setuptools-scm and one-liner setup.py (pydata#3714)

* Replace versioneer with setuptools-scm. Replace setup.py with setup.cfg. Remove pytest-runner.

* Python 3.8 eggs

* Drop minimum pandas version

* twine check

.coveragerc

@@ -5,4 +5,3 @@ omit =
     xarray/core/npcompat.py
     xarray/core/pdcompat.py
     xarray/core/pycompat.py
-    xarray/_version.py

.gitattributes

@@ -1,3 +1,2 @@
 # reduce the number of merge conflicts
 doc/whats-new.rst merge=union
-xarray/_version.py export-subst

.gitignore

@@ -15,6 +15,7 @@ doc/savefig
 # Packages
 *.egg
 *.egg-info
+.eggs
 dist
 build
 eggs
@@ -65,7 +66,6 @@ dask-worker-space/
 # xarray specific
 doc/_build
 doc/generated
-xarray/version.py
 xarray/tests/data/*.grib.*.idx
 
 # Sync tools

MANIFEST.in

@@ -4,6 +4,4 @@ recursive-include doc *
 prune doc/_build
 prune doc/generated
 global-exclude .DS_Store
-include versioneer.py
-include xarray/_version.py
 recursive-include xarray/static *

ci/requirements/doc.yml

@@ -17,7 +17,7 @@ dependencies:
   - numba
   - numpy
   - numpydoc
-  - pandas<0.25  # Hack around https://github.com/pydata/xarray/issues/3369
+  - pandas
   - rasterio
   - seaborn
   - sphinx

doc/whats-new.rst

@@ -133,6 +133,9 @@ Internal Changes
 - Removed internal method ``Dataset._from_vars_and_coord_names``,
   which was dominated by ``Dataset._construct_direct``. (:pull:`3565`)
   By `Maximilian Roos <https://github.com/max-sixty>`_
+- Replaced versioneer with setuptools-scm. Moved contents of setup.py to setup.cfg.
+  Removed pytest-runner from setup.py, as per deprecation notice on the pytest-runner
+  project. (:pull:`3714`) by `Guido Imperiale <https://github.com/crusaderky>`_
 
 
 v0.14.1 (19 Nov 2019)

