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lines changed Original file line number Diff line number Diff line change @@ -1184,7 +1184,7 @@ difference is that a Python list can contain objects of many different types.
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The ``array `` module also provides methods for creating arrays of fixed types
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with compact representations, but they are slower to index than lists. Also
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- note that the Numeric extensions and others define array-like structures with
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+ note that NumPy and other third party packages define array-like structures with
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various characteristics as well.
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To get Lisp-style linked lists, you can emulate cons cells using tuples::
Original file line number Diff line number Diff line change @@ -256,7 +256,6 @@ Examples::
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Packing and unpacking of External Data Representation (XDR) data as used in some
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remote procedure call systems.
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- `The Numerical Python Documentation <https://docs.scipy.org/doc/ >`_
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- The Numeric Python extension (NumPy) defines another array type; see
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- http://www.numpy.org/ for further information about Numerical Python.
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+ `NumPy <https://numpy.org/ >`_
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+ The NumPy package defines another array type.
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Original file line number Diff line number Diff line change @@ -1513,14 +1513,12 @@ are always available. They are listed here in alphabetical order.
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.. class :: slice(stop)
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slice(start, stop[, step])
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- .. index :: single: Numerical Python
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-
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Return a :term: `slice ` object representing the set of indices specified by
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``range(start, stop, step) ``. The *start * and *step * arguments default to
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``None ``. Slice objects have read-only data attributes :attr: `~slice.start `,
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:attr: `~slice.stop ` and :attr: `~slice.step ` which merely return the argument
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values (or their default). They have no other explicit functionality;
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- however they are used by Numerical Python and other third party extensions .
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+ however they are used by NumPy and other third party packages .
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Slice objects are also generated when extended indexing syntax is used. For
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example: ``a[start:stop:step] `` or ``a[start:stop, i] ``. See
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:func: `itertools.islice ` for an alternate version that returns an iterator.
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1/3 can be represented exactly).
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If you are a heavy user of floating point operations you should take a look
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- at the Numerical Python package and many other packages for mathematical and
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+ at the NumPy package and many other packages for mathematical and
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statistical operations supplied by the SciPy project. See <https://scipy.org>.
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Python provides tools that may help on those rare occasions when you really
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