| Name | pymor-oldest-supported-numpy JSON |
| Version |
2023.1.4
JSON |
| download |
| home_page | https://github.com/pymor/pymor-oldest-supported-numpy |
| Summary | Meta-package that provides the oldest NumPy that supports a given Python version and platform. If wheels for the platform became available on PyPI only for a more recent NumPy version, then that NumPy version is specified. |
| upload_time | 2023-01-24 10:10:19 |
| maintainer | |
| docs_url | None |
| author | René Fritze |
| requires_python | >=3.7 |
| license | BSD |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
.. image:: https://img.shields.io/pypi/v/pymor-oldest-supported-numpy
:target: https://pypi.org/project/pymor-oldest-supported-numpy/
:alt: PyPI
About
-----
~~ Original Readme below of unadapted oldest-supported-numpy ~~
This is a meta-package which can be used in ``pyproject.toml`` files
to automatically provide as a build-time dependency the oldest version
of Numpy that supports the given Python version and platform. In case
of platforms for which Numpy has prebuilt wheels, the provided version
also has a prebuilt Numpy wheel.
The reason to use the oldest available Numpy version as a build-time
dependency is because of ABI compatibility. Binaries compiled with old
Numpy versions are binary compatible with newer Numpy versions, but
not vice versa. This meta-package exists to make dealing with this
more convenient, without having to duplicate the same list manually in
all packages requiring it.
In other words:
.. code:: toml
[build-system]
requires = [
"wheel",
"setuptools",
"numpy==1.13.3; python_version=='3.5'",
"numpy==1.13.3; python_version=='3.6'",
"numpy==1.14.5; python_version=='3.7'",
# more numpy requirements...
]
can be replaced by:
.. code:: toml
[build-system]
requires = ["wheel", "setuptools", "oldest-supported-numpy"]
And as new Python versions are released, the ``pyproject.toml`` file does not
need to be updated.
Q&A
---
Why define the Numpy pinnings using install_requires in this repository?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The Numpy version pinnings are defined inside the ``setup.cfg`` file as
``install_requires`` dependencies, rather than as build-time dependencies
inside ``pyproject.toml``. This is deliberate, since Numpy is not actually
required to build wheels of **oldest-supported-numpy**. What we need here
is to make sure that when **oldest-supported-numpy** is installed into
the build environment of a package using it, Numpy gets installed too
as a **runtime** dependency inside the build environment.
Another way to think about this is that since we only publish (universal)
wheels of **oldest-supported-numpy**, the wheel contains no ``pyproject.toml``,
``setup.cfg``, or ``setup.py`` code - it only contains metadata including
dependencies which get installed by pip when **oldest-supported-numpy** is
installed.
Can I use this if my package requires a recent version of Numpy?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In many cases, even though your package may require a version of
Numpy that is more recent than the pinned versions here, this
is often a runtime requirement, i.e. for running (rather than
building) your package. In many cases, unless you use recent
features of the Numpy C API, you will still be able to build your
package with an older version of Numpy and therefore you will still
be able to use **oldest-supported-numpy**. You can still impose a
more recent Numpy requirement in ``install_requires``
What about having a catchier name for this package?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The current name is not very catchy as package names go, but it
is very descriptive. This package is only meant to be used in
``pyproject.toml`` files for defining build-time dependencies,
so it's more important to have a descriptive than a catchy name!
What if I think that one of the pinnings is wrong or out of date?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Please feel free to `open an issue <https://github.com/scipy/oldest-supported-numpy/issues/new>`_
or a pull request if you think something is wrong or could be improved!
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