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New in version 2.3.
This module implements a number of iterator building blocks inspired
by constructs from the Haskell and SML programming languages. Each
has been recast in a form suitable for Python.
The module standardizes a core set of fast, memory efficient tools
that are useful by themselves or in combination. Standardization helps
avoid the readability and reliability problems which arise when many
different individuals create their own slightly varying implementations,
each with their own quirks and naming conventions.
The tools are designed to combine readily with one another. This makes
it easy to construct more specialized tools succinctly and efficiently
in pure Python.
For instance, SML provides a tabulation tool: tabulate(f)
which produces a sequence f(0), f(1), .... This toolbox
provides imap() and count() which can be combined
to form 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 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 compiled 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 performance advantage of iterators becomes more acute as the number
of elements increases - at some point, lists grow large enough to
severely impact memory cache performance and start running slowly.
Release 2.4.5, documentation updated on 18 October 2006.
See About this document... for information on suggesting changes.
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