setup.cfg

@@ -1,3 +1,95 @@
+[metadata]
+name = xarray
+author = xarray Developers
+author_email = xarray@googlegroups.com
+license = Apache
+description = N-D labeled arrays and datasets in Python
+long_description_content_type=x-rst
+long_description =
+    **xarray** (formerly **xray**) is an open source project and Python package
+    that makes working with labelled multi-dimensional arrays simple,
+    efficient, and fun!
+
+    xarray introduces labels in the form of dimensions, coordinates and
+    attributes on top of raw NumPy_-like arrays, which allows for a more
+    intuitive, more concise, and less error-prone developer experience.
+    The package includes a large and growing library of domain-agnostic functions
+    for advanced analytics and visualization with these data structures.
+
+    xarray was inspired by and borrows heavily from pandas_, the popular data
+    analysis package focused on labelled tabular data.
+    It is particularly tailored to working with netCDF_ files, which were the
+    source of xarray's data model, and integrates tightly with dask_ for parallel
+    computing.
+
+    .. _NumPy: https://www.numpy.org
+    .. _pandas: https://pandas.pydata.org
+    .. _dask: https://dask.org
+    .. _netCDF: https://www.unidata.ucar.edu/software/netcdf
+
+    Why xarray?
+    -----------
+    Multi-dimensional (a.k.a. N-dimensional, ND) arrays (sometimes called
+    "tensors") are an essential part of computational science.
+    They are encountered in a wide range of fields, including physics, astronomy,
+    geoscience, bioinformatics, engineering, finance, and deep learning.
+    In Python, NumPy_ provides the fundamental data structure and API for
+    working with raw ND arrays.
+    However, real-world datasets are usually more than just raw numbers;
+    they have labels which encode information about how the array values map
+    to locations in space, time, etc.
+
+    xarray doesn't just keep track of labels on arrays -- it uses them to provide a
+    powerful and concise interface. For example:
+
+    -  Apply operations over dimensions by name: ``x.sum('time')``.
+    -  Select values by label instead of integer location:
+       ``x.loc['2014-01-01']`` or ``x.sel(time='2014-01-01')``.
+    -  Mathematical operations (e.g., ``x - y``) vectorize across multiple
+       dimensions (array broadcasting) based on dimension names, not shape.
+    -  Flexible split-apply-combine operations with groupby:
+       ``x.groupby('time.dayofyear').mean()``.
+    -  Database like alignment based on coordinate labels that smoothly
+       handles missing values: ``x, y = xr.align(x, y, join='outer')``.
+    -  Keep track of arbitrary metadata in the form of a Python dictionary:
+       ``x.attrs``.
+
+    Learn more
+    ----------
+    - Documentation: `<http://xarray.pydata.org>`_
+    - Issue tracker: `<http://github.com/pydata/xarray/issues>`_
+    - Source code: `<http://github.com/pydata/xarray>`_
+    - SciPy2015 talk: `<https://www.youtube.com/watch?v=X0pAhJgySxk>`_
+
+url = https://github.com/pydata/xarray
+classifiers =
+    Development Status :: 5 - Production/Stable
+    License :: OSI Approved :: Apache Software License
+    Operating System :: OS Independent
+    Intended Audience :: Science/Research
+    Programming Language :: Python
+    Programming Language :: Python :: 3
+    Programming Language :: Python :: 3.6
+    Programming Language :: Python :: 3.7
+    Topic :: Scientific/Engineering
+
+[options]
+packages = xarray
+zip_safe = True
+include_package_data = True
+python_requires = >=3.6
+install_requires =
+    numpy >= 1.14
+    pandas >= 0.24
+setup_requires = setuptools_scm
+
+[options.package_data]
+xarray =
+    py.typed
+    tests/data/*
+    static/css/*
+    static/html/*
+
 [tool:pytest]
 python_files=test_*.py
 testpaths=xarray/tests properties
@@ -23,6 +115,7 @@ ignore=
     # line break before binary operator
     W503
 exclude=
+    .eggs
     doc
 
 [isort]
@@ -87,35 +180,19 @@ ignore_missing_imports = True
 ignore_missing_imports = True
 [mypy-seaborn.*]
 ignore_missing_imports = True
+[mypy-setuptools]
+ignore_missing_imports = True
 [mypy-sparse.*]
 ignore_missing_imports = True
 [mypy-toolz.*]
 ignore_missing_imports = True
 [mypy-zarr.*]
 ignore_missing_imports = True
-
-# setuptools is not typed
-[mypy-setup]
-ignore_errors = True
-# versioneer code
-[mypy-versioneer.*]
-ignore_errors = True
-# written by versioneer
-[mypy-xarray._version]
-ignore_errors = True
 # version spanning code is hard to type annotate (and most of this module will
 # be going away soon anyways)
 [mypy-xarray.core.pycompat]
 ignore_errors = True
 
-[versioneer]
-VCS = git
-style = pep440
-versionfile_source = xarray/_version.py
-versionfile_build = xarray/_version.py
-tag_prefix = v
-parentdir_prefix = xarray-
-
 [aliases]
 test = pytest
 

setup.py

@@ -1,110 +1,4 @@
 #!/usr/bin/env python
-import sys
+from setuptools import setup
 
