Upstream CI

.github/workflows/pytest.yml

@@ -6,6 +6,12 @@ on:
   pull_request:
     branches: ['*']
 
+# When this workflow is queued, automatically cancel any previous running
+# or pending jobs from the same branch
+concurrency:
+  group: tests-${{ github.ref }}
+  cancel-in-progress: true
+
 defaults:
   run:
     shell: bash -l {0}
@@ -44,6 +50,10 @@ jobs:
           - os: windows
             python-version: '3.8'
             requirements: minimal
+          # Test on nightly builds of requirements
+          - os: ubuntu
+            python-version: '3.12'
+            requirements: upstream
 
     steps:
       - name: Checkout
@@ -61,6 +71,20 @@ jobs:
           environment-file: ci/requirements-${{ matrix.requirements }}.yml
           activate-environment: ndcsv
 
+      - name: Install nightly builds
+        if: ${{ matrix.requirements == 'upstream' }}
+        run: |
+          # Pick up https://github.com/mamba-org/mamba/pull/2903
+          mamba install -n base 'mamba>=1.5.2'
+
+          mamba uninstall --force numpy pandas pyarrow
+          python -m pip install --no-deps --pre --prefer-binary \
+              --extra-index-url https://pypi.fury.io/arrow-nightlies/ \
+              pyarrow
+          python -m pip install --no-deps --pre \
+              -i https://pypi.anaconda.org/scientific-python-nightly-wheels/simple \
+              numpy pandas
+
       - name: Show conda options
         run: conda config --show
 

ci/requirements-minimal.yml

@@ -2,9 +2,10 @@ name: ndcsv
 channels:
   - conda-forge
 dependencies:
+  - python=3.8
   - pytest
   - pytest-cov
-  - packaging
+  - packaging=22
   - numpy=1.14
   - pandas=0.24
   - pshell=1.0

ci/requirements-upstream.yml

@@ -0,0 +1,15 @@
+name: ndcsv
+channels:
+  - conda-forge
+dependencies:
+  - pytest
+  - pytest-cov
+  - packaging
+  - numpy
+  - pandas
+  - pyarrow  # TODO remove when pandas 3.0 is released
+  - pshell
+  - xarray
+  - pip:
+      - git+https://github.com/pydata/xarray
+      # numpy, pandas, and pyarrow are upgraded to nightly builds by pytest.yml

ndcsv/tests/test_read.py

@@ -7,10 +7,11 @@
 import pandas
 import pytest
 import xarray
+from packaging.version import parse as parse_version
 
 from ndcsv import read_csv
 
-PANDAS_GE_150 = [int(x) for x in pandas.__version__.split(".")] >= [1, 5]
+PANDAS_GE_150 = parse_version(pandas.__version__).release >= (1, 5)
 
 
 def test_malformed_input():

ndcsv/tests/test_roundtrip.py

@@ -301,21 +301,8 @@ def test_duplicate_index():
     xarray.testing.assert_equal(a, b)
 
 
-@pytest.mark.parametrize(
-    "unstack",
-    [
-        False,
-        pytest.param(
-            True,
-            marks=pytest.mark.skipif(
-                xarray.__version__ < "0.17",
-                reason="Unstacking duplicate indices requires xarray 0.17",
-            ),
-        ),
-    ],
-)
-def test_duplicate_index_multiindex(unstack):
-    """Duplicate indices are OK"""
+def test_duplicate_index_multiindex():
+    """Duplicate indices are OK as long as you don't try to unstack"""
     a = xarray.DataArray(
         [1, 2],
         dims=["dim_0"],
@@ -332,5 +319,5 @@ def test_duplicate_index_multiindex(unstack):
     write_csv(a, buf)
     assert buf.getvalue().replace("\r", "") == txt
     buf.seek(0)
-    b = read_csv(buf, unstack=unstack)
-    xarray.testing.assert_equal(a.unstack() if unstack else a, b)
+    b = read_csv(buf, unstack=False)
+    xarray.testing.assert_equal(a, b)

pyproject.toml

@@ -23,6 +23,7 @@ classifiers = [
 ]
 requires-python = ">=3.8"
 dependencies = [
+    "packaging >=22",
     "numpy >=1.14",
     "pandas >=0.24",
     "pshell >=1.0",
@@ -63,8 +64,6 @@ python_files = ["test_*.py"]
 testpaths = ["ndcsv/tests"]
 filterwarnings = [
     "error",
-    # Raised internally by pandas
-    'ignore:datetime.datetime.utcfromtimestamp\(\) is deprecated:DeprecationWarning',
     # minimum versions only
     'ignore:Updating MultiIndexed coordinate .* would corrupt indices for other variables:FutureWarning',
     'ignore:The signature of `Series.to_csv` was aligned to that of `DataFrame.to_csv`:FutureWarning',