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DOC: update numpy versions in test case examples #3331

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Aug 4, 2025
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DOC: update numpy versions in test case examples #3331

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8 changes: 4 additions & 4 deletions docs/developers/contributing.rst
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Expand Up @@ -98,7 +98,7 @@ you can do something like the following::
To verify that your development environment is working, you can run the unit tests
for one of the test environments, e.g.::

$ hatch env run --env test.py3.12-2.1-optional run-pytest
$ hatch env run --env test.py3.12-2.2-optional run-pytest

Creating a branch
~~~~~~~~~~~~~~~~~
Expand Down Expand Up @@ -140,7 +140,7 @@ Zarr includes a suite of unit tests. The simplest way to run the unit tests
is to activate your development environment
(see `creating a development environment`_ above) and invoke::

$ hatch env run --env test.py3.12-2.1-optional run-pytest
$ hatch env run --env test.py3.12-2.2-optional run-pytest

All tests are automatically run via GitHub Actions for every pull
request and must pass before code can be accepted. Test coverage is
Expand Down Expand Up @@ -188,14 +188,14 @@ Test coverage
Zarr strives to maintain 100% test coverage under the latest Python stable release
Both unit tests and docstring doctests are included when computing coverage. Running::

$ hatch env run --env test.py3.12-2.1-optional run-coverage
$ hatch env run --env test.py3.12-2.2-optional run-coverage

will automatically run the test suite with coverage and produce a XML coverage report.
This should be 100% before code can be accepted into the main code base.

You can also generate an HTML coverage report by running::

$ hatch env run --env test.py3.12-2.1-optional run-coverage-html
$ hatch env run --env test.py3.12-2.2-optional run-coverage-html

When submitting a pull request, coverage will also be collected across all supported
Python versions via the Codecov service, and will be reported back within the pull
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