-import versioneer
-from setuptools import find_packages, setup
-
-DISTNAME = "xarray"
-LICENSE = "Apache"
-AUTHOR = "xarray Developers"
-AUTHOR_EMAIL = "xarray@googlegroups.com"
-URL = "https://github.com/pydata/xarray"
-CLASSIFIERS = [
-    "Development Status :: 5 - Production/Stable",
-    "License :: OSI Approved :: Apache Software License",
-    "Operating System :: OS Independent",
-    "Intended Audience :: Science/Research",
-    "Programming Language :: Python",
-    "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.6",
-    "Programming Language :: Python :: 3.7",
-    "Topic :: Scientific/Engineering",
-]
-
-PYTHON_REQUIRES = ">=3.6"
-INSTALL_REQUIRES = ["numpy >= 1.14", "pandas >= 0.24"]
-needs_pytest = {"pytest", "test", "ptr"}.intersection(sys.argv)
-SETUP_REQUIRES = ["pytest-runner >= 4.2"] if needs_pytest else []
-TESTS_REQUIRE = ["pytest >= 2.7.1"]
-
-DESCRIPTION = "N-D labeled arrays and datasets in Python"
-LONG_DESCRIPTION = """
-**xarray** (formerly **xray**) is an open source project and Python package
-that makes working with labelled multi-dimensional arrays simple,
-efficient, and fun!
-
-Xarray introduces labels in the form of dimensions, coordinates and
-attributes on top of raw NumPy_-like arrays, which allows for a more
-intuitive, more concise, and less error-prone developer experience.
-The package includes a large and growing library of domain-agnostic functions
-for advanced analytics and visualization with these data structures.
-
-Xarray was inspired by and borrows heavily from pandas_, the popular data
-analysis package focused on labelled tabular data.
-It is particularly tailored to working with netCDF_ files, which were the
-source of xarray's data model, and integrates tightly with dask_ for parallel
-computing.
-
-.. _NumPy: https://www.numpy.org
-.. _pandas: https://pandas.pydata.org
-.. _dask: https://dask.org
-.. _netCDF: https://www.unidata.ucar.edu/software/netcdf
-
-Why xarray?
------------
-
-Multi-dimensional (a.k.a. N-dimensional, ND) arrays (sometimes called
-"tensors") are an essential part of computational science.
-They are encountered in a wide range of fields, including physics, astronomy,
-geoscience, bioinformatics, engineering, finance, and deep learning.
-In Python, NumPy_ provides the fundamental data structure and API for
-working with raw ND arrays.
-However, real-world datasets are usually more than just raw numbers;
-they have labels which encode information about how the array values map
-to locations in space, time, etc.
-
-Xarray doesn't just keep track of labels on arrays -- it uses them to provide a
-powerful and concise interface. For example:
-
--  Apply operations over dimensions by name: ``x.sum('time')``.
--  Select values by label instead of integer location:
-   ``x.loc['2014-01-01']`` or ``x.sel(time='2014-01-01')``.
--  Mathematical operations (e.g., ``x - y``) vectorize across multiple
-   dimensions (array broadcasting) based on dimension names, not shape.
--  Flexible split-apply-combine operations with groupby:
-   ``x.groupby('time.dayofyear').mean()``.
--  Database like alignment based on coordinate labels that smoothly
-   handles missing values: ``x, y = xr.align(x, y, join='outer')``.
--  Keep track of arbitrary metadata in the form of a Python dictionary:
-   ``x.attrs``.
-
-Learn more
-----------
-
-- Documentation: http://xarray.pydata.org
-- Issue tracker: http://github.com/pydata/xarray/issues
-- Source code: http://github.com/pydata/xarray
-- SciPy2015 talk: https://www.youtube.com/watch?v=X0pAhJgySxk
-"""
-
-
-setup(
-    name=DISTNAME,
-    version=versioneer.get_version(),
-    cmdclass=versioneer.get_cmdclass(),
-    license=LICENSE,
-    author=AUTHOR,
-    author_email=AUTHOR_EMAIL,
-    classifiers=CLASSIFIERS,
-    description=DESCRIPTION,
-    long_description=LONG_DESCRIPTION,
-    python_requires=PYTHON_REQUIRES,
-    install_requires=INSTALL_REQUIRES,
-    setup_requires=SETUP_REQUIRES,
-    tests_require=TESTS_REQUIRE,
-    url=URL,
-    packages=find_packages(),
-    package_data={
-        "xarray": ["py.typed", "tests/data/*", "static/css/*", "static/html/*"]
-    },
-)
+setup(use_scm_version=True)