minimised readme

README.rst

@@ -4,48 +4,7 @@ petl - Extract, Transform and Load (Tables of Data)
 `petl` is a tentative Python module for extracting, transforming and
 loading tables of data.
 
-- Download: http://pypi.python.org/pypi/petl
-- Source: https://github.com/alimanfoo/petl
 - Docs: http://readthedocs.org/docs/petl
+- Source: https://github.com/alimanfoo/petl
+- Download: http://pypi.python.org/pypi/petl
 
-There are already many Python modules in this space, but none (that
-I've found) seem to cover the full range of transformations required,
-and many use different data structures to represent tables of data,
-meaning that functions from different modules cannot easily be
-mixed. It would be magnificent if there was a single Python package
-that brought some of this together, or at least if there were some
-consistency across relevant packages so that, over time, the Python
-ETL toolbox would grow into something even more awesome than it
-already is.
-
-Currently, this module is somewhere between pipe dream, fantasy,
-wishlist, experiment and placeholder (until someone with far more
-talent, time and energy than me comes along and takes on the
-mantle). It's not realistic to expect that I alone will be able to
-come close to covering the full range of ETL functionality required by
-a diverse range of projects in any reasonable space of time. However,
-I would like to do at least the following:
-
-- Try to compile a consistent glossary/terminology for describing
-  transformations on tables of data (e.g., what do "map", "cut",
-  "slice", , "join", "merge", "fold", "transpose", "split", "melt",
-  "cast", ..., mean?) with cross-references to what terminology is
-  used in other tools/modules.
-
-- Work towards an interface/protocol for objects that can consume
-  and/or generate tabular data, that is (a) as bloody simple as
-  possible, so that writing transformation scripts, and developing new
-  transformation functions, is possible for people like me (who aren't
-  Python gods), (b) compatible with the full range of transformations
-  identified in the wish list, (c) compatible with chaining/pipelining
-  multiple transformations, and (d) workable for transformations on
-  big(-ish) datasets.
-
-- Explore and develop a deeper understanding of implementation
-  strategies for a range of tabular data transformations.
-
-If any of this is in any way interesting to you, then I've set up a
-mailing list at http://groups.google.com/group/python-etl - not just
-for this package, but for general discussion about Pythonic ways of
-working with table-shaped data. Feel free to jump in, or to redirect
-me to other projects or forums that have already got this all covered.

README.txt

@@ -4,48 +4,7 @@ petl - Extract, Transform and Load (Tables of Data)
 `petl` is a tentative Python module for extracting, transforming and
 loading tables of data.
 
-- Download: http://pypi.python.org/pypi/petl
-- Source: https://github.com/alimanfoo/petl
 - Docs: http://readthedocs.org/docs/petl
+- Source: https://github.com/alimanfoo/petl
+- Download: http://pypi.python.org/pypi/petl
 
-There are already many Python modules in this space, but none (that
-I've found) seem to cover the full range of transformations required,
-and many use different data structures to represent tables of data,
-meaning that functions from different modules cannot easily be
-mixed. It would be magnificent if there was a single Python package
-that brought some of this together, or at least if there were some
-consistency across relevant packages so that, over time, the Python
-ETL toolbox would grow into something even more awesome than it
-already is.
-
-Currently, this module is somewhere between pipe dream, fantasy,
-wishlist, experiment and placeholder (until someone with far more
-talent, time and energy than me comes along and takes on the
-mantle). It's not realistic to expect that I alone will be able to
-come close to covering the full range of ETL functionality required by
-a diverse range of projects in any reasonable space of time. However,
-I would like to do at least the following:
-
-- Try to compile a consistent glossary/terminology for describing
-  transformations on tables of data (e.g., what do "map", "cut",
-  "slice", , "join", "merge", "fold", "transpose", "split", "melt",
-  "cast", ..., mean?) with cross-references to what terminology is
-  used in other tools/modules.
-
-- Work towards an interface/protocol for objects that can consume
-  and/or generate tabular data, that is (a) as bloody simple as
-  possible, so that writing transformation scripts, and developing new
-  transformation functions, is possible for people like me (who aren't
-  Python gods), (b) compatible with the full range of transformations
-  identified in the wish list, (c) compatible with chaining/pipelining
-  multiple transformations, and (d) workable for transformations on
-  big(-ish) datasets.
-
-- Explore and develop a deeper understanding of implementation
-  strategies for a range of tabular data transformations.
-
-If any of this is in any way interesting to you, then I've set up a
-mailing list at http://groups.google.com/group/python-etl - not just
-for this package, but for general discussion about Pythonic ways of
-working with table-shaped data. Feel free to jump in, or to redirect
-me to other projects or forums that have already got this all covered.