Skip to content

PEP 209: Resolve dangling hyphens #3344

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Sep 1, 2023
Merged

PEP 209: Resolve dangling hyphens #3344

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 7 additions & 7 deletions pep-0209.txt
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,9 +12,9 @@ Post-History:
Abstract
========

This PEP proposes a redesign and re-implementation of the multi-
dimensional array module, Numeric, to make it easier to add new
features and functionality to the module. Aspects of Numeric 2
This PEP proposes a redesign and re-implementation of the
multi-dimensional array module, Numeric, to make it easier to add
new features and functionality to the module. Aspects of Numeric 2
that will receive special attention are efficient access to arrays
exceeding a gigabyte in size and composed of inhomogeneous data
structures or records. The proposed design uses four Python
Expand Down Expand Up @@ -128,8 +128,8 @@ Some planned features are:
automatically handle alignment and representational issues
when data is accessed or operated on. There are two
approaches to implementing records; as either a derived array
class or a special array type, depending on your point-of-
view. We defer this discussion to the Open Issues section.
class or a special array type, depending on your point-of-view.
We defer this discussion to the Open Issues section.


2. Additional array types
Expand Down Expand Up @@ -265,8 +265,8 @@ The design of Numeric 2 has four primary classes:
_ufunc.compute(slice, data, func, swap, conv)

The 'func' argument is a CFuncObject, while the 'swap' and 'conv'
arguments are lists of CFuncObjects for those arrays needing pre-
or post-processing, otherwise None is used. The data argument is
arguments are lists of CFuncObjects for those arrays needing pre- or
post-processing, otherwise None is used. The data argument is
a list of buffer objects, and the slice argument gives the number
of iterations for each dimension along with the buffer offset and
step size for each array and each dimension.
Expand Down