8000 Deprecation docs by rgommers · Pull Request #2 · numpy/numpy · GitHub
[go: up one dir, main page]
Skip to content

Deprecation docs #2

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
1 commit merged into from
Oct 17, 2010
Merged

Deprecation docs #2

Show file tree
Hide file tree
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
6 changes: 6 additions & 0 deletions README.txt
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,12 @@ After installation, tests can be run with:

python -c 'import numpy; numpy.test()'

When installing a new version of numpy for the first time or before upgrading
to a newer version, it is recommended to turn on deprecation warnings when
running the tests:

python -Wd -c 'import numpy; numpy.test()'

The most current development version is always available from our
git repository:

Expand Down
7 changes: 7 additions & 0 deletions doc/TESTS.txt
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,13 @@ follows::
>>> import numpy
>>> numpy.test()

Note that for Python >= 2.7 deprecation warnings are silent by default. They
can be turned on (recommended after installation and before upgrading) by
starting the interpreter with the -Wd switch, or by::

>>> import warnings
>>> wwarnings.simplefilter('always', DeprecationWarning)

The test method may take two or more arguments; the first is a string
label specifying what should be tested and the second is an integer
giving the level of output verbosity. See the docstring for numpy.test
Expand Down
0