesis. Add three examples.
Diffstat (limited to 'Doc/lib/libitertools.tex')
-rw-r--r--Doc/lib/libitertools.tex24
1 files changed, 21 insertions, 3 deletions
diff --git a/Doc/lib/libitertools.tex b/Doc/lib/libitertools.tex
index fafc48b..93116ea 100644
--- a/Doc/lib/libitertools.tex
+++ b/Doc/lib/libitertools.tex
@@ -27,14 +27,21 @@ which produces a sequence \code{f(0), f(1), ...}. This toolbox
provides \function{imap()} and \function{count()} which can be combined
to form \code{imap(f, count())} and produce an equivalent result.
+Likewise, the functional tools are designed to work well with the
+high-speed functions provided by the \refmodule{operator} module.
+
+The module author welcomes suggestions for other basic building blocks
+to be added to future versions of the module.
+
Whether cast in pure python form or C code, tools that use iterators
are more memory efficient (and faster) than their list based counterparts.
Adopting the principles of just-in-time manufacturing, they create
data when and where needed instead of consuming memory with the
computer equivalent of ``inventory''.
-The module author welcomes suggestions for other basic building blocks
-to be added to future versions of the module.
+The performance advantage of iterators becomes more acute as the number
+of elements increases -- at some point, lists grow large enough to
+to severely impact memory cache performance and start running slowly.
\begin{seealso}
\seetext{The Standard ML Basis Library,
@@ -105,7 +112,7 @@ by functions or loops that truncate the stream.
Note, this is the only member of the toolkit that may require
significant auxiliary storage (depending on the length of the
- iterable.
+ iterable).
\end{funcdesc}
\begin{funcdesc}{dropwhile}{predicate, iterable}
@@ -355,4 +362,15 @@ from building blocks.
... "s -> (s0,s1), (s1,s2), (s2, s3), ..."
... return izip(seq, islice(seq,1,len(seq)))
+>>> def padnone(seq):
+... "Returns the sequence elements and then returns None indefinitely"
+... return chain(seq, repeat(None))
+
+>>> def ncycles(seq, n):
+... "Returns the sequence elements n times"
+... return chain(*repeat(seq, n))
+
+>>> def dotproduct(vec1, vec2):
+... return sum(imap(operator.mul, vec1, vec2))
+
\end{verbatim}